HydroShare for iUTAH: Collaborative Publication, Interoperability, and Reuse of Hydrologic Data and Models for a Large, Interdisciplinary Water Research Project

NASA Astrophysics Data System (ADS)

Horsburgh, J. S.; Jones, A. S.

2016-12-01

Data and models used within the hydrologic science community are diverse. New research data and model repositories have succeeded in making data and models more accessible, but have been, in most cases, limited to particular types or classes of data or models and also lack the type of collaborative, and iterative functionality needed to enable shared data collection and modeling workflows. File sharing systems currently used within many scientific communities for private sharing of preliminary and intermediate data and modeling products do not support collaborative data capture, description, visualization, and annotation. More recently, hydrologic datasets and models have been cast as "social objects" that can be published, collaborated around, annotated, discovered, and accessed. Yet it can be difficult using existing software tools to achieve the kind of collaborative workflows and data/model reuse that many envision. HydroShare is a new, web-based system for sharing hydrologic data and models with specific functionality aimed at making collaboration easier and achieving new levels of interactive functionality and interoperability. Within HydroShare, we have developed new functionality for creating datasets, describing them with metadata, and sharing them with collaborators. HydroShare is enabled by a generic data model and content packaging scheme that supports describing and sharing diverse hydrologic datasets and models. Interoperability among the diverse types of data and models used by hydrologic scientists is achieved through the use of consistent storage, management, sharing, publication, and annotation within HydroShare. In this presentation, we highlight and demonstrate how the flexibility of HydroShare's data model and packaging scheme, HydroShare's access control and sharing functionality, and versioning and publication capabilities have enabled the sharing and publication of research datasets for a large, interdisciplinary water research project called iUTAH (innovative Urban Transitions and Aridregion Hydro-sustainability). We discuss the experiences of iUTAH researchers now using HydroShare to collaboratively create, curate, and publish datasets and models in a way that encourages collaboration, promotes reuse, and meets funding agency requirements.

Data Sharing and Cardiology: Platforms and Possibilities.

PubMed

Dey, Pranammya; Ross, Joseph S; Ritchie, Jessica D; Desai, Nihar R; Bhavnani, Sanjeev P; Krumholz, Harlan M

2017-12-19

Sharing deidentified patient-level research data presents immense opportunities to all stakeholders involved in cardiology research and practice. Sharing data encourages the use of existing data for knowledge generation to improve practice, while also allowing for validation of disseminated research. In this review, we discuss key initiatives and platforms that have helped to accelerate progress toward greater sharing of data. These efforts are being prompted by government, universities, philanthropic sponsors of research, major industry players, and collaborations among some of these entities. As data sharing becomes a more common expectation, policy changes will be required to encourage and assist data generators with the process of sharing the data they create. Patients also will need access to their own data and to be empowered to share those data with researchers. Although medicine still lags behind other fields in achieving data sharing's full potential, cardiology research has the potential to lead the way. Copyright © 2017 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Data sharing in neuroimaging research

PubMed Central

Poline, Jean-Baptiste; Breeze, Janis L.; Ghosh, Satrajit; Gorgolewski, Krzysztof; Halchenko, Yaroslav O.; Hanke, Michael; Haselgrove, Christian; Helmer, Karl G.; Keator, David B.; Marcus, Daniel S.; Poldrack, Russell A.; Schwartz, Yannick; Ashburner, John; Kennedy, David N.

2012-01-01

Significant resources around the world have been invested in neuroimaging studies of brain function and disease. Easier access to this large body of work should have profound impact on research in cognitive neuroscience and psychiatry, leading to advances in the diagnosis and treatment of psychiatric and neurological disease. A trend toward increased sharing of neuroimaging data has emerged in recent years. Nevertheless, a number of barriers continue to impede momentum. Many researchers and institutions remain uncertain about how to share data or lack the tools and expertise to participate in data sharing. The use of electronic data capture (EDC) methods for neuroimaging greatly simplifies the task of data collection and has the potential to help standardize many aspects of data sharing. We review here the motivations for sharing neuroimaging data, the current data sharing landscape, and the sociological or technical barriers that still need to be addressed. The INCF Task Force on Neuroimaging Datasharing, in conjunction with several collaborative groups around the world, has started work on several tools to ease and eventually automate the practice of data sharing. It is hoped that such tools will allow researchers to easily share raw, processed, and derived neuroimaging data, with appropriate metadata and provenance records, and will improve the reproducibility of neuroimaging studies. By providing seamless integration of data sharing and analysis tools within a commodity research environment, the Task Force seeks to identify and minimize barriers to data sharing in the field of neuroimaging. PMID:22493576

An Ecosystem Perspective On Asset Management Information

NASA Astrophysics Data System (ADS)

Metso, Lasse; Kans, Mirka

2017-09-01

Big Data and Internet of Things will increase the amount of data on asset management exceedingly. Data sharing with an increased number of partners in the area of asset management is important when developing business opportunities and new ecosystems. An asset management ecosystem is a complex set of relationships between parties taking part in asset management actions. In this paper, the current barriers and benefits of data sharing are identified based on the results of an interview study. The main benefits are transparency, access to data and reuse of data. New services can be created by taking advantage of data sharing. The main barriers to sharing data are an unclear view of the data sharing process and difficulties to recognize the benefits of data sharing. For overcoming the barriers in data sharing, this paper applies the ecosystem perspective on asset management information. The approach is explained by using the Swedish railway industry as an example.

Advancing Collaboration through Hydrologic Data and Model Sharing

NASA Astrophysics Data System (ADS)

Tarboton, D. G.; Idaszak, R.; Horsburgh, J. S.; Ames, D. P.; Goodall, J. L.; Band, L. E.; Merwade, V.; Couch, A.; Hooper, R. P.; Maidment, D. R.; Dash, P. K.; Stealey, M.; Yi, H.; Gan, T.; Castronova, A. M.; Miles, B.; Li, Z.; Morsy, M. M.

2015-12-01

HydroShare is an online, collaborative system for open sharing of hydrologic data, analytical tools, and models. It supports the sharing of and collaboration around "resources" which are defined primarily by standardized metadata, content data models for each resource type, and an overarching resource data model based on the Open Archives Initiative's Object Reuse and Exchange (OAI-ORE) standard and a hierarchical file packaging system called "BagIt". HydroShare expands the data sharing capability of the CUAHSI Hydrologic Information System by broadening the classes of data accommodated to include geospatial and multidimensional space-time datasets commonly used in hydrology. HydroShare also includes new capability for sharing models, model components, and analytical tools and will take advantage of emerging social media functionality to enhance information about and collaboration around hydrologic data and models. It also supports web services and server/cloud based computation operating on resources for the execution of hydrologic models and analysis and visualization of hydrologic data. HydroShare uses iRODS as a network file system for underlying storage of datasets and models. Collaboration is enabled by casting datasets and models as "social objects". Social functions include both private and public sharing, formation of collaborative groups of users, and value-added annotation of shared datasets and models. The HydroShare web interface and social media functions were developed using the Django web application framework coupled to iRODS. Data visualization and analysis is supported through the Tethys Platform web GIS software stack. Links to external systems are supported by RESTful web service interfaces to HydroShare's content. This presentation will introduce the HydroShare functionality developed to date and describe ongoing development of functionality to support collaboration and integration of data and models.

Exploratory study on Marine SDI implementation in Malaysia

NASA Astrophysics Data System (ADS)

Tarmidi, Zakri; Mohd Shariff, Abdul Rashid; Rodzi Mahmud, Ahmad; Zaiton Ibrahim, Zelina; Halim Hamzah, Abdul

2016-06-01

This paper discusses the explanatory study of the implementation of spatial data sharing between Malaysia's marine organisations. The survey method was selected with questionnaire as an instrument for data collection and analysis. The aim of the questionnaire was to determine the critical factors in enabling marine spatial data sharing in Malaysia, and the relationship between these indicators. A questionnaire was sent to 48 marine and coastal organisations in Malaysia, with 84.4% of respondents answering the questionnaire. The respondents selected were people who involved directly with GIS application in the organisations. The results show there are three main issues in implementing spatial data sharing; (1) GIS planning and implementation in the organisation, (2) spatial data sharing knowledge and implementation in the organisation and (3) collaboration to enable spatial data sharing within and between organisations. To improve GIS implementation, spatial data sharing implementation and collaboration in enabling spatial data sharing, a conceptual collaboration model was proposed with components of marine GIS strategic planning, spatial data sharing strategies and collaboration strategy.

In silico tools for sharing data and knowledge on toxicity and metabolism: derek for windows, meteor, and vitic.

PubMed

Marchant, Carol A; Briggs, Katharine A; Long, Anthony

2008-01-01

ABSTRACT Lhasa Limited is a not-for-profit organization that exists to promote the sharing of data and knowledge in chemistry and the life sciences. It has developed the software tools Derek for Windows, Meteor, and Vitic to facilitate such sharing. Derek for Windows and Meteor are knowledge-based expert systems that predict the toxicity and metabolism of a chemical, respectively. Vitic is a chemically intelligent toxicity database. An overview of each software system is provided along with examples of the sharing of data and knowledge in the context of their development. These examples include illustrations of (1) the use of data entry and editing tools for the sharing of data and knowledge within organizations; (2) the use of proprietary data to develop nonconfidential knowledge that can be shared between organizations; (3) the use of shared expert knowledge to refine predictions; (4) the sharing of proprietary data between organizations through the formation of data-sharing groups; and (5) the use of proprietary data to validate predictions. Sharing of chemical toxicity and metabolism data and knowledge in this way offers a number of benefits including the possibilities of faster scientific progress and reductions in the use of animals in testing. Maximizing the accessibility of data also becomes increasingly crucial as in silico systems move toward the prediction of more complex phenomena for which limited data are available.

Institutional and Individual Influences on Scientists' Data Sharing Behaviors

ERIC Educational Resources Information Center

Kim, Youngseek

2013-01-01

In modern research activities, scientific data sharing is essential, especially in terms of data-intensive science and scholarly communication. Scientific communities are making ongoing endeavors to promote scientific data sharing. Currently, however, data sharing is not always well-deployed throughout diverse science and engineering disciplines.…

Qualitative Data Sharing Practices in Social Sciences

ERIC Educational Resources Information Center

Jeng, Wei

2017-01-01

Social scientists have been sharing data for a long time. Sharing qualitative data, however, has not become a common practice, despite the context of e-Research, information growth, and funding agencies' mandates on research data archiving and sharing. Since most systematic and comprehensive studies are based on quantitative data practices, little…

Data sharing platforms for de-identified data from human clinical trials.

PubMed

Huser, Vojtech; Shmueli-Blumberg, Dikla

2018-04-01

Data sharing of de-identified individual participant data is being adopted by an increasing number of sponsors of human clinical trials. In addition to standardizing data syntax for shared trial data, semantic integration of various data elements is the focus of several initiatives that define research common data elements. This perspective article, in the first part, compares several data sharing platforms for de-identified clinical research data in terms of their size, policies and supported features. In the second part, we use a case study approach to describe in greater detail one data sharing platform (Data Share from National Institute of Drug Abuse). We present data on the past use of the platform, data formats offered, data de-identification approaches and its use of research common data elements. We conclude with a summary of current and expected future trends that facilitate secondary research use of data from completed human clinical trials.

To share or not to share: a randomized trial of consent for data sharing in genome research.

PubMed

McGuire, Amy L; Oliver, Jill M; Slashinski, Melody J; Graves, Jennifer L; Wang, Tao; Kelly, P Adam; Fisher, William; Lau, Ching C; Goss, John; Okcu, Mehmet; Treadwell-Deering, Diane; Goldman, Alica M; Noebels, Jeffrey L; Hilsenbeck, Susan G

2011-11-01

Despite growing concerns toward maintaining participants' privacy, individual investigators collecting tissue and other biological specimens for genomic analysis are encouraged to obtain informed consent for broad data sharing. Our purpose was to assess the effect on research enrollment and data sharing decisions of three different consent types (traditional, binary, or tiered) with varying levels of control and choices regarding data sharing. A single-blinded, randomized controlled trial was conducted with 323 eligible adult participants being recruited into one of six genome studies at Baylor College of Medicine in Houston, Texas, between January 2008 and August 2009. Participants were randomly assigned to one of three experimental consent documents (traditional, n = 110; binary, n = 103; and tiered, n = 110). Debriefing in follow-up visits provided participants a detailed review of all consent types and the chance to change data sharing choices or decline genome study participation. Before debriefing, 83.9% of participants chose public data release. After debriefing, 53.1% chose public data release, 33.1% chose restricted (controlled access database) release, and 13.7% opted out of data sharing. Only one participant declined genome study participation due to data sharing concerns. Our findings indicate that most participants are willing to publicly release their genomic data; however, a significant portion prefers restricted release. These results suggest discordance between existing data sharing policies and participants' judgments and desires.

Challenges to complete and useful data sharing.

PubMed

Mbuagbaw, Lawrence; Foster, Gary; Cheng, Ji; Thabane, Lehana

2017-02-14

Data sharing from clinical trials is one way of promoting fair and transparent conduct of clinical trials. It would maximise the use of data and permit the exploration of additional hypotheses. On the other hand, the quality of secondary analyses cannot always be ascertained, and it may be unfair to investigators who have expended resources to collect data to bear the additional burden of sharing. As the discussion on the best modalities of sharing data evolves, some of the practical issues that may arise need to be addressed. In this paper, we discuss issues which impede the use of data even when sharing should be possible: (1) multicentre studies requiring consent from all the investigators in each centre; (2) remote access platforms with software limitations and Internet requirements; (3) on-site data analysis when data cannot be moved; (4) governing bodies for data generated in one jurisdiction and analysed in another; (5) using programmatic data collected as part of routine care; (6) data collected in multiple languages; (7) poor data quality. We believe these issues apply to all primary data and cause undue difficulties in conducting analysis even when there is some willingness to share. They can be avoided by anticipating the possibility of sharing any clinical data and pre-emptively removing or addressing restrictions that limit complete sharing. These issues should be part of the data sharing discussion.

Sharing health-related data: a privacy test?

PubMed Central

Dyke, Stephanie OM; Dove, Edward S; Knoppers, Bartha M

2016-01-01

Greater sharing of potentially sensitive data raises important ethical, legal and social issues (ELSI), which risk hindering and even preventing useful data sharing if not properly addressed. One such important issue is respecting the privacy-related interests of individuals whose data are used in genomic research and clinical care. As part of the Global Alliance for Genomics and Health (GA4GH), we examined the ELSI status of health-related data that are typically considered ‘sensitive’ in international policy and data protection laws. We propose that ‘tiered protection’ of such data could be implemented in contexts such as that of the GA4GH Beacon Project to facilitate responsible data sharing. To this end, we discuss a Data Sharing Privacy Test developed to distinguish degrees of sensitivity within categories of data recognised as ‘sensitive’. Based on this, we propose guidance for determining the level of protection when sharing genomic and health-related data for the Beacon Project and in other international data sharing initiatives. PMID:27990299

Data Management in Astrobiology: Challenges and Opportunities for an Interdisciplinary Community

PubMed Central

Suomela, Todd; Malone, Jim

2014-01-01

Abstract Data management and sharing are growing concerns for scientists and funding organizations throughout the world. Funding organizations are implementing requirements for data management plans, while scientists are establishing new infrastructures for data sharing. One of the difficulties is sharing data among a diverse set of research disciplines. Astrobiology is a unique community of researchers, containing over 110 different disciplines. The current study reports the results of a survey of data management practices among scientists involved in the astrobiology community and the NASA Astrobiology Institute (NAI) in particular. The survey was administered over a 2-month period in the first half of 2013. Fifteen percent of the NAI community responded (n=114), and additional (n=80) responses were collected from members of an astrobiology Listserv. The results of the survey show that the astrobiology community shares many of the same concerns for data sharing as other groups. The benefits of data sharing are acknowledged by many respondents, but barriers to data sharing remain, including lack of acknowledgement, citation, time, and institutional rewards. Overcoming technical, institutional, and social barriers to data sharing will be a challenge into the future. Key Words: Data management—Data sharing—Data preservation. Astrobiology 14, 451–461. PMID:24840364

Parallel compression of data chunks of a shared data object using a log-structured file system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bent, John M.; Faibish, Sorin; Grider, Gary

2016-10-25

Techniques are provided for parallel compression of data chunks being written to a shared object. A client executing on a compute node or a burst buffer node in a parallel computing system stores a data chunk generated by the parallel computing system to a shared data object on a storage node by compressing the data chunk; and providing the data compressed data chunk to the storage node that stores the shared object. The client and storage node may employ Log-Structured File techniques. The compressed data chunk can be de-compressed by the client when the data chunk is read. A storagemore » node stores a data chunk as part of a shared object by receiving a compressed version of the data chunk from a compute node; and storing the compressed version of the data chunk to the shared data object on the storage node.« less

Steganography on multiple MP3 files using spread spectrum and Shamir's secret sharing

NASA Astrophysics Data System (ADS)

Yoeseph, N. M.; Purnomo, F. A.; Riasti, B. K.; Safiie, M. A.; Hidayat, T. N.

2016-11-01

The purpose of steganography is how to hide data into another media. In order to increase security of data, steganography technique is often combined with cryptography. The weakness of this combination technique is the data was centralized. Therefore, a steganography technique is develop by using combination of spread spectrum and secret sharing technique. In steganography with secret sharing, shares of data is created and hidden in several medium. Medium used to concealed shares were MP3 files. Hiding technique used was Spread Spectrum. Secret sharing scheme used was Shamir's Secret Sharing. The result showed that steganography with spread spectrum combined with Shamir's Secret Share using MP3 files as medium produce a technique that could hid data into several cover. To extract and reconstruct the data hidden in stego object, it is needed the amount of stego object which more or equal to its threshold. Furthermore, stego objects were imperceptible and robust.

Citizen Science: Data Sharing For, By, and With the Public

NASA Astrophysics Data System (ADS)

Wiggins, A.

2017-12-01

Data sharing in citizen science is just as challenging as it is for any other type of science, except that there are more parties involved, with more diverse needs and interests. This talk provides an overview of the challenges and current efforts to advance data sharing in citizen science, and suggests refocusing data management activities on supporting the needs of multiple audiences. Early work on data sharing in citizen science advocated applying the standards and practices of academia, which can only address the needs of one of several audiences for citizen science data, and academics are not always the primary audience. Practitioners still need guidance on how to better share data other key parties, such as participants and policymakers, and which data management practices to prioritize for addressing the needs of multiple audiences. The benefits to the project of investing scarce resources into data products and dissemination strategies for each target audience still remain variable, unclear, or unpredictable. And as projects mature and change, the importance of data sharing activities and audiences are likely to change as well. This combination of multiple diverse audiences, shifting priorities, limited resources, and unclear benefits creates a perfect storm of conditions to suppress data sharing. Nonetheless, many citizen science projects make the effort, with exemplars showing substantial returns on data stewardship investments, and international initiatives are underway to bolster the data sharing capacity of the field. To improve the state of data sharing in citizen science, strategic use of limited resources suggests prioritizing data management activities that support the needs of multiple audiences. These may include better transparency about data access and usage, and standardized reporting of broader impacts from secondary data users, to both reward projects and incentivize further data sharing.

Challenges in sharing of geospatial data by data custodians in South Africa

NASA Astrophysics Data System (ADS)

Kay, Sissiel E.

2018-05-01

As most development planning and rendering of public services happens at a place or in a space, geospatial data is required. This geospatial data is best managed through a spatial data infrastructure, which has as a key objective to share geospatial data. The collection and maintenance of geospatial data is expensive and time consuming and so the principle of "collect once - use many times" should apply. It is best to obtain the geospatial data from the authoritative source - the appointed data custodian. In South Africa the South African Spatial Data Infrastructure (SASDI) is the means to achieve the requirement for geospatial data sharing. This requires geospatial data sharing to take place between the data custodian and the user. All data custodians are expected to comply with the Spatial Data Infrastructure Act (SDI Act) in terms of geo-spatial data sharing. Currently data custodians are experiencing challenges with regard to the sharing of geospatial data. This research is based on the current ten data themes selected by the Committee for Spatial Information and the organisations identified as the data custodians for these ten data themes. The objectives are to determine whether the identified data custodians comply with the SDI Act with respect to geospatial data sharing, and if not what are the reasons for this. Through an international comparative assessment it then determines if the compliance with the SDI Act is not too onerous on the data custodians. The research concludes that there are challenges with geospatial data sharing in South Africa and that the data custodians only partially comply with the SDI Act in terms of geospatial data sharing. However, it is shown that the South African legislation is not too onerous on the data custodians.

A game theoretic analysis of research data sharing.

PubMed

Pronk, Tessa E; Wiersma, Paulien H; van Weerden, Anne; Schieving, Feike

2015-01-01

While reusing research data has evident benefits for the scientific community as a whole, decisions to archive and share these data are primarily made by individual researchers. In this paper we analyse, within a game theoretical framework, how sharing and reuse of research data affect individuals who share or do not share their datasets. We construct a model in which there is a cost associated with sharing datasets whereas reusing such sets implies a benefit. In our calculations, conflicting interests appear for researchers. Individual researchers are always better off not sharing and omitting the sharing cost, at the same time both sharing and not sharing researchers are better off if (almost) all researchers share. Namely, the more researchers share, the more benefit can be gained by the reuse of those datasets. We simulated several policy measures to increase benefits for researchers sharing or reusing datasets. Results point out that, although policies should be able to increase the rate of sharing researchers, and increased discoverability and dataset quality could partly compensate for costs, a better measure would be to directly lower the cost for sharing, or even turn it into a (citation-) benefit. Making data available would in that case become the most profitable, and therefore stable, strategy. This means researchers would willingly make their datasets available, and arguably in the best possible way to enable reuse.

Assessing the Extent and Impact of Online Data Sharing in Eddy Covariance Flux Research

NASA Astrophysics Data System (ADS)

Dai, Sheng-Qi; Li, Hong; Xiong, Jun; Ma, Jun; Guo, Hai-Qiang; Xiao, Xiangming; Zhao, Bin

2018-01-01

Research data sharing is appealing for its potential benefits on sharers' scientific impact and is also advocated by various policies. How do scientific benefits and policies correlate with practical ecological data sharing? In this study, we investigated data-sharing practices in eddy covariance flux research as a typical case. First, we collected researchers' data-sharing information from major observation networks. Then, we downloaded bibliometric data from the Web of Science and evaluated scientific impact using LeaderRank, a synthetic algorithm that takes both citation and cooperation impacts into consideration. Our results demonstrated the following: (1) specific to eddy covariance flux research, 8% of researchers published information in public data portals, whereas 64% of researchers provided their available data online in a downloadable form; (2) regional differences in data sharing, publications, and observation networks existed; and (3) the data sharers in impact-ranked ecologists followed a long-tail distribution, which suggested that, although sharing data is not necessary for researchers to be influential, data sharers are more likely to be high-impact researchers. Differentiated policies should be proposed to encourage ecologists in the long tail of data sharers, and from regions with little tradition of data sharing, to embrace a more open model of science.

Development of a consent resource for genomic data sharing in the clinical setting.

PubMed

Riggs, Erin Rooney; Azzariti, Danielle R; Niehaus, Annie; Goehringer, Scott R; Ramos, Erin M; Rodriguez, Laura Lyman; Knoppers, Bartha; Rehm, Heidi L; Martin, Christa Lese

2018-06-13

Data sharing between clinicians, laboratories, and patients is essential for improvements in genomic medicine, but obtaining consent for individual-level data sharing is often hindered by a lack of time and resources. To address this issue, the Clinical Genome Resource (ClinGen) developed tools to facilitate consent, including a one-page consent form and online supplemental video with information on key topics, such as risks and benefits of data sharing. To determine whether the consent form and video accurately conveyed key data sharing concepts, we surveyed 5,162 members of the general public. We measured comprehension at baseline, after reading the form and watching the video. Additionally, we assessed participants' attitudes toward genomic data sharing. Participants' performance on comprehension questions significantly improved over baseline after reading the form and continued to improve after watching the video. Results suggest reading the form alone provided participants with important knowledge regarding broad data sharing, and watching the video allowed for broader comprehension. These materials are now available at http://www.clinicalgenome.org/share . These resources will provide patients a straightforward way to share their genetic and health information, and improve the scientific community's access to data generated through routine healthcare.

"You Cannot Collect Data Using Your Own Resources And Put It On Open Access": Perspectives From Africa About Public Health Data-Sharing.

PubMed

Anane-Sarpong, Evelyn; Wangmo, Tenzin; Ward, Claire Leonie; Sankoh, Osman; Tanner, Marcel; Elger, Bernice Simone

2017-07-25

Data-sharing is a desired default in the field of public health and a source of much ethical deliberation. Sharing data potentially contributes the largest, most efficient source of scientific data, but is fraught with contextual challenges which make stakeholders, particularly those in under-resourced contexts hesitant or slow to share. Relatively little empirical research has engaged stakeholders in discussing the issue. This study sought to explore relevant experiences, contextual, and subjective explanations around the topic to provide a rich and detailed presentation of what it means to different stakeholders and contexts to share data and how that can guide practice and ethical guidance. A qualitative design involving interviews was undertaken with professionals working in public health institutions endowed with data (HDSS), ethics committees, and advisory agencies which help shape health research in Africa. A descriptive form of thematic analysis was used to summarize results into six key themes: (1) The role of HDSSs in research using public health data and data-sharing; (2) Ownership and funding are critical factors influencing data-sharing; (3) Other factors discourage data-sharing; (4) Promoting and sustaining data-sharing; (5) Ethical guidance structures; and (6) Establishing effective guidance. The themes reveal factors regarding the willingness or not to share and an intricate ethical system that current discourse could reflect. Many of the concerns resonate with the literature, but a whole other gamut of people and process issues; commitments, investments, careers, and the right ethical guidance are needed to realize a sustainable goal of reaching 'share' as a default. © 2017 John Wiley & Sons Ltd.

Attitudes Towards Data Collection, Ownership and Sharing Among Patients with Parkinson's Disease.

PubMed

Mursaleen, Leah Rose; Stamford, Jon Andrew; Jones, David Ashford; Windle, Richard; Isaacs, Tom

2017-01-01

The ownership and sharing of patient medical data is an increasingly contentious subject in medicine generally but also within the field of Parkinson's disease (PD). Despite being the providers of the medical data, patients are rarely consulted as to its usage. The objective of this paper is to establish patient attitudes to ownership of their own medical data and the sharing thereof. We report here the results of an online survey of people with Parkinson's. A total of 310 people took part in the 'sharing data' component of the survey, answering some or all of the questions for which they were eligible. Most respondents (208/306) were aged between 55 and 74 years. 55% of the sample were female and the mean number of years diagnosed was 7.1. Although 93% of respondents were willing to share data, only 41% were currently doing so and a further 8% did not know whether they were sharing any information in this way. There was a significant association between age and data sharing (p = 0.006). However, no clear relationship was found between data sharing and the number of years diagnosed, sex, medication class or health confidence. There was also no consensus among patients on ownership of, access to and usage of their research data. The lack of consensus on data ownership and general absence of clear demographic predictors of data sharing implies impaired communication pathways. We suggest that strategies directed towards improved communication may help to clarify data ownership and promote data sharing.

An ethical framework for sharing patient data without consent.

PubMed

Navarro, Robert

2008-01-01

There is no consensus on how to share patient records privately. Data privacy concepts are surveyed and a framework is presented for the safe sharing of sensitive data. It is argued that tailoring the data sharing to the privacy breach risks of each project holds out the best compromise for keeping the trust of the public and providing for the best quality data where detailed patient consent is not possible. To improve the protection of data by reducing privacy breaches and thus enable appropriate patient data sharing without consent. Any harm arising from data sharing must come from the data being identified, either fully or partially. The first step is an agreement on an acceptable privacy breach risk. Next, proceed to measure that risk for the proposed data when held by a given recipient. Finally, select from a menu of mitigation strategies (people, process and technical) to achieve acceptable risk. The framework is tested against the current UK approach administered by the Patient Information Advisory Group. The hard problem of non-consented data sharing should be divided into the easier (though non-trivial) ones of data and recipient breach risk measurement. Directed research in these two areas will help move the data sharing problem into the 'solved' pile.

UK publicly funded Clinical Trials Units supported a controlled access approach to share individual participant data but highlighted concerns

PubMed Central

Hopkins, Carolyn; Sydes, Matthew; Murray, Gordon; Woolfall, Kerry; Clarke, Mike; Williamson, Paula; Tudur Smith, Catrin

2016-01-01

Objectives Evaluate current data sharing activities of UK publicly funded Clinical Trial Units (CTUs) and identify good practices and barriers. Study Design and Setting Web-based survey of Directors of 45 UK Clinical Research Collaboration (UKCRC)–registered CTUs. Results Twenty-three (51%) CTUs responded: Five (22%) of these had an established data sharing policy and eight (35%) specifically requested consent to use patient data beyond the scope of the original trial. Fifteen (65%) CTUs had received requests for data, and seven (30%) had made external requests for data in the previous 12 months. CTUs supported the need for increased data sharing activities although concerns were raised about patient identification, misuse of data, and financial burden. Custodianship of clinical trial data and requirements for a CTU to align its policy to their parent institutes were also raised. No CTUs supported the use of an open access model for data sharing. Conclusion There is support within the publicly funded UKCRC-registered CTUs for data sharing, but many perceived barriers remain. CTUs are currently using a variety of approaches and procedures for sharing data. This survey has informed further work, including development of guidance for publicly funded CTUs, to promote good practice and facilitate data sharing. PMID:26169841

Time to consider sharing data extracted from trials included in systematic reviews.

PubMed

Wolfenden, Luke; Grimshaw, Jeremy; Williams, Christopher M; Yoong, Sze Lin

2016-11-03

While the debate regarding shared clinical trial data has shifted from whether such data should be shared to how this is best achieved, the sharing of data collected as part of systematic reviews has received little attention. In this commentary, we discuss the potential benefits of coordinated efforts to share data collected as part of systematic reviews. There are a number of potential benefits of systematic review data sharing. Shared information and data obtained as part of the systematic review process may reduce unnecessary duplication, reduce demand on trialist to service repeated requests from reviewers for data, and improve the quality and efficiency of future reviews. Sharing also facilitates research to improve clinical trial and systematic review methods and supports additional analyses to address secondary research questions. While concerns regarding appropriate use of data, costs, or the academic return for original review authors may impede more open access to information extracted as part of systematic reviews, many of these issues are being addressed, and infrastructure to enable greater access to such information is being developed. Embracing systems to enable more open access to systematic review data has considerable potential to maximise the benefits of research investment in undertaking systematic reviews.

Changes in Data Sharing and Data Reuse Practices and Perceptions among Scientists Worldwide

PubMed Central

Tenopir, Carol; Dalton, Elizabeth D.; Allard, Suzie; Frame, Mike; Pjesivac, Ivanka; Birch, Ben; Pollock, Danielle; Dorsett, Kristina

2015-01-01

The incorporation of data sharing into the research lifecycle is an important part of modern scholarly debate. In this study, the DataONE Usability and Assessment working group addresses two primary goals: To examine the current state of data sharing and reuse perceptions and practices among research scientists as they compare to the 2009/2010 baseline study, and to examine differences in practices and perceptions across age groups, geographic regions, and subject disciplines. We distributed surveys to a multinational sample of scientific researchers at two different time periods (October 2009 to July 2010 and October 2013 to March 2014) to observe current states of data sharing and to see what, if any, changes have occurred in the past 3–4 years. We also looked at differences across age, geographic, and discipline-based groups as they currently exist in the 2013/2014 survey. Results point to increased acceptance of and willingness to engage in data sharing, as well as an increase in actual data sharing behaviors. However, there is also increased perceived risk associated with data sharing, and specific barriers to data sharing persist. There are also differences across age groups, with younger respondents feeling more favorably toward data sharing and reuse, yet making less of their data available than older respondents. Geographic differences exist as well, which can in part be understood in terms of collectivist and individualist cultural differences. An examination of subject disciplines shows that the constraints and enablers of data sharing and reuse manifest differently across disciplines. Implications of these findings include the continued need to build infrastructure that promotes data sharing while recognizing the needs of different research communities. Moving into the future, organizations such as DataONE will continue to assess, monitor, educate, and provide the infrastructure necessary to support such complex grand science challenges. PMID:26308551

Changes in data sharing and data reuse practices and perceptions among scientists worldwide

USGS Publications Warehouse

Tenopir, Carol; Dalton, Elizabeth D.; Allard, Suzie; Frame, Mike; Pjesivac, Ivanka; Birch, Ben; Pollock, Danielle; Dorsett, Kristina

2015-01-01

The incorporation of data sharing into the research lifecycle is an important part of modern scholarly debate. In this study, the DataONE Usability and Assessment working group addresses two primary goals: To examine the current state of data sharing and reuse perceptions and practices among research scientists as they compare to the 2009/2010 baseline study, and to examine differences in practices and perceptions across age groups, geographic regions, and subject disciplines. We distributed surveys to a multinational sample of scientific researchers at two different time periods (October 2009 to July 2010 and October 2013 to March 2014) to observe current states of data sharing and to see what, if any, changes have occurred in the past 3–4 years. We also looked at differences across age, geographic, and discipline-based groups as they currently exist in the 2013/2014 survey. Results point to increased acceptance of and willingness to engage in data sharing, as well as an increase in actual data sharing behaviors. However, there is also increased perceived risk associated with data sharing, and specific barriers to data sharing persist. There are also differences across age groups, with younger respondents feeling more favorably toward data sharing and reuse, yet making less of their data available than older respondents. Geographic differences exist as well, which can in part be understood in terms of collectivist and individualist cultural differences. An examination of subject disciplines shows that the constraints and enablers of data sharing and reuse manifest differently across disciplines. Implications of these findings include the continued need to build infrastructure that promotes data sharing while recognizing the needs of different research communities. Moving into the future, organizations such as DataONE will continue to assess, monitor, educate, and provide the infrastructure necessary to support such complex grand science challenges.

Hidden concerns of sharing research data by low/middle-income country scientists.

PubMed

Bezuidenhout, Louise; Chakauya, Ereck

2018-01-01

There has considerable interest in bringing low/middle-income countries (LMIC) scientists into discussions on Open Data - both as contributors and users. The establishment of in situ data sharing practices within LMIC research institutions is vital for the development of an Open Data landscape in the Global South. Nonetheless, many LMICs have significant challenges - resource provision, research support and extra-laboratory infrastructures. These low-resourced environments shape data sharing activities, but are rarely examined within Open Data discourse. In particular, little attention is given to how these research environments shape scientists' perceptions of data sharing (dis)incentives. This paper expands on these issues of incentivizing data sharing, using data from a quantitative survey disseminated to life scientists in 13 countries in sub-Saharan Africa. This interrogated not only perceptions of data sharing amongst LMIC scientists, but also how these are connected to the research environments and daily challenges experienced by them. The paper offers a series of analysis around commonly cited (dis)incentives such as data sharing as a means of improving research visibility; sharing and funding; and online connectivity. It identifies key areas that the Open Data community need to consider if true openness in research is to be established in the Global South.

Africa and China Higher Education Cooperation: Establishing Knowledge Sharing Partnership between Students

ERIC Educational Resources Information Center

Gonondo, Jean

2017-01-01

Knowledge sharing should not be confused neither with data sharing nor with information sharing; the knowledge sharing includes data and information sharing, skills and expertise communication, ideas exchange. Since the fourth FOCAC held in Egypt in 2009, many policies have been added to reinforce Africa and China educational cooperation,…

Data Sharing: Convert Challenges into Opportunities.

PubMed

Figueiredo, Ana Sofia

2017-01-01

Initiatives for sharing research data are opportunities to increase the pace of knowledge discovery and scientific progress. The reuse of research data has the potential to avoid the duplication of data sets and to bring new views from multiple analysis of the same data set. For example, the study of genomic variations associated with cancer profits from the universal collection of such data and helps in selecting the most appropriate therapy for a specific patient. However, data sharing poses challenges to the scientific community. These challenges are of ethical, cultural, legal, financial, or technical nature. This article reviews the impact that data sharing has in science and society and presents guidelines to improve the efficient sharing of research data.

Data Sharing: Convert Challenges into Opportunities

PubMed Central

Figueiredo, Ana Sofia

2017-01-01

Initiatives for sharing research data are opportunities to increase the pace of knowledge discovery and scientific progress. The reuse of research data has the potential to avoid the duplication of data sets and to bring new views from multiple analysis of the same data set. For example, the study of genomic variations associated with cancer profits from the universal collection of such data and helps in selecting the most appropriate therapy for a specific patient. However, data sharing poses challenges to the scientific community. These challenges are of ethical, cultural, legal, financial, or technical nature. This article reviews the impact that data sharing has in science and society and presents guidelines to improve the efficient sharing of research data. PMID:29270401

42 CFR 425.700 - General rules.

Code of Federal Regulations, 2014 CFR

2014-10-01

... privacy of individually identifiable health information and comply with the terms of the data use...) MEDICARE PROGRAM (CONTINUED) MEDICARE SHARED SAVINGS PROGRAM Data Sharing With ACOs § 425.700 General rules. (a) CMS shares aggregate reports with the ACO. (b) CMS shares beneficiary identifiable data with ACOs...

Willing and unwilling to share primary biodiversity data: results and implications of an international survey

USDA-ARS?s Scientific Manuscript database

Biodiversity studies and conservation programs increasingly depend on data sharing and integration. But many researchers resist sharing their primary biodiversity data. This international survey was conducted to study the attitudes, experiences and expectations regarding the sharing of biodiversity ...

Data Sharing and Scientific Impact in Eddy Covariance Research

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bond-Lamberty, B.

Do the benefits of data sharing outweigh its perceived costs? This is a critical question, and one with the potential to change culture and behavior. Dai et al. (2018) examine how data sharing is related to scientific impact in the field of eddy covariance (EC), and find that data sharers are disproportionately high-impact researchers, and vice versa; they also note strong regional differences in EC data sharing norms. The current policies and restrictions of EC journals and repositories are highly uneven. Incentivizing data sharing and enhancing computational reproducibility are critical next steps for EC, ecology, and science more broadly.

Impact of HIPAA’s Minimum Necessary Standard on Genomic Data Sharing

PubMed Central

Evans, Barbara J.; Jarvik, Gail P.

2017-01-01

Purpose This article provides a brief introduction to the HIPAA Privacy Rule’s minimum necessary standard, which applies to sharing of genomic data, particularly clinical data, following 2013 Privacy Rule revisions. Methods This research used the Thomson Reuters Westlaw™ database and law library resources in its legal analysis of the HIPAA privacy tiers and the impact of the minimum necessary standard on genomic data-sharing. We considered relevant example cases of genomic data-sharing needs. Results In a climate of stepped-up HIPAA enforcement, this standard is of concern to laboratories that generate, use, and share genomic information. How data-sharing activities are characterized—whether for research, public health, or clinical interpretation and medical practice support—affects how the minimum necessary standard applies and its overall impact on data access and use. Conclusion There is no clear regulatory guidance on how to apply HIPAA’s minimum necessary standard when considering the sharing of information in the data-rich environment of genomic testing. Laboratories that perform genomic testing should engage with policy-makers to foster sound, well-informed policies and appropriate characterization of data-sharing activities to minimize adverse impacts on day-to-day workflows. PMID:28914268

Impact of HIPAA's minimum necessary standard on genomic data sharing.

PubMed

Evans, Barbara J; Jarvik, Gail P

2018-04-01

This article provides a brief introduction to the Health Insurance Portability and Accountability Act of 1996 (HIPAA) Privacy Rule's minimum necessary standard, which applies to sharing of genomic data, particularly clinical data, following 2013 Privacy Rule revisions. This research used the Thomson Reuters Westlaw database and law library resources in its legal analysis of the HIPAA privacy tiers and the impact of the minimum necessary standard on genomic data sharing. We considered relevant example cases of genomic data-sharing needs. In a climate of stepped-up HIPAA enforcement, this standard is of concern to laboratories that generate, use, and share genomic information. How data-sharing activities are characterized-whether for research, public health, or clinical interpretation and medical practice support-affects how the minimum necessary standard applies and its overall impact on data access and use. There is no clear regulatory guidance on how to apply HIPAA's minimum necessary standard when considering the sharing of information in the data-rich environment of genomic testing. Laboratories that perform genomic testing should engage with policy makers to foster sound, well-informed policies and appropriate characterization of data-sharing activities to minimize adverse impacts on day-to-day workflows.

Classification of processes involved in sharing individual participant data from clinical trials.

PubMed

Ohmann, Christian; Canham, Steve; Banzi, Rita; Kuchinke, Wolfgang; Battaglia, Serena

2018-01-01

Background: In recent years, a cultural change in the handling of data from research has resulted in the strong promotion of a culture of openness and increased sharing of data. In the area of clinical trials, sharing of individual participant data involves a complex set of processes and the interaction of many actors and actions. Individual services/tools to support data sharing are available, but what is missing is a detailed, structured and comprehensive list of processes/subprocesses involved and tools/services needed. Methods : Principles and recommendations from a published data sharing consensus document are analysed in detail by a small expert group. Processes/subprocesses involved in data sharing are identified and linked to actors and possible services/tools. Definitions are adapted from the business process model and notation (BPMN) and applied in the analysis. Results: A detailed and comprehensive list of individual processes/subprocesses involved in data sharing, structured according to 9 main processes, is provided. Possible tools/services to support these processes/subprocesses are identified and grouped according to major type of support. Conclusions: The list of individual processes/subprocesses and tools/services identified is a first step towards development of a generic framework or architecture for sharing of data from clinical trials. Such a framework is strongly needed to give an overview of how various actors, research processes and services could form an interoperable system for data sharing.

Classification of processes involved in sharing individual participant data from clinical trials

PubMed Central

Ohmann, Christian; Canham, Steve; Banzi, Rita; Kuchinke, Wolfgang; Battaglia, Serena

2018-01-01

Background: In recent years, a cultural change in the handling of data from research has resulted in the strong promotion of a culture of openness and increased sharing of data. In the area of clinical trials, sharing of individual participant data involves a complex set of processes and the interaction of many actors and actions. Individual services/tools to support data sharing are available, but what is missing is a detailed, structured and comprehensive list of processes/subprocesses involved and tools/services needed. Methods: Principles and recommendations from a published data sharing consensus document are analysed in detail by a small expert group. Processes/subprocesses involved in data sharing are identified and linked to actors and possible services/tools. Definitions are adapted from the business process model and notation (BPMN) and applied in the analysis. Results: A detailed and comprehensive list of individual processes/subprocesses involved in data sharing, structured according to 9 main processes, is provided. Possible tools/services to support these processes/subprocesses are identified and grouped according to major type of support. Conclusions: The list of individual processes/subprocesses and tools/services identified is a first step towards development of a generic framework or architecture for sharing of data from clinical trials. Such a framework is strongly needed to give an overview of how various actors, research processes and services could form an interoperable system for data sharing. PMID:29623192

A review of data sharing statements in observational studies published in the BMJ: A cross-sectional study

PubMed Central

McDonald, Laura; Schultze, Anna; Simpson, Alex; Graham, Sophie; Wasiak, Radek; Ramagopalan, Sreeram V.

2017-01-01

In order to understand the current state of data sharing in observational research studies, we reviewed data sharing statements of observational studies published in a general medical journal, the British Medical Journal. We found that the majority (63%) of observational studies published between 2015 and 2017 included a statement that implied that data used in the study could not be shared. If the findings of our exploratory study are confirmed, room for improvement in the sharing of real-world or observational research data exists. PMID:29167735

Integrating hydrologic modeling web services with online data sharing to prepare, store, and execute models in hydrology

NASA Astrophysics Data System (ADS)

Gan, T.; Tarboton, D. G.; Dash, P. K.; Gichamo, T.; Horsburgh, J. S.

2017-12-01

Web based apps, web services and online data and model sharing technology are becoming increasingly available to support research. This promises benefits in terms of collaboration, platform independence, transparency and reproducibility of modeling workflows and results. However, challenges still exist in real application of these capabilities and the programming skills researchers need to use them. In this research we combined hydrologic modeling web services with an online data and model sharing system to develop functionality to support reproducible hydrologic modeling work. We used HydroDS, a system that provides web services for input data preparation and execution of a snowmelt model, and HydroShare, a hydrologic information system that supports the sharing of hydrologic data, model and analysis tools. To make the web services easy to use, we developed a HydroShare app (based on the Tethys platform) to serve as a browser based user interface for HydroDS. In this integration, HydroDS receives web requests from the HydroShare app to process the data and execute the model. HydroShare supports storage and sharing of the results generated by HydroDS web services. The snowmelt modeling example served as a use case to test and evaluate this approach. We show that, after the integration, users can prepare model inputs or execute the model through the web user interface of the HydroShare app without writing program code. The model input/output files and metadata describing the model instance are stored and shared in HydroShare. These files include a Python script that is automatically generated by the HydroShare app to document and reproduce the model input preparation workflow. Once stored in HydroShare, inputs and results can be shared with other users, or published so that other users can directly discover, repeat or modify the modeling work. This approach provides a collaborative environment that integrates hydrologic web services with a data and model sharing system to enable model development and execution. The entire system comprised of the HydroShare app, HydroShare and HydroDS web services is open source and contributes to capability for web based modeling research.

The HydroShare Collaborative Repository for the Hydrology Community

NASA Astrophysics Data System (ADS)

Tarboton, D. G.; Idaszak, R.; Horsburgh, J. S.; Ames, D. P.; Goodall, J. L.; Couch, A.; Hooper, R. P.; Dash, P. K.; Stealey, M.; Yi, H.; Bandaragoda, C.; Castronova, A. M.

2017-12-01

HydroShare is an online, collaboration system for sharing of hydrologic data, analytical tools, and models. It supports the sharing of, and collaboration around, "resources" which are defined by standardized content types for data formats and models commonly used in hydrology. With HydroShare you can: Share your data and models with colleagues; Manage who has access to the content that you share; Share, access, visualize and manipulate a broad set of hydrologic data types and models; Use the web services application programming interface (API) to program automated and client access; Publish data and models and obtain a citable digital object identifier (DOI); Aggregate your resources into collections; Discover and access data and models published by others; Use web apps to visualize, analyze and run models on data in HydroShare. This presentation will describe the functionality and architecture of HydroShare highlighting our approach to making this system easy to use and serving the needs of the hydrology community represented by the Consortium of Universities for the Advancement of Hydrologic Sciences, Inc. (CUAHSI). Metadata for uploaded files is harvested automatically or captured using easy to use web user interfaces. Users are encouraged to add or create resources in HydroShare early in the data life cycle. To encourage this we allow users to share and collaborate on HydroShare resources privately among individual users or groups, entering metadata while doing the work. HydroShare also provides enhanced functionality for users through web apps that provide tools and computational capability for actions on resources. HydroShare's architecture broadly is comprised of: (1) resource storage, (2) resource exploration website, and (3) web apps for actions on resources. System components are loosely coupled and interact through APIs, which enhances robustness, as components can be upgraded and advanced relatively independently. The full power of this paradigm is the extensibility it supports. Web apps are hosted on separate servers, which may be 3rd party servers. They are registered in HydroShare using a web app resource that configures the connectivity for them to be discovered and launched directly from resource types they are associated with.

How Do Astronomers Share Data? Reliability and Persistence of Datasets Linked in AAS Publications and a Qualitative Study of Data Practices among US Astronomers

PubMed Central

Pepe, Alberto; Goodman, Alyssa; Muench, August; Crosas, Merce; Erdmann, Christopher

2014-01-01

We analyze data sharing practices of astronomers over the past fifteen years. An analysis of URL links embedded in papers published by the American Astronomical Society reveals that the total number of links included in the literature rose dramatically from 1997 until 2005, when it leveled off at around 1500 per year. The analysis also shows that the availability of linked material decays with time: in 2011, 44% of links published a decade earlier, in 2001, were broken. A rough analysis of link types reveals that links to data hosted on astronomers' personal websites become unreachable much faster than links to datasets on curated institutional sites. To gauge astronomers' current data sharing practices and preferences further, we performed in-depth interviews with 12 scientists and online surveys with 173 scientists, all at a large astrophysical research institute in the United States: the Harvard-Smithsonian Center for Astrophysics, in Cambridge, MA. Both the in-depth interviews and the online survey indicate that, in principle, there is no philosophical objection to data-sharing among astronomers at this institution. Key reasons that more data are not presently shared more efficiently in astronomy include: the difficulty of sharing large data sets; over reliance on non-robust, non-reproducible mechanisms for sharing data (e.g. emailing it); unfamiliarity with options that make data-sharing easier (faster) and/or more robust; and, lastly, a sense that other researchers would not want the data to be shared. We conclude with a short discussion of a new effort to implement an easy-to-use, robust, system for data sharing in astronomy, at theastrodata.org, and we analyze the uptake of that system to-date. PMID:25165807

How do astronomers share data? Reliability and persistence of datasets linked in AAS publications and a qualitative study of data practices among US astronomers.

PubMed

Pepe, Alberto; Goodman, Alyssa; Muench, August; Crosas, Merce; Erdmann, Christopher

2014-01-01

We analyze data sharing practices of astronomers over the past fifteen years. An analysis of URL links embedded in papers published by the American Astronomical Society reveals that the total number of links included in the literature rose dramatically from 1997 until 2005, when it leveled off at around 1500 per year. The analysis also shows that the availability of linked material decays with time: in 2011, 44% of links published a decade earlier, in 2001, were broken. A rough analysis of link types reveals that links to data hosted on astronomers' personal websites become unreachable much faster than links to datasets on curated institutional sites. To gauge astronomers' current data sharing practices and preferences further, we performed in-depth interviews with 12 scientists and online surveys with 173 scientists, all at a large astrophysical research institute in the United States: the Harvard-Smithsonian Center for Astrophysics, in Cambridge, MA. Both the in-depth interviews and the online survey indicate that, in principle, there is no philosophical objection to data-sharing among astronomers at this institution. Key reasons that more data are not presently shared more efficiently in astronomy include: the difficulty of sharing large data sets; over reliance on non-robust, non-reproducible mechanisms for sharing data (e.g. emailing it); unfamiliarity with options that make data-sharing easier (faster) and/or more robust; and, lastly, a sense that other researchers would not want the data to be shared. We conclude with a short discussion of a new effort to implement an easy-to-use, robust, system for data sharing in astronomy, at theastrodata.org, and we analyze the uptake of that system to-date.

How Do Astronomers Share Data? Reliability and Persistence of Datasets Linked in AAS Publications and a Qualitative Study of Data Practices among US Astronomers

NASA Astrophysics Data System (ADS)

Pepe, Alberto; Goodman, Alyssa; Muench, August; Crosas, Merce; Erdmann, Christopher

2014-08-01

We analyze data sharing practices of astronomers over the past fifteen years. An analysis of URL links embedded in papers published by the American Astronomical Society reveals that the total number of links included in the literature rose dramatically from 1997 until 2005, when it leveled off at around 1500 per year. The analysis also shows that the availability of linked material decays with time: in 2011, 44% of links published a decade earlier, in 2001, were broken. A rough analysis of link types reveals that links to data hosted on astronomers' personal websites become unreachable much faster than links to datasets on curated institutional sites. To gauge astronomers' current data sharing practices and preferences further, we performed in-depth interviews with 12 scientists and online surveys with 173 scientists, all at a large astrophysical research institute in the United States: the Harvard-Smithsonian Center for Astrophysics, in Cambridge, MA. Both the in-depth interviews and the online survey indicate that, in principle, there is no philosophical objection to data-sharing among astronomers at this institution. Key reasons that more data are not presently shared more efficiently in astronomy include: the difficulty of sharing large data sets; over reliance on non-robust, non-reproducible mechanisms for sharing data (e.g. emailing it); unfamiliarity with options that make data-sharing easier (faster) and/or more robust; and, lastly, a sense that other researchers would not want the data to be shared. We conclude with a short discussion of a new effort to implement an easy-to-use, robust, system for data sharing in astronomy, at theastrodata.org, and we analyze the uptake of that system to-date.

Data and Models as Social Objects in the HydroShare System for Collaboration in the Hydrology Community and Beyond

NASA Astrophysics Data System (ADS)

Tarboton, D. G.; Idaszak, R.; Horsburgh, J. S.; Ames, D. P.; Goodall, J. L.; Band, L. E.; Merwade, V.; Couch, A.; Hooper, R. P.; Maidment, D. R.; Dash, P. K.; Stealey, M.; Yi, H.; Gan, T.; Castronova, A. M.; Miles, B.; Li, Z.; Morsy, M. M.; Crawley, S.; Ramirez, M.; Sadler, J.; Xue, Z.; Bandaragoda, C.

2016-12-01

How do you share and publish hydrologic data and models for a large collaborative project? HydroShare is a new, web-based system for sharing hydrologic data and models with specific functionality aimed at making collaboration easier. HydroShare has been developed with U.S. National Science Foundation support under the auspices of the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) to support the collaboration and community cyberinfrastructure needs of the hydrology research community. Within HydroShare, we have developed new functionality for creating datasets, describing them with metadata, and sharing them with collaborators. We cast hydrologic datasets and models as "social objects" that can be shared, collaborated around, annotated, published and discovered. In addition to data and model sharing, HydroShare supports web application programs (apps) that can act on data stored in HydroShare, just as software programs on your PC act on your data locally. This can free you from some of the limitations of local computing capacity and challenges in installing and maintaining software on your own PC. HydroShare's web-based cyberinfrastructure can take work off your desk or laptop computer and onto infrastructure or "cloud" based data and processing servers. This presentation will describe HydroShare's collaboration functionality that enables both public and private sharing with individual users and collaborative user groups, and makes it easier for collaborators to iterate on shared datasets and models, creating multiple versions along the way, and publishing them with a permanent landing page, metadata description, and citable Digital Object Identifier (DOI) when the work is complete. This presentation will also describe the web app architecture that supports interoperability with third party servers functioning as application engines for analysis and processing of big hydrologic datasets. While developed to support the cyberinfrastructure needs of the hydrology community, the informatics infrastructure for programmatic interoperability of web resources has a generality beyond the solution of hydrology problems that will be discussed.

Involving Research Stakeholders in Developing Policy on Sharing Public Health Research Data in Kenya

PubMed Central

Jao, Irene; Kombe, Francis; Mwalukore, Salim; Bull, Susan; Parker, Michael; Kamuya, Dorcas; Molyneux, Sassy

2015-01-01

Increased global sharing of public health research data has potential to advance scientific progress but may present challenges to the interests of research stakeholders, particularly in low-to-middle income countries. Policies for data sharing should be responsive to public views, but there is little evidence of the systematic study of these from low-income countries. This qualitative study explored views on fair data-sharing processes among 60 stakeholders in Kenya with varying research experience, using a deliberative approach. Stakeholders’ attitudes were informed by perceptions of benefit and concerns for research data sharing, including risks of stigmatization, loss of privacy, and undermining scientific careers and validity, reported in detail elsewhere. In this article, we discuss institutional trust-building processes seen as central to perceptions of fairness in sharing research data in this setting, including forms of community involvement, individual prior awareness and agreement to data sharing, independence and accountability of governance mechanisms, and operating under a national framework. PMID:26297748

Whose data set is it anyway? Sharing raw data from randomized trials.

PubMed

Vickers, Andrew J

2006-05-16

Sharing of raw research data is common in many areas of medical research, genomics being perhaps the most well-known example. In the clinical trial community investigators routinely refuse to share raw data from a randomized trial without giving a reason. Data sharing benefits numerous research-related activities: reproducing analyses; testing secondary hypotheses; developing and evaluating novel statistical methods; teaching; aiding design of future trials; meta-analysis; and, possibly, preventing error, fraud and selective reporting. Clinical trialists, however, sometimes appear overly concerned with being scooped and with misrepresentation of their work. Both possibilities can be avoided with simple measures such as inclusion of the original trialists as co-authors on any publication resulting from data sharing. Moreover, if we treat any data set as belonging to the patients who comprise it, rather than the investigators, such concerns fall away. Technological developments, particularly the Internet, have made data sharing generally a trivial logistical problem. Data sharing should come to be seen as an inherent part of conducting a randomized trial, similar to the way in which we consider ethical review and publication of study results. Journals and funding bodies should insist that trialists make raw data available, for example, by publishing data on the Web. If the clinical trial community continues to fail with respect to data sharing, we will only strengthen the public perception that we do clinical trials to benefit ourselves, not our patients.

Perceived Benefits, Harms, and Views About How to Share Data Responsibly: A Qualitative Study of Experiences With and Attitudes Toward Data Sharing Among Research Staff and Community Representatives in Thailand.

PubMed

Cheah, Phaik Yeong; Tangseefa, Decha; Somsaman, Aimatcha; Chunsuttiwat, Tri; Nosten, François; Day, Nicholas P J; Bull, Susan; Parker, Michael

2015-07-01

The Thailand Major Overseas Programme coordinates large multi-center studies in tropical medicine and generates vast amounts of data. As the data sharing movement gains momentum, we wanted to understand attitudes and experiences of relevant stakeholders about what constitutes good data sharing practice. We conducted 15 interviews and three focus groups discussions involving 25 participants and found that they generally saw data sharing as something positive. Data sharing was viewed as a means to contribute to scientific progress and lead to better quality analysis, better use of resources, greater accountability, and more outputs. However, there were also important reservations including potential harms to research participants, their communities, and the researchers themselves. Given these concerns, several areas for discussion were identified: data standardization, appropriate consent models, and governance. © The Author(s) 2015.

The Research Data Alliance

NASA Astrophysics Data System (ADS)

Fontaine, K. S.

2015-12-01

The Research Data Alliance (RDA) is an international organization created in 2012 to provide researchers with a forum for identifying and removing barriers to data sharing. Since then, RDA has gained over 3000 individual members, over three dozen organizational members, 47 Interest Groups, and 17 Working Groups, all focused on research data sharing. Interoperability is one instantiation of data sharing, but is not the only barrier to overcome. Technology limitations, discipline-specific cultures that do not support sharing, lack of best-practices, or lack of good definitions, are only three of a long list of situations preventing researchers from sharing their data. This presentation will cover how RDA has grown, some details on how the first eight solutions contribute to interoperability and sharing, and a sneak peek at what's in the pipeline.

The national drug abuse treatment clinical trials network data share project: website design, usage, challenges, and future directions.

PubMed

Shmueli-Blumberg, Dikla; Hu, Lian; Allen, Colleen; Frasketi, Michael; Wu, Li-Tzy; Vanveldhuisen, Paul

2013-01-01

There are many benefits of data sharing, including the promotion of new research from effective use of existing data, replication of findings through re-analysis of pooled data files, meta-analysis using individual patient data, and reinforcement of open scientific inquiry. A randomized controlled trial is considered as the 'gold standard' for establishing treatment effectiveness, but clinical trial research is very costly, and sharing data is an opportunity to expand the investment of the clinical trial beyond its original goals at minimal costs. We describe the goals, developments, and usage of the Data Share website (http://www.ctndatashare.org) for the National Drug Abuse Treatment Clinical Trials Network (CTN) in the United States, including lessons learned, limitations, and major revisions, and considerations for future directions to improve data sharing. Data management and programming procedures were conducted to produce uniform and Health Insurance Portability and Accountability Act (HIPAA)-compliant de-identified research data files from the completed trials of the CTN for archiving, managing, and sharing on the Data Share website. Since its inception in 2006 and through October 2012, nearly 1700 downloads from 27 clinical trials have been accessed from the Data Share website, with the use increasing over the years. Individuals from 31 countries have downloaded data from the website, and there have been at least 13 publications derived from analyzing data through the public Data Share website. Minimal control over data requests and usage has resulted in little information and lack of control regarding how the data from the website are used. Lack of uniformity in data elements collected across CTN trials has limited cross-study analyses. The Data Share website offers researchers easy access to de-identified data files with the goal to promote additional research and identify new findings from completed CTN studies. To maximize the utility of the website, ongoing collaborative efforts are needed to standardize the core measures used for data collection in the CTN studies with the goal to increase their comparability and to facilitate the ability to pool data files for cross-study analyses.

The National Drug Abuse Treatment Clinical Trials Network Data Share Project: Website Design, Usage, Challenges and Future Directions

PubMed Central

Shmueli-Blumberg, Dikla; Hu, Lian; Allen, Colleen; Frasketi, Michael; Wu, Li-Tzy; VanVeldhuisen, Paul

2014-01-01

Background The are many benefits of data sharing, including the promotion of new research from effective use of existing data, replication of findings through re-analysis of pooled data files, meta-analysis using individual patient data, and reinforcement of open scientific inquiry. A randomized controlled trial is considered as the “gold standard” for establishing treatment effectiveness, but clinical trial research is very costly and sharing data is an opportunity to expand the investment of the clinical trial beyond its original goals at minimal costs. Purpose We describe the goals, developments, and usage of the Data Share website (www.ctndatashare.org) for the National Drug Abuse Treatment Clinical Trials Network (CTN) in the US, including lessons learned, limitations and major revisions and considerations for future directions to improve data sharing. Methods Data management and programming procedures were conducted to produce uniform and Health Insurance Portability and Accountability Act (HIPAA)-compliant de-identified research data files from the completed trials of the CTN for archiving, managing, and sharing on the Data Share website. Results Since its inception in 2006 and through October 2012, nearly 1700 downloads from 27 clinical trials have been accessed from the Data Share website, with the use increasing over the years. Individuals from 31 countries have downloaded data from the website, and there have been at least 13 publications derived from analyzing data through the public Data Share website. Limitations Minimal control over data requests and usage has resulted in little information and lack of control regarding how the data from the website are used. Lack of uniformity in data elements collected across CTN trials has limited cross-study analyses. Conclusions The Data Share website offers researchers easy access to deidentified data files with the goal to promote additional research and identify new findings from completed CTN studies. To maximize the utility of the website, on-going collaborative efforts are needed to standardize the core measures used for data collection in the CTN studies with the goal to increase their comparability and to facilitate the ability to pool data files for cross-study analyses. PMID:24085772

Sustainable Materials Management: U.S. State Data Measurement Sharing Program

EPA Pesticide Factsheets

The State Data Measurement Sharing Program (SMP) is an online reporting, information sharing, and measurement tool that allows U.S. states to share a wide range of information about waste, recycling, and composting.

Data sharing by scientists: Practices and perceptions

USGS Publications Warehouse

Tenopir, C.; Allard, S.; Douglass, K.; Aydinoglu, A.U.; Wu, L.; Read, E.; Manoff, M.; Frame, M.

2011-01-01

Background: Scientific research in the 21st century is more data intensive and collaborative than in the past. It is important to study the data practices of researchers - data accessibility, discovery, re-use, preservation and, particularly, data sharing. Data sharing is a valuable part of the scientific method allowing for verification of results and extending research from prior results. Methodology/Principal Findings: A total of 1329 scientists participated in this survey exploring current data sharing practices and perceptions of the barriers and enablers of data sharing. Scientists do not make their data electronically available to others for various reasons, including insufficient time and lack of funding. Most respondents are satisfied with their current processes for the initial and short-term parts of the data or research lifecycle (collecting their research data; searching for, describing or cataloging, analyzing, and short-term storage of their data) but are not satisfied with long-term data preservation. Many organizations do not provide support to their researchers for data management both in the short- and long-term. If certain conditions are met (such as formal citation and sharing reprints) respondents agree they are willing to share their data. There are also significant differences and approaches in data management practices based on primary funding agency, subject discipline, age, work focus, and world region. Conclusions/Significance: Barriers to effective data sharing and preservation are deeply rooted in the practices and culture of the research process as well as the researchers themselves. New mandates for data management plans from NSF and other federal agencies and world-wide attention to the need to share and preserve data could lead to changes. Large scale programs, such as the NSF-sponsored DataNET (including projects like DataONE) will both bring attention and resources to the issue and make it easier for scientists to apply sound data management principles. ?? 2011 Tenopir et al.

Data Sharing by Scientists: Practices and Perceptions

PubMed Central

Tenopir, Carol; Allard, Suzie; Douglass, Kimberly; Aydinoglu, Arsev Umur; Wu, Lei; Read, Eleanor; Manoff, Maribeth; Frame, Mike

2011-01-01

Background Scientific research in the 21st century is more data intensive and collaborative than in the past. It is important to study the data practices of researchers – data accessibility, discovery, re-use, preservation and, particularly, data sharing. Data sharing is a valuable part of the scientific method allowing for verification of results and extending research from prior results. Methodology/Principal Findings A total of 1329 scientists participated in this survey exploring current data sharing practices and perceptions of the barriers and enablers of data sharing. Scientists do not make their data electronically available to others for various reasons, including insufficient time and lack of funding. Most respondents are satisfied with their current processes for the initial and short-term parts of the data or research lifecycle (collecting their research data; searching for, describing or cataloging, analyzing, and short-term storage of their data) but are not satisfied with long-term data preservation. Many organizations do not provide support to their researchers for data management both in the short- and long-term. If certain conditions are met (such as formal citation and sharing reprints) respondents agree they are willing to share their data. There are also significant differences and approaches in data management practices based on primary funding agency, subject discipline, age, work focus, and world region. Conclusions/Significance Barriers to effective data sharing and preservation are deeply rooted in the practices and culture of the research process as well as the researchers themselves. New mandates for data management plans from NSF and other federal agencies and world-wide attention to the need to share and preserve data could lead to changes. Large scale programs, such as the NSF-sponsored DataNET (including projects like DataONE) will both bring attention and resources to the issue and make it easier for scientists to apply sound data management principles. PMID:21738610

Data sharing and reanalysis of randomized controlled trials in leading biomedical journals with a full data sharing policy: survey of studies published in The BMJ and PLOS Medicine

PubMed Central

Naudet, Florian; Sakarovitch, Charlotte; Janiaud, Perrine; Cristea, Ioana; Fanelli, Daniele; Moher, David

2018-01-01

Abstract Objectives To explore the effectiveness of data sharing by randomized controlled trials (RCTs) in journals with a full data sharing policy and to describe potential difficulties encountered in the process of performing reanalyses of the primary outcomes. Design Survey of published RCTs. Setting PubMed/Medline. Eligibility criteria RCTs that had been submitted and published by The BMJ and PLOS Medicine subsequent to the adoption of data sharing policies by these journals. Main outcome measure The primary outcome was data availability, defined as the eventual receipt of complete data with clear labelling. Primary outcomes were reanalyzed to assess to what extent studies were reproduced. Difficulties encountered were described. Results 37 RCTs (21 from The BMJ and 16 from PLOS Medicine) published between 2013 and 2016 met the eligibility criteria. 17/37 (46%, 95% confidence interval 30% to 62%) satisfied the definition of data availability and 14 of the 17 (82%, 59% to 94%) were fully reproduced on all their primary outcomes. Of the remaining RCTs, errors were identified in two but reached similar conclusions and one paper did not provide enough information in the Methods section to reproduce the analyses. Difficulties identified included problems in contacting corresponding authors and lack of resources on their behalf in preparing the datasets. In addition, there was a range of different data sharing practices across study groups. Conclusions Data availability was not optimal in two journals with a strong policy for data sharing. When investigators shared data, most reanalyses largely reproduced the original results. Data sharing practices need to become more widespread and streamlined to allow meaningful reanalyses and reuse of data. Trial registration Open Science Framework osf.io/c4zke. PMID:29440066

Sharing Data in the Global Ocean Observing System (Invited)

NASA Astrophysics Data System (ADS)

Lindstrom, E. J.; McCurdy, A.; Young, J.; Fischer, A. S.

2010-12-01

We examine the evolution of data sharing in the field of physical oceanography to highlight the challenges now before us. Synoptic global observation of the ocean from space and in situ platforms has significantly matured over the last two decades. In the early 1990’s the community data sharing challenges facing the World Ocean Circulation Experiment (WOCE) largely focused on the behavior of individual scientists. Satellite data sharing depended on the policy of individual agencies. Global data sets were delivered with considerable delay and with enormous personal sacrifice. In the 2000’s the requirements for global data sets and sustained observations from the likes of the U.N. Framework Convention on Climate Change have led to data sharing and cooperation at a grander level. It is more effective and certainly more efficient. The Joint WMO/IOC Technical Commission on Oceanography and Marine Meteorology (JCOMM) provided the means to organize many aspects of data collection and data dissemination globally, for the common good. In response the Committee on Earth Observing Satellites organized Virtual Constellations to enable the assembly and sharing of like kinds of satellite data (e.g., sea surface topography, ocean vector winds, and ocean color). Individuals in physical oceanography have largely adapted to the new rigors of sharing data for the common good, and as a result of this revolution new science has been enabled. Primary obstacles to sharing have shifted from the individual level to the national level. As we enter into the 2010’s the demands for ocean data continue to evolve with an expanded requirement for more real-time reporting and broader disciplinary coverage, to answer key scientific and societal questions. We are also seeing the development of more numerous national contributions to the global observing system. The drivers for the establishment of global ocean observing systems are expanding beyond climate to include biological and biogeochemical issues (e.g. biodiversity and ecosystem services, fisheries collapse, and ocean acidification). This expanded suite of demands and drivers challenge us further to share data for the common good across specialties. This requires that more ocean scientific communities and national ocean observing programs move towards maturity in terms of global data collection capability, sharing capacity, and data management standards. In oceanography the time has arrived for a cultural shift toward more shared collective observing capabilities. Necessarily we must also rapidly move toward harmony in national data sharing policies for the ocean environment. Building capacity to share ocean observations has been an objective for decades and has resulted in an expanded understanding of technologies and management policies that foster data sharing and provenance tracking.

A Large-Scale Initiative Inviting Patients to Share Personal Fitness Tracker Data with Their Providers: Initial Results

PubMed Central

Pevnick, Joshua M.; Fuller, Garth; Duncan, Ray; Spiegel, Brennan M. R.

2016-01-01

Background Personal fitness trackers (PFT) have substantial potential to improve healthcare. Objective To quantify and characterize early adopters who shared their PFT data with providers. Methods We used bivariate statistics and logistic regression to compare patients who shared any PFT data vs. patients who did not. Results A patient portal was used to invite 79,953 registered portal users to share their data. Of 66,105 users included in our analysis, 499 (0.8%) uploaded data during an initial 37-day study period. Bivariate and regression analysis showed that early adopters were more likely than non-adopters to be younger, male, white, health system employees, and to have higher BMIs. Neither comorbidities nor utilization predicted adoption. Conclusion Our results demonstrate that patients had little intrinsic desire to share PFT data with their providers, and suggest that patients most at risk for poor health outcomes are least likely to share PFT data. Marketing, incentives, and/or cultural change may be needed to induce such data-sharing. PMID:27846287

Neuroinformatics Database (NiDB) – A Modular, Portable Database for the Storage, Analysis, and Sharing of Neuroimaging Data

PubMed Central

Anderson, Beth M.; Stevens, Michael C.; Glahn, David C.; Assaf, Michal; Pearlson, Godfrey D.

2013-01-01

We present a modular, high performance, open-source database system that incorporates popular neuroimaging database features with novel peer-to-peer sharing, and a simple installation. An increasing number of imaging centers have created a massive amount of neuroimaging data since fMRI became popular more than 20 years ago, with much of that data unshared. The Neuroinformatics Database (NiDB) provides a stable platform to store and manipulate neuroimaging data and addresses several of the impediments to data sharing presented by the INCF Task Force on Neuroimaging Datasharing, including 1) motivation to share data, 2) technical issues, and 3) standards development. NiDB solves these problems by 1) minimizing PHI use, providing a cost effective simple locally stored platform, 2) storing and associating all data (including genome) with a subject and creating a peer-to-peer sharing model, and 3) defining a sample, normalized definition of a data storage structure that is used in NiDB. NiDB not only simplifies the local storage and analysis of neuroimaging data, but also enables simple sharing of raw data and analysis methods, which may encourage further sharing. PMID:23912507

Secure and Trustable Electronic Medical Records Sharing using Blockchain.

PubMed

Dubovitskaya, Alevtina; Xu, Zhigang; Ryu, Samuel; Schumacher, Michael; Wang, Fusheng

2017-01-01

Electronic medical records (EMRs) are critical, highly sensitive private information in healthcare, and need to be frequently shared among peers. Blockchain provides a shared, immutable and transparent history of all the transactions to build applications with trust, accountability and transparency. This provides a unique opportunity to develop a secure and trustable EMR data management and sharing system using blockchain. In this paper, we present our perspectives on blockchain based healthcare data management, in particular, for EMR data sharing between healthcare providers and for research studies. We propose a framework on managing and sharing EMR data for cancer patient care. In collaboration with Stony Brook University Hospital, we implemented our framework in a prototype that ensures privacy, security, availability, and fine-grained access control over EMR data. The proposed work can significantly reduce the turnaround time for EMR sharing, improve decision making for medical care, and reduce the overall cost.

Secure and Trustable Electronic Medical Records Sharing using Blockchain

PubMed Central

Dubovitskaya, Alevtina; Xu, Zhigang; Ryu, Samuel; Schumacher, Michael; Wang, Fusheng

2017-01-01

Electronic medical records (EMRs) are critical, highly sensitive private information in healthcare, and need to be frequently shared among peers. Blockchain provides a shared, immutable and transparent history of all the transactions to build applications with trust, accountability and transparency. This provides a unique opportunity to develop a secure and trustable EMR data management and sharing system using blockchain. In this paper, we present our perspectives on blockchain based healthcare data management, in particular, for EMR data sharing between healthcare providers and for research studies. We propose a framework on managing and sharing EMR data for cancer patient care. In collaboration with Stony Brook University Hospital, we implemented our framework in a prototype that ensures privacy, security, availability, and fine-grained access control over EMR data. The proposed work can significantly reduce the turnaround time for EMR sharing, improve decision making for medical care, and reduce the overall cost. PMID:29854130

Sharing and interoperation of Digital Dongying geospatial data

NASA Astrophysics Data System (ADS)

Zhao, Jun; Liu, Gaohuan; Han, Lit-tao; Zhang, Rui-ju; Wang, Zhi-an

2006-10-01

Digital Dongying project was put forward by Dongying city, Shandong province, and authenticated by Ministry of Information Industry, Ministry of Science and Technology and Ministry of Construction P.R.CHINA in 2002. After five years of building, informationization level of Dongying has reached to the advanced degree. In order to forward the step of digital Dongying building, and to realize geospatial data sharing, geographic information sharing standards are drawn up and applied into realization. Secondly, Digital Dongying Geographic Information Sharing Platform has been constructed and developed, which is a highly integrated platform of WEBGIS. 3S (GIS, GPS, RS), Object oriented RDBMS, Internet, DCOM, etc. It provides an indispensable platform for sharing and interoperation of Digital Dongying Geospatial Data. According to the standards, and based on the platform, sharing and interoperation of "Digital Dongying" geospatial data have come into practice and the good results have been obtained. However, a perfect leadership group is necessary for data sharing and interoperation.

The Safe and Effective Use of Shared Data Underpinned by Stakeholder Engagement and Evaluation Practice.

PubMed

Georgiou, Andrew; Magrabi, Farah; Hypponen, Hannele; Wong, Zoie Shui-Yee; Nykänen, Pirkko; Scott, Philip J; Ammenwerth, Elske; Rigby, Michael

2018-04-22

 The paper draws attention to: i) key considerations involving the confidentiality, privacy, and security of shared data; and ii) the requirements needed to build collaborative arrangements encompassing all stakeholders with the goal of ensuring safe, secure, and quality use of shared data.  A narrative review of existing research and policy approaches along with expert perspectives drawn from the International Medical Informatics Association (IMIA) Working Group on Technology Assessment and Quality Development in Health Care and the European Federation for Medical Informatics (EFMI) Working Group for Assessment of Health Information Systems.  The technological ability to merge, link, re-use, and exchange data has outpaced the establishment of policies, procedures, and processes to monitor the ethics and legality of shared use of data. Questions remain about how to guarantee the security of shared data, and how to establish and maintain public trust across large-scale shared data enterprises. This paper identifies the importance of data governance frameworks (incorporating engagement with all stakeholders) to underpin the management of the ethics and legality of shared data use. The paper also provides some key considerations for the establishment of national approaches and measures to monitor compliance with best practice. Data sharing endeavours can help to underpin new collaborative models of health care which provide shared information, engagement, and accountability amongst all stakeholders. We believe that commitment to rigorous evaluation and stakeholder engagement will be critical to delivering health data benefits and the establishment of collaborative models of health care into the future. Georg Thieme Verlag KG Stuttgart.

Attitudes of research participants and the general public towards genomic data sharing: a systematic literature review.

PubMed

Shabani, Mahsa; Bezuidenhout, Louise; Borry, Pascal

2014-11-01

Introducing data sharing practices into the genomic research arena has challenged the current mechanisms established to protect rights of individuals and triggered policy considerations. To inform such policy deliberations, soliciting public and research participants' attitudes with respect to genomic data sharing is a necessity. The main electronic databases were searched in order to retrieve empirical studies, investigating the attitudes of research participants and the public towards genomic data sharing through public databases. In the 15 included studies, participants' attitudes towards genomic data sharing revealed the influence of a constellation of interrelated factors, including the personal perceptions of controllability and sensitivity of data, potential risks and benefits of data sharing at individual and social level and also governance level considerations. This analysis indicates that future policy responses and recruitment practices should be attentive to a wide variety of concerns in order to promote both responsible and progressive research.

Sweat, Skepticism, and Uncharted Territory: A Qualitative Study of Opinions on Data Sharing Among Public Health Researchers and Research Participants in Mumbai, India.

PubMed

Hate, Ketaki; Meherally, Sanna; Shah More, Neena; Jayaraman, Anuja; Bull, Susan; Parker, Michael; Osrin, David

2015-07-01

Efforts to internalize data sharing in research practice have been driven largely by developing international norms that have not incorporated opinions from researchers in low- and middle-income countries. We sought to identify the issues around ethical data sharing in the context of research involving women and children in urban India. We interviewed researchers, managers, and research participants associated with a Mumbai non-governmental organization, as well as researchers from other organizations and members of ethics committees. We conducted 22 individual semi-structured interviews and involved 44 research participants in focus group discussions. We used framework analysis to examine ideas about data and data sharing in general; its potential benefits or harms, barriers, obligations, and governance; and the requirements for consent. Both researchers and participants were generally in favor of data sharing, although limited experience amplified their reservations. We identified three themes: concerns that the work of data producers may not receive appropriate acknowledgment, skepticism about the process of sharing, and the fact that the terrain of data sharing was essentially uncharted and confusing. To increase data sharing in India, we need to provide guidelines, protocols, and examples of good practice in terms of consent, data preparation, screening of applications, and what individuals and organizations can expect in terms of validation, acknowledgment, and authorship. © The Author(s) 2015.

Implementing partnership-driven clinical federated electronic health record data sharing networks.

PubMed

Stephens, Kari A; Anderson, Nicholas; Lin, Ching-Ping; Estiri, Hossein

2016-09-01

Building federated data sharing architectures requires supporting a range of data owners, effective and validated semantic alignment between data resources, and consistent focus on end-users. Establishing these resources requires development methodologies that support internal validation of data extraction and translation processes, sustaining meaningful partnerships, and delivering clear and measurable system utility. We describe findings from two federated data sharing case examples that detail critical factors, shared outcomes, and production environment results. Two federated data sharing pilot architectures developed to support network-based research associated with the University of Washington's Institute of Translational Health Sciences provided the basis for the findings. A spiral model for implementation and evaluation was used to structure iterations of development and support knowledge share between the two network development teams, which cross collaborated to support and manage common stages. We found that using a spiral model of software development and multiple cycles of iteration was effective in achieving early network design goals. Both networks required time and resource intensive efforts to establish a trusted environment to create the data sharing architectures. Both networks were challenged by the need for adaptive use cases to define and test utility. An iterative cyclical model of development provided a process for developing trust with data partners and refining the design, and supported measureable success in the development of new federated data sharing architectures. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

DASH, the data and specimen hub of the National Institute of Child Health and Human Development

PubMed Central

Hazra, Rohan; Tenney, Susan; Shlionskaya, Alexandra; Samavedam, Rajni; Baxter, Kristin; Ilekis, John; Weck, Jennifer; Willinger, Marian; Grave, Gilman; Tsilou, Katerina; Songco, David

2018-01-01

The benefits of data sharing are well-established and an increasing number of policies require that data be shared upon publication of the main study findings. As data sharing becomes the new norm, there is a heightened need for additional resources to drive efficient data reuse. This article describes the development and implementation of the Data and Specimen Hub (DASH) by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) to promote data sharing from NICHD-funded studies and enable researchers to comply with NIH data sharing policies. DASH’s flexible architecture is designed to archive diverse data types and formats from NICHD’s broad scientific portfolio in a manner that promotes FAIR data sharing principles. Performance of DASH over two years since launch is promising: the number of available studies and data requests are growing; three manuscripts have been published from data reanalysis, all within two years of access. Critical success factors included NICHD leadership commitment, stakeholder engagement and close coordination between the governance body and technical team. PMID:29557977

A simple tool for neuroimaging data sharing

PubMed Central

Haselgrove, Christian; Poline, Jean-Baptiste; Kennedy, David N.

2014-01-01

Data sharing is becoming increasingly common, but despite encouragement and facilitation by funding agencies, journals, and some research efforts, most neuroimaging data acquired today is still not shared due to political, financial, social, and technical barriers to sharing data that remain. In particular, technical solutions are few for researchers that are not a part of larger efforts with dedicated sharing infrastructures, and social barriers such as the time commitment required to share can keep data from becoming publicly available. We present a system for sharing neuroimaging data, designed to be simple to use and to provide benefit to the data provider. The system consists of a server at the International Neuroinformatics Coordinating Facility (INCF) and user tools for uploading data to the server. The primary design principle for the user tools is ease of use: the user identifies a directory containing Digital Imaging and Communications in Medicine (DICOM) data, provides their INCF Portal authentication, and provides identifiers for the subject and imaging session. The user tool anonymizes the data and sends it to the server. The server then runs quality control routines on the data, and the data and the quality control reports are made public. The user retains control of the data and may change the sharing policy as they need. The result is that in a few minutes of the user’s time, DICOM data can be anonymized and made publicly available, and an initial quality control assessment can be performed on the data. The system is currently functional, and user tools and access to the public image database are available at http://xnat.incf.org/. PMID:24904398

IMPACT Observatory: tracking the evolution of clinical trial data sharing and research integrity.

PubMed

Krleža-Jerić, Karmela; Gabelica, Mirko; Banzi, Rita; Martinić, Marina Krnić; Pulido, Bibiana; Mahmić-Kaknjo, Mersiha; Reveiz, Ludovic; Šimić, Josip; Utrobičić, Ana; Hrgović, Irena

2016-10-15

The opening of research data is emerging thanks to the increasing possibilities of digital technology. The opening of clinical trial (CT) data is a part of this process, expected to have positive scientific, ethical, health, and economic impacts thus contributing to research integrity. The January 2016 proposal by the International Council of Medical Journal Editors triggered ample discussion about CT data sharing and reconfirmed the need for an ongoing assessment of its dynamics. The IMProving Access to Clinical Trials data (IMPACT) Observatory aims to play such a role, and assess the data sharing culture, policies, and practices of key players, the impact of their interventions on CTs, and contribute to a transformation of research. The objective of this paper is to present the IMPACT Observatory as well as share some of its preliminary findings. Methods include a scoping study of research, surveys, interviews, and an environmental scan of research data repositories. Our preliminary findings indicate that although opening of CT data has not yet been achieved, its evolution is encouraging. Initiatives by key players contribute to increasing of CT data sharing, and many barriers are shrinking or disappearing. The major barrier is the lack of data sharing standards, from preparing data for public sharing to its curatorship, findability and access. However, experiences accumulated by sharing CT data according to "upon request" or "open" mechanisms could inform the development of such standards. The Vivli, CORBEL-ECRIN and Open Trials projects are currently working in this direction.

Transforming Education Research Through Open Video Data Sharing.

PubMed

Gilmore, Rick O; Adolph, Karen E; Millman, David S; Gordon, Andrew

2016-01-01

Open data sharing promises to accelerate the pace of discovery in the developmental and learning sciences, but significant technical, policy, and cultural barriers have limited its adoption. As a result, most research on learning and development remains shrouded in a culture of isolation. Data sharing is the rare exception (Gilmore, 2016). Many researchers who study teaching and learning in classroom, laboratory, museum, and home contexts use video as a primary source of raw research data. Unlike other measures, video captures the complexity, richness, and diversity of behavior. Moreover, because video is self-documenting, it presents significant potential for reuse. However, the potential for reuse goes largely unrealized because videos are rarely shared. Research videos contain information about participants' identities making the materials challenging to share. The large size of video files, diversity of formats, and incompatible software tools pose technical challenges. The Databrary (databrary.org) digital library enables researchers who study learning and development to store, share, stream, and annotate videos. In this article, we describe how Databrary has overcome barriers to sharing research videos and associated data and metadata. Databrary has developed solutions for respecting participants' privacy; for storing, streaming, and sharing videos; and for managing videos and associated metadata. The Databrary experience suggests ways that videos and other identifiable data collected in the context of educational research might be shared. Open data sharing enabled by Databrary can serve as a catalyst for a truly multidisciplinary science of learning.

Transforming Education Research Through Open Video Data Sharing

PubMed Central

Gilmore, Rick O.; Adolph, Karen E.; Millman, David S.; Gordon, Andrew

2016-01-01

Open data sharing promises to accelerate the pace of discovery in the developmental and learning sciences, but significant technical, policy, and cultural barriers have limited its adoption. As a result, most research on learning and development remains shrouded in a culture of isolation. Data sharing is the rare exception (Gilmore, 2016). Many researchers who study teaching and learning in classroom, laboratory, museum, and home contexts use video as a primary source of raw research data. Unlike other measures, video captures the complexity, richness, and diversity of behavior. Moreover, because video is self-documenting, it presents significant potential for reuse. However, the potential for reuse goes largely unrealized because videos are rarely shared. Research videos contain information about participants’ identities making the materials challenging to share. The large size of video files, diversity of formats, and incompatible software tools pose technical challenges. The Databrary (databrary.org) digital library enables researchers who study learning and development to store, share, stream, and annotate videos. In this article, we describe how Databrary has overcome barriers to sharing research videos and associated data and metadata. Databrary has developed solutions for respecting participants’ privacy; for storing, streaming, and sharing videos; and for managing videos and associated metadata. The Databrary experience suggests ways that videos and other identifiable data collected in the context of educational research might be shared. Open data sharing enabled by Databrary can serve as a catalyst for a truly multidisciplinary science of learning. PMID:28042361

Empirical Study of Data Sharing by Authors Publishing in PLoS Journals

PubMed Central

Savage, Caroline J.; Vickers, Andrew J.

2009-01-01

Background Many journals now require authors share their data with other investigators, either by depositing the data in a public repository or making it freely available upon request. These policies are explicit, but remain largely untested. We sought to determine how well authors comply with such policies by requesting data from authors who had published in one of two journals with clear data sharing policies. Methods and Findings We requested data from ten investigators who had published in either PLoS Medicine or PLoS Clinical Trials. All responses were carefully documented. In the event that we were refused data, we reminded authors of the journal's data sharing guidelines. If we did not receive a response to our initial request, a second request was made. Following the ten requests for raw data, three investigators did not respond, four authors responded and refused to share their data, two email addresses were no longer valid, and one author requested further details. A reminder of PLoS's explicit requirement that authors share data did not change the reply from the four authors who initially refused. Only one author sent an original data set. Conclusions We received only one of ten raw data sets requested. This suggests that journal policies requiring data sharing do not lead to authors making their data sets available to independent investigators. PMID:19763261

Stakeholders' views on data sharing in multicenter studies.

PubMed

Mazor, Kathleen M; Richards, Allison; Gallagher, Mia; Arterburn, David E; Raebel, Marsha A; Nowell, W Benjamin; Curtis, Jeffrey R; Paolino, Andrea R; Toh, Sengwee

2017-09-01

To understand stakeholders' views on data sharing in multicenter comparative effectiveness research studies and the value of privacy-protecting methods. Semistructured interviews with five US stakeholder groups. We completed 11 interviews, involving patients (n = 15), researchers (n = 10), Institutional Review Board and regulatory staff (n = 3), multicenter research governance experts (n = 2) and healthcare system leaders (n = 4). Perceptions of the benefits and value of research were the strongest influences toward data sharing; cost and security risks were primary influences against sharing. Privacy-protecting methods that share summary-level data were acknowledged as being appealing, but there were concerns about increased cost and potential loss of research validity. Stakeholders were open to data sharing in multicenter studies that offer value and minimize security risks.

Involving Research Stakeholders in Developing Policy on Sharing Public Health Research Data in Kenya: Views on Fair Process for Informed Consent, Access Oversight, and Community Engagement.

PubMed

Jao, Irene; Kombe, Francis; Mwalukore, Salim; Bull, Susan; Parker, Michael; Kamuya, Dorcas; Molyneux, Sassy; Marsh, Vicki

2015-07-01

Increased global sharing of public health research data has potential to advance scientific progress but may present challenges to the interests of research stakeholders, particularly in low-to-middle income countries. Policies for data sharing should be responsive to public views, but there is little evidence of the systematic study of these from low-income countries. This qualitative study explored views on fair data-sharing processes among 60 stakeholders in Kenya with varying research experience, using a deliberative approach. Stakeholders' attitudes were informed by perceptions of benefit and concerns for research data sharing, including risks of stigmatization, loss of privacy, and undermining scientific careers and validity, reported in detail elsewhere. In this article, we discuss institutional trust-building processes seen as central to perceptions of fairness in sharing research data in this setting, including forms of community involvement, individual prior awareness and agreement to data sharing, independence and accountability of governance mechanisms, and operating under a national framework. © The Author(s) 2015.

Ethical sharing of health data in online platforms - which values should be considered?

PubMed

Riso, Brígida; Tupasela, Aaro; Vears, Danya F; Felzmann, Heike; Cockbain, Julian; Loi, Michele; Kongsholm, Nana C H; Zullo, Silvia; Rakic, Vojin

2017-08-21

Intensified and extensive data production and data storage are characteristics of contemporary western societies. Health data sharing is increasing with the growth of Information and Communication Technology (ICT) platforms devoted to the collection of personal health and genomic data. However, the sensitive and personal nature of health data poses ethical challenges when data is disclosed and shared even if for scientific research purposes.With this in mind, the Science and Values Working Group of the COST Action CHIP ME 'Citizen's Health through public-private Initiatives: Public health, Market and Ethical perspectives' (IS 1303) identified six core values they considered to be essential for the ethical sharing of health data using ICT platforms. We believe that using this ethical framework will promote respectful scientific practices in order to maintain individuals' trust in research.We use these values to analyse five ICT platforms and explore how emerging data sharing platforms are reconfiguring the data sharing experience from a range of perspectives. We discuss which types of values, rights and responsibilities they entail and enshrine within their philosophy or outlook on what it means to share personal health information. Through this discussion we address issues of the design and the development process of personal health data and patient-oriented infrastructures, as well as new forms of technologically-mediated empowerment.

If We Share Data, Will Anyone Use Them? Data Sharing and Reuse in the Long Tail of Science and Technology

PubMed Central

Wallis, Jillian C.; Rolando, Elizabeth; Borgman, Christine L.

2013-01-01

Research on practices to share and reuse data will inform the design of infrastructure to support data collection, management, and discovery in the long tail of science and technology. These are research domains in which data tend to be local in character, minimally structured, and minimally documented. We report on a ten-year study of the Center for Embedded Network Sensing (CENS), a National Science Foundation Science and Technology Center. We found that CENS researchers are willing to share their data, but few are asked to do so, and in only a few domain areas do their funders or journals require them to deposit data. Few repositories exist to accept data in CENS research areas.. Data sharing tends to occur only through interpersonal exchanges. CENS researchers obtain data from repositories, and occasionally from registries and individuals, to provide context, calibration, or other forms of background for their studies. Neither CENS researchers nor those who request access to CENS data appear to use external data for primary research questions or for replication of studies. CENS researchers are willing to share data if they receive credit and retain first rights to publish their results. Practices of releasing, sharing, and reusing of data in CENS reaffirm the gift culture of scholarship, in which goods are bartered between trusted colleagues rather than treated as commodities. PMID:23935830

If we share data, will anyone use them? Data sharing and reuse in the long tail of science and technology.

PubMed

Wallis, Jillian C; Rolando, Elizabeth; Borgman, Christine L

2013-01-01

Research on practices to share and reuse data will inform the design of infrastructure to support data collection, management, and discovery in the long tail of science and technology. These are research domains in which data tend to be local in character, minimally structured, and minimally documented. We report on a ten-year study of the Center for Embedded Network Sensing (CENS), a National Science Foundation Science and Technology Center. We found that CENS researchers are willing to share their data, but few are asked to do so, and in only a few domain areas do their funders or journals require them to deposit data. Few repositories exist to accept data in CENS research areas.. Data sharing tends to occur only through interpersonal exchanges. CENS researchers obtain data from repositories, and occasionally from registries and individuals, to provide context, calibration, or other forms of background for their studies. Neither CENS researchers nor those who request access to CENS data appear to use external data for primary research questions or for replication of studies. CENS researchers are willing to share data if they receive credit and retain first rights to publish their results. Practices of releasing, sharing, and reusing of data in CENS reaffirm the gift culture of scholarship, in which goods are bartered between trusted colleagues rather than treated as commodities.

Practicing what we preach: developing a data sharing policy for the Journal of the Medical Library Association.

PubMed

Read, Kevin B; Amos, Liz; Federer, Lisa M; Logan, Ayaba; Plutchak, T Scott; Akers, Katherine G

2018-04-01

Providing access to the data underlying research results in published literature allows others to reproduce those results or analyze the data in new ways. Health sciences librarians and information professionals have long been advocates of data sharing. It is time for us to practice what we preach and share the data associated with our published research. This editorial describes the activity of a working group charged with developing a research data sharing policy for the Journal of the Medical Library Association.

Practicing what we preach: developing a data sharing policy for the Journal of the Medical Library Association

PubMed Central

Read, Kevin B.; Amos, Liz; Federer, Lisa M.; Logan, Ayaba; Plutchak, T. Scott; Akers, Katherine G.

2018-01-01

Providing access to the data underlying research results in published literature allows others to reproduce those results or analyze the data in new ways. Health sciences librarians and information professionals have long been advocates of data sharing. It is time for us to practice what we preach and share the data associated with our published research. This editorial describes the activity of a working group charged with developing a research data sharing policy for the Journal of the Medical Library Association. PMID:29632437

Report endorses data sharing

NASA Astrophysics Data System (ADS)

The potential benefits of sharing data so outweigh its costs that investigators should be required to include plans for sharing data as part of their grant proposals, according to recommendations issued recently by the Committee on National Statistics (CNSTAT) of the National Research Council (NRC).In their report Sharing Research Data, CNSTAT also recommended that “Journals should give more emphasis to reports of secondary analyses and to replications,” provided that the original collections of data receive full credit. In addition, “Journal editors should require authors to provide access to data during the peer review process.”

Clinical research data sharing: what an open science world means for researchers involved in evidence synthesis.

PubMed

Ross, Joseph S

2016-09-20

The International Committee of Medical Journal Editors (ICMJE) recently announced a bold step forward to require data generated by interventional clinical trials that are published in its member journals to be responsibly shared with external investigators. The movement toward a clinical research culture that supports data sharing has important implications for the design, conduct, and reporting of systematic reviews and meta-analyses. While data sharing is likely to enhance the science of evidence synthesis, facilitating the identification and inclusion of all relevant research, it will also pose key challenges, such as requiring broader search strategies and more thorough scrutiny of identified research. Furthermore, the adoption of data sharing initiatives by the clinical research community should challenge the community of researchers involved in evidence synthesis to follow suit, including the widespread adoption of systematic review registration, results reporting, and data sharing, to promote transparency and enhance the integrity of the research process.

Open research practices: unintended consequences and suggestions for averting them. (Commentary on the Peer Reviewers' Openness Initiative)

PubMed Central

2016-01-01

The Peer Reviewers' Openness Initiative (PROI) is a move to enlist reviewers in the promotion of data-sharing. In this commentary, I discuss objections that can be raised, first to the specific proposals in the PROI, and second to data-sharing in general. I argue that although many objections have strong counter-arguments, others merit more serious consideration. Regarding the PROI, I suggest that it could backfire if editors and authors feel coerced into data-sharing and so may not be the most pragmatic way of encouraging greater openness. More generally, while promoting data-sharing, we need to be sensitive to cases where sharing of data from human participants could create ethical problems. Furthermore, those interested in promoting reproducible science need to defend against an increased risk of data-dredging when large, multivariable datasets are shared. I end with some suggestions to avoid these unintended consequences. PMID:27152225

Challenges and successes in developing a data sharing culture in the Gulf of Mexico following the Deepwater Horizon disaster.

NASA Astrophysics Data System (ADS)

Showalter, L. M.

2017-12-01

The Gulf Research Program (GRP) was developed as part of legal settlements with the companies involved in the Deepwater Horizon (DWH) disaster. The Federal Government asked the National Academy of Sciences to establish a new program to fund and conduct activities to enhance offshore energy system safety and protect human health and the environment in the Gulf of Mexico and other regions along the U.S. outer continental shelf. An important part of the program is a commitment to open data and data sharing among the variety of disciplines it funds. The DWH disaster produced a major influx of funding for the Gulf region and various groups and organizations are collaborating to ensure that the science being conducted via these funding streams is not duplicative. A number of data focused sub groups have formed and are working to leverage existing efforts to strengthen data sharing and collaboration in the region. For its part, the GRP is developing a data program that encourages researchers to share data openly while providing avenues for acknowledgement of data sharing and research collaborations. A main problem with collaborative data sharing is often not the technologies available but instead the human component. The "traditional" path for scientific research has not generally involved making data widely or readily available in a short time frame. It takes a lot of effort to challenge this norm and change the way researchers view data sharing and its value for them and the world at large. The GRP data program aims to build a community of researchers that not only share their data but who also help show the value of this practice to the greater scientific community. To this end, the GRP will support a variety of education and training opportunities to help develop a base of researchers more informed on issues related to open data and data sharing and working to leverage the technology and expertise of others to develop a culture of data sharing in the Gulf of Mexico.

Who shares? Who doesn't? Factors associated with openly archiving raw research data.

PubMed

Piwowar, Heather A

2011-01-01

Many initiatives encourage investigators to share their raw datasets in hopes of increasing research efficiency and quality. Despite these investments of time and money, we do not have a firm grasp of who openly shares raw research data, who doesn't, and which initiatives are correlated with high rates of data sharing. In this analysis I use bibliometric methods to identify patterns in the frequency with which investigators openly archive their raw gene expression microarray datasets after study publication. Automated methods identified 11,603 articles published between 2000 and 2009 that describe the creation of gene expression microarray data. Associated datasets in best-practice repositories were found for 25% of these articles, increasing from less than 5% in 2001 to 30%-35% in 2007-2009. Accounting for sensitivity of the automated methods, approximately 45% of recent gene expression studies made their data publicly available. First-order factor analysis on 124 diverse bibliometric attributes of the data creation articles revealed 15 factors describing authorship, funding, institution, publication, and domain environments. In multivariate regression, authors were most likely to share data if they had prior experience sharing or reusing data, if their study was published in an open access journal or a journal with a relatively strong data sharing policy, or if the study was funded by a large number of NIH grants. Authors of studies on cancer and human subjects were least likely to make their datasets available. These results suggest research data sharing levels are still low and increasing only slowly, and data is least available in areas where it could make the biggest impact. Let's learn from those with high rates of sharing to embrace the full potential of our research output.

Alternative Fuels Data Center

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Health Data Sharing Preferences of Consumers: Public Policy and Legal Implications of Consumer-Mediated Data Management

ERIC Educational Resources Information Center

Moon, Lisa A.

2017-01-01

An individual's choice to share or have control of the sharing or withholding of their personal health information is one of the most significant public policy challenges associated with electronic information exchange. There were four aims of this study. First, to describe predictors of health data sharing preferences of consumers. Second, to…

Meta-analysis of randomized clinical trials in the era of individual patient data sharing.

PubMed

Kawahara, Takuya; Fukuda, Musashi; Oba, Koji; Sakamoto, Junichi; Buyse, Marc

2018-06-01

Individual patient data (IPD) meta-analysis is considered to be a gold standard when the results of several randomized trials are combined. Recent initiatives on sharing IPD from clinical trials offer unprecedented opportunities for using such data in IPD meta-analyses. First, we discuss the evidence generated and the benefits obtained by a long-established prospective IPD meta-analysis in early breast cancer. Next, we discuss a data-sharing system that has been adopted by several pharmaceutical sponsors. We review a number of retrospective IPD meta-analyses that have already been proposed using this data-sharing system. Finally, we discuss the role of data sharing in IPD meta-analysis in the future. Treatment effects can be more reliably estimated in both types of IPD meta-analyses than with summary statistics extracted from published papers. Specifically, with rich covariate information available on each patient, prognostic and predictive factors can be identified or confirmed. Also, when several endpoints are available, surrogate endpoints can be assessed statistically. Although there are difficulties in conducting, analyzing, and interpreting retrospective IPD meta-analysis utilizing the currently available data-sharing systems, data sharing will play an important role in IPD meta-analysis in the future.

Research Data in Core Journals in Biology, Chemistry, Mathematics, and Physics.

PubMed

Womack, Ryan P

2015-01-01

This study takes a stratified random sample of articles published in 2014 from the top 10 journals in the disciplines of biology, chemistry, mathematics, and physics, as ranked by impact factor. Sampled articles were examined for their reporting of original data or reuse of prior data, and were coded for whether the data was publicly shared or otherwise made available to readers. Other characteristics such as the sharing of software code used for analysis and use of data citation and DOIs for data were examined. The study finds that data sharing practices are still relatively rare in these disciplines' top journals, but that the disciplines have markedly different practices. Biology top journals share original data at the highest rate, and physics top journals share at the lowest rate. Overall, the study finds that within the top journals, only 13% of articles with original data published in 2014 make the data available to others.

Research Data in Core Journals in Biology, Chemistry, Mathematics, and Physics

PubMed Central

Womack, Ryan P.

2015-01-01

This study takes a stratified random sample of articles published in 2014 from the top 10 journals in the disciplines of biology, chemistry, mathematics, and physics, as ranked by impact factor. Sampled articles were examined for their reporting of original data or reuse of prior data, and were coded for whether the data was publicly shared or otherwise made available to readers. Other characteristics such as the sharing of software code used for analysis and use of data citation and DOIs for data were examined. The study finds that data sharing practices are still relatively rare in these disciplines’ top journals, but that the disciplines have markedly different practices. Biology top journals share original data at the highest rate, and physics top journals share at the lowest rate. Overall, the study finds that within the top journals, only 13% of articles with original data published in 2014 make the data available to others. PMID:26636676

Collaborative Sharing of Multidimensional Space-time Data Using HydroShare

NASA Astrophysics Data System (ADS)

Gan, T.; Tarboton, D. G.; Horsburgh, J. S.; Dash, P. K.; Idaszak, R.; Yi, H.; Blanton, B.

2015-12-01

HydroShare is a collaborative environment being developed for sharing hydrological data and models. It includes capability to upload data in many formats as resources that can be shared. The HydroShare data model for resources uses a specific format for the representation of each type of data and specifies metadata common to all resource types as well as metadata unique to specific resource types. The Network Common Data Form (NetCDF) was chosen as the format for multidimensional space-time data in HydroShare. NetCDF is widely used in hydrological and other geoscience modeling because it contains self-describing metadata and supports the creation of array-oriented datasets that may include three spatial dimensions, a time dimension and other user defined dimensions. For example, NetCDF may be used to represent precipitation or surface air temperature fields that have two dimensions in space and one dimension in time. This presentation will illustrate how NetCDF files are used in HydroShare. When a NetCDF file is loaded into HydroShare, header information is extracted using the "ncdump" utility. Python functions developed for the Django web framework on which HydroShare is based, extract science metadata present in the NetCDF file, saving the user from having to enter it. Where the file follows Climate Forecast (CF) convention and Attribute Convention for Dataset Discovery (ACDD) standards, metadata is thus automatically populated. Users also have the ability to add metadata to the resource that may not have been present in the original NetCDF file. HydroShare's metadata editing functionality then writes this science metadata back into the NetCDF file to maintain consistency between the science metadata in HydroShare and the metadata in the NetCDF file. This further helps researchers easily add metadata information following the CF and ACDD conventions. Additional data inspection and subsetting functions were developed, taking advantage of Python and command line libraries for working with NetCDF files. We describe the design and implementation of these features and illustrate how NetCDF files from a modeling application may be curated in HydroShare and thus enhance reproducibility of the associated research. We also discuss future development planned for multidimensional space-time data in HydroShare.

Scalable Architecture for Federated Translational Inquiries Network (SAFTINet) Technology Infrastructure for a Distributed Data Network

PubMed Central

Schilling, Lisa M.; Kwan, Bethany M.; Drolshagen, Charles T.; Hosokawa, Patrick W.; Brandt, Elias; Pace, Wilson D.; Uhrich, Christopher; Kamerick, Michael; Bunting, Aidan; Payne, Philip R.O.; Stephens, William E.; George, Joseph M.; Vance, Mark; Giacomini, Kelli; Braddy, Jason; Green, Mika K.; Kahn, Michael G.

2013-01-01

Introduction: Distributed Data Networks (DDNs) offer infrastructure solutions for sharing electronic health data from across disparate data sources to support comparative effectiveness research. Data sharing mechanisms must address technical and governance concerns stemming from network security and data disclosure laws and best practices, such as HIPAA. Methods: The Scalable Architecture for Federated Translational Inquiries Network (SAFTINet) deploys TRIAD grid technology, a common data model, detailed technical documentation, and custom software for data harmonization to facilitate data sharing in collaboration with stakeholders in the care of safety net populations. Data sharing partners host TRIAD grid nodes containing harmonized clinical data within their internal or hosted network environments. Authorized users can use a central web-based query system to request analytic data sets. Discussion: SAFTINet DDN infrastructure achieved a number of data sharing objectives, including scalable and sustainable systems for ensuring harmonized data structures and terminologies and secure distributed queries. Initial implementation challenges were resolved through iterative discussions, development and implementation of technical documentation, governance, and technology solutions. PMID:25848567

Scalable Architecture for Federated Translational Inquiries Network (SAFTINet) Technology Infrastructure for a Distributed Data Network.

PubMed

Schilling, Lisa M; Kwan, Bethany M; Drolshagen, Charles T; Hosokawa, Patrick W; Brandt, Elias; Pace, Wilson D; Uhrich, Christopher; Kamerick, Michael; Bunting, Aidan; Payne, Philip R O; Stephens, William E; George, Joseph M; Vance, Mark; Giacomini, Kelli; Braddy, Jason; Green, Mika K; Kahn, Michael G

2013-01-01

Distributed Data Networks (DDNs) offer infrastructure solutions for sharing electronic health data from across disparate data sources to support comparative effectiveness research. Data sharing mechanisms must address technical and governance concerns stemming from network security and data disclosure laws and best practices, such as HIPAA. The Scalable Architecture for Federated Translational Inquiries Network (SAFTINet) deploys TRIAD grid technology, a common data model, detailed technical documentation, and custom software for data harmonization to facilitate data sharing in collaboration with stakeholders in the care of safety net populations. Data sharing partners host TRIAD grid nodes containing harmonized clinical data within their internal or hosted network environments. Authorized users can use a central web-based query system to request analytic data sets. SAFTINet DDN infrastructure achieved a number of data sharing objectives, including scalable and sustainable systems for ensuring harmonized data structures and terminologies and secure distributed queries. Initial implementation challenges were resolved through iterative discussions, development and implementation of technical documentation, governance, and technology solutions.

Procurement of Shared Data Instruments for Research Electronic Data Capture (REDCap)

PubMed Central

Obeid, Jihad S; McGraw, Catherine A; Minor, Brenda L; Conde, José G; Pawluk, Robert; Lin, Michael; Wang, Janey; Banks, Sean R; Hemphill, Sheree A; Taylor, Rob; Harris, Paul A

2012-01-01

REDCap (Research Electronic Data Capture) is a web-based software solution and tool set that allows biomedical researchers to create secure online forms for data capture, management and analysis with minimal effort and training. The Shared Data Instrument Library (SDIL) is a relatively new component of REDCap that allows sharing of commonly used data collection instruments for immediate study use by 3 research teams. Objectives of the SDIL project include: 1) facilitating reuse of data dictionaries and reducing duplication of effort; 2) promoting the use of validated data collection instruments, data standards and best practices; and 3) promoting research collaboration and data sharing. Instruments submitted to the library are reviewed by a library oversight committee, with rotating membership from multiple institutions, which ensures quality, relevance and legality of shared instruments. The design allows researchers to download the instruments in a consumable electronic format in the REDCap environment. At the time of this writing, the SDIL contains over 128 data collection instruments. Over 2500 instances of instruments have been downloaded by researchers at multiple institutions. In this paper we describe the library platform, provide detail about experience gained during the first 25 months of sharing public domain instruments and provide evidence of impact for the SDIL across the REDCap consortium research community. We postulate that the shared library of instruments reduces the burden of adhering to sound data collection principles while promoting best practices. PMID:23149159

To share or not to share? Expected pros and cons of data sharing in radiological research.

PubMed

Sardanelli, Francesco; Alì, Marco; Hunink, Myriam G; Houssami, Nehmat; Sconfienza, Luca M; Di Leo, Giovanni

2018-06-01

The aims of this paper are to illustrate the trend towards data sharing, i.e. the regulated availability of the original patient-level data obtained during a study, and to discuss the expected advantages (pros) and disadvantages (cons) of data sharing in radiological research. Expected pros include the potential for verification of original results with alternative or supplementary analyses (including estimation of reproducibility), advancement of knowledge by providing new results by testing new hypotheses (not explored by the original authors) on pre-existing databases, larger scale analyses based on individual-patient data, enhanced multidisciplinary cooperation, reduced publication of false studies, improved clinical practice, and reduced cost and time for clinical research. Expected cons are outlined as the risk that the original authors could not exploit the entire potential of the data they obtained, possible failures in patients' privacy protection, technical barriers such as the lack of standard formats, and possible data misinterpretation. Finally, open issues regarding data ownership, the role of individual patients, advocacy groups and funding institutions in decision making about sharing of data and images are discussed. • Regulated availability of patient-level data of published clinical studies (data-sharing) is expected. • Expected benefits include verification/advancement of knowledge, reduced cost/time of research, clinical improvement. • Potential drawbacks include faults in patients' identity protection and data misinterpretation.

IMPACT Observatory: tracking the evolution of clinical trial data sharing and research integrity

PubMed Central

Krleža-Jerić, Karmela; Gabelica, Mirko; Banzi, Rita; Martinić, Marina Krnić; Pulido, Bibiana; Mahmić-Kaknjo, Mersiha; Reveiz, Ludovic; Šimić, Josip; Utrobičić, Ana; Hrgović, Irena

2016-01-01

Introduction The opening of research data is emerging thanks to the increasing possibilities of digital technology. The opening of clinical trial (CT) data is a part of this process, expected to have positive scientific, ethical, health, and economic impacts thus contributing to research integrity. The January 2016 proposal by the International Council of Medical Journal Editors triggered ample discussion about CT data sharing and reconfirmed the need for an ongoing assessment of its dynamics. The IMProving Access to Clinical Trials data (IMPACT) Observatory aims to play such a role, and assess the data sharing culture, policies, and practices of key players, the impact of their interventions on CTs, and contribute to a transformation of research. The objective of this paper is to present the IMPACT Observatory as well as share some of its preliminary findings. Materials and methods Methods include a scoping study of research, surveys, interviews, and an environmental scan of research data repositories. Results Our preliminary findings indicate that although opening of CT data has not yet been achieved, its evolution is encouraging. Initiatives by key players contribute to increasing of CT data sharing, and many barriers are shrinking or disappearing. Conclusions The major barrier is the lack of data sharing standards, from preparing data for public sharing to its curatorship, findability and access. However, experiences accumulated by sharing CT data according to “upon request” or “open” mechanisms could inform the development of such standards. The Vivli, CORBEL-ECRIN and Open Trials projects are currently working in this direction. PMID:27812300

Alternative Fuels Data Center: Alternative Fueling Station Locator

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Alternative Fuels Data Center: Hydrogen Fueling Station Locations

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Hydrogen Printable Version Share this resource Send a link to Alternative Fuels Data Center : Hydrogen Fueling Station Locations to someone by E-mail Share Alternative Fuels Data Center: Hydrogen Fuels Data Center: Hydrogen Fueling Station Locations on Digg Find More places to share Alternative

Offering to Share: How to Put Heads Together in Autism Neuroimaging

ERIC Educational Resources Information Center

Belmonte, Matthew K.; Mazziotta, John C.; Minshew, Nancy J.; Evans, Alan C.; Courchesne, Eric; Dager, Stephen R.; Bookheimer, Susan Y.; Aylward, Elizabeth H.; Amaral, David G.; Cantor, Rita M.; Chugani, Diane C.; Dale, Anders M.; Davatzikos, Christos; Gerig, Guido; Herbert, Martha R.; Lainhart, Janet E.; Murphy, Declan G.; Piven, Joseph; Reiss, Allan L.; Schultz, Robert T.; Zeffiro, Thomas A.; Levi-Pearl, Susan; Lajonchere, Clara; Colamarino, Sophia A.

2008-01-01

Data sharing in autism neuroimaging presents scientific, technical, and social obstacles. We outline the desiderata for a data-sharing scheme that combines imaging with other measures of phenotype and with genetics, defines requirements for comparability of derived data and recommendations for raw data, outlines a core protocol including…

Share and Succeed: The Development of Knowledge Sharing and Brokerage in Data Teams' Network Structures

ERIC Educational Resources Information Center

Hubers, Mireille D.; Moolenaar, Nienke M.; Schildkamp, Kim; Daly, Alan J.; Handelzalts, Adam; Pieters, Jules M.

2018-01-01

The data team intervention was designed to support Dutch secondary schools in using data while developing a solution to an educational problem. A data team can build school-wide capacity for data use through knowledge sharing among data team members, and knowledge brokerage between the team and other colleagues. The goal of this mixed-methods…

Distributed clinical data sharing via dynamic access-control policy transformation.

PubMed

Rezaeibagha, Fatemeh; Mu, Yi

2016-05-01

Data sharing in electronic health record (EHR) systems is important for improving the quality of healthcare delivery. Data sharing, however, has raised some security and privacy concerns because healthcare data could be potentially accessible by a variety of users, which could lead to privacy exposure of patients. Without addressing this issue, large-scale adoption and sharing of EHR data are impractical. The traditional solution to the problem is via encryption. Although encryption can be applied to access control, it is not applicable for complex EHR systems that require multiple domains (e.g. public and private clouds) with various access requirements. This study was carried out to address the security and privacy issues of EHR data sharing with our novel access-control mechanism, which captures the scenario of the hybrid clouds and need of access-control policy transformation, to provide secure and privacy-preserving data sharing among different healthcare enterprises. We introduce an access-control mechanism with some cryptographic building blocks and present a novel approach for secure EHR data sharing and access-control policy transformation in EHR systems for hybrid clouds. We propose a useful data sharing system for healthcare providers to handle various EHR users who have various access privileges in different cloud environments. A systematic study has been conducted on data sharing in EHR systems to provide a solution to the security and privacy issues. In conclusion, we introduce an access-control method for privacy protection of EHRs and EHR policy transformation that allows an EHR access-control policy to be transformed from a private cloud to a public cloud. This method has never been studied previously in the literature. Furthermore, we provide a protocol to demonstrate policy transformation as an application scenario. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Data sharing and reanalysis of randomized controlled trials in leading biomedical journals with a full data sharing policy: survey of studies published in The BMJ and PLOS Medicine.

PubMed

Naudet, Florian; Sakarovitch, Charlotte; Janiaud, Perrine; Cristea, Ioana; Fanelli, Daniele; Moher, David; Ioannidis, John P A

2018-02-13

To explore the effectiveness of data sharing by randomized controlled trials (RCTs) in journals with a full data sharing policy and to describe potential difficulties encountered in the process of performing reanalyses of the primary outcomes. Survey of published RCTs. PubMed/Medline. RCTs that had been submitted and published by The BMJ and PLOS Medicine subsequent to the adoption of data sharing policies by these journals. The primary outcome was data availability, defined as the eventual receipt of complete data with clear labelling. Primary outcomes were reanalyzed to assess to what extent studies were reproduced. Difficulties encountered were described. 37 RCTs (21 from The BMJ and 16 from PLOS Medicine ) published between 2013 and 2016 met the eligibility criteria. 17/37 (46%, 95% confidence interval 30% to 62%) satisfied the definition of data availability and 14 of the 17 (82%, 59% to 94%) were fully reproduced on all their primary outcomes. Of the remaining RCTs, errors were identified in two but reached similar conclusions and one paper did not provide enough information in the Methods section to reproduce the analyses. Difficulties identified included problems in contacting corresponding authors and lack of resources on their behalf in preparing the datasets. In addition, there was a range of different data sharing practices across study groups. Data availability was not optimal in two journals with a strong policy for data sharing. When investigators shared data, most reanalyses largely reproduced the original results. Data sharing practices need to become more widespread and streamlined to allow meaningful reanalyses and reuse of data. Open Science Framework osf.io/c4zke. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Data Storage and sharing for the long tail of science

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, B.; Pouchard, L.; Smith, P. M.

Research data infrastructure such as storage must now accommodate new requirements resulting from trends in research data management that require researchers to store their data for the long term and make it available to other researchers. We propose Data Depot, a system and service that provides capabilities for shared space within a group, shared applications, flexible access patterns and ease of transfer at Purdue University. We evaluate Depot as a solution for storing and sharing multiterabytes of data produced in the long tail of science with a use case in soundscape ecology studies from the Human- Environment Modeling and Analysismore » Laboratory. We observe that with the capabilities enabled by Data Depot, researchers can easily deploy fine-grained data access control, manage data transfer and sharing, as well as integrate their workflows into a High Performance Computing environment.« less

Examining Data Repository Guidelines for Qualitative Data Sharing.

PubMed

Antes, Alison L; Walsh, Heidi A; Strait, Michelle; Hudson-Vitale, Cynthia R; DuBois, James M

2018-02-01

Qualitative data provide rich information on research questions in diverse fields. Recent calls for increased transparency and openness in research emphasize data sharing. However, qualitative data sharing has yet to become the norm internationally and is particularly uncommon in the United States. Guidance for archiving and secondary use of qualitative data is required for progress in this regard. In this study, we review the benefits and concerns associated with qualitative data sharing and then describe the results of a content analysis of guidelines from international repositories that archive qualitative data. A minority of repositories provide qualitative data sharing guidelines. Of the guidelines available, there is substantial variation in whether specific topics are addressed. Some topics, such as removing direct identifiers, are consistently addressed, while others, such as providing an anonymization log, are not. We discuss the implications of our study for education, best practices, and future research.

Big data from small data: data-sharing in the ‘long tail’ of neuroscience

PubMed Central

Ferguson, Adam R; Nielson, Jessica L; Cragin, Melissa H; Bandrowski, Anita E; Martone, Maryann E

2016-01-01

The launch of the US BRAIN and European Human Brain Projects coincides with growing international efforts toward transparency and increased access to publicly funded research in the neurosciences. The need for data-sharing standards and neuroinformatics infrastructure is more pressing than ever. However, ‘big science’ efforts are not the only drivers of data-sharing needs, as neuroscientists across the full spectrum of research grapple with the overwhelming volume of data being generated daily and a scientific environment that is increasingly focused on collaboration. In this commentary, we consider the issue of sharing of the richly diverse and heterogeneous small data sets produced by individual neuroscientists, so-called long-tail data. We consider the utility of these data, the diversity of repositories and options available for sharing such data, and emerging best practices. We provide use cases in which aggregating and mining diverse long-tail data convert numerous small data sources into big data for improved knowledge about neuroscience-related disorders. PMID:25349910

Data Standards for Omics Data: The Basis of Data Sharing and Reuse

PubMed Central

Chervitz, Stephen A.; Deutsch, Eric W.; Field, Dawn; Parkinson, Helen; Quackenbush, John; Rocca-Serra, Phillipe; Sansone, Susanna-Assunta; Stoeckert, Christian J.; Taylor, Chris F.; Taylor, Ronald; Ball, Catherine A.

2014-01-01

To facilitate sharing of Omics data, many groups of scientists have been working to establish the relevant data standards. The main components of data sharing standards are experiment description standards, data exchange standards, terminology standards, and experiment execution standards. Here we provide a survey of existing and emerging standards that are intended to assist the free and open exchange of large-format data. PMID:21370078

Substitute consent to data sharing: a way forward for international dementia research?

PubMed Central

Thorogood, Adrian; Deschênes St-Pierre, Constance; Knoppers, Bartha Maria

2017-01-01

Abstract A deluge of genetic and health-related data is being generated about patients with dementia. International sharing of these data accelerates dementia research. Seeking consent to data sharing is a challenge for dementia research where patients have lost or risk losing legal capacity. The laws of most countries enable substitute decision makers (SDMs) to consent on behalf of incapable adults to research participation. We compare regulatory frameworks governing capacity, research, and personal data protection across eight countries to determine when SDMs can consent to data sharing. In most countries, an SDM can consent to data sharing in the incapable adult's best interests. Best interests typically include consideration of the individual's previously expressed wishes, values and beliefs; well-being; and inclusion in decision making. Countries differ in how these considerations are balanced. A clear previous consent or refusal to share data typically binds the discretion of an SDM. Though generally permissive, National patchworks of laws and guidelines cause confusion. Clarity on the applicable law and processes to enhance ethical decision making are needed to facilitate substitute consent. Researchers can encourage patients to communicate their research preferences before a loss of capacity, and educate SDMs about their ethical and legal duties. The research community must also continue to promote the importance of data sharing in dementia. PMID:28852560

Sharing privacy-sensitive access to neuroimaging and genetics data: a review and preliminary validation

PubMed Central

Sarwate, Anand D.; Plis, Sergey M.; Turner, Jessica A.; Arbabshirani, Mohammad R.; Calhoun, Vince D.

2014-01-01

The growth of data sharing initiatives for neuroimaging and genomics represents an exciting opportunity to confront the “small N” problem that plagues contemporary neuroimaging studies while further understanding the role genetic markers play in the function of the brain. When it is possible, open data sharing provides the most benefits. However, some data cannot be shared at all due to privacy concerns and/or risk of re-identification. Sharing other data sets is hampered by the proliferation of complex data use agreements (DUAs) which preclude truly automated data mining. These DUAs arise because of concerns about the privacy and confidentiality for subjects; though many do permit direct access to data, they often require a cumbersome approval process that can take months. An alternative approach is to only share data derivatives such as statistical summaries—the challenges here are to reformulate computational methods to quantify the privacy risks associated with sharing the results of those computations. For example, a derived map of gray matter is often as identifiable as a fingerprint. Thus alternative approaches to accessing data are needed. This paper reviews the relevant literature on differential privacy, a framework for measuring and tracking privacy loss in these settings, and demonstrates the feasibility of using this framework to calculate statistics on data distributed at many sites while still providing privacy. PMID:24778614

Sharing privacy-sensitive access to neuroimaging and genetics data: a review and preliminary validation.

PubMed

Sarwate, Anand D; Plis, Sergey M; Turner, Jessica A; Arbabshirani, Mohammad R; Calhoun, Vince D

2014-01-01

The growth of data sharing initiatives for neuroimaging and genomics represents an exciting opportunity to confront the "small N" problem that plagues contemporary neuroimaging studies while further understanding the role genetic markers play in the function of the brain. When it is possible, open data sharing provides the most benefits. However, some data cannot be shared at all due to privacy concerns and/or risk of re-identification. Sharing other data sets is hampered by the proliferation of complex data use agreements (DUAs) which preclude truly automated data mining. These DUAs arise because of concerns about the privacy and confidentiality for subjects; though many do permit direct access to data, they often require a cumbersome approval process that can take months. An alternative approach is to only share data derivatives such as statistical summaries-the challenges here are to reformulate computational methods to quantify the privacy risks associated with sharing the results of those computations. For example, a derived map of gray matter is often as identifiable as a fingerprint. Thus alternative approaches to accessing data are needed. This paper reviews the relevant literature on differential privacy, a framework for measuring and tracking privacy loss in these settings, and demonstrates the feasibility of using this framework to calculate statistics on data distributed at many sites while still providing privacy.

Balancing the risks and benefits of genomic data sharing: genome research participants' perspectives.

PubMed

Oliver, J M; Slashinski, M J; Wang, T; Kelly, P A; Hilsenbeck, S G; McGuire, A L

2012-01-01

Technological advancements are rapidly propelling the field of genome research forward, while lawmakers attempt to keep apace with the risks these advances bear. Balancing normative concerns of maximizing data utility and protecting human subjects, whose privacy is at risk due to the identifiability of DNA data, are central to policy decisions. Research on genome research participants making real-time data sharing decisions is limited; yet, these perspectives could provide critical information to ongoing deliberations. We conducted a randomized trial of 3 consent types affording varying levels of control over data release decisions. After debriefing participants about the randomization process, we invited them to a follow-up interview to assess their attitudes toward genetic research, privacy and data sharing. Participants were more restrictive in their reported data sharing preferences than in their actual data sharing decisions. They saw both benefits and risks associated with sharing their genomic data, but risks were seen as less concrete or happening in the future, and were largely outweighed by purported benefits. Policymakers must respect that participants' assessment of the risks and benefits of data sharing and their privacy-utility determinations, which are associated with their final data release decisions, vary. In order to advance the ethical conduct of genome research, proposed policy changes should carefully consider these stakeholder perspectives. Copyright © 2011 S. Karger AG, Basel.

Neuroimaging Data Sharing on the Neuroinformatics Database Platform

PubMed Central

Book, Gregory A; Stevens, Michael; Assaf, Michal; Glahn, David; Pearlson, Godfrey D

2015-01-01

We describe the Neuroinformatics Database (NiDB), an open-source database platform for archiving, analysis, and sharing of neuroimaging data. Data from the multi-site projects Autism Brain Imaging Data Exchange (ABIDE), Bipolar-Schizophrenia Network on Intermediate Phenotypes parts one and two (B-SNIP1, B-SNIP2), and Monetary Incentive Delay task (MID) are available for download from the public instance of NiDB, with more projects sharing data as it becomes available. As demonstrated by making several large datasets available, NiDB is an extensible platform appropriately suited to archive and distribute shared neuroimaging data. PMID:25888923

Sharing Medical Data for Health Research: The Early Personal Health Record Experience

PubMed Central

Kaci, Liljana; Mandl, Kenneth D

2010-01-01

Background Engaging consumers in sharing information from personally controlled health records (PCHRs) for health research may promote goals of improving care and advancing public health consistent with the federal Health Information Technology for Economic and Clinical Health (HITECH) Act. Understanding consumer willingness to share data is critical to advancing this model. Objective The objective was to characterize consumer willingness to share PCHR data for health research and the conditions and contexts bearing on willingness to share. Methods A mixed method approach integrating survey and narrative data was used. Survey data were collected about attitudes toward sharing PCHR information for health research from early adopters (n = 151) of a live PCHR populated with medical records and self-reported behavioral and social data. Data were analyzed using descriptive statistics and logistic regression to characterize willingness, conditions for sharing, and variations by sociodemographic factors. Narrative data were collected through semistructured focus group and one-on-one interviews with a separate sample of community members (n = 30) following exposure to PCHR demonstrations. Two independent analysts coded narrative data for major and minor themes using a shared rubric of a priori defined codes and an iterative inductive process. Findings were triangulated with survey results to identify patterns. Results Of PHCR users, 138 out of 151 (91%) were willing to share medical information for health research with 89 (59%) favoring an opt-in sharing model. Willingness to share was conditioned by anonymity, research use, engagement with a trusted intermediary, transparency around PCHR access and use, and payment. Consumer-determined restrictions on content and timing of sharing may be prerequisites to sharing. Select differences in support for sharing under different conditions were observed across social groups. No gender differences were observed; however differences in age, role, and self-rated health were found. For example, students were more likely than nonstudents to favor an opt-out sharing default (unadjusted odds ratio [OR] = 2.89, 95% confidence interval [CI] 1.10 - 7.62, P = .03). Participants over age 50 were less likely than younger participants to report that payment would increase willingness to share (unadjusted OR = 0.94, 95% CI 0.91 - 0.96, P < .001). Students were more likely than nonstudents to report that payment would increase their willingness to share (unadjusted OR 9.62, 95% CI 3.44 - 26.87, P < .001). Experiencing a public health emergency may increase willingness to share especially among persons over 50 (unadjusted OR 1.03, 95% CI 1.01 - 1.05, P = .02); however, students were less likely than non-students to report this attitude (unadjusted OR 0.13, 95% CI 0.05 - 0.36, P < .001). Finally, subjects with fair or poor self-rated health were less likely than those with good to excellent self-rated health to report that willingness to share would increase during a public health emergency (unadjusted OR 0.61, 95% CI 0.38 - 0.97, P = .04). Conclusions Strong support for sharing of PCHR information for health research existed among early adopters and focus group participants, with support varying by social group under different conditions and contexts. Allowing users to select their preferred conditions for sharing may be vital to supporting sharing and fostering trust as may be development of safety monitoring mechanisms. PMID:20501431

Developing Governance for Federated Community-based EHR Data Sharing

PubMed Central

Lin, Ching-Ping; Stephens, Kari A.; Baldwin, Laura-Mae; Keppel, Gina A.; Whitener, Ron J.; Echo-Hawk, Abigail; Korngiebel, Diane

2014-01-01

Bi-directional translational pathways between scientific discoveries and primary care are crucial for improving individual patient care and population health. The Data QUEST pilot project is a program supporting data sharing amongst community based primary care practices and is built on a technical infrastructure to share electronic health record data. We developed a set of governance requirements from interviewing and collaborating with partner organizations. Recommendations from our partner organizations included: 1) partner organizations can physically terminate the link to the data sharing network and only approved data exits the local site; 2) partner organizations must approve or reject each query; 3) partner organizations and researchers must respect local processes, resource restrictions, and infrastructures; and 4) partner organizations can be seamlessly added and removed from any individual data sharing query or the entire network. PMID:25717404

Data Rights and Responsibilities: A Human Rights Perspective on Data Sharing.

PubMed

Harris, Theresa L; Wyndham, Jessica M

2015-07-01

A human-rights-based analysis can be a useful tool for the scientific community and policy makers as they develop codes of conduct, harmonized standards, and national policies for data sharing. The human rights framework provides a shared set of values and norms across borders, defines rights and responsibilities of various actors involved in data sharing, addresses the potential harms as well as the benefits of data sharing, and offers a framework for balancing competing values. The right to enjoy the benefits of scientific progress and its applications offers a particularly helpful lens through which to view data as both a tool of scientific inquiry to which access is vital and as a product of science from which everyone should benefit. © The Author(s) 2015.

Examples of Effective Data Sharing in Scientific Publishing

DOE PAGES

Kitchin, John R.

2015-05-11

Here, we present a perspective on an approach to data sharing in scientific publications we have been developing in our group. The essence of the approach is that data can be embedded in a human-readable and machine-addressable way within the traditional publishing environment. We show this by example for both computational and experimental data. We articulate a need for new authoring tools to facilitate data sharing, and we discuss the tools we have been developing for this purpose. With these tools, data generation, analysis, and manuscript preparation can be deeply integrated, resulting in easier and better data sharing in scientificmore » publications.« less

Examples of Effective Data Sharing in Scientific Publishing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kitchin, John R.

Here, we present a perspective on an approach to data sharing in scientific publications we have been developing in our group. The essence of the approach is that data can be embedded in a human-readable and machine-addressable way within the traditional publishing environment. We show this by example for both computational and experimental data. We articulate a need for new authoring tools to facilitate data sharing, and we discuss the tools we have been developing for this purpose. With these tools, data generation, analysis, and manuscript preparation can be deeply integrated, resulting in easier and better data sharing in scientificmore » publications.« less

Balancing data sharing requirements for analyses with data sensitivity

USGS Publications Warehouse

Jarnevich, C.S.; Graham, J.J.; Newman, G.J.; Crall, A.W.; Stohlgren, T.J.

2007-01-01

Data sensitivity can pose a formidable barrier to data sharing. Knowledge of species current distributions from data sharing is critical for the creation of watch lists and an early warning/rapid response system and for model generation for the spread of invasive species. We have created an on-line system to synthesize disparate datasets of non-native species locations that includes a mechanism to account for data sensitivity. Data contributors are able to mark their data as sensitive. This data is then 'fuzzed' in mapping applications and downloaded files to quarter-quadrangle grid cells, but the actual locations are available for analyses. We propose that this system overcomes the hurdles to data sharing posed by sensitive data. ?? 2006 Springer Science+Business Media B.V.

30 CFR 280.73 - Will MMS share data and information with coastal States?

Code of Federal Regulations, 2010 CFR

2010-07-01

... Data Requirements Protections § 280.73 Will MMS share data and information with coastal States? (a) We... 30 Mineral Resources 2 2010-07-01 2010-07-01 false Will MMS share data and information with coastal States? 280.73 Section 280.73 Mineral Resources MINERALS MANAGEMENT SERVICE, DEPARTMENT OF THE...

30 CFR 580.73 - Will BOEM share data and information with coastal States?

Code of Federal Regulations, 2012 CFR

2012-07-01

... CONTINENTAL SHELF Data Requirements Protections § 580.73 Will BOEM share data and information with coastal... 30 Mineral Resources 2 2012-07-01 2012-07-01 false Will BOEM share data and information with coastal States? 580.73 Section 580.73 Mineral Resources BUREAU OF OCEAN ENERGY MANAGEMENT, DEPARTMENT OF...

30 CFR 580.73 - Will BOEM share data and information with coastal States?

Code of Federal Regulations, 2014 CFR

2014-07-01

... CONTINENTAL SHELF Data Requirements Protections § 580.73 Will BOEM share data and information with coastal... 30 Mineral Resources 2 2014-07-01 2014-07-01 false Will BOEM share data and information with coastal States? 580.73 Section 580.73 Mineral Resources BUREAU OF OCEAN ENERGY MANAGEMENT, DEPARTMENT OF...

75 FR 66110 - Guidelines for Use of Stored Specimens and Access to Ancillary Data and Proposed Cost Schedule...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-27

... repository of datasets from completed studies, biospecimens, and ancillary data. The Division intends to make... Sharing Policy. The Division has established an internal committee, the Biospecimen Repository Access and Data Sharing Committee (BRADSC), to oversee the repository access and data sharing program. The purpose...

Enriching the Web of Data with Educational Information Using We-Share

ERIC Educational Resources Information Center

Ruiz-Calleja, Adolfo; Asensio-Pérez, Juan I.; Vega-Gorgojo, Guillermo; Gómez-Sánchez, Eduardo; Bote-Lorenzo, Miguel L.; Alario-Hoyos, Carlos

2017-01-01

This paper presents We-Share, a social annotation application that enables educators to publish and retrieve information about educational ICT tools. As a distinctive characteristic, We-Share provides educators data about educational tools already available on the Web of Data while allowing them to enrich such data with their experience using…

Alternative Fuels Data Center: Forgot Your Password?

Science.gov Websites

AFDC Printable Version Share this resource Send a link to Alternative Fuels Data Center: Forgot Your Password? to someone by E-mail Share Alternative Fuels Data Center: Forgot Your Password? on to share Alternative Fuels Data Center: Forgot Your Password? on AddThis.com... Forgot Your Password

Alternative Fuels Data Center: Propane Laws and Incentives

Science.gov Websites

Propane Printable Version Share this resource Send a link to Alternative Fuels Data Center: Propane Laws and Incentives to someone by E-mail Share Alternative Fuels Data Center: Propane Laws and and Incentives on Digg Find More places to share Alternative Fuels Data Center: Propane Laws and

Alternative Fuels Data Center: Hydrogen Laws and Incentives

Science.gov Websites

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Alternative Fuels Data Center: Idle Reduction Laws and Incentives

Science.gov Websites

Conserve Fuel Printable Version Share this resource Send a link to Alternative Fuels Data Center : Idle Reduction Laws and Incentives to someone by E-mail Share Alternative Fuels Data Center: Idle Fuels Data Center: Idle Reduction Laws and Incentives on Digg Find More places to share Alternative

30 CFR 580.73 - Will BOEM share data and information with coastal States?

Code of Federal Regulations, 2013 CFR

2013-07-01

... CONTINENTAL SHELF Data Requirements Protections § 580.73 Will BOEM share data and information with coastal... 30 Mineral Resources 2 2013-07-01 2013-07-01 false Will BOEM share data and information with coastal States? 580.73 Section 580.73 Mineral Resources BUREAU OF OCEAN ENERGY MANAGEMENT, DEPARTMENT OF...

The growth and gaps of genetic data sharing policies in the United States

PubMed Central

Arias, Jalayne J.; Pham-Kanter, Genevieve; Campbell, Eric G.

2014-01-01

The 1996 Bermuda Principles launched a new era in data sharing, reflecting a growing belief that the rapid public dissemination of research data was crucial to scientific progress in genetics. A historical review of data sharing policies in the field of genetics and genomics reflects changing scientific norms and evolving views of genomic data, particularly related to human subjects’ protections and privacy concerns. The 2013 NIH Draft Genomic Data Sharing (GDS) Policy incorporates the most significant protections and guidelines to date. The GDS Policy, however, will face difficult challenges ahead as geneticists seek to balance the very real concerns of research participants and the scientific norms that propel research forward. This article provides a novel evaluation of genetic and GDS policies’ treatment of human subjects’ protections. The article examines not only the policies, but also some of the most pertinent scientific, legal, and regulatory developments that occurred alongside data sharing policies. This historical perspective highlights the challenges that future data sharing policies, including the recently disseminated NIH GDS Draft Policy, will encounter. PMID:27774180

Protecting patient privacy when sharing patient-level data from clinical trials.

PubMed

Tucker, Katherine; Branson, Janice; Dilleen, Maria; Hollis, Sally; Loughlin, Paul; Nixon, Mark J; Williams, Zoë

2016-07-08

Greater transparency and, in particular, sharing of patient-level data for further scientific research is an increasingly important topic for the pharmaceutical industry and other organisations who sponsor and conduct clinical trials as well as generally in the interests of patients participating in studies. A concern remains, however, over how to appropriately prepare and share clinical trial data with third party researchers, whilst maintaining patient confidentiality. Clinical trial datasets contain very detailed information on each participant. Risk to patient privacy can be mitigated by data reduction techniques. However, retention of data utility is important in order to allow meaningful scientific research. In addition, for clinical trial data, an excessive application of such techniques may pose a public health risk if misleading results are produced. After considering existing guidance, this article makes recommendations with the aim of promoting an approach that balances data utility and privacy risk and is applicable across clinical trial data holders. Our key recommendations are as follows: 1. Data anonymisation/de-identification: Data holders are responsible for generating de-identified datasets which are intended to offer increased protection for patient privacy through masking or generalisation of direct and some indirect identifiers. 2. Controlled access to data, including use of a data sharing agreement: A legally binding data sharing agreement should be in place, including agreements not to download or further share data and not to attempt to seek to identify patients. Appropriate levels of security should be used for transferring data or providing access; one solution is use of a secure 'locked box' system which provides additional safeguards. This article provides recommendations on best practices to de-identify/anonymise clinical trial data for sharing with third-party researchers, as well as controlled access to data and data sharing agreements. The recommendations are applicable to all clinical trial data holders. Further work will be needed to identify and evaluate competing possibilities as regulations, attitudes to risk and technologies evolve.

Best Practices for Ethical Sharing of Individual-Level Health Research Data From Low- and Middle-Income Settings

PubMed Central

Cheah, Phaik Yeong; Denny, Spencer; Jao, Irene; Marsh, Vicki; Merson, Laura; Shah More, Neena; Nhan, Le Nguyen Thanh; Osrin, David; Tangseefa, Decha; Wassenaar, Douglas; Parker, Michael

2015-01-01

Sharing individual-level data from clinical and public health research is increasingly being seen as a core requirement for effective and efficient biomedical research. This article discusses the results of a systematic review and multisite qualitative study of key stakeholders’ perspectives on best practices in ethical data sharing in low- and middle-income settings. Our research suggests that for data sharing to be effective and sustainable, multiple social and ethical requirements need to be met. An effective model of data sharing will be one in which considered judgments will need to be made about how best to achieve scientific progress, minimize risks of harm, promote fairness and reciprocity, and build and sustain trust. PMID:26297751

Clinical Trial Data as Public Goods: Fair Trade and the Virtual Knowledge Bank as a Solution to the Free Rider Problem - A Framework for the Promotion of Innovation by Facilitation of Clinical Trial Data Sharing among Biopharmaceutical Companies in the Era of Omics and Big Data.

PubMed

Evangelatos, Nikolaos; Reumann, Matthias; Lehrach, Hans; Brand, Angela

2016-01-01

Knowledge in the era of Omics and Big Data has been increasingly conceptualized as a public good. Sharing of de-identified patient data has been advocated as a means to increase confidence and public trust in the results of clinical trials. On the other hand, research has shown that the current research and development model of the biopharmaceutical industry has reached its innovation capacity. In response to that, the biopharmaceutical industry has adopted open innovation practices, with sharing of clinical trial data being among the most interesting ones. However, due to the free rider problem, clinical trial data sharing among biopharmaceutical companies could undermine their innovativeness. Based on the theory of public goods, we have developed a commons arrangement and devised a model, which enables secure and fair clinical trial data sharing over a Virtual Knowledge Bank based on a web platform. Our model uses data as a virtual currency and treats knowledge as a club good. Fair sharing of clinical trial data over the Virtual Knowledge Bank has positive effects on the innovation capacity of the biopharmaceutical industry without compromising the intellectual rights, proprietary interests and competitiveness of the latter. The Virtual Knowledge Bank is a sustainable and self-expanding model for secure and fair clinical trial data sharing that allows for sharing of clinical trial data, while at the same time it increases the innovation capacity of the biopharmaceutical industry. © 2016 S. Karger AG, Basel.

Data sharing policy design for consortia: challenges for sustainability.

PubMed

Kaye, Jane; Hawkins, Naomi

2014-01-01

The field of human genomics has led advances in the sharing of data with a view to facilitating translation of research into innovations for human health. This change in scientific practice has been implemented through new policy developed by many principal investigators, project managers and funders, which has ultimately led to new forms of practice and innovative governance models for data sharing. Here, we examine the development of the governance of data sharing in genomics, and explore some of the key challenges associated with the design and implementation of these policies. We examine how the incremental nature of policy design, the perennial problem of consent, the gridlock caused by multiple and overlapping access systems, the administrative burden and the problems with incentives and acknowledgment all have an impact on the potential for data sharing to be maximized. We conclude by proposing ways in which the scientific community can address these problems, to improve the sustainability of data sharing into the future.

COINSTAC: A Privacy Enabled Model and Prototype for Leveraging and Processing Decentralized Brain Imaging Data.

PubMed

Plis, Sergey M; Sarwate, Anand D; Wood, Dylan; Dieringer, Christopher; Landis, Drew; Reed, Cory; Panta, Sandeep R; Turner, Jessica A; Shoemaker, Jody M; Carter, Kim W; Thompson, Paul; Hutchison, Kent; Calhoun, Vince D

2016-01-01

The field of neuroimaging has embraced the need for sharing and collaboration. Data sharing mandates from public funding agencies and major journal publishers have spurred the development of data repositories and neuroinformatics consortia. However, efficient and effective data sharing still faces several hurdles. For example, open data sharing is on the rise but is not suitable for sensitive data that are not easily shared, such as genetics. Current approaches can be cumbersome (such as negotiating multiple data sharing agreements). There are also significant data transfer, organization and computational challenges. Centralized repositories only partially address the issues. We propose a dynamic, decentralized platform for large scale analyses called the Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation (COINSTAC). The COINSTAC solution can include data missing from central repositories, allows pooling of both open and "closed" repositories by developing privacy-preserving versions of widely-used algorithms, and incorporates the tools within an easy-to-use platform enabling distributed computation. We present an initial prototype system which we demonstrate on two multi-site data sets, without aggregating the data. In addition, by iterating across sites, the COINSTAC model enables meta-analytic solutions to converge to "pooled-data" solutions (i.e., as if the entire data were in hand). More advanced approaches such as feature generation, matrix factorization models, and preprocessing can be incorporated into such a model. In sum, COINSTAC enables access to the many currently unavailable data sets, a user friendly privacy enabled interface for decentralized analysis, and a powerful solution that complements existing data sharing solutions.

DataONE: Survey of Earth Scientists, To Share or Not to Share Data

NASA Astrophysics Data System (ADS)

Branch, B. D.; Tenopir, C.; Allard, S.; Douglas, K.; Wu, L.; Frame, M.; Dataone-The Data Observation NetworkEarth

2010-12-01

A primary goal of the Data Observation Network for Earth (DataONE; http://dataone.org) is to ensure preservation and access to multi-scale, multi-discipline, and multi-national science data, particularly in the Earth and Environmental Sciences. As a means to measure project success and to better understand the needs of the community, we have conducted a baseline assessment of the data sharing practices and preferences of domain scientists. The survey is motivated by the understanding that improving access to the sharing of data requires changes in both technology and expectations of the scientific community. A follow-up survey conducted in the future will measure how data sharing initiatives such as DataONE have influenced attitudes and behaviors. A letter of invitation with a link to an online survey instrument was emailed to scientists. Scientists were contacted by several methods: through contacts at the universities where they work, through journal editors of science journals, and directly to biology and environmental science faculty at major U.S. universities. A total of 1329 responses were received. The overall findings from the baseline assessment demonstrate several key findings. -Data management practices vary: {56.1%of respondents did not use any metadata standard, 22.1% used a lab created metadata standard, and over half of respondents 59% (local site) and 55% (national site) mentioned that at least some of their data were available; only 42% (global) and 35% (regional site) respondents mentioned that their data were available.} -Many scientists are interested in sharing data. Over 80% of respondents agreed with the statements: {“I would use other researchers' datasets if their datasets were easily accessible.” and “I would be willing to share data across a broad group of researchers who use data in different ways.”} -There are many barriers to sharing data. The two most common barriers identified were: {Insufficient time (54%) and Lack of funding (40%)} -Some disciplines are using good data management practices: {90% of atmospheric scientists say they share data with others, and 49% of atmospheric scientists agree with the statement “Others can access my data easily”} Results will be compared with other recent surveys of data management practices, including Dryad digital repository efforts (NSF EF-0423641) and Permanent Access to the Records of Science in Europe (2010) study. Future work will seek to further investigate such findings by conducting in-depth profiles and possible personas development as an evidenced based rationale for earth scientists’ data sharing practices.

Win–win data sharing in neuroscience

PubMed Central

Ascoli, Giorgio A; Maraver, Patricia; Nanda, Sumit; Polavaram, Sridevi; Armañanzas, Rubén

2017-01-01

Most neuroscientists have yet to embrace a culture of data sharing. Using our decade-long experience at NeuroMorpho.Org as an example, we discuss how publicly available repositories may benefit data producers and end-users alike. We outline practical recipes for resource developers to maximize the research impact of data sharing platforms for both contributors and users. PMID:28139675

Sharing Overdose Data Across State Agencies to Inform Public Health Strategies: A Case Study.

PubMed

Cherico-Hsii, Sara; Bankoski, Andrea; Singal, Pooja; Horon, Isabelle; Beane, Eric; Casey, Meghan; Rebbert-Franklin, Kathleen; Sharfstein, Joshua

2016-01-01

Data sharing and analysis are important components of coordinated and cost-effective public health strategies. However, legal and policy barriers have made data from different agencies difficult to share and analyze for policy development. To address a rise in overdose deaths, Maryland used an innovative and focused approach to bring together data on overdose decedents across multiple agencies. The effort was focused on developing discrete intervention points based on information yielded on decedents' lives, such as vulnerability upon release from incarceration. Key aspects of this approach included gubernatorial leadership, a unified commitment to data sharing across agencies with memoranda of understanding, and designation of a data management team. Preliminary results have yielded valuable insights and have helped inform policy. This process of navigating legal and privacy concerns in data sharing across multiple agencies may be applied to a variety of public health problems challenging health departments across the country.

COINSTAC: A Privacy Enabled Model and Prototype for Leveraging and Processing Decentralized Brain Imaging Data

PubMed Central

Plis, Sergey M.; Sarwate, Anand D.; Wood, Dylan; Dieringer, Christopher; Landis, Drew; Reed, Cory; Panta, Sandeep R.; Turner, Jessica A.; Shoemaker, Jody M.; Carter, Kim W.; Thompson, Paul; Hutchison, Kent; Calhoun, Vince D.

2016-01-01

The field of neuroimaging has embraced the need for sharing and collaboration. Data sharing mandates from public funding agencies and major journal publishers have spurred the development of data repositories and neuroinformatics consortia. However, efficient and effective data sharing still faces several hurdles. For example, open data sharing is on the rise but is not suitable for sensitive data that are not easily shared, such as genetics. Current approaches can be cumbersome (such as negotiating multiple data sharing agreements). There are also significant data transfer, organization and computational challenges. Centralized repositories only partially address the issues. We propose a dynamic, decentralized platform for large scale analyses called the Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation (COINSTAC). The COINSTAC solution can include data missing from central repositories, allows pooling of both open and “closed” repositories by developing privacy-preserving versions of widely-used algorithms, and incorporates the tools within an easy-to-use platform enabling distributed computation. We present an initial prototype system which we demonstrate on two multi-site data sets, without aggregating the data. In addition, by iterating across sites, the COINSTAC model enables meta-analytic solutions to converge to “pooled-data” solutions (i.e., as if the entire data were in hand). More advanced approaches such as feature generation, matrix factorization models, and preprocessing can be incorporated into such a model. In sum, COINSTAC enables access to the many currently unavailable data sets, a user friendly privacy enabled interface for decentralized analysis, and a powerful solution that complements existing data sharing solutions. PMID:27594820

Availability and Use of Shared Data From Cardiometabolic Clinical Trials.

PubMed

Vaduganathan, Muthiah; Nagarur, Amulya; Qamar, Arman; Patel, Ravi B; Navar, Ann Marie; Peterson, Eric D; Bhatt, Deepak L; Fonarow, Gregg C; Yancy, Clyde W; Butler, Javed

2018-02-27

Sharing of patient-level clinical trial data has been widely endorsed. Little is known about how extensively these data have been used for cardiometabolic diseases. We sought to evaluate the availability and use of shared data from cardiometabolic clinical trials. We extracted data from ClinicalStudyDataRequest.com, a large, multisponsor data-sharing platform hosting individual patient-level data from completed studies sponsored by 13 pharmaceutical companies. From January 2013 to May 2017, the platform had data from 3374 clinical trials, of which 537 (16%) evaluated cardiometabolic therapeutics (phase 1, 36%; phase 2, 17%; phase 2/3, 1%; phase 3, 42%; phase 4, 4%). They covered 74 therapies and 398 925 patients. Diabetes mellitus (60%) and hypertension (15%) were the most common study topics. Median time from study completion to data availability was 79 months. As of May 2017, ClinicalStudyDataRequest.com had received 318 submitted proposals, of which 163 had signed data-sharing agreements. Thirty of these proposals were related to cardiometabolic therapies and requested data from 79 unique studies (15% of all trials, 29% of phase 3/4 trials). Most (96%) data requesters of cardiometabolic clinical trial data were from academic centers in North America and Western Europe, and half the proposals were unfunded. Most proposals were for secondary hypothesis-generating questions, with only 1 proposed reanalysis of the original study primary hypothesis. To date, 3 peer-reviewed articles have been published after a median of 19 months (9-32 months) from the data-sharing agreement. Despite availability of data from >500 cardiometabolic trials in a multisponsor data-sharing platform, only 15% of these trials and 29% of phase 3/4 trials have been accessed by investigators thus far, and a negligible minority of analyses have reached publication. © 2017 American Heart Association, Inc.

Classification of cognitive systems dedicated to data sharing

NASA Astrophysics Data System (ADS)

Ogiela, Lidia; Ogiela, Marek R.

2017-08-01

In this paper will be presented classification of new cognitive information systems dedicated to cryptographic data splitting and sharing processes. Cognitive processes of semantic data analysis and interpretation, will be used to describe new classes of intelligent information and vision systems. In addition, cryptographic data splitting algorithms and cryptographic threshold schemes will be used to improve processes of secure and efficient information management with application of such cognitive systems. The utility of the proposed cognitive sharing procedures and distributed data sharing algorithms will be also presented. A few possible application of cognitive approaches for visual information management and encryption will be also described.

Sharing Research Data and Intellectual Property Law: A Primer.

PubMed

Carroll, Michael W

2015-08-01

Sharing research data by depositing it in connection with a published article or otherwise making data publicly available sometimes raises intellectual property questions in the minds of depositing researchers, their employers, their funders, and other researchers who seek to reuse research data. In this context or in the drafting of data management plans, common questions are (1) what are the legal rights in data; (2) who has these rights; and (3) how does one with these rights use them to share data in a way that permits or encourages productive downstream uses? Leaving to the side privacy and national security laws that regulate sharing certain types of data, this Perspective explains how to work through the general intellectual property and contractual issues for all research data.

Designing for Global Data Sharing, Designing for Educational Transformation

ERIC Educational Resources Information Center

Adams, Robin S.; Radcliffe, David; Fosmire, Michael

2016-01-01

This paper provides an example of a global data sharing project with an educational transformation agenda. This agenda shaped both the design of the shared dataset and the experience of sharing the common dataset to support multiple perspective inquiry and enable integrative and critically reflexive research-to-practice dialogue. The shared…

Promises and pitfalls of data sharing in qualitative research

PubMed Central

Tsai, Alexander C.; Kohrt, Brandon A.; Matthews, Lynn T.; Betancourt, Theresa S.; Lee, Jooyoung K.; Papachristos, Andrew V.; Weiser, Sheri D.; Dworkin, Shari L.

2017-01-01

The movement for research transparency has gained irresistible momentum over the past decade. Although qualitative research is rarely published in the high-impact journals that have adopted, or are most likely to adopt, data sharing policies, qualitative researchers who publish work in these and similar venues will likely encounter questions about data sharing within the next few years. The fundamental ways in which qualitative and quantitative data differ should be considered when assessing the extent to which qualitative and mixed methods researchers should be expected to adhere to data sharing policies developed with quantitative studies in mind. We outline several of the most critical concerns below, while also suggesting possible modifications that may help to reduce the probability of unintended adverse consequences and to ensure that the sharing of qualitative data is consistent with ethical standards in research. PMID:27535900

Comparison of consumers’ views on electronic data sharing for healthcare and research

PubMed Central

Joseph, Jill G; Ohno-Machado, Lucila

2015-01-01

New models of healthcare delivery such as accountable care organizations and patient-centered medical homes seek to improve quality, access, and cost. They rely on a robust, secure technology infrastructure provided by health information exchanges (HIEs) and distributed research networks and the willingness of patients to share their data. There are few large, in-depth studies of US consumers’ views on privacy, security, and consent in electronic data sharing for healthcare and research together. Objective This paper addresses this gap, reporting on a survey which asks about California consumers’ views of data sharing for healthcare and research together. Materials and Methods The survey conducted was a representative, random-digit dial telephone survey of 800 Californians, performed in Spanish and English. Results There is a great deal of concern that HIEs will worsen privacy (40.3%) and security (42.5%). Consumers are in favor of electronic data sharing but elements of transparency are important: individual control, who has access, and the purpose for use of data. Respondents were more likely to agree to share deidentified information for research than to share identified information for healthcare (76.2% vs 57.3%, p < .001). Discussion While consumers show willingness to share health information electronically, they value individual control and privacy. Responsiveness to these needs, rather than mere reliance on Health Insurance Portability and Accountability Act (HIPAA), may improve support of data networks. Conclusion Responsiveness to the public’s concerns regarding their health information is a pre-requisite for patient-centeredness. This is one of the first in-depth studies of attitudes about electronic data sharing that compares attitudes of the same individual towards healthcare and research. PMID:25829461

Big heart data: advancing health informatics through data sharing in cardiovascular imaging.

PubMed

Suinesiaputra, Avan; Medrano-Gracia, Pau; Cowan, Brett R; Young, Alistair A

2015-07-01

The burden of heart disease is rapidly worsening due to the increasing prevalence of obesity and diabetes. Data sharing and open database resources for heart health informatics are important for advancing our understanding of cardiovascular function, disease progression and therapeutics. Data sharing enables valuable information, often obtained at considerable expense and effort, to be reused beyond the specific objectives of the original study. Many government funding agencies and journal publishers are requiring data reuse, and are providing mechanisms for data curation and archival. Tools and infrastructure are available to archive anonymous data from a wide range of studies, from descriptive epidemiological data to gigabytes of imaging data. Meta-analyses can be performed to combine raw data from disparate studies to obtain unique comparisons or to enhance statistical power. Open benchmark datasets are invaluable for validating data analysis algorithms and objectively comparing results. This review provides a rationale for increased data sharing and surveys recent progress in the cardiovascular domain. We also highlight the potential of recent large cardiovascular epidemiological studies enabling collaborative efforts to facilitate data sharing, algorithms benchmarking, disease modeling and statistical atlases.

Solutions for research data from a publisher's perspective

NASA Astrophysics Data System (ADS)

Cotroneo, P.

2015-12-01

Sharing research data has the potential to make research more efficient and reproducible. Elsevier has developed several initiatives to address the different needs of research data users. These include PANGEA Linked data, which provides geo-referenced, citable datasets from earth and life sciences, archived as supplementary data from publications by the PANGEA data repository; Mendeley Data, which allows users to freely upload and share their data; a database linking program that creates links between articles on ScienceDirect and datasets held in external data repositories such as EarthRef and EarthChem; a pilot for searching for research data through a map interface; an open data pilot that allows authors publishing in Elsevier journals to store and share research data and make this publicly available as a supplementary file alongside their article; and data journals, including Data in Brief, which allow researchers to share their data open access. Through these initiatives, researchers are not only encouraged to share their research data, but also supported in optimizing their research data management. By making data more readily citable and visible, and hence generating citations for authors, these initiatives also aim to ensure that researchers get the recognition they deserve for publishing their data.

Panel A report: Standards needed to interconnect ADS pilots for data sharing for catalogues, directories, and dictionaries

NASA Technical Reports Server (NTRS)

1981-01-01

User requirements, guidelines, and standards for interconnecting an Applications Data Service (ADS) program for data sharing are discussed. Methods for effective sharing of information (catalogues, directories, and dictionaries) among member installations are addressed. An ADS Directory/Catalog architectural model is also given.

Views of Ethical Best Practices in Sharing Individual-Level Data From Medical and Public Health Research

PubMed Central

Roberts, Nia; Parker, Michael

2015-01-01

There is increasing support for sharing individual-level data generated by medical and public health research. This scoping review of empirical research and conceptual literature examined stakeholders’ perspectives of ethical best practices in data sharing, particularly in low- and middle-income settings. Sixty-nine empirical and conceptual articles were reviewed, of which, only five were empirical studies and eight were conceptual articles focusing on low- and middle-income settings. We conclude that support for sharing individual-level data is contingent on the development and implementation of international and local policies and processes to support ethical best practices. Further conceptual and empirical research is needed to ensure data sharing policies and processes in low- and middle-income settings are appropriately informed by stakeholders’ perspectives. PMID:26297745

Surrogate data--a secure way to share corporate data.

PubMed

Tetko, Igor V; Abagyan, Ruben; Oprea, Tudor I

2005-01-01

The privacy of chemical structure is of paramount importance for the industrial sector, in particular for the pharmaceutical industry. At the same time, companies handle large amounts of physico-chemical and biological data that could be shared in order to improve our molecular understanding of pharmacokinetic and toxicological properties, which could lead to improved predictivity and shorten the development time for drugs, in particular in the early phases of drug discovery. The current study provides some theoretical limits on the information required to produce reverse engineering of molecules from generated descriptors and demonstrates that the information content of molecules can be as low as less than one bit per atom. Thus theoretically just one descriptor can be used to completely disclose the molecular structure. Instead of sharing descriptors, we propose to share surrogate data. The sharing of surrogate data is nothing else but sharing of reliably predicted molecules. The use of surrogate data can provide the same information as the original set. We consider the practical application of this idea to predict lipophilicity of chemical compounds and we demonstrate that surrogate and real (original) data provides similar prediction ability. Thus, our proposed strategy makes it possible not only to share descriptors, but also complete collections of surrogate molecules without the danger of disclosing the underlying molecular structures.

Developing a data sharing community for spinal cord injury research.

PubMed

Callahan, Alison; Anderson, Kim D; Beattie, Michael S; Bixby, John L; Ferguson, Adam R; Fouad, Karim; Jakeman, Lyn B; Nielson, Jessica L; Popovich, Phillip G; Schwab, Jan M; Lemmon, Vance P

2017-09-01

The rapid growth in data sharing presents new opportunities across the spectrum of biomedical research. Global efforts are underway to develop practical guidance for implementation of data sharing and open data resources. These include the recent recommendation of 'FAIR Data Principles', which assert that if data is to have broad scientific value, then digital representations of that data should be Findable, Accessible, Interoperable and Reusable (FAIR). The spinal cord injury (SCI) research field has a long history of collaborative initiatives that include sharing of preclinical research models and outcome measures. In addition, new tools and resources are being developed by the SCI research community to enhance opportunities for data sharing and access. With this in mind, the National Institute of Neurological Disorders and Stroke (NINDS) at the National Institutes of Health (NIH) hosted a workshop on October 5-6, 2016 in Bethesda, MD, in collaboration with the Open Data Commons for Spinal Cord Injury (ODC-SCI) titled "Preclinical SCI Data: Creating a FAIR Share Community". Workshop invitees were nominated by the workshop steering committee (co-chairs: ARF and VPL; members: AC, KDA, MSB, KF, LBJ, PGP, JMS), to bring together junior and senior level experts including preclinical and basic SCI researchers from academia and industry, data science and bioinformatics experts, investigators with expertise in other neurological disease fields, clinical researchers, members of the SCI community, and program staff representing federal and private funding agencies. The workshop and ODC-SCI efforts were sponsored by the International Spinal Research Trust (ISRT), the Rick Hansen Institute, Wings for Life, the Craig H. Neilsen Foundation and NINDS. The number of attendees was limited to ensure active participation and feedback in small groups. The goals were to examine the current landscape for data sharing in SCI research and provide a path to its future. Below are highlights from the workshop, including perspectives on the value of data sharing in SCI research, workshop participant perspectives and concerns, descriptions of existing resources and actionable directions for further engaging the SCI research community in a model that may be applicable to many other areas of neuroscience. This manuscript is intended to share these initial findings with the broader research community, and to provide talking points for continued feedback from the SCI field, as it continues to move forward in the age of data sharing. Copyright © 2017. Published by Elsevier Inc.

Alternative Fuels Data Center: Maps and Data

Science.gov Websites

reduced AFV acquisition requirements. However, overall AFV acquisitions have since rebounded to pre-Great acquisitions have since rebounded to pre-Great Recession levels. Share Embed Share Copy and share this link

Sharing all types of clinical data and harmonizing journal standards.

PubMed

Barbui, Corrado

2016-04-03

Despite recent efforts to enforce policies requiring the sharing of data underlying clinical findings, current policies of biomedical journals remain largely heterogeneous. As this heterogeneity does not optimally serve the cause of data sharing, a first step towards better harmonization would be the requirement of a data sharing statement for all clinical studies and not simply for randomized studies. Although the publication of a data sharing statement does not imply that all data is made readily available, such a policy would swiftly implement a cultural change in the definition of scientific outputs. Currently, a scientific output only corresponds to a study report published in a medical journal, while in the near future it might consist of all materials described in the manuscript, including all relevant raw data. When such a cultural shift has been achieved, the logical conclusion would be for biomedical journals to require authors to make all data fully available without restriction as a condition for publication.

iDASH: integrating data for analysis, anonymization, and sharing

PubMed Central

Bafna, Vineet; Boxwala, Aziz A; Chapman, Brian E; Chapman, Wendy W; Chaudhuri, Kamalika; Day, Michele E; Farcas, Claudiu; Heintzman, Nathaniel D; Jiang, Xiaoqian; Kim, Hyeoneui; Kim, Jihoon; Matheny, Michael E; Resnic, Frederic S; Vinterbo, Staal A

2011-01-01

iDASH (integrating data for analysis, anonymization, and sharing) is the newest National Center for Biomedical Computing funded by the NIH. It focuses on algorithms and tools for sharing data in a privacy-preserving manner. Foundational privacy technology research performed within iDASH is coupled with innovative engineering for collaborative tool development and data-sharing capabilities in a private Health Insurance Portability and Accountability Act (HIPAA)-certified cloud. Driving Biological Projects, which span different biological levels (from molecules to individuals to populations) and focus on various health conditions, help guide research and development within this Center. Furthermore, training and dissemination efforts connect the Center with its stakeholders and educate data owners and data consumers on how to share and use clinical and biological data. Through these various mechanisms, iDASH implements its goal of providing biomedical and behavioral researchers with access to data, software, and a high-performance computing environment, thus enabling them to generate and test new hypotheses. PMID:22081224

iDASH: integrating data for analysis, anonymization, and sharing.

PubMed

Ohno-Machado, Lucila; Bafna, Vineet; Boxwala, Aziz A; Chapman, Brian E; Chapman, Wendy W; Chaudhuri, Kamalika; Day, Michele E; Farcas, Claudiu; Heintzman, Nathaniel D; Jiang, Xiaoqian; Kim, Hyeoneui; Kim, Jihoon; Matheny, Michael E; Resnic, Frederic S; Vinterbo, Staal A

2012-01-01

iDASH (integrating data for analysis, anonymization, and sharing) is the newest National Center for Biomedical Computing funded by the NIH. It focuses on algorithms and tools for sharing data in a privacy-preserving manner. Foundational privacy technology research performed within iDASH is coupled with innovative engineering for collaborative tool development and data-sharing capabilities in a private Health Insurance Portability and Accountability Act (HIPAA)-certified cloud. Driving Biological Projects, which span different biological levels (from molecules to individuals to populations) and focus on various health conditions, help guide research and development within this Center. Furthermore, training and dissemination efforts connect the Center with its stakeholders and educate data owners and data consumers on how to share and use clinical and biological data. Through these various mechanisms, iDASH implements its goal of providing biomedical and behavioral researchers with access to data, software, and a high-performance computing environment, thus enabling them to generate and test new hypotheses.

Promises and pitfalls of data sharing in qualitative research.

PubMed

Tsai, Alexander C; Kohrt, Brandon A; Matthews, Lynn T; Betancourt, Theresa S; Lee, Jooyoung K; Papachristos, Andrew V; Weiser, Sheri D; Dworkin, Shari L

2016-11-01

The movement for research transparency has gained irresistible momentum over the past decade. Although qualitative research is rarely published in the high-impact journals that have adopted, or are most likely to adopt, data sharing policies, qualitative researchers who publish work in these and similar venues will likely encounter questions about data sharing within the next few years. The fundamental ways in which qualitative and quantitative data differ should be considered when assessing the extent to which qualitative and mixed methods researchers should be expected to adhere to data sharing policies developed with quantitative studies in mind. We outline several of the most critical concerns below, while also suggesting possible modifications that may help to reduce the probability of unintended adverse consequences and to ensure that the sharing of qualitative data is consistent with ethical standards in research. Copyright © 2016 Elsevier Ltd. All rights reserved.

Sharing Research Data and Intellectual Property Law: A Primer

PubMed Central

Carroll, Michael W.

2015-01-01

Sharing research data by depositing it in connection with a published article or otherwise making data publicly available sometimes raises intellectual property questions in the minds of depositing researchers, their employers, their funders, and other researchers who seek to reuse research data. In this context or in the drafting of data management plans, common questions are (1) what are the legal rights in data; (2) who has these rights; and (3) how does one with these rights use them to share data in a way that permits or encourages productive downstream uses? Leaving to the side privacy and national security laws that regulate sharing certain types of data, this Perspective explains how to work through the general intellectual property and contractual issues for all research data. PMID:26313685

Data Sharing & Publishing at Nature Publishing Group

NASA Astrophysics Data System (ADS)

VanDecar, J. C.; Hrynaszkiewicz, I.; Hufton, A. L.

2015-12-01

In recent years, the research community has come to recognize that upon-request data sharing has important limitations1,2. The Nature-titled journals feel that researchers have a duty to share data without undue qualifications, in a manner that allows others to replicate and build upon their published findings. Historically, the Nature journals have been strong supporters of data deposition in communities with existing data mandates, and have required data sharing upon request in all other cases. To help address some of the limitations of upon-request data sharing, the Nature titles have strengthened their existing data policies and forged a new partnership with Scientific Data, to promote wider data sharing in discoverable, citeable and reusable forms, and to ensure that scientists get appropriate credit for sharing3. Scientific Data is a new peer-reviewed journal for descriptions of research datasets, which works with a wide of range of public data repositories4. Articles at Scientific Data may either expand on research publications at other journals or may be used to publish new datasets. The Nature Publishing Group has also signed the Joint Declaration of Data Citation Principles5, and Scientific Data is our first journal to include formal data citations. We are currently in the process of adding data citation support to our various journals. 1 Wicherts, J. M., Borsboom, D., Kats, J. & Molenaar, D. The poor availability of psychological research data for reanalysis. Am. Psychol. 61, 726-728, doi:10.1037/0003-066x.61.7.726 (2006). 2 Vines, T. H. et al. Mandated data archiving greatly improves access to research data. FASEB J. 27, 1304-1308, doi:10.1096/fj.12-218164 (2013). 3 Data-access practices strengthened. Nature 515, 312, doi:10.1038/515312a (2014). 4 More bang for your byte. Sci. Data 1, 140010, doi:10.1038/sdata.2014.10 (2014). 5 Data Citation Synthesis Group: Joint Declaration of Data Citation Principles. (FORCE11, San Diego, CA, 2014).

NREL Develops OpenEI.org, a Public Website Where Energy Data can be Generated, Shared, and Compared (Fact Sheet)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

2013-12-01

The National Renewable Energy Laboratory (NREL) has developed OpenEI.org, a public, open, data-sharing platform where consumers, analysts, industry experts, and energy decision makers can go to boost their energy IQs, search for energy data, share data, and get access to energy applications. The free site blends elements of social media, linked open-data practices, and MediaWiki-based technology to build a collaborative environment for creating and sharing energy data with the world. The result is a powerful platform that is helping government and industry leaders around the world define policy options, make informed investment decisions, and create new businesses.

Transforming Education Research through Open Video Data Sharing

ERIC Educational Resources Information Center

Gilmore, Rick O.; Adolph, Karen E.; Millman, David S.; Gordon, Andrew

2016-01-01

Open data sharing promises to accelerate the pace of discovery in the developmental and learning sciences, but significant technical, policy, and cultural barriers have limited its adoption. As a result, most research on learning and development remains shrouded in a culture of isolation. Data sharing is the rare exception (Gilmore, 2016). Many…

Perceptions and Practices of Data Sharing in Engineering Education

ERIC Educational Resources Information Center

Johri, Aditya; Yang, Seungwon; Vorvoreanu, Mihaela; Madhavan, Krishna

2016-01-01

As part of our NSF funded collaborative project on Data Sharing within Engineering Education Community, we conducted an empirical study to better understand the current climate of data sharing and participants' future expectations of the field. We present findings of this mixed method study and discuss implications. Overall, we found strong…

Research on models of Digital City geo-information sharing platform

NASA Astrophysics Data System (ADS)

Xu, Hanwei; Liu, Zhihui; Badawi, Rami; Liu, Haiwang

2009-10-01

The data related to Digital City has the property of large quantity, isomerous and multiple dimensions. In the original copy method of data sharing, the application departments can not solve the problem of data updating and data security in real-time. This paper firstly analyzes various patterns of sharing Digital City information and on this basis the author provides a new shared mechanism of GIS Services, with which the data producers provide Geographic Information Services to the application users through Web API, so as to the data producers and the data users can do their best respectively. Then the author takes the application system in supermarket management as an example to explain the correctness and effectiveness of the method provided in this paper.

International Charter of principles for sharing bio-specimens and data.

PubMed

Mascalzoni, Deborah; Dove, Edward S; Rubinstein, Yaffa; Dawkins, Hugh J S; Kole, Anna; McCormack, Pauline; Woods, Simon; Riess, Olaf; Schaefer, Franz; Lochmüller, Hanns; Knoppers, Bartha M; Hansson, Mats

2015-06-01

There is a growing international agreement on the need to provide greater access to research data and bio-specimen collections to optimize their long-term value and exploit their potential for health discovery and validation. This is especially evident for rare disease research. Currently, the rising value of data and bio-specimen collections does not correspond with an equal increase in data/sample-sharing and data/sample access. Contradictory legal and ethical frameworks across national borders are obstacles to effective sharing: more specifically, the absence of an integrated model proves to be a major logistical obstruction. The Charter intends to amend the obstacle by providing both the ethical foundations on which data sharing should be based, as well as a general Material and Data Transfer Agreement (MTA/DTA). This Charter is the result of a careful negotiation of different stakeholders' interest and is built on earlier consensus documents and position statements, which provided the general international legal framework. Further to this, the Charter provides tools that may help accelerate sharing. The Charter has been formulated to serve as an enabling tool for effective and transparent data and bio-specimen sharing and the general MTA/DTA constitutes a mechanism to ensure uniformity of access across projects and countries, and may be regarded as a consistent basic agreement for addressing data and material sharing globally. The Charter is forward looking in terms of emerging issues from the perspective of a multi-stakeholder group, and where possible, provides strategies that may address these issues.

Open sharing of genomic data: Who does it and why?

PubMed

Haeusermann, Tobias; Greshake, Bastian; Blasimme, Alessandro; Irdam, Darja; Richards, Martin; Vayena, Effy

2017-01-01

We explored the characteristics and motivations of people who, having obtained their genetic or genomic data from Direct-To-Consumer genetic testing (DTC-GT) companies, voluntarily decide to share them on the publicly accessible web platform openSNP. The study is the first attempt to describe open data sharing activities undertaken by individuals without institutional oversight. In the paper we provide a detailed overview of the distribution of the demographic characteristics and motivations of people engaged in genetic or genomic open data sharing. The geographical distribution of the respondents showed the USA as dominant. There was no significant gender divide, the age distribution was broad, educational background varied and respondents with and without children were equally represented. Health, even though prominent, was not the respondents' primary or only motivation to be tested. As to their motivations to openly share their data, 86.05% indicated wanting to learn about themselves as relevant, followed by contributing to the advancement of medical research (80.30%), improving the predictability of genetic testing (76.02%) and considering it fun to explore genotype and phenotype data (75.51%). Whereas most respondents were well aware of the privacy risks of their involvement in open genetic data sharing and considered the possibility of direct, personal repercussions troubling, they estimated the risk of this happening to be negligible. Our findings highlight the diversity of DTC-GT consumers who decide to openly share their data. Instead of focusing exclusively on health-related aspects of genetic testing and data sharing, our study emphasizes the importance of taking into account benefits and risks that stretch beyond the health spectrum. Our results thus lend further support to the call for a broader and multi-faceted conceptualization of genomic utility.

Neuroinformatics Software Applications Supporting Electronic Data Capture, Management, and Sharing for the Neuroimaging Community

PubMed Central

Nichols, B. Nolan; Pohl, Kilian M.

2017-01-01

Accelerating insight into the relation between brain and behavior entails conducting small and large-scale research endeavors that lead to reproducible results. Consensus is emerging between funding agencies, publishers, and the research community that data sharing is a fundamental requirement to ensure all such endeavors foster data reuse and fuel reproducible discoveries. Funding agency and publisher mandates to share data are bolstered by a growing number of data sharing efforts that demonstrate how information technologies can enable meaningful data reuse. Neuroinformatics evaluates scientific needs and develops solutions to facilitate the use of data across the cognitive and neurosciences. For example, electronic data capture and management tools designed to facilitate human neurocognitive research can decrease the setup time of studies, improve quality control, and streamline the process of harmonizing, curating, and sharing data across data repositories. In this article we outline the advantages and disadvantages of adopting software applications that support these features by reviewing the tools available and then presenting two contrasting neuroimaging study scenarios in the context of conducting a cross-sectional and a multisite longitudinal study. PMID:26267019

A Service Oriented Web Application for Learner Knowledge Representation, Management and Sharing Conforming to IMS LIP

ERIC Educational Resources Information Center

Lazarinis, Fotis

2014-01-01

iLM is a Web based application for representation, management and sharing of IMS LIP conformant user profiles. The tool is developed using a service oriented architecture with emphasis on the easy data sharing. Data elicitation from user profiles is based on the utilization of XQuery scripts and sharing with other applications is achieved through…

Communication from the Information Sharing Working Group: Agreement for Data Sharing Among Caribbean Foresters

Treesearch

Tamara Heartsill Scalley; Saara DeWalt; François Korysko; Guy Van Laere; Kasey Jacobs; Seth Panka; Joseph Torres

2016-01-01

We presented a new information-sharing platform at the 16th Caribbean Foresters Meeting in August 2013 to facilitate and promote collaboration among Caribbean foresters. The platform can be accessed through the Caribbean Foresters website where information and data on forest research sites can be shared. There is a special focus on identifying potential collaborations...

Perspectives of the optical coherence tomography community on code and data sharing

NASA Astrophysics Data System (ADS)

Lurie, Kristen L.; Mistree, Behram F. T.; Ellerbee, Audrey K.

2015-03-01

As optical coherence tomography (OCT) grows to be a mature and successful field, it is important for the research community to develop a stronger practice of sharing code and data. A prolific culture of sharing can enable new and emerging laboratories to enter the field, allow research groups to gain new exposure and notoriety, and enable benchmarking of new algorithms and methods. Our long-term vision is to build tools to facilitate a stronger practice of sharing within this community. In line with this goal, our first aim was to understand the perceptions and practices of the community with respect to sharing research contributions (i.e., as code and data). We surveyed 52 members of the OCT community using an online polling system. Our main findings indicate that while researchers infrequently share their code and data, they are willing to contribute their research resources to a shared repository, and they believe that such a repository would benefit both their research and the OCT community at large. We plan to use the results of this survey to design a platform targeted to the OCT research community - an effort that ultimately aims to facilitate a more prolific culture of sharing.

Legal and policy barriers to sharing data between public health programs in New York City: a case study.

PubMed

Gasner, M Rose; Fuld, Jennifer; Drobnik, Ann; Varma, Jay K

2014-06-01

Integration of public health surveillance data within health departments is important for public health activities and cost-efficient coordination of care. Access to and use of surveillance data are governed by public health law and by agency confidentiality and security policies. In New York City, we examined public health laws and agency policies for data sharing across HIV, sexually transmitted disease, tuberculosis, and viral hepatitis surveillance programs. We found that recent changes to state laws provide greater opportunities for data sharing but that agency policies must be updated because they limit increased data integration. Our case study can help other health departments conduct similar reviews of laws and policies to increase data sharing and integration of surveillance data.

Patient consent to publication and data sharing in industry and NIH-funded clinical trials.

PubMed

Spence, O'Mareen; Onwuchekwa Uba, Richie; Shin, Seongbin; Doshi, Peter

2018-05-03

Participants are recruited into clinical trials under the assumption that the research will contribute to medical knowledge. Therefore, non-publication trials-and, more recently, lack of data sharing-are widely considered to violate the trust of trial participants. Existing practices regarding patient consent to publication and data sharing have not been evaluated. Analyzing informed consent forms (ICFs), we studied what trial participants were told regarding investigators' intention to contribute to medical knowledge, publish trial results, and share de-identified trial data. We obtained 98 ICFs of industry-funded pre-marketing trials for all (17) antibiotics approved by the European Medicines Agency and 46 ICFs of publicly funded trials from the National Heart, Lung and Blood Institute Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC) data repository. Three authors independently reviewed ICFs to identify and extract what was stated or implied regarding: (1) publication of results; (2) sharing de-identified data; (3) data ownership; (4) confidentiality of identifiable data; and (5) whether the trial will produce knowledge that offers public benefit. Consensus was obtained from the two reviewers with the greatest overall agreement on all five measures. Disagreements were resolved through discussion among all authors. Four (3%) trials indicated a commitment to publish trial results; 140 (97%) did not commit to publishing trial results; six (4%) indicated a commitment to share de-identified data with third party researchers. Commitments to share were more common in publicly funded trials than industry-funded trials (7% vs 3%). A total of 103 (72%) ICFs indicated the trials will or may produce knowledge that offers public benefits, while 131 (91%) ICFs left unstated who "owned" trial data; of those with statements, the sponsor always claimed ownership. Patient confidentiality was guaranteed in 137 (95%) trials. Our results suggest that consent forms rarely disclose investigators' intentions regarding the sharing of de-identified data or publication of trial results.

Data management strategies for multinational large-scale systems biology projects.

PubMed

Wruck, Wasco; Peuker, Martin; Regenbrecht, Christian R A

2014-01-01

Good accessibility of publicly funded research data is essential to secure an open scientific system and eventually becomes mandatory [Wellcome Trust will Penalise Scientists Who Don't Embrace Open Access. The Guardian 2012]. By the use of high-throughput methods in many research areas from physics to systems biology, large data collections are increasingly important as raw material for research. Here, we present strategies worked out by international and national institutions targeting open access to publicly funded research data via incentives or obligations to share data. Funding organizations such as the British Wellcome Trust therefore have developed data sharing policies and request commitment to data management and sharing in grant applications. Increased citation rates are a profound argument for sharing publication data. Pre-publication sharing might be rewarded by a data citation credit system via digital object identifiers (DOIs) which have initially been in use for data objects. Besides policies and incentives, good practice in data management is indispensable. However, appropriate systems for data management of large-scale projects for example in systems biology are hard to find. Here, we give an overview of a selection of open-source data management systems proved to be employed successfully in large-scale projects.

Data management strategies for multinational large-scale systems biology projects

PubMed Central

Peuker, Martin; Regenbrecht, Christian R.A.

2014-01-01

Good accessibility of publicly funded research data is essential to secure an open scientific system and eventually becomes mandatory [Wellcome Trust will Penalise Scientists Who Don’t Embrace Open Access. The Guardian 2012]. By the use of high-throughput methods in many research areas from physics to systems biology, large data collections are increasingly important as raw material for research. Here, we present strategies worked out by international and national institutions targeting open access to publicly funded research data via incentives or obligations to share data. Funding organizations such as the British Wellcome Trust therefore have developed data sharing policies and request commitment to data management and sharing in grant applications. Increased citation rates are a profound argument for sharing publication data. Pre-publication sharing might be rewarded by a data citation credit system via digital object identifiers (DOIs) which have initially been in use for data objects. Besides policies and incentives, good practice in data management is indispensable. However, appropriate systems for data management of large-scale projects for example in systems biology are hard to find. Here, we give an overview of a selection of open-source data management systems proved to be employed successfully in large-scale projects. PMID:23047157

[Study of sharing platform of web-based enhanced extracorporeal counterpulsation hemodynamic waveform data].

PubMed

Huang, Mingbo; Hu, Ding; Yu, Donglan; Zheng, Zhensheng; Wang, Kuijian

2011-12-01

Enhanced extracorporeal counterpulsation (EECP) information consists of both text and hemodynamic waveform data. At present EECP text information has been successfully managed through Web browser, while the management and sharing of hemodynamic waveform data through Internet has not been solved yet. In order to manage EECP information completely, based on the in-depth analysis of EECP hemodynamic waveform file of digital imaging and communications in medicine (DICOM) format and its disadvantages in Internet sharing, we proposed the use of the extensible markup language (XML), which is currently the Internet popular data exchange standard, as the storage specification for the sharing of EECP waveform data. Then we designed a web-based sharing system of EECP hemodynamic waveform data via ASP. NET 2.0 platform. Meanwhile, we specifically introduced the four main system function modules and their implement methods, including DICOM to XML conversion module, EECP waveform data management module, retrieval and display of EECP waveform module and the security mechanism of the system.

Data sharing system for lithography APC

NASA Astrophysics Data System (ADS)

Kawamura, Eiichi; Teranishi, Yoshiharu; Shimabara, Masanori

2007-03-01

We have developed a simple and cost-effective data sharing system between fabs for lithography advanced process control (APC). Lithography APC requires process flow, inter-layer information, history information, mask information and so on. So, inter-APC data sharing system has become necessary when lots are to be processed in multiple fabs (usually two fabs). The development cost and maintenance cost also have to be taken into account. The system handles minimum information necessary to make trend prediction for the lots. Three types of data have to be shared for precise trend prediction. First one is device information of the lots, e.g., process flow of the device and inter-layer information. Second one is mask information from mask suppliers, e.g., pattern characteristics and pattern widths. Last one is history data of the lots. Device information is electronic file and easy to handle. The electronic file is common between APCs and uploaded into the database. As for mask information sharing, mask information described in common format is obtained via Wide Area Network (WAN) from mask-vender will be stored in the mask-information data server. This information is periodically transferred to one specific lithography-APC server and compiled into the database. This lithography-APC server periodically delivers the mask-information to every other lithography-APC server. Process-history data sharing system mainly consists of function of delivering process-history data. In shipping production lots to another fab, the product-related process-history data is delivered by the lithography-APC server from the shipping site. We have confirmed the function and effectiveness of data sharing systems.

Including all voices in international data-sharing governance.

PubMed

Kaye, Jane; Terry, Sharon F; Juengst, Eric; Coy, Sarah; Harris, Jennifer R; Chalmers, Don; Dove, Edward S; Budin-Ljøsne, Isabelle; Adebamowo, Clement; Ogbe, Emilomo; Bezuidenhout, Louise; Morrison, Michael; Minion, Joel T; Murtagh, Madeleine J; Minari, Jusaku; Teare, Harriet; Isasi, Rosario; Kato, Kazuto; Rial-Sebbag, Emmanuelle; Marshall, Patricia; Koenig, Barbara; Cambon-Thomsen, Anne

2018-03-07

Governments, funding bodies, institutions, and publishers have developed a number of strategies to encourage researchers to facilitate access to datasets. The rationale behind this approach is that this will bring a number of benefits and enable advances in healthcare and medicine by allowing the maximum returns from the investment in research, as well as reducing waste and promoting transparency. As this approach gains momentum, these data-sharing practices have implications for many kinds of research as they become standard practice across the world. The governance frameworks that have been developed to support biomedical research are not well equipped to deal with the complexities of international data sharing. This system is nationally based and is dependent upon expert committees for oversight and compliance, which has often led to piece-meal decision-making. This system tends to perpetuate inequalities by obscuring the contributions and the important role of different data providers along the data stream, whether they be low- or middle-income country researchers, patients, research participants, groups, or communities. As research and data-sharing activities are largely publicly funded, there is a strong moral argument for including the people who provide the data in decision-making and to develop governance systems for their continued participation. We recommend that governance of science becomes more transparent, representative, and responsive to the voices of many constituencies by conducting public consultations about data-sharing addressing issues of access and use; including all data providers in decision-making about the use and sharing of data along the whole of the data stream; and using digital technologies to encourage accessibility, transparency, and accountability. We anticipate that this approach could enhance the legitimacy of the research process, generate insights that may otherwise be overlooked or ignored, and help to bring valuable perspectives into the decision-making around international data sharing.

ISA-TAB-Nano: a specification for sharing nanomaterial research data in spreadsheet-based format.

PubMed

Thomas, Dennis G; Gaheen, Sharon; Harper, Stacey L; Fritts, Martin; Klaessig, Fred; Hahn-Dantona, Elizabeth; Paik, David; Pan, Sue; Stafford, Grace A; Freund, Elaine T; Klemm, Juli D; Baker, Nathan A

2013-01-14

The high-throughput genomics communities have been successfully using standardized spreadsheet-based formats to capture and share data within labs and among public repositories. The nanomedicine community has yet to adopt similar standards to share the diverse and multi-dimensional types of data (including metadata) pertaining to the description and characterization of nanomaterials. Owing to the lack of standardization in representing and sharing nanomaterial data, most of the data currently shared via publications and data resources are incomplete, poorly-integrated, and not suitable for meaningful interpretation and re-use of the data. Specifically, in its current state, data cannot be effectively utilized for the development of predictive models that will inform the rational design of nanomaterials. We have developed a specification called ISA-TAB-Nano, which comprises four spreadsheet-based file formats for representing and integrating various types of nanomaterial data. Three file formats (Investigation, Study, and Assay files) have been adapted from the established ISA-TAB specification; while the Material file format was developed de novo to more readily describe the complexity of nanomaterials and associated small molecules. In this paper, we have discussed the main features of each file format and how to use them for sharing nanomaterial descriptions and assay metadata. The ISA-TAB-Nano file formats provide a general and flexible framework to record and integrate nanomaterial descriptions, assay data (metadata and endpoint measurements) and protocol information. Like ISA-TAB, ISA-TAB-Nano supports the use of ontology terms to promote standardized descriptions and to facilitate search and integration of the data. The ISA-TAB-Nano specification has been submitted as an ASTM work item to obtain community feedback and to provide a nanotechnology data-sharing standard for public development and adoption.

ISA-TAB-Nano: A Specification for Sharing Nanomaterial Research Data in Spreadsheet-based Format

PubMed Central

2013-01-01

Background and motivation The high-throughput genomics communities have been successfully using standardized spreadsheet-based formats to capture and share data within labs and among public repositories. The nanomedicine community has yet to adopt similar standards to share the diverse and multi-dimensional types of data (including metadata) pertaining to the description and characterization of nanomaterials. Owing to the lack of standardization in representing and sharing nanomaterial data, most of the data currently shared via publications and data resources are incomplete, poorly-integrated, and not suitable for meaningful interpretation and re-use of the data. Specifically, in its current state, data cannot be effectively utilized for the development of predictive models that will inform the rational design of nanomaterials. Results We have developed a specification called ISA-TAB-Nano, which comprises four spreadsheet-based file formats for representing and integrating various types of nanomaterial data. Three file formats (Investigation, Study, and Assay files) have been adapted from the established ISA-TAB specification; while the Material file format was developed de novo to more readily describe the complexity of nanomaterials and associated small molecules. In this paper, we have discussed the main features of each file format and how to use them for sharing nanomaterial descriptions and assay metadata. Conclusion The ISA-TAB-Nano file formats provide a general and flexible framework to record and integrate nanomaterial descriptions, assay data (metadata and endpoint measurements) and protocol information. Like ISA-TAB, ISA-TAB-Nano supports the use of ontology terms to promote standardized descriptions and to facilitate search and integration of the data. The ISA-TAB-Nano specification has been submitted as an ASTM work item to obtain community feedback and to provide a nanotechnology data-sharing standard for public development and adoption. PMID:23311978

ShareSync: A Solution for Deterministic Data Sharing over Ethernet

NASA Technical Reports Server (NTRS)

Dunn, Daniel J., II; Koons, William A.; Kennedy, Richard D.; Davis, Philip A.

2007-01-01

As part of upgrading the Contact Dynamics Simulation Laboratory (CDSL) at the NASA Marshall Space Flight Center (MSFC), a simple, cost effective method was needed to communicate data among the networked simulation machines and I/O controllers used to run the facility. To fill this need and similar applicable situations, a generic protocol was developed, called ShareSync. ShareSync is a lightweight, real-time, publish-subscribe Ethernet protocol for simple and deterministic data sharing across diverse machines and operating systems. ShareSync provides a simple Application Programming Interface (API) for simulation programmers to incorporate into their code. The protocol is compatible with virtually all Ethernet-capable machines, is flexible enough to support a variety of applications, is fast enough to provide soft real-time determinism, and is a low-cost resource for distributed simulation development, deployment, and maintenance. The first design cycle iteration of ShareSync has been completed, and the protocol has undergone several testing procedures including endurance and benchmarking tests and approaches the 2001ts data synchronization design goal for the CDSL.

Trust, confidentiality, and the acceptability of sharing HIV-related patient data: lessons learned from a mixed methods study about Health Information Exchanges.

PubMed

Maiorana, Andre; Steward, Wayne T; Koester, Kimberly A; Pearson, Charles; Shade, Starley B; Chakravarty, Deepalika; Myers, Janet J

2012-04-19

Concerns about the confidentiality of personal health information have been identified as a potential obstacle to implementation of Health Information Exchanges (HIEs). Considering the stigma and confidentiality issues historically associated with human immunodeficiency virus (HIV) disease, we examine how trust-in technology, processes, and people-influenced the acceptability of data sharing among stakeholders prior to implementation of six HIEs intended to improve HIV care in parts of the United States. Our analyses identify the kinds of concerns expressed by stakeholders about electronic data sharing and focus on the factors that ultimately facilitated acceptability of the new exchanges. We conducted 549 surveys with patients and 66 semi-structured interviews with providers and other stakeholders prior to implementation of the HIEs to assess concerns about confidentiality in the electronic sharing of patient data. The patient quantitative data were analyzed using SAS 9.2 to yield sample descriptive statistics. The analysis of the qualitative interviews with providers and other stakeholders followed an open-coding process, and convergent and divergent perspectives emerging from those data were examined within and across the HIEs. We found widespread acceptability for electronic sharing of HIV-related patient data through HIEs. This acceptability appeared to be driven by growing comfort with information technologies, confidence in the security protocols utilized to protect data, trust in the providers and institutions who use the technologies, belief in the benefits to the patients, and awareness that electronic exchange represents an enhancement of data sharing already taking place by other means. HIE acceptability depended both on preexisting trust among patients, providers, and institutions and on building consensus and trust in the HIEs as part of preparation for implementation. The process of HIE development also resulted in forging shared vision among institutions. Patients and providers are willing to accept the electronic sharing of HIV patient data to improve care for a disease historically seen as highly stigmatized. Acceptability depends on the effort expended to understand and address potential concerns related to data sharing and confidentiality, and on the trust established among stakeholders in terms of the nature of the systems and how they will be used.

District decision-making for health in low-income settings: a qualitative study in Uttar Pradesh, India, on engaging the private health sector in sharing health-related data

PubMed Central

Gautham, Meenakshi; Spicer, Neil; Subharwal, Manish; Gupta, Sanjay; Srivastava, Aradhana; Bhattacharyya, Sanghita; Avan, Bilal Iqbal; Schellenberg, Joanna

2016-01-01

Health information systems are an important planning and monitoring tool for public health services, but may lack information from the private health sector. In this fourth article in a series on district decision-making for health, we assessed the extent of maternal, newborn and child health (MNCH)-related data sharing between the private and public sectors in two districts of Uttar Pradesh, India; analysed barriers to data sharing; and identified key inputs required for data sharing. Between March 2013 and August 2014, we conducted 74 key informant interviews at national, state and district levels. Respondents were stakeholders from national, state and district health departments, professional associations, non-governmental programmes and private commercial health facilities with 3–200 beds. Qualitative data were analysed using a framework based on a priori and emerging themes. Private facilities registered for ultrasounds and abortions submitted standardized records on these services, which is compulsory under Indian laws. Data sharing for other services was weak, but most facilities maintained basic records related to institutional deliveries and newborns. Public health facilities in blocks collected these data from a few private facilities using different methods. The major barriers to data sharing included the public sector’s non-standardized data collection and utilization systems for MNCH and lack of communication and follow up with private facilities. Private facilities feared information disclosure and the additional burden of reporting, but were willing to share data if asked officially, provided the process was simple and they were assured of confidentiality. Unregistered facilities, managed by providers without a biomedical qualification, also conducted institutional deliveries, but were outside any reporting loops. Our findings suggest that even without legislation, the public sector could set up an effective MNCH data sharing strategy with private registered facilities by developing a standardized and simple system with consistent communication and follow up. PMID:27591205

External validation of the Cardiff model of information sharing to reduce community violence: natural experiment.

PubMed

Boyle, Adrian A; Snelling, Katrina; White, Laura; Ariel, Barak; Ashelford, Lawrence

2013-12-01

Community violence is a substantial problem for the NHS. Information sharing of emergency department data with community safety partnerships (CSP) has been associated with substantial reductions in assault attendances in emergency departments supported by academic institutions. We sought to validate these findings in a setting not supported by a public health or academic structure. We instituted anonymous data sharing with the police to reduce community violence, and increased involvement with the local CSP. We measured the effectiveness of this approach with routinely collected data at the emergency department and the police. We used police data from 2009, and emergency department data from 2000. Initially, the number of assault patients requiring emergency department treatment rose after we initiated data sharing. After improving the data flows, the number of assault patients fell back to the predata-sharing level. There was no change in the number of hospital admissions during the study period. There were decreases in the numbers of violent crimes against the person, with and without injury, recorded by the police. We have successfully implemented data sharing in our institution without the support of an academic institution. This has been associated with reductions in violent crime, but it is not clear whether this association is causal.

Data Rights and Responsibilities

PubMed Central

Wyndham, Jessica M.

2015-01-01

A human-rights-based analysis can be a useful tool for the scientific community and policy makers as they develop codes of conduct, harmonized standards, and national policies for data sharing. The human rights framework provides a shared set of values and norms across borders, defines rights and responsibilities of various actors involved in data sharing, addresses the potential harms as well as the benefits of data sharing, and offers a framework for balancing competing values. The right to enjoy the benefits of scientific progress and its applications offers a particularly helpful lens through which to view data as both a tool of scientific inquiry to which access is vital and as a product of science from which everyone should benefit. PMID:26297755

Parallel file system with metadata distributed across partitioned key-value store c

DOEpatents

Bent, John M.; Faibish, Sorin; Grider, Gary; Torres, Aaron

2017-09-19

Improved techniques are provided for storing metadata associated with a plurality of sub-files associated with a single shared file in a parallel file system. The shared file is generated by a plurality of applications executing on a plurality of compute nodes. A compute node implements a Parallel Log Structured File System (PLFS) library to store at least one portion of the shared file generated by an application executing on the compute node and metadata for the at least one portion of the shared file on one or more object storage servers. The compute node is also configured to implement a partitioned data store for storing a partition of the metadata for the shared file, wherein the partitioned data store communicates with partitioned data stores on other compute nodes using a message passing interface. The partitioned data store can be implemented, for example, using Multidimensional Data Hashing Indexing Middleware (MDHIM).

Sharing Patient-Generated Data in Clinical Practices: An Interview Study.

PubMed

Zhu, Haining; Colgan, Joanna; Reddy, Madhu; Choe, Eun Kyoung

2016-01-01

Patients are tracking and generating an increasingly large volume of personal health data outside the clinic due to an explosion of wearable sensing and mobile health (mHealth) apps. The potential usefulness of these data is enormous as they can provide good measures of everyday behavior and lifestyle. However, how we can fully leverage patient-generated data (PGD) and integrate them in clinical practice is less clear. In this interview study, we aim to understand how patients and clinicians currently share patient-generated data in clinical care practice. From the study, we identified technical, social, and organizational challenges in sharing and fully leveraging patient-generated data in clinical practices. Our findings can provide researchers potential avenues for enablers and barriers in sharing patient-generated data in clinical settings.

Securing the data economy: translating privacy and enacting security in the development of DataSHIELD.

PubMed

Murtagh, M J; Demir, I; Jenkings, K N; Wallace, S E; Murtagh, B; Boniol, M; Bota, M; Laflamme, P; Boffetta, P; Ferretti, V; Burton, P R

2012-01-01

Contemporary bioscience is seeing the emergence of a new data economy: with data as its fundamental unit of exchange. While sharing data within this new 'economy' provides many potential advantages, the sharing of individual data raises important social and ethical concerns. We examine ongoing development of one technology, DataSHIELD, which appears to elide privacy concerns about sharing data by enabling shared analysis while not actually sharing any individual-level data. We combine presentation of the development of DataSHIELD with presentation of an ethnographic study of a workshop to test the technology. DataSHIELD produced an application of the norm of privacy that was practical, flexible and operationalizable in researchers' everyday activities, and one which fulfilled the requirements of ethics committees. We demonstrated that an analysis run via DataSHIELD could precisely replicate results produced by a standard analysis where all data are physically pooled and analyzed together. In developing DataSHIELD, the ethical concept of privacy was transformed into an issue of security. Development of DataSHIELD was based on social practices as well as scientific and ethical motivations. Therefore, the 'success' of DataSHIELD would, likewise, be dependent on more than just the mathematics and the security of the technology. Copyright © 2012 S. Karger AG, Basel.

Legal assessment tool (LAT): an interactive tool to address privacy and data protection issues for data sharing.

PubMed

Kuchinke, Wolfgang; Krauth, Christian; Bergmann, René; Karakoyun, Töresin; Woollard, Astrid; Schluender, Irene; Braasch, Benjamin; Eckert, Martin; Ohmann, Christian

2016-07-07

In an unprecedented rate data in the life sciences is generated and stored in many different databases. An ever increasing part of this data is human health data and therefore falls under data protected by legal regulations. As part of the BioMedBridges project, which created infrastructures that connect more than 10 ESFRI research infrastructures (RI), the legal and ethical prerequisites of data sharing were examined employing a novel and pragmatic approach. We employed concepts from computer science to create legal requirement clusters that enable legal interoperability between databases for the areas of data protection, data security, Intellectual Property (IP) and security of biosample data. We analysed and extracted access rules and constraints from all data providers (databases) involved in the building of data bridges covering many of Europe's most important databases. These requirement clusters were applied to five usage scenarios representing the data flow in different data bridges: Image bridge, Phenotype data bridge, Personalised medicine data bridge, Structural data bridge, and Biosample data bridge. A matrix was built to relate the important concepts from data protection regulations (e.g. pseudonymisation, identifyability, access control, consent management) with the results of the requirement clusters. An interactive user interface for querying the matrix for requirements necessary for compliant data sharing was created. To guide researchers without the need for legal expert knowledge through legal requirements, an interactive tool, the Legal Assessment Tool (LAT), was developed. LAT provides researchers interactively with a selection process to characterise the involved types of data and databases and provides suitable requirements and recommendations for concrete data access and sharing situations. The results provided by LAT are based on an analysis of the data access and sharing conditions for different kinds of data of major databases in Europe. Data sharing for research purposes must be opened for human health data and LAT is one of the means to achieve this aim. In summary, LAT provides requirements in an interactive way for compliant data access and sharing with appropriate safeguards, restrictions and responsibilities by introducing a culture of responsibility and data governance when dealing with human data.

Parallel checksumming of data chunks of a shared data object using a log-structured file system

DOEpatents

Bent, John M.; Faibish, Sorin; Grider, Gary

2016-09-06

Checksum values are generated and used to verify the data integrity. A client executing in a parallel computing system stores a data chunk to a shared data object on a storage node in the parallel computing system. The client determines a checksum value for the data chunk; and provides the checksum value with the data chunk to the storage node that stores the shared object. The data chunk can be stored on the storage node with the corresponding checksum value as part of the shared object. The storage node may be part of a Parallel Log-Structured File System (PLFS), and the client may comprise, for example, a Log-Structured File System client on a compute node or burst buffer. The checksum value can be evaluated when the data chunk is read from the storage node to verify the integrity of the data that is read.

A web-portal for interactive data exploration, visualization, and hypothesis testing

PubMed Central

Bartsch, Hauke; Thompson, Wesley K.; Jernigan, Terry L.; Dale, Anders M.

2014-01-01

Clinical research studies generate data that need to be shared and statistically analyzed by their participating institutions. The distributed nature of research and the different domains involved present major challenges to data sharing, exploration, and visualization. The Data Portal infrastructure was developed to support ongoing research in the areas of neurocognition, imaging, and genetics. Researchers benefit from the integration of data sources across domains, the explicit representation of knowledge from domain experts, and user interfaces providing convenient access to project specific data resources and algorithms. The system provides an interactive approach to statistical analysis, data mining, and hypothesis testing over the lifetime of a study and fulfills a mandate of public sharing by integrating data sharing into a system built for active data exploration. The web-based platform removes barriers for research and supports the ongoing exploration of data. PMID:24723882

Agile Data Curation Case Studies Leading to the Identification and Development of Data Curation Design Patterns

NASA Astrophysics Data System (ADS)

Benedict, K. K.; Lenhardt, W. C.; Young, J. W.; Gordon, L. C.; Hughes, S.; Santhana Vannan, S. K.

2017-12-01

The planning for and development of efficient workflows for the creation, reuse, sharing, documentation, publication and preservation of research data is a general challenge that research teams of all sizes face. In response to: requirements from funding agencies for full-lifecycle data management plans that will result in well documented, preserved, and shared research data products increasing requirements from publishers for shared data in conjunction with submitted papers interdisciplinary research team's needs for efficient data sharing within projects, and increasing reuse of research data for replication and new, unanticipated research, policy development, and public use alternative strategies to traditional data life cycle approaches must be developed and shared that enable research teams to meet these requirements while meeting the core science objectives of their projects within the available resources. In support of achieving these goals, the concept of Agile Data Curation has been developed in which there have been parallel activities in support of 1) identifying a set of shared values and principles that underlie the objectives of agile data curation, 2) soliciting case studies from the Earth science and other research communities that illustrate aspects of what the contributors consider agile data curation methods and practices, and 3) identifying or developing design patterns that are high-level abstractions from successful data curation practice that are related to common data curation problems for which common solution strategies may be employed. This paper provides a collection of case studies that have been contributed by the Earth science community, and an initial analysis of those case studies to map them to emerging shared data curation problems and their potential solutions. Following the initial analysis of these problems and potential solutions, existing design patterns from software engineering and related disciplines are identified as a starting point for the development of a catalog of data curation design patterns that may be reused in the design and execution of new data curation processes.

Making open data work for plant scientists.

PubMed

Leonelli, Sabina; Smirnoff, Nicholas; Moore, Jonathan; Cook, Charis; Bastow, Ruth

2013-11-01

Despite the clear demand for open data sharing, its implementation within plant science is still limited. This is, at least in part, because open data-sharing raises several unanswered questions and challenges to current research practices. In this commentary, some of the challenges encountered by plant researchers at the bench when generating, interpreting, and attempting to disseminate their data have been highlighted. The difficulties involved in sharing sequencing, transcriptomics, proteomics, and metabolomics data are reviewed. The benefits and drawbacks of three data-sharing venues currently available to plant scientists are identified and assessed: (i) journal publication; (ii) university repositories; and (iii) community and project-specific databases. It is concluded that community and project-specific databases are the most useful to researchers interested in effective data sharing, since these databases are explicitly created to meet the researchers' needs, support extensive curation, and embody a heightened awareness of what it takes to make data reuseable by others. Such bottom-up and community-driven approaches need to be valued by the research community, supported by publishers, and provided with long-term sustainable support by funding bodies and government. At the same time, these databases need to be linked to generic databases where possible, in order to be discoverable to the majority of researchers and thus promote effective and efficient data sharing. As we look forward to a future that embraces open access to data and publications, it is essential that data policies, data curation, data integration, data infrastructure, and data funding are linked together so as to foster data access and research productivity.

Enabling Interoperable and Selective Data Sharing among Social Networking Sites

NASA Astrophysics Data System (ADS)

Shin, Dongwan; Lopes, Rodrigo

With the widespread use of social networking (SN) sites and even introduction of a social component in non-social oriented services, there is a growing concern over user privacy in general, how to handle and share user profiles across SN sites in particular. Although there have been several proprietary or open source-based approaches to unifying the creation of third party applications, the availability and retrieval of user profile information are still limited to the site where the third party application is run, mostly devoid of the support for data interoperability. In this paper we propose an approach to enabling interopearable and selective data sharing among SN sites. To support selective data sharing, we discuss an authenticated dictionary (ADT)-based credential which enables a user to share only a subset of her information certified by external SN sites with applications running on an SN site. For interoperable data sharing, we propose an extension to the OpenSocial API so that it can provide an open source-based framework for allowing the ADT-based credential to be used seamlessly among different SN sites.

Sharing Health Big Data for Research - A Design by Use Cases: The INSHARE Platform Approach.

PubMed

Bouzillé, Guillaume; Westerlynck, Richard; Defossez, Gautier; Bouslimi, Dalel; Bayat, Sahar; Riou, Christine; Busnel, Yann; Le Guillou, Clara; Cauvin, Jean-Michel; Jacquelinet, Christian; Pladys, Patrick; Oger, Emmanuel; Stindel, Eric; Ingrand, Pierre; Coatrieux, Gouenou; Cuggia, Marc

2017-01-01

Sharing and exploiting Health Big Data (HBD) allow tackling challenges: data protection/governance taking into account legal, ethical, and deontological aspects enables trust, transparent and win-win relationship between researchers, citizens, and data providers. Lack of interoperability: compartmentalized and syntactically/semantica heterogeneous data. INSHARE project using experimental proof of concept explores how recent technologies overcome such issues. Using 6 data providers, platform is designed via 3 steps to: (1) analyze use cases, needs, and requirements; (2) define data sharing governance, secure access to platform; and (3) define platform specifications. Three use cases - from 5 studies and 11 data sources - were analyzed for platform design. Governance derived from SCANNER model was adapted to data sharing. Platform architecture integrates: data repository and hosting, semantic integration services, data processing, aggregate computing, data quality and integrity monitoring, Id linking, multisource query builder, visualization and data export services, data governance, study management service and security including data watermarking.

Genomic Data Sharing Administrator | Center for Cancer Research

Cancer.gov

Be part of our mission to support research against cancer. We are looking for an organized, detail oriented, dependable person with strong interpersonal skills to serve as a key member of the genomic data sharing administration team at the National Cancer Institute (NCI) on the campus of NIH. Work supports the implementation of the NIH Genomic Data Sharing Policy (GDS) in the

Design and study of geosciences data share platform :platform framework, data interoperability, share approach

NASA Astrophysics Data System (ADS)

Lu, H.; Yi, D.

2010-12-01

The Deep Exploration is one of the important approaches to the Geoscience research. Since 1980s we had started it and achieved a lot of data. Researchers usually integrate both data of space exploration and deep exploration to study geological structures and represent the Earth’s subsurface, and analyze and explain on the base of integrated data. Due to the different exploration approach it results the heterogeneity of data, and therefore the data achievement is always of the import issue to make the researchers confused. The problem of data share and interaction has to be solved during the development of the SinoProbe research project. Through the research of domestic and overseas well-known exploration project and geosciences data platform, the subject explores the solution of data share and interaction. Based on SOA we present the deep exploration data share framework which comprises three level: data level is used for the solution of data store and the integration of the heterogeneous data; medial level provides the data service of geophysics, geochemistry, etc. by the means of Web service, and carry out kinds of application combination by the use of GIS middleware and Eclipse RCP; interaction level provides professional and non-professional customer the access to different accuracy data. The framework adopts GeoSciML data interaction approach. GeoSciML is a geosciences information markup language, as an application of the OpenGIS Consortium’s (OGC) Geography Markup Language (GML). It transfers heterogeneous data into one earth frame and implements inter-operation. We dissertate in this article the solution how to integrate the heterogeneous data and share the data in the project of SinoProbe.

Willingness to Share Research Data Is Related to the Strength of the Evidence and the Quality of Reporting of Statistical Results

PubMed Central

Wicherts, Jelte M.; Bakker, Marjan; Molenaar, Dylan

2011-01-01

Background The widespread reluctance to share published research data is often hypothesized to be due to the authors' fear that reanalysis may expose errors in their work or may produce conclusions that contradict their own. However, these hypotheses have not previously been studied systematically. Methods and Findings We related the reluctance to share research data for reanalysis to 1148 statistically significant results reported in 49 papers published in two major psychology journals. We found the reluctance to share data to be associated with weaker evidence (against the null hypothesis of no effect) and a higher prevalence of apparent errors in the reporting of statistical results. The unwillingness to share data was particularly clear when reporting errors had a bearing on statistical significance. Conclusions Our findings on the basis of psychological papers suggest that statistical results are particularly hard to verify when reanalysis is more likely to lead to contrasting conclusions. This highlights the importance of establishing mandatory data archiving policies. PMID:22073203

Genomic research and wide data sharing: views of prospective participants.

PubMed

Trinidad, Susan Brown; Fullerton, Stephanie M; Bares, Julie M; Jarvik, Gail P; Larson, Eric B; Burke, Wylie

2010-08-01

Sharing study data within the research community generates tension between two important goods: promoting scientific goals and protecting the privacy interests of study participants. This study was designed to explore the perceptions, beliefs, and attitudes of research participants and possible future participants regarding genome-wide association studies and repository-based research. Focus group sessions with (1) current research participants, (2) surrogate decision-makers, and (3) three age-defined cohorts (18-34 years, 35-50, >50). Participants expressed a variety of opinions about the acceptability of wide sharing of genetic and phenotypic information for research purposes through large, publicly accessible data repositories. Most believed that making de-identified study data available to the research community is a social good that should be pursued. Privacy and confidentiality concerns were common, although they would not necessarily preclude participation. Many participants voiced reservations about sharing data with for-profit organizations. Trust is central in participants' views regarding data sharing. Further research is needed to develop governance models that enact the values of stewardship.

Adaptative Peer to Peer Data Sharing for Technology Enhanced Learning

NASA Astrophysics Data System (ADS)

Angelaccio, Michele; Buttarazzi, Berta

Starting from the hypothesis that P2P Data Sharing in a direct teaching scenario (e.g.: a classroom lesson) may lead to relevant benefits, this paper explores the features of EduSHARE a Collaborative Learning System useful for Enhanced Learning Process.

Privacy Technology to Support Data Sharing for Comparative Effectiveness Research: A SYSTEMATIC REVIEW

PubMed Central

Jiang, Xiaoqian; Sarwate, Anand D.; Ohno-Machado, Lucila

2013-01-01

Objective Effective data sharing is critical for comparative effectiveness research (CER), but there are significant concerns about inappropriate disclosure of patient data. These concerns have spurred the development of new technologies for privacy preserving data sharing and data mining. Our goal is to review existing and emerging techniques that may be appropriate for data sharing related to CER. Material and methods We adapted a systematic review methodology to comprehensively search the research literature. We searched 7 databases and applied three stages of filtering based on titles, abstracts, and full text to identify those works most relevant to CER. Results Based on agreement and using the arbitrage of a third party expert, we selected 97 articles for meta-analysis. Our findings are organized along major types of data sharing in CER applications (i.e., institution-to-institution, institution-hosted, and public release). We made recommendations based on specific scenarios. Limitation We limited the scope of our study to methods that demonstrated practical impact, eliminating many theoretical studies of privacy that have been surveyed elsewhere. We further limited our study to data sharing for data tables, rather than complex genomic, set-valued, time series, text, image, or network data. Conclusion State-of-the-art privacy preserving technologies can guide the development of practical tools that will scale up the CER studies of the future. However, many challenges remain in this fast moving field in terms of practical evaluations as well as applications to a wider range of data types. PMID:23774511

Data Democratization - Promoting Real-Time Data Sharing and Use Worldwide

NASA Astrophysics Data System (ADS)

Yoksas, T. C.; Almeida, W. G.; Leon, V. C.

2007-05-01

The Unidata Program Center (Unidata) of the University Corporation of Atmospheric Research (UCAR) is actively involved in international collaborations whose goals are the free-and-open sharing of hydro-meteorological data; the distribution of analysis and visualization tools for those data; the establishment of server technologies that provide easy-to-use, programmatic remote-access to a wide variety of datasets, and in the building of a community where data, tools, and best practices in education and research are shared. The tools and services provided by Unidata are available to the research and education community free-of-charge. Data sharing capabilities are being provided by Unidata's Internet Data Distribution (IDD) system, a community-based effort that has been the primary source of real-time meteorological data in the US university community for over a decade. A collaboration among Unidata, Brazil's Centro de Previso de Tempo e Estudos Climaticos (CPTEC), the Universidad Federal do Rio de Janeiro (UFRJ), and the Universidade de Sao Paulo (USP) has resulted in the creation of a Brazilian peer of the North American IDD, the IDD-Brasil. Collaboration between Unidata and the Universidad de Costa Rica (UCR) seeks to extend IDD data sharing throughout Central America and the Caribbean in an IDD-Caribe. Efforts aimed at creating a data sharing network for researchers on the Antarctic continent have resulted in the establishment of the Antarctic-IDD. Most recently, explorations of data sharing between UCAR and select countries in Africa have begun. Data analysis and visualization capabilities are available through Unidata in a suite of freely-available applications: the National Centers for Environmental Prediction (NCEP) GEneral Meteorology PAcKage (GEMPAK); the Unidata Integrated Data Viewer (IDV); and University of Wisconsin, Space Science and Engineering Center (SSEC) Man-computer Interactive Data Access System (McIDAS). Remote data access capabilities are provided by Unidata's Thematic Realtime Environmental Data Services (THREDDS) servers (which incorporate Open-source Project for a Network Data Access (OPeNDAP) data services), and the Abstract Data Distribution Environment (ADDE) of McIDAS. It is envisioned that the data sharing capabilities available in the IDD, IDD-Brasil, IDD-Caribe, and Antarctic-IDD, remote data access capabilities available in THREDDS and ADDE, and analysis capabilities available in GEMPAK, the IDV, and McIDAS will help foster new collaborations among prominent universities, national meteorological agencies, and WMO Regional Meteorological Training Centers throughout North, Central, and South America, in the Antarctic research community, and eventually in Africa. This paper is intended to inform AGU 2007 Joint Assembly attendees, especially those in Mexico and Central America, of the availability of real-time data and tools to analyze/visualize those data, and to promote the free-and-open sharing of data, especially of locally-held datasets of general interest.

The OCHIN community information network: bringing together community health centers, information technology, and data to support a patient-centered medical village.

PubMed

Devoe, Jennifer E; Sears, Abigail

2013-01-01

Creating integrated, comprehensive care practices requires access to data and informatics expertise. Information technology (IT) resources are not readily available to individual practices. One model of shared IT resources and learning is a "patient-centered medical village." We describe the OCHIN Community Health Information Network as an example of this model; community practices have come together collectively to form an organization that leverages shared IT expertise, resources, and data, providing members with the means to fully capitalize on new technologies that support improved care. This collaborative facilitates the identification of "problem sheds" through surveillance of network-wide data, enables shared learning regarding best practices, and provides a "community laboratory" for practice-based research. As an example of a community of solution, OCHIN uses health IT and data-sharing innovations to enhance partnerships between public health leaders, clinicians in community health centers, informatics experts, and policy makers. OCHIN community partners benefit from the shared IT resource (eg, a linked electronic health record, centralized data warehouse, informatics, and improvement expertise). This patient-centered medical village provides (1) the collective mechanism to build community-tailored IT solutions, (2) "neighbors" to share data and improvement strategies, and (3) infrastructure to support innovations based on electronic health records across communities, using experimental approaches.

Enabling an Open Data Ecosystem for the Neurosciences.

PubMed

Wiener, Martin; Sommer, Friedrich T; Ives, Zachary G; Poldrack, Russell A; Litt, Brian

2016-11-02

As the pace and complexity of neuroscience data grow, an open data ecosystem must develop and grow with it to allow neuroscientists the ability to reach for new heights of discovery. However, the problems and complexities of neuroscience data sharing must first be addressed. Among the challenges facing data sharing in neuroscience, the problem of incentives, discoverability, and sustainability may be the most pressing. We here describe these problems and provide potential future solutions to help cultivate an ecosystem for data sharing. Copyright © 2016 Elsevier Inc. All rights reserved.

Security controls in an integrated Biobank to protect privacy in data sharing: rationale and study design.

PubMed

Takai-Igarashi, Takako; Kinoshita, Kengo; Nagasaki, Masao; Ogishima, Soichi; Nakamura, Naoki; Nagase, Sachiko; Nagaie, Satoshi; Saito, Tomo; Nagami, Fuji; Minegishi, Naoko; Suzuki, Yoichi; Suzuki, Kichiya; Hashizume, Hiroaki; Kuriyama, Shinichi; Hozawa, Atsushi; Yaegashi, Nobuo; Kure, Shigeo; Tamiya, Gen; Kawaguchi, Yoshio; Tanaka, Hiroshi; Yamamoto, Masayuki

2017-07-06

With the goal of realizing genome-based personalized healthcare, we have developed a biobank that integrates personal health, genome, and omics data along with biospecimens donated by volunteers of 150,000. Such a large-scale of data integration involves obvious risks of privacy violation. The research use of personal genome and health information is a topic of global discussion with regard to the protection of privacy while promoting scientific advancement. The present paper reports on our plans, current attempts, and accomplishments in addressing security problems involved in data sharing to ensure donor privacy while promoting scientific advancement. Biospecimens and data have been collected in prospective cohort studies with the comprehensive agreement. The sample size of 150,000 participants was required for multiple researches including genome-wide screening of gene by environment interactions, haplotype phasing, and parametric linkage analysis. We established the T ohoku M edical M egabank (TMM) data sharing policy: a privacy protection rule that requires physical, personnel, and technological safeguards against privacy violation regarding the use and sharing of data. The proposed policy refers to that of NCBI and that of the Sanger Institute. The proposed policy classifies shared data according to the strength of re-identification risks. Local committees organized by TMM evaluate re-identification risk and assign a security category to a dataset. Every dataset is stored in an assigned segment of a supercomputer in accordance with its security category. A security manager should be designated to handle all security problems at individual data use locations. The proposed policy requires closed networks and IP-VPN remote connections. The mission of the biobank is to distribute biological resources most productively. This mission motivated us to collect biospecimens and health data and simultaneously analyze genome/omics data in-house. The biobank also has the mission of improving the quality and quantity of the contents of the biobank. This motivated us to request users to share the results of their research as feedback to the biobank. The TMM data sharing policy has tackled every security problem originating with the missions. We believe our current implementation to be the best way to protect privacy in data sharing.

Data sharing and dual-use issues.

PubMed

Bezuidenhout, Louise

2013-03-01

The concept of dual-use encapsulates the potential for well-intentioned, beneficial scientific research to also be misused by a third party for malicious ends. The concept of dual-use challenges scientists to look beyond the immediate outcomes of their research and to develop an awareness of possible future (mis)uses of scientific research. Since 2001 much attention has been paid to the possible need to regulate the dual-use potential of the life sciences. Regulation initiatives fall under two broad categories-those that develop the ethical education of scientists and foster an awareness and responsibility of dual-use issues, and those which assess the regulation of information being generated by current research. Both types of initiatives are premised on a cautious, risk-adverse philosophy which advocates careful examination of all future endpoints of research endeavors. This caution advocated within initiatives such as pre-publication review of journal articles contrasts to the obligation to share underpinning data sharing discussions. As the dual-use debate has yet to make a significant impact on data sharing discussions (and vice versa) it is possible that these two areas of knowledge control may present areas of ethical conflict for scientists, and thus need to be more closely examined. This paper examines the tension between the obligation to share exemplified by data sharing principles and the concerns raised by the risk-cautious culture of the dual-use debates. The paper concludes by reflecting on the issues of responsibility as raised by dual-use as relating to data sharing, such as the chain of custody for shared data.

Balancing Benefits and Risks of Immortal Data: Participants’ Views of Open Consent in the Personal Genome Project

PubMed Central

Zarate, Oscar A.; Brody, Julia Green; Brown, Phil; Ramírez-Andreotta, Mónica D.; Perovich, Laura; Matz, Jacob

2016-01-01

The NIH Genomic Data Sharing Policy, effective in January 2015, encourages researchers to obtain broad consent to share data for unspecified biomedical research. The ethics of extensive data sharing depend in part on study participants’ understanding of the risks and benefits. Interviews with participants in the Personal Genome Project show that study participants can readily discuss the risks, including loss of privacy, and are willing to accept risks because they value the opportunity to contribute to health science. They have expansive views of the benefits for science, medicine, and their own health and curiosity. With justice in mind, further exploration is needed to evaluate consent for data sharing among more diverse and vulnerable populations. PMID:26678513

Research Stakeholders' Views on Benefits and Challenges for Public Health Research Data Sharing in Kenya: The Importance of Trust and Social Relations.

PubMed

Jao, Irene; Kombe, Francis; Mwalukore, Salim; Bull, Susan; Parker, Michael; Kamuya, Dorcas; Molyneux, Sassy; Marsh, Vicki

2015-01-01

There is increasing recognition of the importance of sharing research data within the international scientific community, but also of the ethical and social challenges this presents, particularly in the context of structural inequities and varied capacity in international research. Public involvement is essential to building locally responsive research policies, including on data sharing, but little research has involved stakeholders from low-to-middle income countries. Between January and June 2014, a qualitative study was conducted in Kenya involving sixty stakeholders with varying experiences of research in a deliberative process to explore views on benefits and challenges in research data sharing. In-depth interviews and extended small group discussions based on information sharing and facilitated debate were used to collect data. Data were analysed using Framework Analysis, and charting flow and dynamics in debates. The findings highlight both the opportunities and challenges of communicating about this complex and relatively novel topic for many stakeholders. For more and less research-experienced stakeholders, ethical research data sharing is likely to rest on the development and implementation of appropriate trust-building processes, linked to local perceptions of benefits and challenges. The central nature of trust is underpinned by uncertainties around who might request what data, for what purpose and when. Key benefits perceived in this consultation were concerned with the promotion of public health through science, with legitimate beneficiaries defined differently by different groups. Important challenges were risks to the interests of study participants, communities and originating researchers through stigmatisation, loss of privacy, impacting autonomy and unfair competition, including through forms of intentional and unintentional 'misuse' of data. Risks were also seen for science. Given background structural inequities in much international research, building trust in this low-to-middle income setting includes ensuring that the interests of study participants, primary communities and originating researchers will be promoted as far as possible, as well as protected. Important ways of building trust in data sharing include involving the public in policy development and implementation, promoting scientific collaborations around data sharing and building close partnerships between researchers and government health authorities to provide checks and balances on data sharing, and promote near and long-term translational benefits.

Research Stakeholders’ Views on Benefits and Challenges for Public Health Research Data Sharing in Kenya: The Importance of Trust and Social Relations

PubMed Central

Jao, Irene; Kombe, Francis; Mwalukore, Salim; Bull, Susan; Parker, Michael; Kamuya, Dorcas; Molyneux, Sassy; Marsh, Vicki

2015-01-01

Background There is increasing recognition of the importance of sharing research data within the international scientific community, but also of the ethical and social challenges this presents, particularly in the context of structural inequities and varied capacity in international research. Public involvement is essential to building locally responsive research policies, including on data sharing, but little research has involved stakeholders from low-to-middle income countries. Methods Between January and June 2014, a qualitative study was conducted in Kenya involving sixty stakeholders with varying experiences of research in a deliberative process to explore views on benefits and challenges in research data sharing. In-depth interviews and extended small group discussions based on information sharing and facilitated debate were used to collect data. Data were analysed using Framework Analysis, and charting flow and dynamics in debates. Findings The findings highlight both the opportunities and challenges of communicating about this complex and relatively novel topic for many stakeholders. For more and less research-experienced stakeholders, ethical research data sharing is likely to rest on the development and implementation of appropriate trust-building processes, linked to local perceptions of benefits and challenges. The central nature of trust is underpinned by uncertainties around who might request what data, for what purpose and when. Key benefits perceived in this consultation were concerned with the promotion of public health through science, with legitimate beneficiaries defined differently by different groups. Important challenges were risks to the interests of study participants, communities and originating researchers through stigmatisation, loss of privacy, impacting autonomy and unfair competition, including through forms of intentional and unintentional 'misuse' of data. Risks were also seen for science. Discussion Given background structural inequities in much international research, building trust in this low-to-middle income setting includes ensuring that the interests of study participants, primary communities and originating researchers will be promoted as far as possible, as well as protected. Important ways of building trust in data sharing include involving the public in policy development and implementation, promoting scientific collaborations around data sharing and building close partnerships between researchers and government health authorities to provide checks and balances on data sharing, and promote near and long-term translational benefits. PMID:26331716

Big data, open science and the brain: lessons learned from genomics.

PubMed

Choudhury, Suparna; Fishman, Jennifer R; McGowan, Michelle L; Juengst, Eric T

2014-01-01

The BRAIN Initiative aims to break new ground in the scale and speed of data collection in neuroscience, requiring tools to handle data in the magnitude of yottabytes (10(24)). The scale, investment and organization of it are being compared to the Human Genome Project (HGP), which has exemplified "big science" for biology. In line with the trend towards Big Data in genomic research, the promise of the BRAIN Initiative, as well as the European Human Brain Project, rests on the possibility to amass vast quantities of data to model the complex interactions between the brain and behavior and inform the diagnosis and prevention of neurological disorders and psychiatric disease. Advocates of this "data driven" paradigm in neuroscience argue that harnessing the large quantities of data generated across laboratories worldwide has numerous methodological, ethical and economic advantages, but it requires the neuroscience community to adopt a culture of data sharing and open access to benefit from them. In this article, we examine the rationale for data sharing among advocates and briefly exemplify these in terms of new "open neuroscience" projects. Then, drawing on the frequently invoked model of data sharing in genomics, we go on to demonstrate the complexities of data sharing, shedding light on the sociological and ethical challenges within the realms of institutions, researchers and participants, namely dilemmas around public/private interests in data, (lack of) motivation to share in the academic community, and potential loss of participant anonymity. Our paper serves to highlight some foreseeable tensions around data sharing relevant to the emergent "open neuroscience" movement.

Social Networking Adapted for Distributed Scientific Collaboration

NASA Technical Reports Server (NTRS)

Karimabadi, Homa

2012-01-01

Share is a social networking site with novel, specially designed feature sets to enable simultaneous remote collaboration and sharing of large data sets among scientists. The site will include not only the standard features found on popular consumer-oriented social networking sites such as Facebook and Myspace, but also a number of powerful tools to extend its functionality to a science collaboration site. A Virtual Observatory is a promising technology for making data accessible from various missions and instruments through a Web browser. Sci-Share augments services provided by Virtual Observatories by enabling distributed collaboration and sharing of downloaded and/or processed data among scientists. This will, in turn, increase science returns from NASA missions. Sci-Share also enables better utilization of NASA s high-performance computing resources by providing an easy and central mechanism to access and share large files on users space or those saved on mass storage. The most common means of remote scientific collaboration today remains the trio of e-mail for electronic communication, FTP for file sharing, and personalized Web sites for dissemination of papers and research results. Each of these tools has well-known limitations. Sci-Share transforms the social networking paradigm into a scientific collaboration environment by offering powerful tools for cooperative discourse and digital content sharing. Sci-Share differentiates itself by serving as an online repository for users digital content with the following unique features: a) Sharing of any file type, any size, from anywhere; b) Creation of projects and groups for controlled sharing; c) Module for sharing files on HPC (High Performance Computing) sites; d) Universal accessibility of staged files as embedded links on other sites (e.g. Facebook) and tools (e.g. e-mail); e) Drag-and-drop transfer of large files, replacing awkward e-mail attachments (and file size limitations); f) Enterprise-level data and messaging encryption; and g) Easy-to-use intuitive workflow.

The geographic and demographic scope of shared sanitation: an analysis of national survey data from low- and middle-income countries.

PubMed

Heijnen, Marieke; Rosa, Ghislaine; Fuller, James; Eisenberg, Joseph N S; Clasen, Thomas

2014-11-01

A large and growing proportion of the world's population rely on shared sanitation facilities that have historically been excluded from international targets due to concerns about acceptability, hygiene and access. In connection with a proposed change in such policy, we undertook this study to describe the prevalence and scope of households that report relying on shared sanitation and to characterise them in terms of selected socio-economic and demographic covariates. We extracted data from the most recent national household surveys of 84 low- and middle-income countries from Demographic and Health Surveys and Multiple Indicator Cluster Surveys. We describe the prevalence of shared sanitation and explore associations between specified covariates and reliance on shared sanitation using log-binomial regression. While household reliance on any type of shared sanitation is relatively rare in Europe (2.5%) and the Eastern Mediterranean (7.7%), it is not uncommon in the Americas (14.2%), Western Pacific (16.4%) and South-East Asia (31.3%), and it is most prevalent in Africa (44.6%) where many shared facilities do not meet the definition of 'improved' even if they were not shared (17.7%). Overall, shared sanitation is more common in urban (28.6%) than in rural settings (25.9%), even after adjusting for wealth. While results vary geographically, people who rely on shared sanitation tend to be poorer, reside in urban areas and live in households with more young children and headed by people with no formal education. Data from 21 countries suggest that most sharing is with neighbours and other acquaintances (82.0%) rather than the public. The determinants of shared sanitation identified from these data suggest potential confounders that may explain the apparent increased health risk from sharing and should be considered in any policy recommendation. Both geographic and demographic heterogeneity indicate the need for further research to support a change in policies. © 2014 John Wiley & Sons Ltd.

Capturing, Sharing, and Discovering Product Data at a Semantic Level--Moving Forward to the Semantic Web for Advancing the Engineering Product Design Process

ERIC Educational Resources Information Center

Zhu, Lijuan

2011-01-01

Along with the greater productivity that CAD automation provides nowadays, the product data of engineering applications needs to be shared and managed efficiently to gain a competitive edge for the engineering product design. However, exchanging and sharing the heterogeneous product data is still challenging. This dissertation first presents a…

Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking.

PubMed

Wang, Mingxun; Carver, Jeremy J; Phelan, Vanessa V; Sanchez, Laura M; Garg, Neha; Peng, Yao; Nguyen, Don Duy; Watrous, Jeramie; Kapono, Clifford A; Luzzatto-Knaan, Tal; Porto, Carla; Bouslimani, Amina; Melnik, Alexey V; Meehan, Michael J; Liu, Wei-Ting; Crüsemann, Max; Boudreau, Paul D; Esquenazi, Eduardo; Sandoval-Calderón, Mario; Kersten, Roland D; Pace, Laura A; Quinn, Robert A; Duncan, Katherine R; Hsu, Cheng-Chih; Floros, Dimitrios J; Gavilan, Ronnie G; Kleigrewe, Karin; Northen, Trent; Dutton, Rachel J; Parrot, Delphine; Carlson, Erin E; Aigle, Bertrand; Michelsen, Charlotte F; Jelsbak, Lars; Sohlenkamp, Christian; Pevzner, Pavel; Edlund, Anna; McLean, Jeffrey; Piel, Jörn; Murphy, Brian T; Gerwick, Lena; Liaw, Chih-Chuang; Yang, Yu-Liang; Humpf, Hans-Ulrich; Maansson, Maria; Keyzers, Robert A; Sims, Amy C; Johnson, Andrew R; Sidebottom, Ashley M; Sedio, Brian E; Klitgaard, Andreas; Larson, Charles B; P, Cristopher A Boya; Torres-Mendoza, Daniel; Gonzalez, David J; Silva, Denise B; Marques, Lucas M; Demarque, Daniel P; Pociute, Egle; O'Neill, Ellis C; Briand, Enora; Helfrich, Eric J N; Granatosky, Eve A; Glukhov, Evgenia; Ryffel, Florian; Houson, Hailey; Mohimani, Hosein; Kharbush, Jenan J; Zeng, Yi; Vorholt, Julia A; Kurita, Kenji L; Charusanti, Pep; McPhail, Kerry L; Nielsen, Kristian Fog; Vuong, Lisa; Elfeki, Maryam; Traxler, Matthew F; Engene, Niclas; Koyama, Nobuhiro; Vining, Oliver B; Baric, Ralph; Silva, Ricardo R; Mascuch, Samantha J; Tomasi, Sophie; Jenkins, Stefan; Macherla, Venkat; Hoffman, Thomas; Agarwal, Vinayak; Williams, Philip G; Dai, Jingqui; Neupane, Ram; Gurr, Joshua; Rodríguez, Andrés M C; Lamsa, Anne; Zhang, Chen; Dorrestein, Kathleen; Duggan, Brendan M; Almaliti, Jehad; Allard, Pierre-Marie; Phapale, Prasad; Nothias, Louis-Felix; Alexandrov, Theodore; Litaudon, Marc; Wolfender, Jean-Luc; Kyle, Jennifer E; Metz, Thomas O; Peryea, Tyler; Nguyen, Dac-Trung; VanLeer, Danielle; Shinn, Paul; Jadhav, Ajit; Müller, Rolf; Waters, Katrina M; Shi, Wenyuan; Liu, Xueting; Zhang, Lixin; Knight, Rob; Jensen, Paul R; Palsson, Bernhard O; Pogliano, Kit; Linington, Roger G; Gutiérrez, Marcelino; Lopes, Norberto P; Gerwick, William H; Moore, Bradley S; Dorrestein, Pieter C; Bandeira, Nuno

2016-08-09

The potential of the diverse chemistries present in natural products (NP) for biotechnology and medicine remains untapped because NP databases are not searchable with raw data and the NP community has no way to share data other than in published papers. Although mass spectrometry (MS) techniques are well-suited to high-throughput characterization of NP, there is a pressing need for an infrastructure to enable sharing and curation of data. We present Global Natural Products Social Molecular Networking (GNPS; http://gnps.ucsd.edu), an open-access knowledge base for community-wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. In GNPS, crowdsourced curation of freely available community-wide reference MS libraries will underpin improved annotations. Data-driven social-networking should facilitate identification of spectra and foster collaborations. We also introduce the concept of 'living data' through continuous reanalysis of deposited data.

Global Data Spatially Interrelate System for Scientific Big Data Spatial-Seamless Sharing

NASA Astrophysics Data System (ADS)

Yu, J.; Wu, L.; Yang, Y.; Lei, X.; He, W.

2014-04-01

A good data sharing system with spatial-seamless services will prevent the scientists from tedious, boring, and time consuming work of spatial transformation, and hence encourage the usage of the scientific data, and increase the scientific innovation. Having been adopted as the framework of Earth datasets by Group on Earth Observation (GEO), Earth System Spatial Grid (ESSG) is potential to be the spatial reference of the Earth datasets. Based on the implementation of ESSG, SDOG-ESSG, a data sharing system named global data spatially interrelate system (GASE) was design to make the data sharing spatial-seamless. The architecture of GASE was introduced. The implementation of the two key components, V-Pools, and interrelating engine, and the prototype is presented. Any dataset is firstly resampled into SDOG-ESSG, and is divided into small blocks, and then are mapped into hierarchical system of the distributed file system in V-Pools, which together makes the data serving at a uniform spatial reference and at a high efficiency. Besides, the datasets from different data centres are interrelated by the interrelating engine at the uniform spatial reference of SDOGESSG, which enables the system to sharing the open datasets in the internet spatial-seamless.

Willingness to share personal health record data for care improvement and public health: a survey of experienced personal health record users.

PubMed

Weitzman, Elissa R; Kelemen, Skyler; Kaci, Liljana; Mandl, Kenneth D

2012-05-22

Data stored in personally controlled health records (PCHRs) may hold value for clinicians and public health entities, if patients and their families will share them. We sought to characterize consumer willingness and unwillingness (reticence) to share PCHR data across health topics, and with different stakeholders, to advance understanding of this issue. Cross-sectional 2009 Web survey of repeat PCHR users who were patients over 18 years old or parents of patients, to assess willingness to share their PCHR data with an-out-of-hospital provider to support care, and the state/local public health authority to support monitoring; the odds of reticence to share PCHR information about ten exemplary health topics were estimated using a repeated measures approach. Of 261 respondents (56% response rate), more reported they would share all information with the state/local public health authority (63.3%) than with an out-of-hospital provider (54.1%) (OR 1.5, 95% CI 1.1, 1.9; p = .005); few would not share any information with these parties (respectively, 7.9% and 5.2%). For public health sharing, reticence was higher for most topics compared to contagious illness (ORs 4.9 to 1.4, all p-values < .05), and reflected concern about anonymity (47.2%), government insensitivity (41.5%), discrimination (24%). For provider sharing, reticence was higher for all topics compared to contagious illness (ORs 6.3 to 1.5, all p-values < .05), and reflected concern for relevance (52%), disclosure to insurance (47.6%) and/or family (20.5%). Pediatric patients and their families are often willing to share electronic health information to support health improvement, but remain cautious. Robust trust models for PCHR sharing are needed.

Essentials of the disclosure review process: a federal perspective.

PubMed

Zarate, Alvan O; Zayatz, Laura

2006-09-01

MANY RESEARCHERS NEED TO MAKE arrangements to share de-identified electronic data files. However, the ways in which respondent identity may be protected are not well understood or are assumed to be the special province of large statistical agencies or specialized statisticians. Approaches to data sharing and protecting respondent identity have been pioneered by federal agencies which gather data vital to political and economic decision making. These agencies are required by statutory law both to assure confidentiality and to share data in usable form with other governmental agencies and with scholars who perform needed analyses of those data. The basic principles of disclosure limitation developed by the Census Bureau, the National Center for Health Statistics, and other federal agencies are fundamental to meeting new funding requirements to share and deidentify data, and are often referred to in the literature on data sharing. We describe how these principles are employed by the Disclosure Review Boards (DRBs) of these two agencies, and then state these principles in more general terms that are applicable to any disclosure review process. The kinds of data that academic institutions share may call for less complex or stringent DRBs and specific nondisclosure procedures different from those employed by federal agencies, but the same general principles apply. Specific application of these six principles by non-government researchers will depend on the nature of their data, their own institutional resources, and the likely future usefulness of their data.

Fulfilling Schmidt Ocean Institute's commitment to open sharing of information, data, and research outcomes: Successes and Lessons Learned from Proposal Evaluation to Public Repositories to Lasting Achievements

NASA Astrophysics Data System (ADS)

Miller, A.; Zykov, V.

2016-02-01

Schmidt Ocean Institute's vision is that the world's ocean be understood through technological advancement, intelligent observation, and open sharing of information. As such, making data collected aboard R/V Falkor available to the general public is a key pillar of the organization and a major strategic focus. Schmidt Ocean Institute supports open sharing of information about the ocean to stimulate the growth of its applications and user community, and amplify further exploration, discovery, and deeper understanding of our environment. These efforts are supported through partnerships with data management experts in the oceanographic community to enable standards-compliant sharing of scientific information and data collected during research cruises. To properly fulfill the commitment, proponents' data management plans are evaluated as part of the proposal process when applying for ship time. We request a thorough data management plan be submitted and expert reviewers evaluate the proposal's plan as part of the review process. Once a project is successfully selected, the chief scientist signs an agreement stating delivery dates for post-cruise data deliverables in a timely manner, R/V Falkor underway and meterological data is shared via public repositories, and links and reports are posted on the cruise webpage. This allows many more creative minds and thinkers to analyze, process, and study the data collected in the world ocean rather than privileging one scientist with the proprietary information, driving international and national scientific progress. This presentation will include the Institute's mission, vision, and strategy for sharing data, based on our Founders' passions, the process for evaluating proposed data management plans, and our partnering efforts to make data publically available in fulfillment of our commitment. Recent achievements and successes in data sharing, as well as future plans to improve our efforts will also be discussed.

What Drives Academic Data Sharing?

PubMed Central

Fecher, Benedikt; Friesike, Sascha; Hebing, Marcel

2015-01-01

Despite widespread support from policy makers, funding agencies, and scientific journals, academic researchers rarely make their research data available to others. At the same time, data sharing in research is attributed a vast potential for scientific progress. It allows the reproducibility of study results and the reuse of old data for new research questions. Based on a systematic review of 98 scholarly papers and an empirical survey among 603 secondary data users, we develop a conceptual framework that explains the process of data sharing from the primary researcher’s point of view. We show that this process can be divided into six descriptive categories: Data donor, research organization, research community, norms, data infrastructure, and data recipients. Drawing from our findings, we discuss theoretical implications regarding knowledge creation and dissemination as well as research policy measures to foster academic collaboration. We conclude that research data cannot be regarded as knowledge commons, but research policies that better incentivise data sharing are needed to improve the quality of research results and foster scientific progress. PMID:25714752

Trust, confidentiality, and the acceptability of sharing HIV-related patient data: lessons learned from a mixed methods study about Health Information Exchanges

PubMed Central

2012-01-01

Background Concerns about the confidentiality of personal health information have been identified as a potential obstacle to implementation of Health Information Exchanges (HIEs). Considering the stigma and confidentiality issues historically associated with human immunodeficiency virus (HIV) disease, we examine how trust—in technology, processes, and people—influenced the acceptability of data sharing among stakeholders prior to implementation of six HIEs intended to improve HIV care in parts of the United States. Our analyses identify the kinds of concerns expressed by stakeholders about electronic data sharing and focus on the factors that ultimately facilitated acceptability of the new exchanges. Methods We conducted 549 surveys with patients and 66 semi-structured interviews with providers and other stakeholders prior to implementation of the HIEs to assess concerns about confidentiality in the electronic sharing of patient data. The patient quantitative data were analyzed using SAS 9.2 to yield sample descriptive statistics. The analysis of the qualitative interviews with providers and other stakeholders followed an open-coding process, and convergent and divergent perspectives emerging from those data were examined within and across the HIEs. Results We found widespread acceptability for electronic sharing of HIV-related patient data through HIEs. This acceptability appeared to be driven by growing comfort with information technologies, confidence in the security protocols utilized to protect data, trust in the providers and institutions who use the technologies, belief in the benefits to the patients, and awareness that electronic exchange represents an enhancement of data sharing already taking place by other means. HIE acceptability depended both on preexisting trust among patients, providers, and institutions and on building consensus and trust in the HIEs as part of preparation for implementation. The process of HIE development also resulted in forging shared vision among institutions. Conclusions Patients and providers are willing to accept the electronic sharing of HIV patient data to improve care for a disease historically seen as highly stigmatized. Acceptability depends on the effort expended to understand and address potential concerns related to data sharing and confidentiality, and on the trust established among stakeholders in terms of the nature of the systems and how they will be used. PMID:22515736

An International Framework for Data Sharing: Moving Forward with the Global Alliance for Genomics and Health.

PubMed

Rahimzadeh, Vasiliki; Dyke, Stephanie O M; Knoppers, Bartha M

2016-06-01

The Global Alliance for Genomics and Health is marshaling expertise in biomedical research and data sharing policy to propel bench-to-bedside translation of genomics in parallel with many of the BioSHaRE-EU initiatives described at length in this Issue. Worldwide representation of institutions, funders, researchers, and patient advocacy groups at the Global Alliance is testament to a shared ideal that sees maximizing the public good as a chief priority of genomic innovation in health. The Global Alliance has made a critical stride in this regard with the development of its Framework for Responsible Sharing of Genomic and Health-related Data.(1) This article first discusses the human rights pillars that underlie the Framework and mission of the Global Alliance. Second, it outlines the Global Alliance's use of data governance policies through a number of demonstration projects. Finally, the authors describe how the Global Alliance envisions international data sharing moving forward in the postgenomic era.

Open Data in Global Environmental Research: The Belmont Forum's Open Data Survey.

PubMed

Schmidt, Birgit; Gemeinholzer, Birgit; Treloar, Andrew

2016-01-01

This paper presents the findings of the Belmont Forum's survey on Open Data which targeted the global environmental research and data infrastructure community. It highlights users' perceptions of the term "open data", expectations of infrastructure functionalities, and barriers and enablers for the sharing of data. A wide range of good practice examples was pointed out by the respondents which demonstrates a substantial uptake of data sharing through e-infrastructures and a further need for enhancement and consolidation. Among all policy responses, funder policies seem to be the most important motivator. This supports the conclusion that stronger mandates will strengthen the case for data sharing.

Cyberinfrastructure for Open Science at the Montreal Neurological Institute

PubMed Central

Das, Samir; Glatard, Tristan; Rogers, Christine; Saigle, John; Paiva, Santiago; MacIntyre, Leigh; Safi-Harab, Mouna; Rousseau, Marc-Etienne; Stirling, Jordan; Khalili-Mahani, Najmeh; MacFarlane, David; Kostopoulos, Penelope; Rioux, Pierre; Madjar, Cecile; Lecours-Boucher, Xavier; Vanamala, Sandeep; Adalat, Reza; Mohaddes, Zia; Fonov, Vladimir S.; Milot, Sylvain; Leppert, Ilana; Degroot, Clotilde; Durcan, Thomas M.; Campbell, Tara; Moreau, Jeremy; Dagher, Alain; Collins, D. Louis; Karamchandani, Jason; Bar-Or, Amit; Fon, Edward A.; Hoge, Rick; Baillet, Sylvain; Rouleau, Guy; Evans, Alan C.

2017-01-01

Data sharing is becoming more of a requirement as technologies mature and as global research and communications diversify. As a result, researchers are looking for practical solutions, not only to enhance scientific collaborations, but also to acquire larger amounts of data, and to access specialized datasets. In many cases, the realities of data acquisition present a significant burden, therefore gaining access to public datasets allows for more robust analyses and broadly enriched data exploration. To answer this demand, the Montreal Neurological Institute has announced its commitment to Open Science, harnessing the power of making both clinical and research data available to the world (Owens, 2016a,b). As such, the LORIS and CBRAIN (Das et al., 2016) platforms have been tasked with the technical challenges specific to the institutional-level implementation of open data sharing, including: Comprehensive linking of multimodal data (phenotypic, clinical, neuroimaging, biobanking, and genomics, etc.)Secure database encryption, specifically designed for institutional and multi-project data sharing, ensuring subject confidentiality (using multi-tiered identifiers).Querying capabilities with multiple levels of single study and institutional permissions, allowing public data sharing for all consented and de-identified subject data.Configurable pipelines and flags to facilitate acquisition and analysis, as well as access to High Performance Computing clusters for rapid data processing and sharing of software tools.Robust Workflows and Quality Control mechanisms ensuring transparency and consistency in best practices.Long term storage (and web access) of data, reducing loss of institutional data assets.Enhanced web-based visualization of imaging, genomic, and phenotypic data, allowing for real-time viewing and manipulation of data from anywhere in the world.Numerous modules for data filtering, summary statistics, and personalized and configurable dashboards. Implementing the vision of Open Science at the Montreal Neurological Institute will be a concerted undertaking that seeks to facilitate data sharing for the global research community. Our goal is to utilize the years of experience in multi-site collaborative research infrastructure to implement the technical requirements to achieve this level of public data sharing in a practical yet robust manner, in support of accelerating scientific discovery. PMID:28111547

Cyberinfrastructure for Open Science at the Montreal Neurological Institute.

PubMed

Das, Samir; Glatard, Tristan; Rogers, Christine; Saigle, John; Paiva, Santiago; MacIntyre, Leigh; Safi-Harab, Mouna; Rousseau, Marc-Etienne; Stirling, Jordan; Khalili-Mahani, Najmeh; MacFarlane, David; Kostopoulos, Penelope; Rioux, Pierre; Madjar, Cecile; Lecours-Boucher, Xavier; Vanamala, Sandeep; Adalat, Reza; Mohaddes, Zia; Fonov, Vladimir S; Milot, Sylvain; Leppert, Ilana; Degroot, Clotilde; Durcan, Thomas M; Campbell, Tara; Moreau, Jeremy; Dagher, Alain; Collins, D Louis; Karamchandani, Jason; Bar-Or, Amit; Fon, Edward A; Hoge, Rick; Baillet, Sylvain; Rouleau, Guy; Evans, Alan C

2016-01-01

Data sharing is becoming more of a requirement as technologies mature and as global research and communications diversify. As a result, researchers are looking for practical solutions, not only to enhance scientific collaborations, but also to acquire larger amounts of data, and to access specialized datasets. In many cases, the realities of data acquisition present a significant burden, therefore gaining access to public datasets allows for more robust analyses and broadly enriched data exploration. To answer this demand, the Montreal Neurological Institute has announced its commitment to Open Science, harnessing the power of making both clinical and research data available to the world (Owens, 2016a,b). As such, the LORIS and CBRAIN (Das et al., 2016) platforms have been tasked with the technical challenges specific to the institutional-level implementation of open data sharing, including: Comprehensive linking of multimodal data (phenotypic, clinical, neuroimaging, biobanking, and genomics, etc.)Secure database encryption, specifically designed for institutional and multi-project data sharing, ensuring subject confidentiality (using multi-tiered identifiers).Querying capabilities with multiple levels of single study and institutional permissions, allowing public data sharing for all consented and de-identified subject data.Configurable pipelines and flags to facilitate acquisition and analysis, as well as access to High Performance Computing clusters for rapid data processing and sharing of software tools.Robust Workflows and Quality Control mechanisms ensuring transparency and consistency in best practices.Long term storage (and web access) of data, reducing loss of institutional data assets.Enhanced web-based visualization of imaging, genomic, and phenotypic data, allowing for real-time viewing and manipulation of data from anywhere in the world.Numerous modules for data filtering, summary statistics, and personalized and configurable dashboards. Implementing the vision of Open Science at the Montreal Neurological Institute will be a concerted undertaking that seeks to facilitate data sharing for the global research community. Our goal is to utilize the years of experience in multi-site collaborative research infrastructure to implement the technical requirements to achieve this level of public data sharing in a practical yet robust manner, in support of accelerating scientific discovery.

Open innovation: Towards sharing of data, models and workflows.

PubMed

Conrado, Daniela J; Karlsson, Mats O; Romero, Klaus; Sarr, Céline; Wilkins, Justin J

2017-11-15

Sharing of resources across organisations to support open innovation is an old idea, but which is being taken up by the scientific community at increasing speed, concerning public sharing in particular. The ability to address new questions or provide more precise answers to old questions through merged information is among the attractive features of sharing. Increased efficiency through reuse, and increased reliability of scientific findings through enhanced transparency, are expected outcomes from sharing. In the field of pharmacometrics, efforts to publicly share data, models and workflow have recently started. Sharing of individual-level longitudinal data for modelling requires solving legal, ethical and proprietary issues similar to many other fields, but there are also pharmacometric-specific aspects regarding data formats, exchange standards, and database properties. Several organisations (CDISC, C-Path, IMI, ISoP) are working to solve these issues and propose standards. There are also a number of initiatives aimed at collecting disease-specific databases - Alzheimer's Disease (ADNI, CAMD), malaria (WWARN), oncology (PDS), Parkinson's Disease (PPMI), tuberculosis (CPTR, TB-PACTS, ReSeqTB) - suitable for drug-disease modelling. Organized sharing of pharmacometric executable model code and associated information has in the past been sparse, but a model repository (DDMoRe Model Repository) intended for the purpose has recently been launched. In addition several other services can facilitate model sharing more generally. Pharmacometric workflows have matured over the last decades and initiatives to more fully capture those applied to analyses are ongoing. In order to maximize both the impact of pharmacometrics and the knowledge extracted from clinical data, the scientific community needs to take ownership of and create opportunities for open innovation. Copyright © 2017 Elsevier B.V. All rights reserved.

Sharing and reuse of individual participant data from clinical trials: principles and recommendations

PubMed Central

Ohmann, Christian; Banzi, Rita; Canham, Steve; Battaglia, Serena; Matei, Mihaela; Ariyo, Christopher; Becnel, Lauren; Bierer, Barbara; Bowers, Sarion; Clivio, Luca; Dias, Monica; Druml, Christiane; Faure, Hélène; Fenner, Martin; Galvez, Jose; Ghersi, Davina; Gluud, Christian; Houston, Paul; Karam, Ghassan; Kalra, Dipak; Krleža-Jerić, Karmela; Kubiak, Christine; Kuchinke, Wolfgang; Kush, Rebecca; Lukkarinen, Ari; Marques, Pedro Silverio; Newbigging, Andrew; O’Callaghan, Jennifer; Ravaud, Philippe; Schlünder, Irene; Shanahan, Daniel; Sitter, Helmut; Spalding, Dylan; Tudur-Smith, Catrin; van Reusel, Peter; van Veen, Evert-Ben; Visser, Gerben Rienk; Wilson, Julia; Demotes-Mainard, Jacques

2017-01-01

Objectives We examined major issues associated with sharing of individual clinical trial data and developed a consensus document on providing access to individual participant data from clinical trials, using a broad interdisciplinary approach. Design and methods This was a consensus-building process among the members of a multistakeholder task force, involving a wide range of experts (researchers, patient representatives, methodologists, information technology experts, and representatives from funders, infrastructures and standards development organisations). An independent facilitator supported the process using the nominal group technique. The consensus was reached in a series of three workshops held over 1 year, supported by exchange of documents and teleconferences within focused subgroups when needed. This work was set within the Horizon 2020-funded project CORBEL (Coordinated Research Infrastructures Building Enduring Life-science Services) and coordinated by the European Clinical Research Infrastructure Network. Thus, the focus was on non-commercial trials and the perspective mainly European. Outcome We developed principles and practical recommendations on how to share data from clinical trials. Results The task force reached consensus on 10 principles and 50 recommendations, representing the fundamental requirements of any framework used for the sharing of clinical trials data. The document covers the following main areas: making data sharing a reality (eg, cultural change, academic incentives, funding), consent for data sharing, protection of trial participants (eg, de-identification), data standards, rights, types and management of access (eg, data request and access models), data management and repositories, discoverability, and metadata. Conclusions The adoption of the recommendations in this document would help to promote and support data sharing and reuse among researchers, adequately inform trial participants and protect their rights, and provide effective and efficient systems for preparing, storing and accessing data. The recommendations now need to be implemented and tested in practice. Further work needs to be done to integrate these proposals with those from other geographical areas and other academic domains. PMID:29247106

Sharing and community curation of mass spectrometry data with GNPS

PubMed Central

Nguyen, Don Duy; Watrous, Jeramie; Kapono, Clifford A; Luzzatto-Knaan, Tal; Porto, Carla; Bouslimani, Amina; Melnik, Alexey V; Meehan, Michael J; Liu, Wei-Ting; Crüsemann, Max; Boudreau, Paul D; Esquenazi, Eduardo; Sandoval-Calderón, Mario; Kersten, Roland D; Pace, Laura A; Quinn, Robert A; Duncan, Katherine R; Hsu, Cheng-Chih; Floros, Dimitrios J; Gavilan, Ronnie G; Kleigrewe, Karin; Northen, Trent; Dutton, Rachel J; Parrot, Delphine; Carlson, Erin E; Aigle, Bertrand; Michelsen, Charlotte F; Jelsbak, Lars; Sohlenkamp, Christian; Pevzner, Pavel; Edlund, Anna; McLean, Jeffrey; Piel, Jörn; Murphy, Brian T; Gerwick, Lena; Liaw, Chih-Chuang; Yang, Yu-Liang; Humpf, Hans-Ulrich; Maansson, Maria; Keyzers, Robert A; Sims, Amy C; Johnson, Andrew R.; Sidebottom, Ashley M; Sedio, Brian E; Klitgaard, Andreas; Larson, Charles B; P., Cristopher A Boya; Torres-Mendoza, Daniel; Gonzalez, David J; Silva, Denise B; Marques, Lucas M; Demarque, Daniel P; Pociute, Egle; O'Neill, Ellis C; Briand, Enora; Helfrich, Eric J. N.; Granatosky, Eve A; Glukhov, Evgenia; Ryffel, Florian; Houson, Hailey; Mohimani, Hosein; Kharbush, Jenan J; Zeng, Yi; Vorholt, Julia A; Kurita, Kenji L; Charusanti, Pep; McPhail, Kerry L; Nielsen, Kristian Fog; Vuong, Lisa; Elfeki, Maryam; Traxler, Matthew F; Engene, Niclas; Koyama, Nobuhiro; Vining, Oliver B; Baric, Ralph; Silva, Ricardo R; Mascuch, Samantha J; Tomasi, Sophie; Jenkins, Stefan; Macherla, Venkat; Hoffman, Thomas; Agarwal, Vinayak; Williams, Philip G; Dai, Jingqui; Neupane, Ram; Gurr, Joshua; Rodríguez, Andrés M. C.; Lamsa, Anne; Zhang, Chen; Dorrestein, Kathleen; Duggan, Brendan M; Almaliti, Jehad; Allard, Pierre-Marie; Phapale, Prasad; Nothias, Louis-Felix; Alexandrov, Theodore; Litaudon, Marc; Wolfender, Jean-Luc; Kyle, Jennifer E; Metz, Thomas O; Peryea, Tyler; Nguyen, Dac-Trung; VanLeer, Danielle; Shinn, Paul; Jadhav, Ajit; Müller, Rolf; Waters, Katrina M; Shi, Wenyuan; Liu, Xueting; Zhang, Lixin; Knight, Rob; Jensen, Paul R; Palsson, Bernhard O; Pogliano, Kit; Linington, Roger G; Gutiérrez, Marcelino; Lopes, Norberto P; Gerwick, William H; Moore, Bradley S; Dorrestein, Pieter C; Bandeira, Nuno

2017-01-01

The potential of the diverse chemistries present in natural products (NP) for biotechnology and medicine remains untapped because NP databases are not searchable with raw data and the NP community has no way to share data other than in published papers. Although mass spectrometry techniques are well-suited to high-throughput characterization of natural products, there is a pressing need for an infrastructure to enable sharing and curation of data. We present Global Natural Products Social molecular networking (GNPS, http://gnps.ucsd.edu), an open-access knowledge base for community wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. In GNPS crowdsourced curation of freely available community-wide reference MS libraries will underpin improved annotations. Data-driven social-networking should facilitate identification of spectra and foster collaborations. We also introduce the concept of ‘living data’ through continuous reanalysis of deposited data. PMID:27504778

District decision-making for health in low-income settings: a qualitative study in Uttar Pradesh, India, on engaging the private health sector in sharing health-related data.

PubMed

Gautham, Meenakshi; Spicer, Neil; Subharwal, Manish; Gupta, Sanjay; Srivastava, Aradhana; Bhattacharyya, Sanghita; Avan, Bilal Iqbal; Schellenberg, Joanna

2016-09-01

Health information systems are an important planning and monitoring tool for public health services, but may lack information from the private health sector. In this fourth article in a series on district decision-making for health, we assessed the extent of maternal, newborn and child health (MNCH)-related data sharing between the private and public sectors in two districts of Uttar Pradesh, India; analysed barriers to data sharing; and identified key inputs required for data sharing. Between March 2013 and August 2014, we conducted 74 key informant interviews at national, state and district levels. Respondents were stakeholders from national, state and district health departments, professional associations, non-governmental programmes and private commercial health facilities with 3-200 beds. Qualitative data were analysed using a framework based on a priori and emerging themes. Private facilities registered for ultrasounds and abortions submitted standardized records on these services, which is compulsory under Indian laws. Data sharing for other services was weak, but most facilities maintained basic records related to institutional deliveries and newborns. Public health facilities in blocks collected these data from a few private facilities using different methods. The major barriers to data sharing included the public sector's non-standardized data collection and utilization systems for MNCH and lack of communication and follow up with private facilities. Private facilities feared information disclosure and the additional burden of reporting, but were willing to share data if asked officially, provided the process was simple and they were assured of confidentiality. Unregistered facilities, managed by providers without a biomedical qualification, also conducted institutional deliveries, but were outside any reporting loops. Our findings suggest that even without legislation, the public sector could set up an effective MNCH data sharing strategy with private registered facilities by developing a standardized and simple system with consistent communication and follow up. © The Author 2016. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine.

When data sharing gets close to 100%: what human paleogenetics can teach the open science movement.

PubMed

Anagnostou, Paolo; Capocasa, Marco; Milia, Nicola; Sanna, Emanuele; Battaggia, Cinzia; Luzi, Daniela; Destro Bisol, Giovanni

2015-01-01

This study analyzes data sharing regarding mitochondrial, Y chromosomal and autosomal polymorphisms in a total of 162 papers on ancient human DNA published between 1988 and 2013. The estimated sharing rate was not far from totality (97.6% ± 2.1%) and substantially higher than observed in other fields of genetic research (evolutionary, medical and forensic genetics). Both a questionnaire-based survey and the examination of Journals' editorial policies suggest that this high sharing rate cannot be simply explained by the need to comply with stakeholders requests. Most data were made available through body text, but the use of primary databases increased in coincidence with the introduction of complete mitochondrial and next-generation sequencing methods. Our study highlights three important aspects. First, our results imply that researchers' awareness of the importance of openness and transparency for scientific progress may complement stakeholders' policies in achieving very high sharing rates. Second, widespread data sharing does not necessarily coincide with a prevalent use of practices which maximize data findability, accessibility, useability and preservation. A detailed look at the different ways in which data are released can be very useful to detect failures to adopt the best sharing modalities and understand how to correct them. Third and finally, the case of human paleogenetics tells us that a widespread awareness of the importance of Open Science may be important to build reliable scientific practices even in the presence of complex experimental challenges.

Informatics methods to enable sharing of quantitative imaging research data.

PubMed

Levy, Mia A; Freymann, John B; Kirby, Justin S; Fedorov, Andriy; Fennessy, Fiona M; Eschrich, Steven A; Berglund, Anders E; Fenstermacher, David A; Tan, Yongqiang; Guo, Xiaotao; Casavant, Thomas L; Brown, Bartley J; Braun, Terry A; Dekker, Andre; Roelofs, Erik; Mountz, James M; Boada, Fernando; Laymon, Charles; Oborski, Matt; Rubin, Daniel L

2012-11-01

The National Cancer Institute Quantitative Research Network (QIN) is a collaborative research network whose goal is to share data, algorithms and research tools to accelerate quantitative imaging research. A challenge is the variability in tools and analysis platforms used in quantitative imaging. Our goal was to understand the extent of this variation and to develop an approach to enable sharing data and to promote reuse of quantitative imaging data in the community. We performed a survey of the current tools in use by the QIN member sites for representation and storage of their QIN research data including images, image meta-data and clinical data. We identified existing systems and standards for data sharing and their gaps for the QIN use case. We then proposed a system architecture to enable data sharing and collaborative experimentation within the QIN. There are a variety of tools currently used by each QIN institution. We developed a general information system architecture to support the QIN goals. We also describe the remaining architecture gaps we are developing to enable members to share research images and image meta-data across the network. As a research network, the QIN will stimulate quantitative imaging research by pooling data, algorithms and research tools. However, there are gaps in current functional requirements that will need to be met by future informatics development. Special attention must be given to the technical requirements needed to translate these methods into the clinical research workflow to enable validation and qualification of these novel imaging biomarkers. Copyright © 2012 Elsevier Inc. All rights reserved.

Social capital and knowledge sharing: effects on patient safety.

PubMed

Chang, Chia-Wen; Huang, Heng-Chiang; Chiang, Chi-Yun; Hsu, Chiu-Ping; Chang, Chia-Chen

2012-08-01

This article is a report on a study that empirically examines the influence of social capital on knowledge sharing and the impact of knowledge sharing on patient safety. Knowledge sharing is linked to many desirable managerial outcomes, including learning and problem-solving, which are essential for patient safety. Rather than studying the tangible effects of rewards, this study examines whether social capital (including social interaction, trust and shared vision) directly supports individual knowledge sharing in an organization. This cross-sectional study analysed data collected through a questionnaire survey of nurses from a major medical centre in northern Taiwan. The data were collected over a 9-month period from 2008 to 2009. The data analysis was conducted using the Partial Least Squares Graph v3.0 program to evaluate the measurement properties and the structural relationships specified in the research model. Based on a large-scale survey, empirical results indicate that Registered Nurses' perceptions of trust and shared vision have statistically significant and direct effects on knowledge sharing. In addition, knowledge sharing is significantly and positively associated with patient safety. The findings suggest that hospital administrators should foster group trust and initiate a common vision among Registered Nurses. In addition, administrators and chief knowledge officers of hospitals should encourage positive intentions towards knowledge sharing. © 2011 The Authors. Journal of Advanced Nursing © 2011 Blackwell Publishing Ltd.

Data sharing in stem cell translational science: policy statement by the International Stem Cell Forum Ethics Working Party.

PubMed

Bredenoord, Annelien L; Mostert, Menno; Isasi, Rosario; Knoppers, Bartha M

2015-01-01

Data and sample sharing constitute a scientific and ethical imperative but need to be conducted in a responsible manner in order to protect individual interests as well as maintain public trust. In 2014, the Global Alliance for Genomics and Health (GA4GH) adopted a common Framework for Responsible Sharing of Genomic and Health-Related Data. The GA4GH Framework is applicable to data sharing in the stem cell field, however, interpretation is required so as to provide guidance for this specific context. In this paper, the International Stem Cell Forum Ethics Working Party discusses those principles that are specific to translational stem cell science, including engagement, data quality and safety, privacy, security and confidentiality, risk-benefit analysis and sustainability.

An Overview of ISS Human Research Data Sharing

NASA Technical Reports Server (NTRS)

Morshedi, Pasha

2015-01-01

This presentation is an attempt to clarify several aspects of the current procedures, tools, and challenges of human data sharing for ISS flight activities. There are several binary variables to consider with respect to human spaceflight data sharing: Medical vs. Research, Active Flight vs. Non-Flight, Tactical vs. Supplemental, Prospective vs. Retrospective. This presentation will address each of these variables and how they determine which processes and mechanisms are used both to document and facilitate human data sharing. Some of these variables will likely be so obvious that they induce eye rolls. Please bear with us. We're trying to make these slides fairly rudimentary for a wide, (eventually) international audience. Other distinctions are made if data originated from a NASA vs. IP crewmember. Those distinctions will be made apparent when needed.

Information And Data-Sharing Plan of IPY China Activity

NASA Astrophysics Data System (ADS)

Zhang, X.; Cheng, W.

2007-12-01

Polar Data-Sharing is an effective resolution to global system and polar science problems and to interdisciplinary and sustainable study, as well as an important means to deal with IPY scientific heritages and realize IPY goals. Corresponding to IPY Data-Sharing policies, Information and Data-Sharing Plan was listed in five sub-plans of IPY Chinese Programme launched in March, 2007,they are Scientific research program of the Prydz Bay, Amery Ice Shelf and Dome A transects(short title:'PANDA'), the Arctic Scientific Research Expedition Plan, International Cooperation Plan, Information and Data-Sharing Plan, Education and Outreach. China, since the foundation of Antarctic Zhongshan Station in 1989, has carried out systematic scientific expeditions and researches in Larsemann Hills, Prydz Bay and the neighbouring sea areas, organized 14 Prydz Bay oceanographic investigations, 3 Amery Ice Shelf expeditions, 4 Grove Mountains expeditions and 5 inland ice cap scientific expeditions. 2 comprehensive oceanographic investigations in the Arctic Ocean were conducted in 1999 and 2003, acquired a large amount of data and samples in PANDA section and fan areas of Pacific Ocean in the Arctic Ocean. A mechanism of basic data submitting ,sharing and archiving has been gradually set up since 2000. Presently, Polar Science Database and Polar Sample Resource Sharing Platform of China with the aim of sharing polar data and samples has been initially established and began to provide sharing service to domestic and oversea users. According to IPY Chinese Activity, 2 scientific expeditions in the Arctic Ocean, 3 in the South Ocean, 2 at Amery Ice Shelf, 1 on Grove Mountains and 2 inland ice cap expeditions on Dome A will be carried out during IPY period. According to the experiences accumulated in the past and the jobs in the future, the Information and Data- Sharing Plan, during 2007-2010, will save, archive, and provide exchange and sharing services upon the data obtained by scientific expeditions on the site of IPY Chinese Programme. Meanwhile, focusing on areas in east Antarctic Dome A-Grove Mountain-Zhongshan Station-Amery Ice Shelf-Prydz Bay Section and the fan areas of Pacific Ocean in the Arctic Ocean, the Plan will also collect and integrate IPY data and historical data and establish database of PANDA Section and the Arctic Ocean. The details are as follows: On the basis of integrating the observed data acquired during the expeditions of China, the Plan will, adopting portal technology, develop 5 subject databases (English version included):(1) Database of Zhongshan Station- Dome A inner land ice cap section;(2) Database of interaction of ocean-ice-atmosphere-ice shelf in east Antarctica;(3) Database of geological and glaciological advance and retreat evolvement in Grove Mountains; (4) Database of Solar Terrestrial Physics at Zhongshan Station; (5) Oceanographic database of fan area of Pacific Ocean in the Arctic Ocean. CN-NADC of PRIC is the institute which assumes the responsibility for the Plan, specifically, it coordinates and organizes the operation of the Plan which includes data management, developing the portal of data and information sharing, and international exchanges. The specific assignments under the Plan will be carried out by research institutes under CAS (Chinese Academy of Sciences), SOA ( State Oceanic Administration), State Bureau of Surveying and Mapping and Ministry of Education.

Data sharing and the evolving role of statisticians.

PubMed

Manamley, Nick; Mallett, Steve; Sydes, Matthew R; Hollis, Sally; Scrimgeour, Alison; Burger, Hans Ulrich; Urban, Hans-Joerg

2016-07-08

Greater transparency and, in particular, sharing of clinical study reports and patient level data for further research is an increasingly important topic for the pharmaceutical and biotechnology industry and other organisations who sponsor and conduct clinical research as well as academic researchers and patient advocacy groups. Statisticians are ambassadors for data sharing and are central to its success. They play an integral role in data sharing discussions within their companies and also externally helping to shape policy and processes while providing input into practical solutions to aid data sharing. Data sharing is generating changes in the required profile for statisticians in the pharmaceutical and biotechnology industry, as well as academic institutions and patient advocacy groups. Successful statisticians need to possess many qualities required in today's pharmaceutical environment such as collaboration, diplomacy, written and oral skills and an ability to be responsive; they are also knowledgeable when debating strategy and analytical techniques. However, increasing data transparency will require statisticians to evolve and learn new skills and behaviours during their career which may not have been an accepted part of the traditional role. Statisticians will move from being the gate-keepers of data to be data facilitators. To adapt successfully to this new environment, the role of the statistician is likely to be broader, including defining new responsibilities that lie beyond the boundaries of the traditional role. Statisticians should understand how data transparency can benefit them and the potential strategic advantage it can bring and be fully aware of the pharmaceutical and biotechnology industry commitments to data transparency and the policies within their company or research institute in addition to focusing on reviewing requests and provisioning data. Data transparency will evolve the role of statisticians within the pharmaceutical and biotechnology industry, academia and research bodies to a level which may not have been an accepted part of their traditional role or career. In the future, skills will be required to manage challenges arising from data sharing; statisticians will need strong scientific and statistical guiding principles for reanalysis and supplementary analyses based on researchers' requests, have enhanced consultancy skills, in particular the ability to defend good statistical practice in the face of criticism and the ability to critique methods of analysis. Statisticians will also require expertise in data privacy regulations, data redaction and anonymisation and be able to assess the probability of re-identification, an ability to understand analyses conducted by researchers and recognise why such analyses may propose different results compared to the original analyses. Bringing these skills to the implementation of data sharing and interpretation of the results will help to maximise the value of shared data while guarding against misleading conclusions.

Library Information System Time-Sharing (LISTS) Project. Final Report.

ERIC Educational Resources Information Center

Black, Donald V.

The Library Information System Time-Sharing (LISTS) experiment was based on three innovations in data processing technology: (1) the advent of computer time-sharing on third-generation machines, (2) the development of general-purpose file-management software and (3) the introduction of large, library-oriented data bases. The main body of the…

General Revenue Sharing Data Study: Executive Summary. Volume I.

ERIC Educational Resources Information Center

Wilson, Reese C.; Bowditch, E. Francis, Jr.

The results of the General Revenue Sharing Data Study carried out by Stanford Research Institute for the Office of Revenue Sharing are reported in four volumes. This volume, Executive Summary, presents highlights excerpted from Volumes II, III, and IV. Emphasis is placed on those findings, conclusions, and recommendations that deserve special…

Bringing Together Community Health Centers, Information Technology and Data to Support a Patient-Centered Medical Village from the OCHIN community of solutions

PubMed Central

DeVoe, Jennifer E.; Sears, Abigail

2013-01-01

Creating integrated, comprehensive care practices requires access to data and informatics expertise. Information technology (IT) resources are not readily available to individual practices. One model of shared IT resources and learning is a “patient-centered medical village.” We describe the OCHIN Community Health Information Network as an example of this model where community practices have come together collectively to form an organization which leverages shared IT expertise, resources, and data, providing members with the means to fully capitalize on new technologies that support improved care. This collaborative facilitates the identification of “problem-sheds” through surveillance of network-wide data, enables shared learning regarding best practices, and provides a “community laboratory” for practice-based research. As an example of a Community of Solution, OCHIN utilizes health IT and data-sharing innovations to enhance partnerships between public health leaders, community health center clinicians, informatics experts, and policy makers. OCHIN community partners benefit from the shared IT resource (e.g. a linked electronic health record (EHR), centralized data warehouse, informatics and improvement expertise). This patient-centered medical village provides (1) the collective mechanism to build community tailored IT solutions, (2) “neighbors” to share data and improvement strategies, and (3) infrastructure to support EHR-based innovations across communities, using experimental approaches. PMID:23657695

Building and Sustaining International Scientific Partnerships Through Data Sharing

NASA Astrophysics Data System (ADS)

Ramamurthy, M. K.; Yoksas, T.; Miller, L.

2007-05-01

Understanding global environmental processes and their regional linkages has heightened the importance of full, open, and timely access to earth system science data and strong international scientific partnerships. To that end, the Unidata Program at the University Corporation for Atmospheric Research has developed a growing portfolio of international outreach activities, conducted in close collaboration with academic, research and operational institutions on several continents. The overarching goals of Unidata's international activities include: - democratization of access-to and use-of data that describe the dynamic earth system - building capacity and empowering geoscientists and educators worldwide - strengthening international science partnerships for exchanging knowledge and expertise - effectuating sustainable cultural changes that recognize the benefits of data sharing, and - helping to build regional and global communities around specific geoscientific themes Using an Internet-based data sharing network, Unidata has made great strides in establishing the underpinnings of a worldwide data sharing network. To date, over 160 institutions of higher education worldwide are participating in this data sharing effort. The Internet Data Distribution (IDD) system, as it is known, was originally developed for sharing mostly atmospheric science data among U.S. institutions. It has now been extended beyond North America into a system of interconnected regional data networks encompassing Latin America, the Caribbean, Antarctica, Asia, Europe, and most recently Africa. The adoption of the IDD concept in Brazil has been so successful that Brazil now ranks second behind the U. S. in the number of institutions participating in their own regionally customized and managed data sharing network, which is dubbed the IDD-Brazil. Another noteworthy data distribution network, Antarctic IDD, is leveraging the IDD system for the benefit of the Antarctic meteorological research community. The availability of observations from polar areas is especially crucial for documenting the nature and extent of climate change, for those are the very regions that are projected to experience the most significant warming in climate simulations and as such most vulnerable from an Earth system science perspective. The democratizing and transformative effects of access to data in atmospheric science education and research cannot be overstated. A critical component of successful scientific inquiry includes learning how to collect, process, analyze, and integrate data from myriad sources, and geoscience education is uniquely suited in making science relevant by drawing connections between the dynamic Earth system and societal impacts. Continued collaborations that emerge from such data sharing efforts will result in greater understanding of a range of geoscientific problems including advances in climate change and hydrologic sciences, and weather and El Nino predictions. Moreover, they will provide a richer analysis of the evolving state of the planet. An overview of Unidata's international data sharing activities that are resulting in an organic growth of the Unidata community and increased partnership for sharing knowledge and experience will be presented.

Application description and policy model in collaborative environment for sharing of information on epidemiological and clinical research data sets.

PubMed

de Carvalho, Elias César Araujo; Batilana, Adelia Portero; Simkins, Julie; Martins, Henrique; Shah, Jatin; Rajgor, Dimple; Shah, Anand; Rockart, Scott; Pietrobon, Ricardo

2010-02-19

Sharing of epidemiological and clinical data sets among researchers is poor at best, in detriment of science and community at large. The purpose of this paper is therefore to (1) describe a novel Web application designed to share information on study data sets focusing on epidemiological clinical research in a collaborative environment and (2) create a policy model placing this collaborative environment into the current scientific social context. The Database of Databases application was developed based on feedback from epidemiologists and clinical researchers requiring a Web-based platform that would allow for sharing of information about epidemiological and clinical study data sets in a collaborative environment. This platform should ensure that researchers can modify the information. A Model-based predictions of number of publications and funding resulting from combinations of different policy implementation strategies (for metadata and data sharing) were generated using System Dynamics modeling. The application allows researchers to easily upload information about clinical study data sets, which is searchable and modifiable by other users in a wiki environment. All modifications are filtered by the database principal investigator in order to maintain quality control. The application has been extensively tested and currently contains 130 clinical study data sets from the United States, Australia, China and Singapore. Model results indicated that any policy implementation would be better than the current strategy, that metadata sharing is better than data-sharing, and that combined policies achieve the best results in terms of publications. Based on our empirical observations and resulting model, the social network environment surrounding the application can assist epidemiologists and clinical researchers contribute and search for metadata in a collaborative environment, thus potentially facilitating collaboration efforts among research communities distributed around the globe.

Bed sharing among mother-infant pairs in Klang district, Peninsular Malaysia and its relationship to breast-feeding.

PubMed

Tan, Kok Leong

2009-10-01

The aim of the study was to determine the prevalence of mother-infant bed sharing in Klang district, Peninsular Malaysia and to identify factors associated with bed sharing. This was a cross-sectional study involving 682 mother-infant pairs with infants up to 6 months attending government clinics in Klang district, Peninsular Malaysia. Data were collected by face-to-face interview using a pretested structured questionnaire for a 4-month period in 2006. Data regarding maternal, paternal, obstetric, infant, occupancy, breast-feeding characteristics, and bed-sharing practice were collected. Data on bed sharing were based on practice in the past 1-month period. Bed sharing was defined as an infant sharing a bed with mother, and infant must be within arms reach from the mother, whereas a bed was defined as either a sleeping mattress placed on a bed frame or placed on the floor. The prevalence of bed sharing was estimated. Relationship and magnitude of association between independent factors and bed sharing were examined using odds ratio and 95% confidence interval. Logistic regression analysis was used to control for confounding factors. The prevalence of bed sharing among mothers with infants aged between 1 and 6 months was 73.5% (95% confidence interval: 70.0-76.7). In multivariate analysis, urban/rural differences, mothers' ethnicity, occupation, family income, husbands' support on bed sharing, number of children younger than 12 years staying in the house, and breast-feeding were associated with bed sharing. These factors need to be considered in analyzing the overall risks and benefits of bed sharing, paying attention to breastfeeding practices.

Maritime domain awareness community of interest net centric information sharing

NASA Astrophysics Data System (ADS)

Andress, Mark; Freeman, Brian; Rhiddlehover, Trey; Shea, John

2007-04-01

This paper highlights the approach taken by the Maritime Domain Awareness (MDA) Community of Interest (COI) in establishing an approach to data sharing that seeks to overcome many of the obstacles to sharing both within the federal government and with international and private sector partners. The approach uses the DOD Net Centric Data Strategy employed through Net Centric Enterprise Services (NCES) Service Oriented Architecture (SOA) foundation provided by Defense Information Systems Agency (DISA), but is unique in that the community is made up of more than just Defense agencies. For the first pilot project, the MDA COI demonstrated how four agencies from DOD, the Intelligence Community, Department of Homeland Security (DHS), and Department of Transportation (DOT) could share Automatic Identification System (AIS) data in a common format using shared enterprise service components.

Anonymizing patient genomic data for public sharing association studies.

PubMed

Fernandez-Lozano, Carlos; Lopez-Campos, Guillermo; Seoane, Jose A; Lopez-Alonso, Victoria; Dorado, Julian; Martín-Sanchez, Fernando; Pazos, Alejandro

2013-01-01

The development of personalized medicine is tightly linked with the correct exploitation of molecular data, especially those associated with the genome sequence along with these use of genomic data there is an increasing demand to share these data for research purposes. Transition of clinical data to research is based in the anonymization of these data so the patient cannot be identified, the use of genomic data poses a great challenge because its nature of identifying data. In this work we have analyzed current methods for genome anonymization and propose a one way encryption method that may enable the process of genomic data sharing accessing only to certain regions of genomes for research purposes.

Memory Network For Distributed Data Processors

NASA Technical Reports Server (NTRS)

Bolen, David; Jensen, Dean; Millard, ED; Robinson, Dave; Scanlon, George

1992-01-01

Universal Memory Network (UMN) is modular, digital data-communication system enabling computers with differing bus architectures to share 32-bit-wide data between locations up to 3 km apart with less than one millisecond of latency. Makes it possible to design sophisticated real-time and near-real-time data-processing systems without data-transfer "bottlenecks". This enterprise network permits transmission of volume of data equivalent to an encyclopedia each second. Facilities benefiting from Universal Memory Network include telemetry stations, simulation facilities, power-plants, and large laboratories or any facility sharing very large volumes of data. Main hub of UMN is reflection center including smaller hubs called Shared Memory Interfaces.

Network Information Management Subsystem

NASA Technical Reports Server (NTRS)

Chatburn, C. C.

1985-01-01

The Deep Space Network is implementing a distributed data base management system in which the data are shared among several applications and the host machines are not totally dedicated to a particular application. Since the data and resources are to be shared, the equipment must be operated carefully so that the resources are shared equitably. The current status of the project is discussed and policies, roles, and guidelines are recommended for the organizations involved in the project.

FORCEnet Net Centric Architecture - A Standards View

DTIC Science & Technology

2006-06-01

SHARED SERVICES NETWORKING/COMMUNICATIONS STORAGE COMPUTING PLATFORM DATA INTERCHANGE/INTEGRATION DATA MANAGEMENT APPLICATION...R V I C E P L A T F O R M S E R V I C E F R A M E W O R K USER-FACING SERVICES SHARED SERVICES NETWORKING/COMMUNICATIONS STORAGE COMPUTING PLATFORM...E F R A M E W O R K USER-FACING SERVICES SHARED SERVICES NETWORKING/COMMUNICATIONS STORAGE COMPUTING PLATFORM DATA INTERCHANGE/INTEGRATION

To share or not to share: Drivers and barriers for sharing data via online amateur weather networks

NASA Astrophysics Data System (ADS)

Gharesifard, Mohammad; Wehn, Uta

2016-04-01

Increasing attention is being paid to the importance and potential of crowd-sourced data to complement current environmental data-streams (i.e. in-situ observations and RS data). In parallel, the diffusion of Information Communication Technologies (ICTs) that are interactive and easy to use have provided a way forward in facing extreme climatic events and the threatening hazards resulting from those. The combination of these two trends is referred to as ICT-enabled 'citizen observatories' of the environment. Nevertheless, the success of these citizen observatories hinges on the continued involvement of citizens as central actors of these initiatives. Developing strategies to (further) engage citizens requires in-depth understanding of the behavioral determinants that encourage or impede individuals to collect and share environment-related data. This paper takes the case of citizen-sensed weather data using Personal Weather Stations (PWSs) and looks at the drivers and barriers for sharing such data via online amateur weather networks. This is done employing a behavioral science lens that considers data sharing a decision and systematically investigates the influential factors that affect this decision. The analysis and findings are based on qualitative empirical research carried out in the Netherlands, United Kingdom and Italy. Subsequently, a model was developed that depicts the main drivers and barriers for citizen participation in weather observatories. This resulting model can be utilized as a tool to develop strategies for further enhancing ICT-enabled citizen participation in climatic observations and, consequently, in environmental management.

Unbreakable distributed storage with quantum key distribution network and password-authenticated secret sharing

PubMed Central

Fujiwara, M.; Waseda, A.; Nojima, R.; Moriai, S.; Ogata, W.; Sasaki, M.

2016-01-01

Distributed storage plays an essential role in realizing robust and secure data storage in a network over long periods of time. A distributed storage system consists of a data owner machine, multiple storage servers and channels to link them. In such a system, secret sharing scheme is widely adopted, in which secret data are split into multiple pieces and stored in each server. To reconstruct them, the data owner should gather plural pieces. Shamir’s (k, n)-threshold scheme, in which the data are split into n pieces (shares) for storage and at least k pieces of them must be gathered for reconstruction, furnishes information theoretic security, that is, even if attackers could collect shares of less than the threshold k, they cannot get any information about the data, even with unlimited computing power. Behind this scenario, however, assumed is that data transmission and authentication must be perfectly secure, which is not trivial in practice. Here we propose a totally information theoretically secure distributed storage system based on a user-friendly single-password-authenticated secret sharing scheme and secure transmission using quantum key distribution, and demonstrate it in the Tokyo metropolitan area (≤90 km). PMID:27363566

Unbreakable distributed storage with quantum key distribution network and password-authenticated secret sharing.

PubMed

Fujiwara, M; Waseda, A; Nojima, R; Moriai, S; Ogata, W; Sasaki, M

2016-07-01

Distributed storage plays an essential role in realizing robust and secure data storage in a network over long periods of time. A distributed storage system consists of a data owner machine, multiple storage servers and channels to link them. In such a system, secret sharing scheme is widely adopted, in which secret data are split into multiple pieces and stored in each server. To reconstruct them, the data owner should gather plural pieces. Shamir's (k, n)-threshold scheme, in which the data are split into n pieces (shares) for storage and at least k pieces of them must be gathered for reconstruction, furnishes information theoretic security, that is, even if attackers could collect shares of less than the threshold k, they cannot get any information about the data, even with unlimited computing power. Behind this scenario, however, assumed is that data transmission and authentication must be perfectly secure, which is not trivial in practice. Here we propose a totally information theoretically secure distributed storage system based on a user-friendly single-password-authenticated secret sharing scheme and secure transmission using quantum key distribution, and demonstrate it in the Tokyo metropolitan area (≤90 km).

Shared address collectives using counter mechanisms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blocksome, Michael; Dozsa, Gabor; Gooding, Thomas M

A shared address space on a compute node stores data received from a network and data to transmit to the network. The shared address space includes an application buffer that can be directly operated upon by a plurality of processes, for instance, running on different cores on the compute node. A shared counter is used for one or more of signaling arrival of the data across the plurality of processes running on the compute node, signaling completion of an operation performed by one or more of the plurality of processes, obtaining reservation slots by one or more of the pluralitymore » of processes, or combinations thereof.« less

Alternative Fuels Data Center: Truck Stop Electrification Site Data

Science.gov Websites

Collection Methods Tools Printable Version Share this resource Send a link to Alternative Fuels Data Center: Truck Stop Electrification Site Data Collection Methods to someone by E-mail Share Alternative Fuels Data Center: Truck Stop Electrification Site Data Collection Methods on Facebook Tweet about

Facilitating a culture of responsible and effective sharing of cancer genome data.

PubMed

Siu, Lillian L; Lawler, Mark; Haussler, David; Knoppers, Bartha Maria; Lewin, Jeremy; Vis, Daniel J; Liao, Rachel G; Andre, Fabrice; Banks, Ian; Barrett, J Carl; Caldas, Carlos; Camargo, Anamaria Aranha; Fitzgerald, Rebecca C; Mao, Mao; Mattison, John E; Pao, William; Sellers, William R; Sullivan, Patrick; Teh, Bin Tean; Ward, Robyn L; ZenKlusen, Jean Claude; Sawyers, Charles L; Voest, Emile E

2016-05-05

Rapid and affordable tumor molecular profiling has led to an explosion of clinical and genomic data poised to enhance the diagnosis, prognostication and treatment of cancer. A critical point has now been reached at which the analysis and storage of annotated clinical and genomic information in unconnected silos will stall the advancement of precision cancer care. Information systems must be harmonized to overcome the multiple technical and logistical barriers to data sharing. Against this backdrop, the Global Alliance for Genomic Health (GA4GH) was established in 2013 to create a common framework that enables responsible, voluntary and secure sharing of clinical and genomic data. This Perspective from the GA4GH Clinical Working Group Cancer Task Team highlights the data-aggregation challenges faced by the field, suggests potential collaborative solutions and describes how GA4GH can catalyze a harmonized data-sharing culture.

Do open access data policies inhibit innovation?

USGS Publications Warehouse

Katzner, Todd E.

2015-01-01

There has been a great deal of attention paid recently to the idea of data sharing (Van Noorden 2014, Beardsley 2015, Nature Publishing Group2015, www.copdess.com). However, the vast majority of these arguments are in agreement and present as fait accompli the idea that data are a public good and that therefore, once published, they should become open access. In fact, although there are many good reasons for data sharing, there also are a number of cogent and coherent cases to be made against open-access policies (e.g., Fenichel and Skelly 2015). The goal of this piece is not to debate the relevance or accuracy of the points made in favor of data sharing but to elevate the discussion by pointing out key problems with open-access policies and to identify central issues that, if solved, will enhance the utility of data sharing to science and society.

SCSODC: Integrating Ocean Data for Visualization Sharing and Application

NASA Astrophysics Data System (ADS)

Xu, C.; Li, S.; Wang, D.; Xie, Q.

2014-02-01

The South China Sea Ocean Data Center (SCSODC) was founded in 2010 in order to improve collecting and managing of ocean data of the South China Sea Institute of Oceanology (SCSIO). The mission of SCSODC is to ensure the long term scientific stewardship of ocean data, information and products - collected through research groups, monitoring stations and observation cruises - and to facilitate the efficient use and distribution to possible users. However, data sharing and applications were limited due to the characteristics of distribution and heterogeneity that made it difficult to integrate the data. To surmount those difficulties, the Data Sharing System has been developed by the SCSODC using the most appropriate information management and information technology. The Data Sharing System uses open standards and tools to promote the capability to integrate ocean data and to interact with other data portals or users and includes a full range of processes such as data discovery, evaluation and access combining C/S and B/S mode. It provides a visualized management interface for the data managers and a transparent and seamless data access and application environment for users. Users are allowed to access data using the client software and to access interactive visualization application interface via a web browser. The architecture, key technologies and functionality of the system are discussed briefly in this paper. It is shown that the system of SCSODC is able to implement web visualization sharing and seamless access to ocean data in a distributed and heterogeneous environment.

Genomic Data Commons | Office of Cancer Genomics

Cancer.gov

The NCI’s Center for Cancer Genomics launches the Genomic Data Commons (GDC), a unified data sharing platform for the cancer research community. The mission of the GDC is to enable data sharing across the entire cancer research community, to ultimately support precision medicine in oncology.

Armenian Virtual Observatory: Services and Data Sharing

NASA Astrophysics Data System (ADS)

Knyazyan, A. V.; Astsatryan, H. V.; Mickaelian, A. M.

2016-06-01

The main aim of this article is to introduce the data management and services of the Armenian Virtual Observatory (ArVO), which consists of user friendly data management mechanisms, a new and productive cross-correlation service, and data sharing API based on international standards and protocols.

Minnesota Department of Transportation (Mn/DOT) cadastral and right of way data sharing pilot project : phase 1 and phase 2 summary report.

DOT National Transportation Integrated Search

2007-12-10

The Cadastral and Right of Way Data Sharing Pilot Project is divided into three phases: Phase 1 Identify Information to Share, Phase 2 Information Collection, Phase 3 Web-based Information Access and Transfer. The Phase 1 and Phase 2 Summary Report d...

Generating community-built tools for data sharing and analysis in environmental networks

USGS Publications Warehouse

Read, Jordan S.; Gries, Corinna; Read, Emily K.; Klug, Jennifer; Hanson, Paul C.; Hipsey, Matthew R.; Jennings, Eleanor; O'Reilley, Catherine; Winslow, Luke A.; Pierson, Don; McBride, Christopher G.; Hamilton, David

2016-01-01

Rapid data growth in many environmental sectors has necessitated tools to manage and analyze these data. The development of tools often lags behind the proliferation of data, however, which may slow exploratory opportunities and scientific progress. The Global Lake Ecological Observatory Network (GLEON) collaborative model supports an efficient and comprehensive data–analysis–insight life cycle, including implementations of data quality control checks, statistical calculations/derivations, models, and data visualizations. These tools are community-built and openly shared. We discuss the network structure that enables tool development and a culture of sharing, leading to optimized output from limited resources. Specifically, data sharing and a flat collaborative structure encourage the development of tools that enable scientific insights from these data. Here we provide a cross-section of scientific advances derived from global-scale analyses in GLEON. We document enhancements to science capabilities made possible by the development of analytical tools and highlight opportunities to expand this framework to benefit other environmental networks.

A Secure and Efficient Audit Mechanism for Dynamic Shared Data in Cloud Storage

PubMed Central

2014-01-01

With popularization of cloud services, multiple users easily share and update their data through cloud storage. For data integrity and consistency in the cloud storage, the audit mechanisms were proposed. However, existing approaches have some security vulnerabilities and require a lot of computational overheads. This paper proposes a secure and efficient audit mechanism for dynamic shared data in cloud storage. The proposed scheme prevents a malicious cloud service provider from deceiving an auditor. Moreover, it devises a new index table management method and reduces the auditing cost by employing less complex operations. We prove the resistance against some attacks and show less computation cost and shorter time for auditing when compared with conventional approaches. The results present that the proposed scheme is secure and efficient for cloud storage services managing dynamic shared data. PMID:24959630

A secure and efficient audit mechanism for dynamic shared data in cloud storage.

PubMed

Kwon, Ohmin; Koo, Dongyoung; Shin, Yongjoo; Yoon, Hyunsoo

2014-01-01

With popularization of cloud services, multiple users easily share and update their data through cloud storage. For data integrity and consistency in the cloud storage, the audit mechanisms were proposed. However, existing approaches have some security vulnerabilities and require a lot of computational overheads. This paper proposes a secure and efficient audit mechanism for dynamic shared data in cloud storage. The proposed scheme prevents a malicious cloud service provider from deceiving an auditor. Moreover, it devises a new index table management method and reduces the auditing cost by employing less complex operations. We prove the resistance against some attacks and show less computation cost and shorter time for auditing when compared with conventional approaches. The results present that the proposed scheme is secure and efficient for cloud storage services managing dynamic shared data.

Why is data sharing in collaborative natural resource efforts so hard and what can we do to improve it?

PubMed

Volk, Carol J; Lucero, Yasmin; Barnas, Katie

2014-05-01

Increasingly, research and management in natural resource science rely on very large datasets compiled from multiple sources. While it is generally good to have more data, utilizing large, complex datasets has introduced challenges in data sharing, especially for collaborating researchers in disparate locations ("distributed research teams"). We surveyed natural resource scientists about common data-sharing problems. The major issues identified by our survey respondents (n = 118) when providing data were lack of clarity in the data request (including format of data requested). When receiving data, survey respondents reported various insufficiencies in documentation describing the data (e.g., no data collection description/no protocol, data aggregated, or summarized without explanation). Since metadata, or "information about the data," is a central obstacle in efficient data handling, we suggest documenting metadata through data dictionaries, protocols, read-me files, explicit null value documentation, and process metadata as essential to any large-scale research program. We advocate for all researchers, but especially those involved in distributed teams to alleviate these problems with the use of several readily available communication strategies including the use of organizational charts to define roles, data flow diagrams to outline procedures and timelines, and data update cycles to guide data-handling expectations. In particular, we argue that distributed research teams magnify data-sharing challenges making data management training even more crucial for natural resource scientists. If natural resource scientists fail to overcome communication and metadata documentation issues, then negative data-sharing experiences will likely continue to undermine the success of many large-scale collaborative projects.

Why is Data Sharing in Collaborative Natural Resource Efforts so Hard and What can We Do to Improve it?

NASA Astrophysics Data System (ADS)

Volk, Carol J.; Lucero, Yasmin; Barnas, Katie

2014-05-01

Increasingly, research and management in natural resource science rely on very large datasets compiled from multiple sources. While it is generally good to have more data, utilizing large, complex datasets has introduced challenges in data sharing, especially for collaborating researchers in disparate locations ("distributed research teams"). We surveyed natural resource scientists about common data-sharing problems. The major issues identified by our survey respondents ( n = 118) when providing data were lack of clarity in the data request (including format of data requested). When receiving data, survey respondents reported various insufficiencies in documentation describing the data (e.g., no data collection description/no protocol, data aggregated, or summarized without explanation). Since metadata, or "information about the data," is a central obstacle in efficient data handling, we suggest documenting metadata through data dictionaries, protocols, read-me files, explicit null value documentation, and process metadata as essential to any large-scale research program. We advocate for all researchers, but especially those involved in distributed teams to alleviate these problems with the use of several readily available communication strategies including the use of organizational charts to define roles, data flow diagrams to outline procedures and timelines, and data update cycles to guide data-handling expectations. In particular, we argue that distributed research teams magnify data-sharing challenges making data management training even more crucial for natural resource scientists. If natural resource scientists fail to overcome communication and metadata documentation issues, then negative data-sharing experiences will likely continue to undermine the success of many large-scale collaborative projects.

SHARE: system design and case studies for statistical health information release

PubMed Central

Gardner, James; Xiong, Li; Xiao, Yonghui; Gao, Jingjing; Post, Andrew R; Jiang, Xiaoqian; Ohno-Machado, Lucila

2013-01-01

Objectives We present SHARE, a new system for statistical health information release with differential privacy. We present two case studies that evaluate the software on real medical datasets and demonstrate the feasibility and utility of applying the differential privacy framework on biomedical data. Materials and Methods SHARE releases statistical information in electronic health records with differential privacy, a strong privacy framework for statistical data release. It includes a number of state-of-the-art methods for releasing multidimensional histograms and longitudinal patterns. We performed a variety of experiments on two real datasets, the surveillance, epidemiology and end results (SEER) breast cancer dataset and the Emory electronic medical record (EeMR) dataset, to demonstrate the feasibility and utility of SHARE. Results Experimental results indicate that SHARE can deal with heterogeneous data present in medical data, and that the released statistics are useful. The Kullback–Leibler divergence between the released multidimensional histograms and the original data distribution is below 0.5 and 0.01 for seven-dimensional and three-dimensional data cubes generated from the SEER dataset, respectively. The relative error for longitudinal pattern queries on the EeMR dataset varies between 0 and 0.3. While the results are promising, they also suggest that challenges remain in applying statistical data release using the differential privacy framework for higher dimensional data. Conclusions SHARE is one of the first systems to provide a mechanism for custodians to release differentially private aggregate statistics for a variety of use cases in the medical domain. This proof-of-concept system is intended to be applied to large-scale medical data warehouses. PMID:23059729

A Game Theoretic Framework for Analyzing Re-Identification Risk

PubMed Central

Wan, Zhiyu; Vorobeychik, Yevgeniy; Xia, Weiyi; Clayton, Ellen Wright; Kantarcioglu, Murat; Ganta, Ranjit; Heatherly, Raymond; Malin, Bradley A.

2015-01-01

Given the potential wealth of insights in personal data the big databases can provide, many organizations aim to share data while protecting privacy by sharing de-identified data, but are concerned because various demonstrations show such data can be re-identified. Yet these investigations focus on how attacks can be perpetrated, not the likelihood they will be realized. This paper introduces a game theoretic framework that enables a publisher to balance re-identification risk with the value of sharing data, leveraging a natural assumption that a recipient only attempts re-identification if its potential gains outweigh the costs. We apply the framework to a real case study, where the value of the data to the publisher is the actual grant funding dollar amounts from a national sponsor and the re-identification gain of the recipient is the fine paid to a regulator for violation of federal privacy rules. There are three notable findings: 1) it is possible to achieve zero risk, in that the recipient never gains from re-identification, while sharing almost as much data as the optimal solution that allows for a small amount of risk; 2) the zero-risk solution enables sharing much more data than a commonly invoked de-identification policy of the U.S. Health Insurance Portability and Accountability Act (HIPAA); and 3) a sensitivity analysis demonstrates these findings are robust to order-of-magnitude changes in player losses and gains. In combination, these findings provide support that such a framework can enable pragmatic policy decisions about de-identified data sharing. PMID:25807380

Sharing data for public health research by members of an international online diabetes social network.

PubMed

Weitzman, Elissa R; Adida, Ben; Kelemen, Skyler; Mandl, Kenneth D

2011-04-27

Surveillance and response to diabetes may be accelerated through engaging online diabetes social networks (SNs) in consented research. We tested the willingness of an online diabetes community to share data for public health research by providing members with a privacy-preserving social networking software application for rapid temporal-geographic surveillance of glycemic control. SN-mediated collection of cross-sectional, member-reported data from an international online diabetes SN entered into a software application we made available in a "Facebook-like" environment to enable reporting, charting and optional sharing of recent hemoglobin A1c values through a geographic display. Self-enrollment by 17% (n = 1,136) of n = 6,500 active members representing 32 countries and 50 US states. Data were current with 83.1% of most recent A1c values reported obtained within the past 90 days. Sharing was high with 81.4% of users permitting data donation to the community display. 34.1% of users also displayed their A1cs on their SN profile page. Users selecting the most permissive sharing options had a lower average A1c (6.8%) than users not sharing with the community (7.1%, p = .038). 95% of users permitted re-contact. Unadjusted aggregate A1c reported by US users closely resembled aggregate 2007-2008 NHANES estimates (respectively, 6.9% and 6.9%, p = 0.85). Success within an early adopter community demonstrates that online SNs may comprise efficient platforms for bidirectional communication with and data acquisition from disease populations. Advancing this model for cohort and translational science and for use as a complementary surveillance approach will require understanding of inherent selection and publication (sharing) biases in the data and a technology model that supports autonomy, anonymity and privacy.

Design Considerations for a Web-based Database System of ELISpot Assay in Immunological Research

PubMed Central

Ma, Jingming; Mosmann, Tim; Wu, Hulin

2005-01-01

The enzyme-linked immunospot (ELISpot) assay has been a primary means in immunological researches (such as HIV-specific T cell response). Due to huge amount of data involved in ELISpot assay testing, the database system is needed for efficient data entry, easy retrieval, secure storage, and convenient data process. Besides, the NIH has recently issued a policy to promote the sharing of research data (see http://grants.nih.gov/grants/policy/data_sharing). The Web-based database system will be definitely benefit to data sharing among broad research communities. Here are some considerations for a database system of ELISpot assay (DBSEA). PMID:16779326

Issues in Big-Data Database Systems

DTIC Science & Technology

2014-06-01

Post, 18 August 2013. Berman, Jules K. (2013). Principles of Big Data: Preparing, Sharing, and Analyzing Complex Information. New York: Elsevier... Jules K. (2013). Principles of Big Data: Preparing, Sharing, and Analyzing Complex Information. New York: Elsevier. 261pp. Characterization of

Participants' recall and understanding of genomic research and large-scale data sharing.

PubMed

Robinson, Jill Oliver; Slashinski, Melody J; Wang, Tao; Hilsenbeck, Susan G; McGuire, Amy L

2013-10-01

As genomic researchers are urged to openly share generated sequence data with other researchers, it is important to examine the utility of informed consent documents and processes, particularly as these relate to participants' engagement with and recall of the information presented to them, their objective or subjective understanding of the key elements of genomic research (e.g., data sharing), as well as how these factors influence or mediate the decisions they make. We conducted a randomized trial of three experimental informed consent documents (ICDs) with participants (n = 229) being recruited to genomic research studies; each document afforded varying control over breadth of release of genetic information. Recall and understanding, their impact on data sharing decisions, and comfort in decision making were assessed in a follow-up structured interview. Over 25% did not remember signing an ICD to participate in a genomic study, and the majority (54%) could not correctly identify with whom they had agreed to share their genomic data. However, participants felt that they understood enough to make an informed decision, and lack of recall did not impact final data sharing decisions or satisfaction with participation. These findings raise questions about the types of information participants need in order to provide valid informed consent, and whether subjective understanding and comfort with decision making are sufficient to satisfy the ethical principle of respect for persons.

Network Computing Infrastructure to Share Tools and Data in Global Nuclear Energy Partnership

NASA Astrophysics Data System (ADS)

Kim, Guehee; Suzuki, Yoshio; Teshima, Naoya

CCSE/JAEA (Center for Computational Science and e-Systems/Japan Atomic Energy Agency) integrated a prototype system of a network computing infrastructure for sharing tools and data to support the U.S. and Japan collaboration in GNEP (Global Nuclear Energy Partnership). We focused on three technical issues to apply our information process infrastructure, which are accessibility, security, and usability. In designing the prototype system, we integrated and improved both network and Web technologies. For the accessibility issue, we adopted SSL-VPN (Security Socket Layer-Virtual Private Network) technology for the access beyond firewalls. For the security issue, we developed an authentication gateway based on the PKI (Public Key Infrastructure) authentication mechanism to strengthen the security. Also, we set fine access control policy to shared tools and data and used shared key based encryption method to protect tools and data against leakage to third parties. For the usability issue, we chose Web browsers as user interface and developed Web application to provide functions to support sharing tools and data. By using WebDAV (Web-based Distributed Authoring and Versioning) function, users can manipulate shared tools and data through the Windows-like folder environment. We implemented the prototype system in Grid infrastructure for atomic energy research: AEGIS (Atomic Energy Grid Infrastructure) developed by CCSE/JAEA. The prototype system was applied for the trial use in the first period of GNEP.

Factors Related to Public Health Data Sharing between Local and State Health Departments

PubMed Central

Vest, Joshua R; Issel, L Michele

2014-01-01

Objective Public health organizations increasingly face the need to be able to share data among themselves and ultimately with other providers. We examined what factors contribute to public health organizations’ data exchange capabilities. Data Sources National Association of County and City Health Officials’ 2008 National Profile of Local Health Departments survey was linked to the Association of State and Territorial Health Official’s 2007 Profile of State Public Health Survey. Study Design We conducted a cross-sectional analysis of organizational factors associated with gaps in data sharing between state health agencies (SHAs) and local health departments (LHDs) in the areas of childhood immunizations, vital records, and reportable conditions. Data Collection Based on reported information system (IS) capabilities, we created a binary variable that measured whether bidirectional data sharing was structurally possible between an LHD and its respective SHA. Principal Findings The proportion of LHDs experiencing a data sharing gap was 34.0 percent for immunizations, 69.8 percent for vital records, and 81.8 percent for reportable conditions. Increased SHA technological capacity and size reduced the odds of gaps. Conclusions Improving the IS capabilities of public health agencies may be the key to their remaining relevant in the currently evolving health care system. PMID:24359636

Solutions and debugging for data consistency in multiprocessors with noncoherent caches

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bernstein, D.; Mendelson, B.; Breternitz, M. Jr.

1995-02-01

We analyze two important problems that arise in shared-memory multiprocessor systems. The stale data problem involves ensuring that data items in local memory of individual processors are current, independent of writes done by other processors. False sharing occurs when two processors have copies of the same shared data block but update different portions of the block. The false sharing problem involves guaranteeing that subsequent writes are properly combined. In modern architectures these problems are usually solved in hardware, by exploiting mechanisms for hardware controlled cache consistency. This leads to more expensive and nonscalable designs. Therefore, we are concentrating on softwaremore » methods for ensuring cache consistency that would allow for affordable and scalable multiprocessing systems. Unfortunately, providing software control is nontrivial, both for the compiler writer and for the application programmer. For this reason we are developing a debugging environment that will facilitate the development of compiler-based techniques and will help the programmer to tune his or her application using explicit cache management mechanisms. We extend the notion of a race condition for IBM Shared Memory System POWER/4, taking into consideration its noncoherent caches, and propose techniques for detection of false sharing problems. Identification of the stale data problem is discussed as well, and solutions are suggested.« less

Shared Decision-Making for Nursing Practice: An Integrative Review.

PubMed

Truglio-Londrigan, Marie; Slyer, Jason T

2018-01-01

Shared decision-making has received national and international interest by providers, educators, researchers, and policy makers. The literature on shared decision-making is extensive, dealing with the individual components of shared decision-making rather than a comprehensive process. This view of shared decision-making leaves healthcare providers to wonder how to integrate shared decision-making into practice. To understand shared decision-making as a comprehensive process from the perspective of the patient and provider in all healthcare settings. An integrative review was conducted applying a systematic approach involving a literature search, data evaluation, and data analysis. The search included articles from PubMed, CINAHL, the Cochrane Central Register of Controlled Trials, and PsycINFO from 1970 through 2016. Articles included quantitative experimental and non-experimental designs, qualitative, and theoretical articles about shared decision-making between all healthcare providers and patients in all healthcare settings. Fifty-two papers were included in this integrative review. Three categories emerged from the synthesis: (a) communication/ relationship building; (b) working towards a shared decision; and (c) action for shared decision-making. Each major theme contained sub-themes represented in the proposed visual representation for shared decision-making. A comprehensive understanding of shared decision-making between the nurse and the patient was identified. A visual representation offers a guide that depicts shared decision-making as a process taking place during a healthcare encounter with implications for the continuation of shared decisions over time offering patients an opportunity to return to the nurse for reconsiderations of past shared decisions.

Securely and Flexibly Sharing a Biomedical Data Management System

PubMed Central

Wang, Fusheng; Hussels, Phillip; Liu, Peiya

2011-01-01

Biomedical database systems need not only to address the issues of managing complex data, but also to provide data security and access control to the system. These include not only system level security, but also instance level access control such as access of documents, schemas, or aggregation of information. The latter is becoming more important as multiple users can share a single scientific data management system to conduct their research, while data have to be protected before they are published or IP-protected. This problem is challenging as users’ needs for data security vary dramatically from one application to another, in terms of who to share with, what resources to be shared, and at what access level. We develop a comprehensive data access framework for a biomedical data management system SciPort. SciPort provides fine-grained multi-level space based access control of resources at not only object level (documents and schemas), but also space level (resources set aggregated in a hierarchy way). Furthermore, to simplify the management of users and privileges, customizable role-based user model is developed. The access control is implemented efficiently by integrating access privileges into the backend XML database, thus efficient queries are supported. The secure access approach we take makes it possible for multiple users to share the same biomedical data management system with flexible access management and high data security. PMID:21625285

Publish (Your Data) or (Let the Data) Perish! Why Not Publish Your Data Too?

ERIC Educational Resources Information Center

Wicherts, Jelte M.; Bakker, Marjan

2012-01-01

The authors argue that upon publication of a paper, the data should be made available through online archives or repositories. Reasons for not sharing data are discussed and contrasted with advantages of sharing, which include abiding by the scientific principle of openness, keeping the data for posterity, increasing one's impact, facilitation of…

EOS situational data shared service mechanism

NASA Astrophysics Data System (ADS)

Lv, L.; Xu, Q.; Lan, C. Z.; Shi, Q. S.; Lu, W. J.; Wu, W. Q.

2016-11-01

With the rapid development of aerospace and remote sensing technology, various high-resolution Earth Observation Systems (EOS) are widely used in economic, social, military and other fields and playing an increasingly prominent role in the construction of Digital Earth and national strategic planning. The normal operation of the system is the premise of high quality data acquisition. Compared with the ground observation mode, EOS itself and the surrounding environment are more complex, and its operation control mainly depends on all kinds of Space Situational Awareness (SSA) data acquisition and analysis. SSA data has more extensive sources, larger volume, stronger time-effectiveness and more complicated structure than traditional geographical spatial data. For effective data sharing and utilization, combined with the analysis of data types and structures, a SSA data sharing identity language SSDSML is designed based on the extensible mark-up language XML, which realizes a comprehensive description of satellites and their attributes, space environment, ground stations, etc. Then EOS situational data shared service mechanism is established and provides a powerful data support for the normal operation of the system.

Open Data in Global Environmental Research: The Belmont Forum’s Open Data Survey

PubMed Central

Schmidt, Birgit; Gemeinholzer, Birgit; Treloar, Andrew

2016-01-01

This paper presents the findings of the Belmont Forum’s survey on Open Data which targeted the global environmental research and data infrastructure community. It highlights users’ perceptions of the term “open data”, expectations of infrastructure functionalities, and barriers and enablers for the sharing of data. A wide range of good practice examples was pointed out by the respondents which demonstrates a substantial uptake of data sharing through e-infrastructures and a further need for enhancement and consolidation. Among all policy responses, funder policies seem to be the most important motivator. This supports the conclusion that stronger mandates will strengthen the case for data sharing. PMID:26771577

Representing Hydrologic Models as HydroShare Resources to Facilitate Model Sharing and Collaboration

NASA Astrophysics Data System (ADS)

Castronova, A. M.; Goodall, J. L.; Mbewe, P.

2013-12-01

The CUAHSI HydroShare project is a collaborative effort that aims to provide software for sharing data and models within the hydrologic science community. One of the early focuses of this work has been establishing metadata standards for describing models and model-related data as HydroShare resources. By leveraging this metadata definition, a prototype extension has been developed to create model resources that can be shared within the community using the HydroShare system. The extension uses a general model metadata definition to create resource objects, and was designed so that model-specific parsing routines can extract and populate metadata fields from model input and output files. The long term goal is to establish a library of supported models where, for each model, the system has the ability to extract key metadata fields automatically, thereby establishing standardized model metadata that will serve as the foundation for model sharing and collaboration within HydroShare. The Soil Water & Assessment Tool (SWAT) is used to demonstrate this concept through a case study application.

Implementation of a health data-sharing infrastructure across diverse primary care organizations.

PubMed

Cole, Allison M; Stephens, Kari A; Keppel, Gina A; Lin, Ching-Ping; Baldwin, Laura-Mae

2014-01-01

Practice-based research networks bring together academic researchers and primary care clinicians to conduct research that improves health outcomes in real-world settings. The Washington, Wyoming, Alaska, Montana, and Idaho region Practice and Research Network implemented a health data-sharing infrastructure across 9 clinics in 3 primary care organizations. Following implementation, we identified challenges and solutions. Challenges included working with diverse primary care organizations, adoption of health information data-sharing technology in a rapidly changing local and national landscape, and limited resources for implementation. Overarching solutions included working with a multidisciplinary academic implementation team, maintaining flexibility, and starting with an established network for primary care organizations. Approaches outlined may generalize to similar initiatives and facilitate adoption of health data sharing in other practice-based research networks.

Implementation of a Health Data-Sharing Infrastructure Across Diverse Primary Care Organizations

PubMed Central

Cole, Allison M.; Stephens, Kari A.; Keppel, Gina A.; Lin, Ching-Ping; Baldwin, Laura-Mae

2014-01-01

Practice-based research networks bring together academic researchers and primary care clinicians to conduct research that improves health outcomes in real-world settings. The Washington, Wyoming, Alaska, Montana, and Idaho region Practice and Research Network implemented a health data-sharing infrastructure across 9 clinics in 3 primary care organizations. Following implementation, we identified challenges and solutions. Challenges included working with diverse primary care organizations, adoption of health information data-sharing technology in a rapidly changing local and national landscape, and limited resources for implementation. Overarching solutions included working with a multidisciplinary academic implementation team, maintaining flexibility, and starting with an established network for primary care organizations. Approaches outlined may generalize to similar initiatives and facilitate adoption of health data sharing in other practice-based research networks. PMID:24594564

Alternative Fuels Data Center: About the Alternative Fuels Data Center

Science.gov Websites

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Sharing with More Caring: Coordinating and Improving the Ethical Governance of Data and Biomaterials Obtained from Children.

PubMed

Longstaff, Holly; Khramova, Vera; Portales-Casamar, Elodie; Illes, Judy

2015-01-01

Research on complex health conditions such as neurodevelopmental disorders increasingly relies on large-scale research and clinical studies that would benefit from data sharing initiatives. Organizations that share data stand to maximize the efficiency of invested research dollars, expedite research findings, minimize the burden on the patient community, and increase citation rates of publications associated with the data. This study examined ethics and governance information on websites of databases involving neurodevelopmental disorders to determine the availability of information on key factors crucial for comprehension of, and trust and participation in such initiatives. We identified relevant databases identified using online keyword searches. Two researchers reviewed each of the websites and identified thematic content using principles from grounded theory. The content for each organization was interrogated using the gap analysis method. Sixteen websites from data sharing organizations met our inclusion criteria. Information about types of data and tissues stored, data access requirements and procedures, and protections for confidentiality were significantly addressed by data sharing organizations. However, special considerations for minors (absent from 63%), controls to check if data and tissues are being submitted (absent from 81%), disaster recovery plans (absent from 81%), and discussions of incidental findings (absent from 88%) emerged as major gaps in thematic website content. When present, content pertaining to special considerations for youth, along with other ethics guidelines and requirements, were scattered throughout the websites or available only from associated documents accessed through live links. The complexities of sharing data acquired from children and adolescents will only increase with advances in genomic and neuro science. Our findings suggest that there is a need to improve the consistency, depth and accessibility of governance and policies on which these collaborations can lean specifically for vulnerable young populations.

Facilitating Secure Sharing of Personal Health Data in the Cloud.

PubMed

Thilakanathan, Danan; Calvo, Rafael A; Chen, Shiping; Nepal, Surya; Glozier, Nick

2016-05-27

Internet-based applications are providing new ways of promoting health and reducing the cost of care. Although data can be kept encrypted in servers, the user does not have the ability to decide whom the data are shared with. Technically this is linked to the problem of who owns the data encryption keys required to decrypt the data. Currently, cloud service providers, rather than users, have full rights to the key. In practical terms this makes the users lose full control over their data. Trust and uptake of these applications can be increased by allowing patients to feel in control of their data, generally stored in cloud-based services. This paper addresses this security challenge by providing the user a way of controlling encryption keys independently of the cloud service provider. We provide a secure and usable system that enables a patient to share health information with doctors and specialists. We contribute a secure protocol for patients to share their data with doctors and others on the cloud while keeping complete ownership. We developed a simple, stereotypical health application and carried out security tests, performance tests, and usability tests with both students and doctors (N=15). We developed the health application as an app for Android mobile phones. We carried out the usability tests on potential participants and medical professionals. Of 20 participants, 14 (70%) either agreed or strongly agreed that they felt safer using our system. Using mixed methods, we show that participants agreed that privacy and security of health data are important and that our system addresses these issues. We presented a security protocol that enables patients to securely share their eHealth data with doctors and nurses and developed a secure and usable system that enables patients to share mental health information with doctors.

Extending Engineering Practice Research with Shared Qualitative Data

ERIC Educational Resources Information Center

Trevelyan, James

2016-01-01

Research on engineering practice is scarce and sharing of qualitative research data can reduce the effort required for an aspiring researcher to obtain enough data from engineering workplaces to draw generalizable conclusions, both qualitative and quantitative. This paper describes how a large shareable qualitative data set on engineering…

On the evolving portfolio of community-standards and data sharing policies: turning challenges into new opportunities.

PubMed

Sansone, Susanna-Assunta; Rocca-Serra, Philippe

2012-07-12

There are thousands of biology databases with hundreds of terminologies, reporting guidelines, representations models, and exchange formats to help annotate, report, and share bioscience investigations. It is evident, however, that researchers and bioinformaticians struggle to navigate the various standards and to find the appropriate database to collect, manage, and share data. Further, policy makers, funders, and publishers lack sufficient information to formulate their guidelines. In this paper, we highlight a number of key issues that can be used to turn these challenges into new opportunities. It is time for all stakeholders to work together to reconcile cause and effect and make the data-sharing culture functional and efficient.

A Secret 3D Model Sharing Scheme with Reversible Data Hiding Based on Space Subdivision

NASA Astrophysics Data System (ADS)

Tsai, Yuan-Yu

2016-03-01

Secret sharing is a highly relevant research field, and its application to 2D images has been thoroughly studied. However, secret sharing schemes have not kept pace with the advances of 3D models. With the rapid development of 3D multimedia techniques, extending the application of secret sharing schemes to 3D models has become necessary. In this study, an innovative secret 3D model sharing scheme for point geometries based on space subdivision is proposed. Each point in the secret point geometry is first encoded into a series of integer values that fall within [0, p - 1], where p is a predefined prime number. The share values are derived by substituting the specified integer values for all coefficients of the sharing polynomial. The surface reconstruction and the sampling concepts are then integrated to derive a cover model with sufficient model complexity for each participant. Finally, each participant has a separate 3D stego model with embedded share values. Experimental results show that the proposed technique supports reversible data hiding and the share values have higher levels of privacy and improved robustness. This technique is simple and has proven to be a feasible secret 3D model sharing scheme.

Feasibility, Process, and Outcomes of Cardiovascular Clinical Trial Data Sharing: A Reproduction Analysis of the SMART-AF Trial.

PubMed

Gay, Hawkins C; Baldridge, Abigail S; Huffman, Mark D

2017-12-01

Data sharing is as an expanding initiative for enhancing trust in the clinical research enterprise. To evaluate the feasibility, process, and outcomes of a reproduction analysis of the THERMOCOOL SMARTTOUCH Catheter for the Treatment of Symptomatic Paroxysmal Atrial Fibrillation (SMART-AF) trial using shared clinical trial data. A reproduction analysis of the SMART-AF trial was performed using the data sets, data dictionary, case report file, and statistical analysis plan from the original trial accessed through the Yale Open Data Access Project using the SAS Clinical Trials Data Transparency platform. SMART-AF was a multicenter, single-arm trial evaluating the effectiveness and safety of an irrigated, contact force-sensing catheter for ablation of drug refractory, symptomatic paroxysmal atrial fibrillation in 172 participants recruited from 21 sites between June 2011 and December 2011. Analysis of the data was conducted between December 2016 and April 2017. Effectiveness outcomes included freedom from atrial arrhythmias after ablation and proportion of participants without any arrhythmia recurrence over the 12 months of follow-up after a 3-month blanking period. Safety outcomes included major adverse device- or procedure-related events. The SMART AF trial participants' mean age was 58.7 (10.8) years, and 72% were men. The time from initial proposal submission to final analysis was 11 months. Freedom from atrial arrhythmias at 12 months postprocedure was similar compared with the primary study report (74.0%; 95% CI, 66.0-82.0 vs 76.4%; 95% CI, 68.7-84.1). The reproduction analysis success rate was higher than the primary study report (65.8%; 95% CI 56.5-74.2 vs 75.6%; 95% CI, 67.2-82.5). Adverse events were minimal and similar between the 2 analyses, but contact force range or regression models could not be reproduced. The feasibility of a reproduction analysis of the SMART-AF trial was demonstrated through an academic data-sharing platform. Data sharing can be facilitated through incentivizing collaboration, sharing statistical code, and creating more decentralized data sharing platforms with fewer restrictions to data access.

Sharing and reuse of individual participant data from clinical trials: principles and recommendations.

PubMed

Ohmann, Christian; Banzi, Rita; Canham, Steve; Battaglia, Serena; Matei, Mihaela; Ariyo, Christopher; Becnel, Lauren; Bierer, Barbara; Bowers, Sarion; Clivio, Luca; Dias, Monica; Druml, Christiane; Faure, Hélène; Fenner, Martin; Galvez, Jose; Ghersi, Davina; Gluud, Christian; Groves, Trish; Houston, Paul; Karam, Ghassan; Kalra, Dipak; Knowles, Rachel L; Krleža-Jerić, Karmela; Kubiak, Christine; Kuchinke, Wolfgang; Kush, Rebecca; Lukkarinen, Ari; Marques, Pedro Silverio; Newbigging, Andrew; O'Callaghan, Jennifer; Ravaud, Philippe; Schlünder, Irene; Shanahan, Daniel; Sitter, Helmut; Spalding, Dylan; Tudur-Smith, Catrin; van Reusel, Peter; van Veen, Evert-Ben; Visser, Gerben Rienk; Wilson, Julia; Demotes-Mainard, Jacques

2017-12-14

We examined major issues associated with sharing of individual clinical trial data and developed a consensus document on providing access to individual participant data from clinical trials, using a broad interdisciplinary approach. This was a consensus-building process among the members of a multistakeholder task force, involving a wide range of experts (researchers, patient representatives, methodologists, information technology experts, and representatives from funders, infrastructures and standards development organisations). An independent facilitator supported the process using the nominal group technique. The consensus was reached in a series of three workshops held over 1 year, supported by exchange of documents and teleconferences within focused subgroups when needed. This work was set within the Horizon 2020-funded project CORBEL (Coordinated Research Infrastructures Building Enduring Life-science Services) and coordinated by the European Clinical Research Infrastructure Network. Thus, the focus was on non-commercial trials and the perspective mainly European. We developed principles and practical recommendations on how to share data from clinical trials. The task force reached consensus on 10 principles and 50 recommendations, representing the fundamental requirements of any framework used for the sharing of clinical trials data. The document covers the following main areas: making data sharing a reality (eg, cultural change, academic incentives, funding), consent for data sharing, protection of trial participants (eg, de-identification), data standards, rights, types and management of access (eg, data request and access models), data management and repositories, discoverability, and metadata. The adoption of the recommendations in this document would help to promote and support data sharing and reuse among researchers, adequately inform trial participants and protect their rights, and provide effective and efficient systems for preparing, storing and accessing data. The recommendations now need to be implemented and tested in practice. Further work needs to be done to integrate these proposals with those from other geographical areas and other academic domains. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Supporting the Maritime Information Dominance: Optimizing Tactical Network for Biometric Data Sharing in Maritime Interdiction Operations

DTIC Science & Technology

2015-03-01

information dominance in the maritime domain by optimizing tactical mobile ad hoc network (MANET) systems for wireless sharing of biometric data in maritime interdiction operations (MIO). Current methods for sharing biometric data in MIO are unnecessarily slow and do not leverage wireless networks at the tactical edge to maximize information dominance . Field experiments allow students to test wireless MANETs at the tactical edge. Analysis is focused on determining optimal MANET design and implementation. It considers various implementations with

From Rosalind Franklin to Barack Obama: Data Sharing Challenges and Solutions in Genomics and Personalised Medicine

PubMed Central

Lawler, Mark; Maughan, Tim

2017-01-01

The collection, storage and use of genomic and clinical data from patients and healthy individuals is a key component of personalised medicine enterprises such as the Precision Medicine Initiative, the Cancer Moonshot and the 100,000 Genomes Project. In order to maximise the value of this data, it is important to embed a culture within the scientific, medical and patient communities that supports the appropriate sharing of genomic and clinical information. However, this aspiration raises a number of ethical, legal and regulatory challenges that need to be addressed. The Global Alliance for Genomics and Health, a worldwide coalition of researchers, healthcare professionals, patients and industry partners, is developing innovative solutions to support the responsible and effective sharing of genomic and clinical data. This article identifies the challenges that a data sharing culture poses and highlights a series of practical solutions that will benefit patients, researchers and society. PMID:28517986

From Rosalind Franklin to Barack Obama: Data Sharing Challenges and Solutions in Genomics and Personalised Medicine.

PubMed

Lawler, Mark; Maughan, Tim

2017-04-01

The collection, storage and use of genomic and clinical data from patients and healthy individuals is a key component of personalised medicine enterprises such as the Precision Medicine Initiative, the Cancer Moonshot and the 100,000 Genomes Project. In order to maximise the value of this data, it is important to embed a culture within the scientific, medical and patient communities that supports the appropriate sharing of genomic and clinical information. However, this aspiration raises a number of ethical, legal and regulatory challenges that need to be addressed. The Global Alliance for Genomics and Health, a worldwide coalition of researchers, healthcare professionals, patients and industry partners, is developing innovative solutions to support the responsible and effective sharing of genomic and clinical data. This article identifies the challenges that a data sharing culture poses and highlights a series of practical solutions that will benefit patients, researchers and society.

Sharing Epigraphic Information as Linked Data

NASA Astrophysics Data System (ADS)

Álvarez, Fernando-Luis; García-Barriocanal, Elena; Gómez-Pantoja, Joaquín-L.

The diffusion of epigraphic data has evolved in the last years from printed catalogues to indexed digital databases shared through the Web. Recently, the open EpiDoc specifications have resulted in an XML-based schema for the interchange of ancient texts that uses XSLT to render typographic representations. However, these schemas and representation systems are still not providing a way to encode computational semantics and semantic relations between pieces of epigraphic data. This paper sketches an approach to bring these semantics into an EpiDoc based schema using the Ontology Web Language (OWL) and following the principles and methods of information sharing known as "linked data". The paper describes the general principles of the OWL mapping of the EpiDoc schema and how epigraphic data can be shared in RDF format via dereferenceable URIs that can be used to build advanced search, visualization and analysis systems.

Patient-controlled sharing of medical imaging data across unaffiliated healthcare organizations

PubMed Central

Ahn, David K; Unde, Bhagyashree; Gage, H Donald; Carr, J Jeffrey

2013-01-01

Background Current image sharing is carried out by manual transportation of CDs by patients or organization-coordinated sharing networks. The former places a significant burden on patients and providers. The latter faces challenges to patient privacy. Objective To allow healthcare providers efficient access to medical imaging data acquired at other unaffiliated healthcare facilities while ensuring strong protection of patient privacy and minimizing burden on patients, providers, and the information technology infrastructure. Methods An image sharing framework is described that involves patients as an integral part of, and with full control of, the image sharing process. Central to this framework is the Patient Controlled Access-key REgistry (PCARE) which manages the access keys issued by image source facilities. When digitally signed by patients, the access keys are used by any requesting facility to retrieve the associated imaging data from the source facility. A centralized patient portal, called a PCARE patient control portal, allows patients to manage all the access keys in PCARE. Results A prototype of the PCARE framework has been developed by extending open-source technology. The results for feasibility, performance, and user assessments are encouraging and demonstrate the benefits of patient-controlled image sharing. Discussion The PCARE framework is effective in many important clinical cases of image sharing and can be used to integrate organization-coordinated sharing networks. The same framework can also be used to realize a longitudinal virtual electronic health record. Conclusion The PCARE framework allows prior imaging data to be shared among unaffiliated healthcare facilities while protecting patient privacy with minimal burden on patients, providers, and infrastructure. A prototype has been implemented to demonstrate the feasibility and benefits of this approach. PMID:22886546

State of the practice on data access, sharing, and integration.

DOT National Transportation Integrated Search

2016-12-01

The purpose of this state-of-the-practice review was to lay both technical and institutional foundation for all aspects of the development of the Virtual Data Access Framework. The review focused on current data sharing and integration practices amon...

easyDAS: Automatic creation of DAS servers

PubMed Central

2011-01-01

Background The Distributed Annotation System (DAS) has proven to be a successful way to publish and share biological data. Although there are more than 750 active registered servers from around 50 organizations, setting up a DAS server comprises a fair amount of work, making it difficult for many research groups to share their biological annotations. Given the clear advantage that the generalized sharing of relevant biological data is for the research community it would be desirable to facilitate the sharing process. Results Here we present easyDAS, a web-based system enabling anyone to publish biological annotations with just some clicks. The system, available at http://www.ebi.ac.uk/panda-srv/easydas is capable of reading different standard data file formats, process the data and create a new publicly available DAS source in a completely automated way. The created sources are hosted on the EBI systems and can take advantage of its high storage capacity and network connection, freeing the data provider from any network management work. easyDAS is an open source project under the GNU LGPL license. Conclusions easyDAS is an automated DAS source creation system which can help many researchers in sharing their biological data, potentially increasing the amount of relevant biological data available to the scientific community. PMID:21244646

Minimum information required for a DMET experiment reporting.

PubMed

Kumuthini, Judit; Mbiyavanga, Mamana; Chimusa, Emile R; Pathak, Jyotishman; Somervuo, Panu; Van Schaik, Ron Hn; Dolzan, Vita; Mizzi, Clint; Kalideen, Kusha; Ramesar, Raj S; Macek, Milan; Patrinos, George P; Squassina, Alessio

2016-09-01

To provide pharmacogenomics reporting guidelines, the information and tools required for reporting to public omic databases. For effective DMET data interpretation, sharing, interoperability, reproducibility and reporting, we propose the Minimum Information required for a DMET Experiment (MIDE) reporting. MIDE provides reporting guidelines and describes the information required for reporting, data storage and data sharing in the form of XML. The MIDE guidelines will benefit the scientific community with pharmacogenomics experiments, including reporting pharmacogenomics data from other technology platforms, with the tools that will ease and automate the generation of such reports using the standardized MIDE XML schema, facilitating the sharing, dissemination, reanalysis of datasets through accessible and transparent pharmacogenomics data reporting.

The limits of sharing: an ethical analysis of the arguments for and against the sharing of databases and material banks.

PubMed

Smith, Elise

2011-11-01

In this article, I study the challenges that make database and material bank sharing difficult for many researchers. I assert that if sharing is prima facie ethical (a view that I will defend), then any practices that limit sharing require justification. I argue that: 1) data and material sharing is ethical for many stakeholders; 2) there are, however, certain reasonable limits to sharing; and 3) the rationale and validity of arguments for any limitations to sharing must be made transparent. I conclude by providing general recommendations for how to ethically share databases and material banks.

Alternative Fuels Data Center: Natural Gas

Science.gov Websites

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A Study to Determine the Most Popular Lifestyle Smartphone Applications and Willingness of the Public to Share Their Personal Data for Health Research.

PubMed

Chen, Juliana; Bauman, Adrian; Allman-Farinelli, Margaret

2016-08-01

Smartphone lifestyle applications (apps) and wearable fitness-tracking devices collect a wealth of data that could provide research insights to support prevention and treatment of obesity and chronic diseases. The aim of this study was to pilot a survey to explore patterns of behavioral tracking using smartphone lifestyle apps and individuals' willingness to share their app-generated data. A cross-sectional Web-based survey was conducted within a university setting. The 35-item survey asked participants about their self-tracking patterns; use of lifestyle apps and wearable devices; how their self-tracked health data could be useful to them; and any restrictions they would impose on sharing personal data. Responses were tabulated and analyzed for trends. The survey was completed by 101 participants. On average, 3.1 (standard deviation [SD] ±1.9) health and fitness apps were installed by current app users (n = 85), with MyFitnessPal, MapMyRun, Nike+, and Fitbit being most popular. Most participants were willing to share their personal health data for research (77%). Those who did not normally share their health-tracking data were more likely than sharers to be concerned about privacy (odds ratio [OR] = 5.93; 95% confidence interval [95% CI] = 2.09-16.78), as were those not identifying with the quantified-self movement compared with those who were (OR = 5.04; 95% CI = 1.64-15.50). Participants were generally willing to share personal data, thus increasing the potential for these data to inform public health research and for use in targeted personalized program and intervention development. Opportunities for partnerships between researchers and commercial app developers or industry could improve public health research and practice.

Data disclosure and data sharing in scientific research.

PubMed

Allison, J R; Cooper, W W

1992-01-01

Data sharing is examined for its bearing on (i) quality assurance and (ii) extensions of results in scientific research as well as (iii) part of a tradition of openness in science. It is suggested that sharing can be accomplished in a simple manner that is also sufficiently flexible to fit varying individual situations by asking authors of data dependent articles and grant proposals to footnote (a) whether they are willing to make their data available to others and, if so, (b) how the data may be accessed. Appendices report results from a survey of current policies and practices in professional societies and in Federal government fund granting agencies. Emphasis is on the social and management sciences.

Factors affecting willingness to share electronic health data among California consumers.

PubMed

Kim, Katherine K; Sankar, Pamela; Wilson, Machelle D; Haynes, Sarah C

2017-04-04

Robust technology infrastructure is needed to enable learning health care systems to improve quality, access, and cost. Such infrastructure relies on the trust and confidence of individuals to share their health data for healthcare and research. Few studies have addressed consumers' views on electronic data sharing and fewer still have explored the dual purposes of healthcare and research together. The objective of the study is to explore factors that affect consumers' willingness to share electronic health information for healthcare and research. This study involved a random-digit dial telephone survey of 800 adult Californians conducted in English and Spanish. Logistic regression was performed using backward selection to test for significant (p-value ≤ 0.05) associations of each explanatory variable with the outcome variable. The odds of consent for electronic data sharing for healthcare decreased as Likert scale ratings for EHR impact on privacy worsened, odds ratio (OR) = 0.74, 95% CI [0.60, 0.90]; security, OR = 0.80, 95% CI [0.66, 0.98]; and quality, OR = 0.59, 95% CI [0.46-0.75]. The odds of consent for sharing for research was greater for those who think EHR will improve research quality, OR = 11.26, 95% CI [4.13, 30.73]; those who value research benefit over privacy OR = 2.72, 95% CI [1.55, 4.78]; and those who value control over research benefit OR = 0.49, 95% CI [0.26, 0.94]. Consumers' choices about electronically sharing health information are affected by their attitudes toward EHRs as well as beliefs about research benefit and individual control. Design of person-centered interventions utilizing electronically collected health information, and policies regarding data sharing should address these values of importance to people. Understanding of these perspectives is critical for leveraging health data to support learning health care systems.

A prototype system for multilingual data discovery of International Long-Term Ecological Research (ILTER) Network data

Treesearch

Kristin Vanderbilt; John H. Porter; Sheng-Shan Lu; Nic Bertrand; David Blankman; Xuebing Guo; Honglin He; Don Henshaw; Karpjoo Jeong; Eun-Shik Kim; Chau-Chin Lin; Margaret O' Brien; Takeshi Osawa; Éamonn Ó Tuama; Wen Su; Haibo Yang

2017-01-01

Shared ecological data have the potential to revolutionize ecological research just as shared genetic sequence data have done for biological research. However, for ecological data to be useful, it must first be discoverable. A broad-scale research topic may require that a researcher be able to locate suitable data from a variety of global, regional and national data...

The Mason Water Data Information System (MWDIS): Enabling data sharing and discovery at George Mason University

NASA Astrophysics Data System (ADS)

Ferreira, C.; Da Silva, A. L.; Nunes, A.; Haddad, J.; Lawler, S.

2014-12-01

Enabling effective data use and re-use in scientific investigations relies heavily not only on data availability but also on efficient data sharing discovery. The CUAHSI led Hydrological Information Systems (HIS) and supporting products have paved the way to efficient data sharing and discovery in the hydrological sciences. Based on the CUAHSI-HIS framework concepts for hydrologic data sharing we developed a unique system devoted to the George Mason University scientific community to support university wide data sharing and discovery as well as real time data access for extreme events situational awareness. The internet-based system will provide an interface where the researchers will input data collected from the measurement stations and present them to the public in form of charts, tables, maps, and documents. Moreover, the system is developed in ASP.NET MVC 4 using as Database Management System, Microsoft SQL Server 2008 R2, and hosted by Amazon Web Services. Currently the system is supporting the Mason Watershed Project providing historical hydrological, atmospheric and water quality data for the campus watershed and real time flood conditions in the campus. The system is also a gateway for unprecedented data collection of hurricane storm surge hydrodynamics in coastal wetlands in the Chesapeake Bay providing not only access to historical data but recent storms such as Hurricane Arthur. Future research includes coupling the system to a real-time flood alert system on campus, and besides providing data on the World Wide Web, to foment and provide a venue for interdisciplinary collaboration within the water scientists in the region.

GeoSearch: a new virtual globe application for the submission, storage, and sharing of point-based ecological data

NASA Astrophysics Data System (ADS)

Cardille, J. A.; Gonzales, R.; Parrott, L.; Bai, J.

2009-12-01

How should researchers store and share data? For most of history, scientists with results and data to share have been mostly limited to books and journal articles. In recent decades, the advent of personal computers and shared data formats has made it feasible, though often cumbersome, to transfer data between individuals or among small groups. Meanwhile, the use of automatic samplers, simulation models, and other data-production techniques has increased greatly. The result is that there is more and more data to store, and a greater expectation that they will be available at the click of a button. In 10 or 20 years, will we still send emails to each other to learn about what data exist? The development and widespread familiarity with virtual globes like Google Earth and NASA WorldWind has created the potential, in just the last few years, to revolutionize the way we share data, search for and search through data, and understand the relationship between individual projects in research networks, where sharing and dissemination of knowledge is encouraged. For the last two years, we have been building the GeoSearch application, a cutting-edge online resource for the storage, sharing, search, and retrieval of data produced by research networks. Linking NASA’s WorldWind globe platform, the data browsing toolkit prefuse, and SQL databases, GeoSearch’s version 1.0 enables flexible searches and novel geovisualizations of large amounts of related scientific data. These data may be submitted to the database by individual researchers and processed by GeoSearch’s data parser. Ultimately, data from research groups gathered in a research network would be shared among users via the platform. Access is not limited to the scientists themselves; administrators can determine which data can be presented publicly and which require group membership. Under the auspices of the Canada’s Sustainable Forestry Management Network of Excellence, we have created a moderate-sized database of ecological measurements in forests; we expect to extend the approach to a Quebec lake research network encompassing decades of lake measurements. In this session, we will describe and present four related components of the new system: GeoSearch’s globe-based searching and display of scientific data; prefuse-based visualization of social connections among members of a scientific research network; geolocation of research projects using Google Spreadsheets, KML, and Google Earth/Maps; and collaborative construction of a geolocated database of research articles. Each component is designed to have applications for scientists themselves as well as the general public. Although each implementation is in its infancy, we believe they could be useful to other researcher networks.

Shared Decision-Making for Nursing Practice: An Integrative Review

PubMed Central

Truglio-Londrigan, Marie; Slyer, Jason T.

2018-01-01

Background: Shared decision-making has received national and international interest by providers, educators, researchers, and policy makers. The literature on shared decision-making is extensive, dealing with the individual components of shared decision-making rather than a comprehensive process. This view of shared decision-making leaves healthcare providers to wonder how to integrate shared decision-making into practice. Objective: To understand shared decision-making as a comprehensive process from the perspective of the patient and provider in all healthcare settings. Methods: An integrative review was conducted applying a systematic approach involving a literature search, data evaluation, and data analysis. The search included articles from PubMed, CINAHL, the Cochrane Central Register of Controlled Trials, and PsycINFO from 1970 through 2016. Articles included quantitative experimental and non-experimental designs, qualitative, and theoretical articles about shared decision-making between all healthcare providers and patients in all healthcare settings. Results: Fifty-two papers were included in this integrative review. Three categories emerged from the synthesis: (a) communication/ relationship building; (b) working towards a shared decision; and (c) action for shared decision-making. Each major theme contained sub-themes represented in the proposed visual representation for shared decision-making. Conclusion: A comprehensive understanding of shared decision-making between the nurse and the patient was identified. A visual representation offers a guide that depicts shared decision-making as a process taking place during a healthcare encounter with implications for the continuation of shared decisions over time offering patients an opportunity to return to the nurse for reconsiderations of past shared decisions. PMID:29456779

Genomic data-sharing: what will be our legacy?

PubMed Central

Callier, Shawneequa; Husain, Rajah; Simpson, Rachel

2014-01-01

Prior to 1974, the Tuskegee Syphilis experiments, expansive use of the HeLa cells, and other blatant instances of research abuse pervaded the medical research field. Ongoing challenges to informed consent, privacy and data-sharing will influence the stories that research participants today share with future generations. This has significant implications for the advancement of genomic science, and the public's perception of genomic research. PMID:24634673

Emerging Geospatial Sharing Technologies in Earth and Space Science Informatics

NASA Astrophysics Data System (ADS)

Singh, R.; Bermudez, L. E.

2013-12-01

Emerging Geospatial Sharing Technologies in Earth and Space Science Informatics The Open Geospatial Consortium (OGC) mission is to serve as a global forum for the collaboration of developers and users of spatial data products and services, and to advance the development of international standards for geospatial interoperability. The OGC coordinates with over 400 institutions in the development of geospatial standards. In the last years two main trends are making disruptions in geospatial applications: mobile and context sharing. People now have more and more mobile devices to support their work and personal life. Mobile devices are intermittently connected to the internet and have smaller computing capacity than a desktop computer. Based on this trend a new OGC file format standard called GeoPackage will enable greater geospatial data sharing on mobile devices. GeoPackage is perhaps best understood as the natural evolution of Shapefiles, which have been the predominant lightweight geodata sharing format for two decades. However the format is extremely limited. Four major shortcomings are that only vector points, lines, and polygons are supported; property names are constrained by the dBASE format; multiple files are required to encode a single data set; and multiple Shapefiles are required to encode multiple data sets. A more modern lingua franca for geospatial data is long overdue. GeoPackage fills this need with support for vector data, image tile matrices, and raster data. And it builds upon a database container - SQLite - that's self-contained, single-file, cross-platform, serverless, transactional, and open source. A GeoPackage, in essence, is a set of SQLite database tables whose content and layout is described in the candidate GeoPackage Implementation Specification available at https://portal.opengeospatial.org/files/?artifact_id=54838&version=1. The second trend is sharing client 'contexts'. When a user is looking into an article or a product on the web, they can easily share this information with colleagues or friends via an email that includes URLs (links to web resources) and attachments (inline data). In the case of geospatial information, a user would like to share a map created from different OGC sources, which may include for example, WMS and WFS links, and GML and KML annotations. The emerging OGC file format is called the OGC Web Services Context Document (OWS Context), which allows clients to reproduce a map previously created by someone else. Context sharing is important in a variety of domains, from emergency response, where fire, police and emergency medical personnel need to work off a common map, to multi-national military operations, where coalition forces need to share common data sources, but have cartographic displays in different languages and symbology sets. OWS Contexts can be written in XML (building upon the Atom Syndication Format) or JSON. This presentation will provide an introduction of GeoPackage and OWS Context and how they can be used to advance sharing of Earth and Space Science information.

Data Sharing to Improve Close Approach Monitoring and Safety of Flight

NASA Astrophysics Data System (ADS)

Chan, Joseph; DalBello, Richard; Hope, Dean; Wauthier, Pascal; Douglas, Tim; Inghram, Travis

2009-03-01

Individual satellite operators have done a good job of developing the internal protocols and procedures to ensure the safe operation of their fleets. However, data sharing among operators for close approach monitoring is conducted in an ad-hoc manner during relocations, and there is currently no standardized agreement among operators on the content, format, and distribution protocol for data sharing. Crowding in geostationary orbit, participation by new commercial actors, government interest in satellite constellations, and highly maneuverable spacecraft all suggest that satellite operators will need to begin a dialogue on standard communication protocols and procedure to improve situation awareness. We will give an overview of the current best practices among different operators for close approach monitoring and discuss the concept of an active data center to improve data sharing, conjunction monitoring, and avoidance among satellite operators. We will also report on the progress and lessons learned from a Data Center prototype conducted by several operators over a one year period.

30 CFR 280.73 - Will MMS share data and information with coastal States?

Code of Federal Regulations, 2011 CFR

2011-07-01

... coastal States? 280.73 Section 280.73 Mineral Resources BUREAU OF OCEAN ENERGY MANAGEMENT, REGULATION, AND... THE OUTER CONTINENTAL SHELF Data Requirements Protections § 280.73 Will MMS share data and information with coastal States? (a) We can disclose proprietary data, information, and samples submitted to us by...

Alternative Fuels Data Center: Ethanol Laws and Incentives

Science.gov Websites

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Wild Data: Collaborative E-Research and University Libraries

ERIC Educational Resources Information Center

Kennan, Mary Anne; Williamson, Kirsty; Johanson, Graeme

2012-01-01

The literature speaks of a "deluge" of scientific and research data and the importance of capturing and managing it for use beyond its original creating community, purpose, and time. Data value increases as it is interconnected, networked, shared, used, and re-used. This paper extends the conversation about data sharing to "wild…

Alternative Fuels Data Center: Electricity Laws and Incentives

Science.gov Websites

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Alternative Fuels Data Center: Vehicle Search

Science.gov Websites

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Alternative Fuels Data Center: Biodiesel Laws and Incentives

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Alternative Fuels Data Center: State Laws and Incentives

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Tracing the Potential Flow of Consumer Data: A Network Analysis of Prominent Health and Fitness Apps

PubMed Central

Held, Fabian P; Bero, Lisa A

2017-01-01

Background A great deal of consumer data, collected actively through consumer reporting or passively through sensors, is shared among apps. Developers increasingly allow their programs to communicate with other apps, sensors, and Web-based services, which are promoted as features to potential users. However, health apps also routinely pose risks related to information leaks, information manipulation, and loss of information. There has been less investigation into the kinds of user data that developers are likely to collect, and who might have access to it. Objective We sought to describe how consumer data generated from mobile health apps might be distributed and reused. We also aimed to outline risks to individual privacy and security presented by this potential for aggregating and combining user data across apps. Methods We purposively sampled prominent health and fitness apps available in the United States, Canada, and Australia Google Play and iTunes app stores in November 2015. Two independent coders extracted data from app promotional materials on app and developer characteristics, and the developer-reported collection and sharing of user data. We conducted a descriptive analysis of app, developer, and user data collection characteristics. Using structural equivalence analysis, we conducted a network analysis of sampled apps’ self-reported sharing of user-generated data. Results We included 297 unique apps published by 231 individual developers, which requested 58 different permissions (mean 7.95, SD 6.57). We grouped apps into 222 app families on the basis of shared ownership. Analysis of self-reported data sharing revealed a network of 359 app family nodes, with one connected central component of 210 app families (58.5%). Most (143/222, 64.4%) of the sampled app families did not report sharing any data and were therefore isolated from each other and from the core network. Fifteen app families assumed more central network positions as gatekeepers on the shortest paths that data would have to travel between other app families. Conclusions This cross-sectional analysis highlights the possibilities for user data collection and potential paths that data is able to travel among a sample of prominent health and fitness apps. While individual apps may not collect personally identifiable information, app families and the partners with which they share data may be able to aggregate consumer data, thus achieving a much more comprehensive picture of the individual consumer. The organizations behind the centrally connected app families represent diverse industries, including apparel manufacturers and social media platforms that are not traditionally involved in health or fitness. This analysis highlights the potential for anticipated and voluntary but also possibly unanticipated and involuntary sharing of user data, validating privacy and security concerns in mobile health. PMID:28659254

Axiope tools for data management and data sharing.

PubMed

Goddard, Nigel H; Cannon, Robert C; Howell, Fred W

2003-01-01

Many areas of biological research generate large volumes of very diverse data. Managing this data can be a difficult and time-consuming process, particularly in an academic environment where there are very limited resources for IT support staff such as database administrators. The most economical and efficient solutions are those that enable scientists with minimal IT expertise to control and operate their own desktop systems. Axiope provides one such solution, Catalyzer, which acts as flexible cataloging system for creating structured records describing digital resources. The user is able specify both the content and structure of the information included in the catalog. Information and resources can be shared by a variety of means, including automatically generated sets of web pages. Federation and integration of this information, where needed, is handled by Axiope's Mercat server. Where there is a need for standardization or compatibility of the structures usedby different researchers this canbe achieved later by applying user-defined mappings in Mercat. In this way, large-scale data sharing can be achieved without imposing unnecessary constraints or interfering with the way in which individual scientists choose to record and catalog their work. We summarize the key technical issues involved in scientific data management and data sharing, describe the main features and functionality of Axiope Catalyzer and Axiope Mercat, and discuss future directions and requirements for an information infrastructure to support large-scale data sharing and scientific collaboration.

Harnessing modern web application technology to create intuitive and efficient data visualization and sharing tools.

PubMed

Wood, Dylan; King, Margaret; Landis, Drew; Courtney, William; Wang, Runtang; Kelly, Ross; Turner, Jessica A; Calhoun, Vince D

2014-01-01

Neuroscientists increasingly need to work with big data in order to derive meaningful results in their field. Collecting, organizing and analyzing this data can be a major hurdle on the road to scientific discovery. This hurdle can be lowered using the same technologies that are currently revolutionizing the way that cultural and social media sites represent and share information with their users. Web application technologies and standards such as RESTful webservices, HTML5 and high-performance in-browser JavaScript engines are being utilized to vastly improve the way that the world accesses and shares information. The neuroscience community can also benefit tremendously from these technologies. We present here a web application that allows users to explore and request the complex datasets that need to be shared among the neuroimaging community. The COINS (Collaborative Informatics and Neuroimaging Suite) Data Exchange uses web application technologies to facilitate data sharing in three phases: Exploration, Request/Communication, and Download. This paper will focus on the first phase, and how intuitive exploration of large and complex datasets is achieved using a framework that centers around asynchronous client-server communication (AJAX) and also exposes a powerful API that can be utilized by other applications to explore available data. First opened to the neuroscience community in August 2012, the Data Exchange has already provided researchers with over 2500 GB of data.

Harnessing modern web application technology to create intuitive and efficient data visualization and sharing tools

PubMed Central

Wood, Dylan; King, Margaret; Landis, Drew; Courtney, William; Wang, Runtang; Kelly, Ross; Turner, Jessica A.; Calhoun, Vince D.

2014-01-01

Neuroscientists increasingly need to work with big data in order to derive meaningful results in their field. Collecting, organizing and analyzing this data can be a major hurdle on the road to scientific discovery. This hurdle can be lowered using the same technologies that are currently revolutionizing the way that cultural and social media sites represent and share information with their users. Web application technologies and standards such as RESTful webservices, HTML5 and high-performance in-browser JavaScript engines are being utilized to vastly improve the way that the world accesses and shares information. The neuroscience community can also benefit tremendously from these technologies. We present here a web application that allows users to explore and request the complex datasets that need to be shared among the neuroimaging community. The COINS (Collaborative Informatics and Neuroimaging Suite) Data Exchange uses web application technologies to facilitate data sharing in three phases: Exploration, Request/Communication, and Download. This paper will focus on the first phase, and how intuitive exploration of large and complex datasets is achieved using a framework that centers around asynchronous client-server communication (AJAX) and also exposes a powerful API that can be utilized by other applications to explore available data. First opened to the neuroscience community in August 2012, the Data Exchange has already provided researchers with over 2500 GB of data. PMID:25206330

Public Trust in Health Information Sharing: A Measure of System Trust.

PubMed

Platt, Jodyn E; Jacobson, Peter D; Kardia, Sharon L R

2018-04-01

To measure public trust in a health information sharing in a broadly defined health system (system trust), inclusive of health care, public health, and research; to identify individual characteristics that predict system trust; and to consider these findings in the context of national health initiatives (e.g., learning health systems and precision medicine) that will expand the scope of data sharing. Survey data (n = 1,011) were collected in February 2014. We constructed a composite index of four dimensions of system trust-competency, fidelity, integrity, and trustworthiness. The index was used in linear regression evaluating demographic and psychosocial predictors of system trust. Data were collected by GfK Custom using a nationally representative sample and analyzed in Stata 13.0. Our findings suggest the public's trust may not meet the needs of health systems as they enter an era of expanded data sharing. We found that a majority of the U.S. public does not trust the organizations that have health information and share it (i.e., the health system) in one or more dimensions. Together, demographic and psychosocial factors accounted for ~18 percent of the observed variability in system trust. Future research should consider additional predictors of system trust such as knowledge, attitudes, and beliefs to inform policies and practices for health data sharing. © Health Research and Educational Trust.

Reproducing Epidemiologic Research and Ensuring Transparency.

PubMed

Coughlin, Steven S

2017-08-15

Measures for ensuring that epidemiologic studies are reproducible include making data sets and software available to other researchers so they can verify published findings, conduct alternative analyses of the data, and check for statistical errors or programming errors. Recent developments related to the reproducibility and transparency of epidemiologic studies include the creation of a global platform for sharing data from clinical trials and the anticipated future extension of the global platform to non-clinical trial data. Government agencies and departments such as the US Department of Veterans Affairs Cooperative Studies Program have also enhanced their data repositories and data sharing resources. The Institute of Medicine and the International Committee of Medical Journal Editors released guidance on sharing clinical trial data. The US National Institutes of Health has updated their data-sharing policies. In this issue of the Journal, Shepherd et al. (Am J Epidemiol. 2017;186:387-392) outline a pragmatic approach for reproducible research with sensitive data for studies for which data cannot be shared because of legal or ethical restrictions. Their proposed quasi-reproducible approach facilitates the dissemination of statistical methods and codes to independent researchers. Both reproducibility and quasi-reproducibility can increase transparency for critical evaluation, further dissemination of study methods, and expedite the exchange of ideas among researchers. © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Dataworks for GNSS: Software for Supporting Data Sharing and Federation of Geodetic Networks

NASA Astrophysics Data System (ADS)

Boler, F. M.; Meertens, C. M.; Miller, M. M.; Wier, S.; Rost, M.; Matykiewicz, J.

2015-12-01

Continuously-operating Global Navigation Satellite System (GNSS) networks are increasingly being installed globally for a wide variety of science and societal applications. GNSS enables Earth science research in areas including tectonic plate interactions, crustal deformation in response to loading by tectonics, magmatism, water and ice, and the dynamics of water - and thereby energy transfer - in the atmosphere at regional scale. The many individual scientists and organizations that set up GNSS stations globally are often open to sharing data, but lack the resources or expertise to deploy systems and software to manage and curate data and metadata and provide user tools that would support data sharing. UNAVCO previously gained experience in facilitating data sharing through the NASA-supported development of the Geodesy Seamless Archive Centers (GSAC) open source software. GSAC provides web interfaces and simple web services for data and metadata discovery and access, supports federation of multiple data centers, and simplifies transfer of data and metadata to long-term archives. The NSF supported the dissemination of GSAC to multiple European data centers forming the European Plate Observing System. To expand upon GSAC to provide end-to-end, instrument-to-distribution capability, UNAVCO developed Dataworks for GNSS with NSF funding to the COCONet project, and deployed this software on systems that are now operating as Regional GNSS Data Centers as part of the NSF-funded TLALOCNet and COCONet projects. Dataworks consists of software modules written in Python and Java for data acquisition, management and sharing. There are modules for GNSS receiver control and data download, a database schema for metadata, tools for metadata handling, ingest software to manage file metadata, data file management scripts, GSAC, scripts for mirroring station data and metadata from partner GSACs, and extensive software and operator documentation. UNAVCO plans to provide a cloud VM image of Dataworks that would allow standing up a Dataworks-enabled GNSS data center without requiring upfront investment in server hardware. By enabling data creators to organize their data and metadata for sharing, Dataworks helps scientists expand their data curation awareness and responsibility, and enhances data access for all.

Unidata: A geoscience e-infrastructure for International Data Sharing

NASA Astrophysics Data System (ADS)

Ramamurthy, Mohan

2017-04-01

The Internet and its myriad manifestations, including the World Wide Web, have amply demonstrated the compounding benefits of a global cyberinfrastructure and the power of networked communities as institutions and people exchange knowledge, ideas, and resources. The Unidata Program recognizes those benefits, and over the past several years it has developed a growing portfolio of international data distribution activities, conducted in close collaboration with academic, research and operational institutions on several continents, to advance earth system science education and research. The portfolio includes provision of data, tools, support and training as well as outreach activities that bring various stakeholders together to address important issues, all toward the goals of building a community with a shared vision. The overarching goals of Unidata's international data sharing activities include: • democratization of access-to and use-of data that describe the dynamic earth system by facilitating data access to a broad spectrum of observations and forecasts • building capacity and empowering geoscientists and educators worldwide by building encouraging local communities where data, tools, and best practices in education and research are shared • strengthening international science partnerships for exchanging knowledge and expertise • Supporting faculty and students at research and educational institutions in the use of Unidata systems building regional and global communities around specific geoscientific themes. In this presentation, I will present Unidata's ongoing data sharing activities in Latin America, Europe, Africa and Antarctica that are enabling linkages to existing and emergent e-infrastructures and operational networks, including recent advances to develop interoperable data systems, tools, and services that benefit the geosciences. Particular emphasis in the presentation will be made to describe the examples of the use of Unidata's International Data Distribution Network, Local Data Manager, and THREDDS in various settings, as well as experiences and lessons learned with the implementation and benefits of the myriad data sharing efforts.

Data Democratization - Promoting Real-Time Data Sharing and Use throughout the Americas

NASA Astrophysics Data System (ADS)

Yoksas, T. C.

2006-05-01

The Unidata Program Center (Unidata) of the University Corporation of Atmospheric Research (UCAR) is actively involved in international collaborations whose goals are real-time sharing of hydro-meteorological data by institutions of higher education throughout the Americas; in the distribution of analysis and visualization tools for those data; and in the establishment of server sites that provide easy-to-use, programmatic remote- access to a wide variety of datasets. Data sharing capabilities are being provided by Unidata's Internet Data Distribution (IDD) system, a community-based effort that has been the primary source of real-time meteorological data for approximately 150 US universities for over a decade. A collaboration among Unidata, Brazil's Centro de PreviSão de Tempo e Estudos Climáticos (CPTEC), the Universidad Federal do Rio de Janeiro (UFRJ), and the Universidade de São Paulo (USP) has resulted in the creation of a Brazilian peer of the North American IDD, the IDD-Brasil. Collaboration among Unidata, the Universidad de Costa Rica (UCR), and the University of Puerto Rico at Mayaguez (UPRM) seeks to extend IDD data sharing throughout Central America and the Caribbean in an IDD-Caribe. Collaboration between Unidata and the Caribbean Institute for Meteorology and Hydrology (CIMH), a World Meteorological Organization (WMO) Regional Meteorological Training Center (RMTC) based in Barbados, has been launched to investigate the possibility of expansion of IDD data sharing throughout Caribbean RMTC member countries. Most recently, efforts aimed at creating a data sharing network for researchers on the Antarctic continent have resulted in the establishment of the Antarctic-IDD. Data analysis and visualization capabilities are being provided by Unidata through a suite of freely-available applications: the National Centers for Environmental Prediction (NCEP) GEneral Meteorology PAcKage (GEMPAK); the Unidata Integrated Data Viewer (IDV); and University of Wisconsin, Space Science and Engineering Center (SSEC) Man-computer Interactive Data Access System (McIDAS). Remote data access capabilities are provided by Unidata's Thematic Realtime Environmental Data Services (THREDDS) servers (which incorporate Open-source Project for a Network Data Access (OPeNDAP) data services), and the Abstract Data Distribution Environment (ADDE) of McIDAS. It is envisioned that the data sharing capabilities available in the IDD, IDD-Brasil, and IDD-Caribe, remote data access capabilities available in THREDDS and ADDE, and analysis capabilities available in GEMPAK, the IDV, and McIDAS will help foster new collaborations among prominent university educators and researchers, national meteorological agencies, and WMO Regional Meteorological Training Centers throughout North, Central, and South America.

Spatially explicit data: stewardship and ethical challenges in science.

PubMed

Hartter, Joel; Ryan, Sadie J; Mackenzie, Catrina A; Parker, John N; Strasser, Carly A

2013-09-01

Scholarly communication is at an unprecedented turning point created in part by the increasing saliency of data stewardship and data sharing. Formal data management plans represent a new emphasis in research, enabling access to data at higher volumes and more quickly, and the potential for replication and augmentation of existing research. Data sharing has recently transformed the practice, scope, content, and applicability of research in several disciplines, in particular in relation to spatially specific data. This lends exciting potentiality, but the most effective ways in which to implement such changes, particularly for disciplines involving human subjects and other sensitive information, demand consideration. Data management plans, stewardship, and sharing, impart distinctive technical, sociological, and ethical challenges that remain to be adequately identified and remedied. Here, we consider these and propose potential solutions for their amelioration.

Issues central to a useful image understanding environment

NASA Astrophysics Data System (ADS)

Beveridge, J. Ross; Draper, Bruce A.; Hanson, Allen R.; Riseman, Edward M.

1992-04-01

A recent DARPA initiative has sparked interested in software environments for computer vision. The goal is a single environment to support both basic research and technology transfer. This paper lays out six fundamental attributes such a system must possess: (1) support for both C and Lisp, (2) extensibility, (3) data sharing, (4) data query facilities tailored to vision, (5) graphics, and (6) code sharing. The first three attributes fundamentally constrain the system design. Support for both C and Lisp demands some form of database or data-store for passing data between languages. Extensibility demands that system support facilities, such as spatial retrieval of data, be readily extended to new user-defined datatypes. Finally, data sharing demands that data saved by one user, including data of a user-defined type, must be readable by another user.

Integrated Air Surveillance Concept of Operations

DTIC Science & Technology

2011-11-01

information, intelligence, weather data, and other situational awareness-related information. 4.2.4 Shared Services Automated processing of sensor and...other surveillance information will occur through shared services , accessible through an enterprise network infrastructure, that provide for collecting...also be provided, such as information discovery and translation. The IS architecture effort will identify specific shared services . Shared

USDOT guidance summary for connected vehicle deployments : data sharing.

DOT National Transportation Integrated Search

2016-07-01

AbstractThe document provides guidance to Pilot Deployers in the timely and successful completion of Concept Development Phase deliverables, specifically in developing the Data Sharing Framework portion of the Performance Measurement and Evaluation S...

DataUp: Helping manage and archive data within the researcher's workflow

NASA Astrophysics Data System (ADS)

Strasser, C.

2012-12-01

There are many barriers to data management and sharing among earth and environmental scientists; among the most significant are lacks of knowledge about best practices for data management, metadata standards, or appropriate data repositories for archiving and sharing data. We have developed an open-source add-in for Excel and an open source web application intended to help researchers overcome these barriers. DataUp helps scientists to (1) determine whether their file is CSV compatible, (2) generate metadata in a standard format, (3) retrieve an identifier to facilitate data citation, and (4) deposit their data into a repository. The researcher does not need a prior relationship with a data repository to use DataUp; the newly implemented ONEShare repository, a DataONE member node, is available for any researcher to archive and share their data. By meeting researchers where they already work, in spreadsheets, DataUp becomes part of the researcher's workflow and data management and sharing becomes easier. Future enhancement of DataUp will rely on members of the community adopting and adapting the DataUp tools to meet their unique needs, including connecting to analytical tools, adding new metadata schema, and expanding the list of connected data repositories. DataUp is a collaborative project between Microsoft Research Connections, the University of California's California Digital Library, the Gordon and Betty Moore Foundation, and DataONE.

A Utility Maximizing and Privacy Preserving Approach for Protecting Kinship in Genomic Databases.

PubMed

Kale, Gulce; Ayday, Erman; Tastan, Oznur

2017-09-12

Rapid and low cost sequencing of genomes enabled widespread use of genomic data in research studies and personalized customer applications, where genomic data is shared in public databases. Although the identities of the participants are anonymized in these databases, sensitive information about individuals can still be inferred. One such information is kinship. We define two routes kinship privacy can leak and propose a technique to protect kinship privacy against these risks while maximizing the utility of shared data. The method involves systematic identification of minimal portions of genomic data to mask as new participants are added to the database. Choosing the proper positions to hide is cast as an optimization problem in which the number of positions to mask is minimized subject to privacy constraints that ensure the familial relationships are not revealed.We evaluate the proposed technique on real genomic data. Results indicate that concurrent sharing of data pertaining to a parent and an offspring results in high risks of kinship privacy, whereas the sharing data from further relatives together is often safer. We also show arrival order of family members have a high impact on the level of privacy risks and on the utility of sharing data. Available at: https://github.com/tastanlab/Kinship-Privacy. erman@cs.bilkent.edu.tr or oznur.tastan@cs.bilkent.edu.tr. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Dynamic Collaboration Infrastructure for Hydrologic Science

NASA Astrophysics Data System (ADS)

Tarboton, D. G.; Idaszak, R.; Castillo, C.; Yi, H.; Jiang, F.; Jones, N.; Goodall, J. L.

2016-12-01

Data and modeling infrastructure is becoming increasingly accessible to water scientists. HydroShare is a collaborative environment that currently offers water scientists the ability to access modeling and data infrastructure in support of data intensive modeling and analysis. It supports the sharing of and collaboration around "resources" which are social objects defined to include both data and models in a structured standardized format. Users collaborate around these objects via comments, ratings, and groups. HydroShare also supports web services and cloud based computation for the execution of hydrologic models and analysis and visualization of hydrologic data. However, the quantity and variety of data and modeling infrastructure available that can be accessed from environments like HydroShare is increasing. Storage infrastructure can range from one's local PC to campus or organizational storage to storage in the cloud. Modeling or computing infrastructure can range from one's desktop to departmental clusters to national HPC resources to grid and cloud computing resources. How does one orchestrate this vast number of data and computing infrastructure without needing to correspondingly learn each new system? A common limitation across these systems is the lack of efficient integration between data transport mechanisms and the corresponding high-level services to support large distributed data and compute operations. A scientist running a hydrology model from their desktop may require processing a large collection of files across the aforementioned storage and compute resources and various national databases. To address these community challenges a proof-of-concept prototype was created integrating HydroShare with RADII (Resource Aware Data-centric collaboration Infrastructure) to provide software infrastructure to enable the comprehensive and rapid dynamic deployment of what we refer to as "collaborative infrastructure." In this presentation we discuss the results of this proof-of-concept prototype which enabled HydroShare users to readily instantiate virtual infrastructure marshaling arbitrary combinations, varieties, and quantities of distributed data and computing infrastructure in addressing big problems in hydrology.

Multilateral Biomedical Data Sharing in the One-year Joint US-Russian Mission on the International Space Station

NASA Technical Reports Server (NTRS)

Charles, John B.; Haven, C.; Johnson-Throop, K.; Van Baalen, M.; McFather, J.

2014-01-01

The One Year Mission (1YM) by two astronauts on the International Space Station (ISS), starting in March 2015, offers a unique opportunity to expand multilateral collaboration by sharing data and resources among the partner agencies in preparation for planned space exploration missions beyond low Earth orbit. Agreements and protocols will be established for the collection, distribution, analysis and reporting of both research and clinical data. Data will be shared between the agencies sponsoring the investigators, and between the research and clinical medicine communities where common interests are identified. The assignment of only two astronauts, one Russian and the other American, to the 1YM necessitated creativity in bilateral efforts to maximize the biomedical return from the opportunity. Addition of Canadian, European and Japanese investigations make the effort even more integrative. There will be three types of investigations: joint, cross-participation and data-exchange. The joint investigations have US and Russian coprincipal investigators, and the data acquired will be their common responsibility. The other two types must develop data sharing agreements and processes specific to their needs. A multilateral panel of ISS partner space agencies will develop policies for international exchange of scientific information to meet their science objectives and priorities. They will promote archiving of space flight data and will inform each other and the scientific community at large about the results obtained from space life sciences studies. Integration tasks for the 1YM are based on current experience from the ISS and previous efforts on the Russian space station Mir. Closer coordination between international partners requires more common approaches to remove barriers to multilateral resource utilization on the ISS. Greater integration in implementation should increase utilization efficiency to benefit all participants in spaceflight human research. This presentation will describe the overarching principles for multilateral data collection, analysis and sharing and for data security for medical and research data shared between ISS partners prior to release in public forums.

Alternative Fuels Data Center: Natural Gas Laws and Incentives

Science.gov Websites

Natural Gas Printable Version Share this resource Send a link to Alternative Fuels Data Center : Natural Gas Laws and Incentives to someone by E-mail Share Alternative Fuels Data Center: Natural Gas Laws and Incentives on Facebook Tweet about Alternative Fuels Data Center: Natural Gas Laws and Incentives

The Data Warehouse: Keeping It Simple. MIT Shares Valuable Lessons Learned from a Successful Data Warehouse Implementation.

ERIC Educational Resources Information Center

Thorne, Scott

2000-01-01

Explains why the data warehouse is important to the Massachusetts Institute of Technology community, describing its basic functions and technical design points; sharing some non-technical aspects of the school's data warehouse implementation that have proved to be important; examining the importance of proper training in a successful warehouse…

Leveraging EHR Data for Outcomes and Comparative Effectiveness Research in Oncology

PubMed Central

Harris, Marcelline R.; Buyuktur, Ayse G.; Clark, Patricia M.; An, Lawrence C.; Hanauer, David A.

2012-01-01

Along with the increasing adoption of electronic health records (EHRs) are expectations that data collected within EHRs will be readily available for outcomes and comparative effectiveness research. Yet the ability to effectively share and reuse data depends on implementing and configuring EHRs with these goals in mind from the beginning. Data sharing and integration must be planned both locally as well as nationally. The rich data transmission and semantic infrastructure developed by the National Cancer Institute (NCI) for research provides an excellent example of moving beyond paper-based paradigms and exploiting the power of semantically robust, network-based systems, and engaging both domain and informatics expertise. Similar efforts are required to address current challenges in sharing EHR data. PMID:22948276

Data-intensive science gateway for rock physicists and volcanologists.

NASA Astrophysics Data System (ADS)

Filgueira, Rosa; Atkinson, Malcom; Bell, Andrew; Main, Ian; Boon, Steve; Meredith, Philp; Kilburn, Christopher

2014-05-01

Scientists have always shared data and mathematical models of the phenomena they study. Rock physics and Volcanology, as well as other solid-Earth sciences, have increasingly used Internet communications and computational renditions of their models for this purpose over the last two decades. Here we consider how to organise rock physics and volcanology data to open up opportunities for sharing and comparing both experiment data from experiments, observations and model runs and analytic interpretations of these data. Our hypothesis is that if we facilitate productive information sharing across those communities by using a new science gateway, it will benefit the science. The proposed science gateway should make the first steps for making existing research practices easier and facilitate new research. It will achieve this by supporting three major functions: 1) sharing data from laboratories and observatories, experimental facilities and models; 2) sharing models of rock fracture and methods for analysing experimental data; and 3) supporting recurrent operational tasks, such as data collection and model application in real time. We report initial work in two projects (NERC EFFORT and NERC CREEP-2) and experience with an early web-accessible protytpe called EFFORT gateway, where we are implementing such information sharing services for those projects. 1. Sharing data: In EFFORT gateway, we are working on several facilities for sharing data: *Upload data: We have designed and developed a new adaptive data transfer java tool called FAST (Flexible Automated Streaming Transfer) to upload experimental data and metadata periodically from laboratories to our repository. *Visualisation: As data are deposited in the repository, a visualisation of the accumulated data is made available for display in the Web portal. *Metadata and catalogues: The gateway uses a repository to hold all the data and a catalogue to hold all the corresponding metadata. 2. Sharing models and methods: The EFFORT gateway uses a repository to hold all of the models and a catalogue to hold the corresponding metadata. It provides several Web facilities for uploading, accessing and testing models. *Upload and store models: Through the gateway, researchers can upload as many models to the repository as they want. *Description of models: The gateway solicits and creates metadata for every model uploaded to store in the catalogue. *Search for models: Researchers can search the catalogue for models by using prepackaged sql-queries. *Access to models: Once a researcher has selected the model(s) that is going to be used for analysing an experiment, it will be obtained from the gateway. *Services to test and run models: Once a researcher selects a model and the experimental data to which it should be applied, the gateway submits the corresponding computational job to a high-performance computational (HPC) resource hiding technical details. Once a job is submitted to the HPC cluster, the results are displayed in the gateway in real time, catalogued and stored in the data repository, allowing further researcher-instigated operations to retrieve, inspect and aggregate results. *Services to write models: We have desgined VarPy library, which is an open-source toolbox which provides a Python framework for analysing volcanology and rock physics data. It provides several functions, which allow users to define their own workflows to develop models, analyses and visualizations. 3. Recurrent Operations: We have started to introduce some recurrent operations: *Automated data upload: FAST provides a mechanism to automate the data upload. *Periodic activation of models: The EFFORT gateway allows researchers to run different models periodically against the experimental data that are being or have been uploaded

78 FR 45565 - Notice Pursuant to the National Cooperative Research and Production Act of 1993 -- tranSMART...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-29

... activities are to enable effective sharing, integration, standardization, and analysis of heterogeneous data from collaborative translational research by mobilizing the tranSMART open- source and open-data...: (a) Establish and sustain tranSMART as the preferred data sharing and analytics platform for...

Sharing Research Results

ERIC Educational Resources Information Center

Ashbrook, Peggy

2011-01-01

There are many ways to share a collection of data and students' thinking about that data. Explaining the results of science inquiry is important--working scientists and amateurs both contribute information to the body of scientific knowledge. Students can collect data about an activity that is already happening in a classroom (e.g., the qualities…

Development and Classroom Implementation of an Environmental Data Creation and Sharing Tool

ERIC Educational Resources Information Center

Brogan, Daniel S.; McDonald, Walter M.; Lohani, Vinod K.; Dymond, Randel L.; Bradner, Aaron J.

2016-01-01

Education is essential for solving the complex water-related challenges facing society. The Learning Enhanced Watershed Assessment System (LEWAS) and the Online Watershed Learning System (OWLS) provide data creation and data sharing infrastructures, respectively, that combine to form an environmental learning tool. This system collects, integrates…

Reproducibility in Computational Neuroscience Models and Simulations

PubMed Central

McDougal, Robert A.; Bulanova, Anna S.; Lytton, William W.

2016-01-01

Objective Like all scientific research, computational neuroscience research must be reproducible. Big data science, including simulation research, cannot depend exclusively on journal articles as the method to provide the sharing and transparency required for reproducibility. Methods Ensuring model reproducibility requires the use of multiple standard software practices and tools, including version control, strong commenting and documentation, and code modularity. Results Building on these standard practices, model sharing sites and tools have been developed that fit into several categories: 1. standardized neural simulators, 2. shared computational resources, 3. declarative model descriptors, ontologies and standardized annotations; 4. model sharing repositories and sharing standards. Conclusion A number of complementary innovations have been proposed to enhance sharing, transparency and reproducibility. The individual user can be encouraged to make use of version control, commenting, documentation and modularity in development of models. The community can help by requiring model sharing as a condition of publication and funding. Significance Model management will become increasingly important as multiscale models become larger, more detailed and correspondingly more difficult to manage by any single investigator or single laboratory. Additional big data management complexity will come as the models become more useful in interpreting experiments, thus increasing the need to ensure clear alignment between modeling data, both parameters and results, and experiment. PMID:27046845

A systematic literature review of individuals' perspectives on broad consent and data sharing in the United States.

PubMed

Garrison, Nanibaa' A; Sathe, Nila A; Antommaria, Armand H Matheny; Holm, Ingrid A; Sanderson, Saskia C; Smith, Maureen E; McPheeters, Melissa L; Clayton, Ellen W

2016-07-01

In 2011, an Advanced Notice of Proposed Rulemaking proposed that de-identified human data and specimens be included in biobanks only if patients provide consent. The National Institutes of Health Genomic Data Sharing policy went into effect in 2015, requiring broad consent from almost all research participants. We conducted a systematic literature review of attitudes toward biobanking, broad consent, and data sharing. Bibliographic databases included MEDLINE, Web of Science, EthxWeb, and GenETHX. Study screening was conducted using DistillerSR. The final 48 studies included surveys (n = 23), focus groups (n = 8), mixed methods (n = 14), interviews (n = 1), and consent form analyses (n = 2). Study quality was characterized as good (n = 19), fair (n = 27), and poor (n = 2). Although many participants objected, broad consent was often preferred over tiered or study-specific consent, particularly when broad consent was the only option, samples were de-identified, logistics of biobanks were communicated, and privacy was addressed. Willingness for data to be shared was high, but it was lower among individuals from under-represented minorities, individuals with privacy and confidentiality concerns, and when pharmaceutical companies had access to data. Additional research is needed to understand factors affecting willingness to give broad consent for biobank research and data sharing in order to address concerns to enhance acceptability.Genet Med 18 7, 663-671.

Exploring Pathways to Trust: A Tribal Perspective on Data Sharing

PubMed Central

James, Rosalina; Tsosie, Rebecca; Sahota, Puneet; Parker, Myra; Dillard, Denise; Sylvester, Ileen; Lewis, John; Klejka, Joseph; Muzquiz, LeeAnna; Olsen, Polly; Whitener, Ron; Burke, Wylie

2014-01-01

National Institutes of Health data-sharing policies aim to maximize public benefit derived from genetic studies by increasing research efficiency and the use of a pooled data resource for future studies. While broad access to data may lead to benefits for populations underrepresented in genetic studies, such as indigenous groups, tribes have ownership interest in their data. The Northwest-Alaska Pharmacogenetic Research Network, a partnership involving tribal organizations and universities conducting basic and translational pharmacogenetic research, convened a meeting to discuss the collection, management, and secondary use of research data, and of the processes surrounding access to data stored in federal repositories. This article reports on tribal perspectives that emerged from the dialogue and discusses the implications of tribal government sovereign status on research agreements and data-sharing negotiations. There is strong tribal support for efficient research processes that expedite the benefits from collaborative research, but there is also a need for data sharing procedures that take into account tribal sovereignty and appropriate oversight of research ¬ such as tribally-based research review processes and review of draft manuscripts. We also note specific ways in which accountability could be encouraged by National Institutes of Health as part of the research process. PMID:24830328

Developing Privacy Solutions for Sharing and Analyzing Healthcare Data

PubMed Central

Motiwalla, Luvai; Li, Xiao-Bai

2013-01-01

The extensive use of electronic health data has increased privacy concerns. While most healthcare organizations are conscientious in protecting their data in their databases, very few organizations take enough precautions to protect data that is shared with third party organizations. Recently the regulatory environment has tightened the laws to enforce privacy protection. The goal of this research is to explore the application of data masking solutions for protecting patient privacy when data is shared with external organizations for research, analysis and other similar purposes. Specifically, this research project develops a system that protects data without removing sensitive attributes. Our application allows high quality data analysis with the masked data. Dataset-level properties and statistics remain approximately the same after data masking; however, individual record-level values are altered to prevent privacy disclosure. A pilot evaluation study on large real-world healthcare data shows the effectiveness of our solution in privacy protection. PMID:24285983

The NGEE Arctic Data Archive -- Portal for Archiving and Distributing Data and Documentation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boden, Thomas A; Palanisamy, Giri; Devarakonda, Ranjeet

2014-01-01

The Next-Generation Ecosystem Experiments (NGEE Arctic) project is committed to implementing a rigorous and high-quality data management program. The goal is to implement innovative and cost-effective guidelines and tools for collecting, archiving, and sharing data within the project, the larger scientific community, and the public. The NGEE Arctic web site is the framework for implementing these data management and data sharing tools. The open sharing of NGEE Arctic data among project researchers, the broader scientific community, and the public is critical to meeting the scientific goals and objectives of the NGEE Arctic project and critical to advancing the mission ofmore » the Department of Energy (DOE), Office of Science, Biological and Environmental (BER) Terrestrial Ecosystem Science (TES) program.« less

Human Proteinpedia enables sharing of human protein data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mathivanan, Suresh; Ahmed, Mukhtar; Ahn, Natalie G.

2008-02-01

Proteomic technologies, such as yeast twohybrid, mass spectrometry (MS), protein/ peptide arrays and fluorescence microscopy, yield multi-dimensional data sets, which are often quite large and either not published or published as supplementary information that is not easily searchable. Without a system in place for standardizing and sharing data, it is not fruitful for the biomedical community to contribute these types of data to centralized repositories. Even more difficult is the annotation and display of pertinent information in the context of the corresponding proteins. Wikipedia, an online encyclopedia that anyone can edit, has already proven quite successful1 and can be usedmore » as a model for sharing biological data. However, the need for experimental evidence, data standardization and ownership of data creates scientific obstacles.« less

CloudMan as a platform for tool, data, and analysis distribution.

PubMed

Afgan, Enis; Chapman, Brad; Taylor, James

2012-11-27

Cloud computing provides an infrastructure that facilitates large scale computational analysis in a scalable, democratized fashion, However, in this context it is difficult to ensure sharing of an analysis environment and associated data in a scalable and precisely reproducible way. CloudMan (usecloudman.org) enables individual researchers to easily deploy, customize, and share their entire cloud analysis environment, including data, tools, and configurations. With the enabled customization and sharing of instances, CloudMan can be used as a platform for collaboration. The presented solution improves accessibility of cloud resources, tools, and data to the level of an individual researcher and contributes toward reproducibility and transparency of research solutions.

Full and Open Access to Data in the Global Earth Observing System of Systems (GEOSS): Implementing the GEOSS Data Sharing Principles

NASA Astrophysics Data System (ADS)

Chen, R. S.; Uhlir, P. F.; Gabrinowicz, J. I.

2008-12-01

Full and open access to data from remote sensing platforms and other sources can facilitate not only scientific research but also the more widespread and effective use of scientific data for the benefit of society. The Global Earth Observing System of Systems (GEOSS) is a major international initiative of the Group on Earth Observations (GEO) to develop "coordinated, comprehensive and sustained Earth observations and information." In 2005, GEO adopted the GEOSS Data Sharing Principles, which call for the "full and open exchange of data, metadata, and products shared within GEOSS, recognizing relevant international instruments and national policies and legislation." These Principles also note that "All shared data, metadata, and products will be made available with minimum time delay and at minimum cost" and that "All shared data, metadata, and products being free of charge or no more than cost of reproduction will be encouraged for research and education." GEOSS Task DA-06-01, aimed at developing a set of recommended implementation guidelines for the Principles, was established in 2006 under the leadership of CODATA, the Committee on Data for Science and Technology of the International Council for Science (ICSU). An international team of authors has developed a draft White Paper on the GEOSS Data Sharing Principles and a proposed set of implementation guidelines. These have been carefully reviewed by independent reviewers, various GEO Committees, and GEO National Members and Participating Organizations. It is expected that the proposed implementation guidelines will be discussed at the GEO-V Plenary in Budapest in November 2008. The current version of the proposed implementation guidelines recognizes the importance of good faith, voluntary adherence to the Principles by GEO National Members and Participating Organizations. It underscores the value of reuse and re-dissemination of GEOSS data with minimum restrictions, not only within GEOSS itself but on the part of GEOSS users. Consistency with relevant international instruments and applicable policies and legislation is essential, and therefore clarification and coordination of applicable policies and procedures are needed. Pricing of GEOSS data, metadata, and products should be based on the premise that the data and information within GEOSS is a public good for public-interest use in the nine societal benefit areas. Time delays for data access from both operational and research systems should be kept to a minimum, reflecting the norms of the relevant scientific communities or data processing centers. The proposed guidelines also emphasize the need to better define research and education uses and to develop and collect usage metrics and indicators. The draft White Paper provides a more detailed review of past and current data policies related to space-based and spatial data, assesses the implications of the Data Sharing Principles for selected case studies, and discusses a number of other important implementation issues. Successful implementation of the GEOSS Data Sharing Principles is likely to be a critical element in the future effectiveness and value of GEOSS.

Development of a prehospital vital signs chart sharing system.

PubMed

Nakada, Taka-aki; Masunaga, Naohisa; Nakao, Shota; Narita, Maiko; Fuse, Takashi; Watanabe, Hiroaki; Mizushima, Yasuaki; Matsuoka, Tetsuya

2016-01-01

Physiological parameters are crucial for the caring of trauma patients. There is a significant loss of prehospital vital signs data of patients during handover between prehospital and in-hospital teams. Effective strategies for reducing the loss remain a challenging research area. We tested whether the newly developed electronic automated prehospital vital signs chart sharing system would increase the amount of prehospital vital signs data shared with a remote trauma center prior to hospital arrival. Fifty trauma patients, transferred to a level I trauma center in Japan, were studied. The primary outcome variable was the number of prehospital vital signs shared with the trauma center prior to hospital arrival. The prehospital vital signs chart sharing system significantly increased the number of prehospital vital signs, including blood pressure, heart rate, and oxygen saturation, shared with the in-hospital team at a remote trauma center prior to patient arrival at the hospital (P < .0001). There were significant differences in prehospital vital signs during ambulance transfer between patients who had severe bleeding and non-severe bleeding within 24 hours after injury onset. Vital signs data collected during ambulance transfer via patient monitors could be automatically converted to easily visible patient charts and effectively shared with the remote trauma center prior to hospital arrival. The prehospital vital signs chart sharing system increased the number of precise vital signs shared prior to patient arrival at the hospital, which can potentially contribute to better trauma care without increasing labor and reduce information loss during clinical handover. Copyright © 2015 Elsevier Inc. All rights reserved.

Facilitating Secure Sharing of Personal Health Data in the Cloud

PubMed Central

Nepal, Surya; Glozier, Nick

2016-01-01

Background Internet-based applications are providing new ways of promoting health and reducing the cost of care. Although data can be kept encrypted in servers, the user does not have the ability to decide whom the data are shared with. Technically this is linked to the problem of who owns the data encryption keys required to decrypt the data. Currently, cloud service providers, rather than users, have full rights to the key. In practical terms this makes the users lose full control over their data. Trust and uptake of these applications can be increased by allowing patients to feel in control of their data, generally stored in cloud-based services. Objective This paper addresses this security challenge by providing the user a way of controlling encryption keys independently of the cloud service provider. We provide a secure and usable system that enables a patient to share health information with doctors and specialists. Methods We contribute a secure protocol for patients to share their data with doctors and others on the cloud while keeping complete ownership. We developed a simple, stereotypical health application and carried out security tests, performance tests, and usability tests with both students and doctors (N=15). Results We developed the health application as an app for Android mobile phones. We carried out the usability tests on potential participants and medical professionals. Of 20 participants, 14 (70%) either agreed or strongly agreed that they felt safer using our system. Using mixed methods, we show that participants agreed that privacy and security of health data are important and that our system addresses these issues. Conclusions We presented a security protocol that enables patients to securely share their eHealth data with doctors and nurses and developed a secure and usable system that enables patients to share mental health information with doctors. PMID:27234691

Collaborative Data Publication Utilizing the Open Data Repository's (ODR) Data Publisher

NASA Technical Reports Server (NTRS)

Stone, N.; Lafuente, B.; Bristow, T.; Keller, R. M.; Downs, R. T.; Blake, D.; Fonda, M.; Dateo, C.; Pires, A.

2017-01-01

Introduction: For small communities in diverse fields such as astrobiology, publishing and sharing data can be a difficult challenge. While large, homogenous fields often have repositories and existing data standards, small groups of independent researchers have few options for publishing standards and data that can be utilized within their community. In conjunction with teams at NASA Ames and the University of Arizona, the Open Data Repository's (ODR) Data Publisher has been conducting ongoing pilots to assess the needs of diverse research groups and to develop software to allow them to publish and share their data collaboratively. Objectives: The ODR's Data Publisher aims to provide an easy-to-use and implement software tool that will allow researchers to create and publish database templates and related data. The end product will facilitate both human-readable interfaces (web-based with embedded images, files, and charts) and machine-readable interfaces utilizing semantic standards. Characteristics: The Data Publisher software runs on the standard LAMP (Linux, Apache, MySQL, PHP) stack to provide the widest server base available. The software is based on Symfony (www.symfony.com) which provides a robust framework for creating extensible, object-oriented software in PHP. The software interface consists of a template designer where individual or master database templates can be created. A master database template can be shared by many researchers to provide a common metadata standard that will set a compatibility standard for all derivative databases. Individual researchers can then extend their instance of the template with custom fields, file storage, or visualizations that may be unique to their studies. This allows groups to create compatible databases for data discovery and sharing purposes while still providing the flexibility needed to meet the needs of scientists in rapidly evolving areas of research. Research: As part of this effort, a number of ongoing pilot and test projects are currently in progress. The Astrobiology Habitable Environments Database Working Group is developing a shared database standard using the ODR's Data Publisher and has a number of example databases where astrobiology data are shared. Soon these databases will be integrated via the template-based standard. Work with this group helps determine what data researchers in these diverse fields need to share and archive. Additionally, this pilot helps determine what standards are viable for sharing these types of data from internally developed standards to existing open standards such as the Dublin Core (http://dublincore.org) and Darwin Core (http://rs.twdg.org) metadata standards. Further studies are ongoing with the University of Arizona Department of Geosciences where a number of mineralogy databases are being constructed within the ODR Data Publisher system. Conclusions: Through the ongoing pilots and discussions with individual researchers and small research teams, a definition of the tools desired by these groups is coming into focus. As the software development moves forward, the goal is to meet the publication and collaboration needs of these scientists in an unobtrusive and functional way.

High Performance Programming Using Explicit Shared Memory Model on Cray T3D1

NASA Technical Reports Server (NTRS)

Simon, Horst D.; Saini, Subhash; Grassi, Charles

1994-01-01

The Cray T3D system is the first-phase system in Cray Research, Inc.'s (CRI) three-phase massively parallel processing (MPP) program. This system features a heterogeneous architecture that closely couples DEC's Alpha microprocessors and CRI's parallel-vector technology, i.e., the Cray Y-MP and Cray C90. An overview of the Cray T3D hardware and available programming models is presented. Under Cray Research adaptive Fortran (CRAFT) model four programming methods (data parallel, work sharing, message-passing using PVM, and explicit shared memory model) are available to the users. However, at this time data parallel and work sharing programming models are not available to the user community. The differences between standard PVM and CRI's PVM are highlighted with performance measurements such as latencies and communication bandwidths. We have found that the performance of neither standard PVM nor CRI s PVM exploits the hardware capabilities of the T3D. The reasons for the bad performance of PVM as a native message-passing library are presented. This is illustrated by the performance of NAS Parallel Benchmarks (NPB) programmed in explicit shared memory model on Cray T3D. In general, the performance of standard PVM is about 4 to 5 times less than obtained by using explicit shared memory model. This degradation in performance is also seen on CM-5 where the performance of applications using native message-passing library CMMD on CM-5 is also about 4 to 5 times less than using data parallel methods. The issues involved (such as barriers, synchronization, invalidating data cache, aligning data cache etc.) while programming in explicit shared memory model are discussed. Comparative performance of NPB using explicit shared memory programming model on the Cray T3D and other highly parallel systems such as the TMC CM-5, Intel Paragon, Cray C90, IBM-SP1, etc. is presented.

LC Data QUEST: A Technical Architecture for Community Federated Clinical Data Sharing.

PubMed

Stephens, Kari A; Lin, Ching-Ping; Baldwin, Laura-Mae; Echo-Hawk, Abigail; Keppel, Gina A; Buchwald, Dedra; Whitener, Ron J; Korngiebel, Diane M; Berg, Alfred O; Black, Robert A; Tarczy-Hornoch, Peter

2012-01-01

The University of Washington Institute of Translational Health Sciences is engaged in a project, LC Data QUEST, building data sharing capacity in primary care practices serving rural and tribal populations in the Washington, Wyoming, Alaska, Montana, Idaho region to build research infrastructure. We report on the iterative process of developing the technical architecture for semantically aligning electronic health data in primary care settings across our pilot sites and tools that will facilitate linkages between the research and practice communities. Our architecture emphasizes sustainable technical solutions for addressing data extraction, alignment, quality, and metadata management. The architecture provides immediate benefits to participating partners via a clinical decision support tool and data querying functionality to support local quality improvement efforts. The FInDiT tool catalogues type, quantity, and quality of the data that are available across the LC Data QUEST data sharing architecture. These tools facilitate the bi-directional process of translational research.

LC Data QUEST: A Technical Architecture for Community Federated Clinical Data Sharing

PubMed Central

Stephens, Kari A.; Lin, Ching-Ping; Baldwin, Laura-Mae; Echo-Hawk, Abigail; Keppel, Gina A.; Buchwald, Dedra; Whitener, Ron J.; Korngiebel, Diane M.; Berg, Alfred O.; Black, Robert A.; Tarczy-Hornoch, Peter

2012-01-01

The University of Washington Institute of Translational Health Sciences is engaged in a project, LC Data QUEST, building data sharing capacity in primary care practices serving rural and tribal populations in the Washington, Wyoming, Alaska, Montana, Idaho region to build research infrastructure. We report on the iterative process of developing the technical architecture for semantically aligning electronic health data in primary care settings across our pilot sites and tools that will facilitate linkages between the research and practice communities. Our architecture emphasizes sustainable technical solutions for addressing data extraction, alignment, quality, and metadata management. The architecture provides immediate benefits to participating partners via a clinical decision support tool and data querying functionality to support local quality improvement efforts. The FInDiT tool catalogues type, quantity, and quality of the data that are available across the LC Data QUEST data sharing architecture. These tools facilitate the bi-directional process of translational research. PMID:22779052

A rocket-borne pulse-height analyzer for energetic particle measurements

NASA Technical Reports Server (NTRS)

Leung, W.; Smith, L. G.; Voss, H. D.

1979-01-01

The pulse-height analyzer basically resembles a time-sharing multiplexing data-acquisition system which acquires analog data (from energetic particle spectrometers) and converts them into digital code. The PHA simultaneously acquires pulse-height information from the analog signals of the four input channels and sequentially multiplexes the digitized data to a microprocessor. The PHA together with the microprocessor form an on-board real-time data-manipulation system. The system processes data obtained during the rocket flight and reduces the amount of data to be sent back to the ground station. Consequently the data-reduction process for the rocket experiments is speeded up. By using a time-sharing technique, the throughput rate of the microprocessor is increased. Moreover, data from several particle spectrometers are manipulated to share one information channel; consequently, the TM capacity is increased.

Runtime support for parallelizing data mining algorithms

NASA Astrophysics Data System (ADS)

Jin, Ruoming; Agrawal, Gagan

2002-03-01

With recent technological advances, shared memory parallel machines have become more scalable, and offer large main memories and high bus bandwidths. They are emerging as good platforms for data warehousing and data mining. In this paper, we focus on shared memory parallelization of data mining algorithms. We have developed a series of techniques for parallelization of data mining algorithms, including full replication, full locking, fixed locking, optimized full locking, and cache-sensitive locking. Unlike previous work on shared memory parallelization of specific data mining algorithms, all of our techniques apply to a large number of common data mining algorithms. In addition, we propose a reduction-object based interface for specifying a data mining algorithm. We show how our runtime system can apply any of the technique we have developed starting from a common specification of the algorithm.

42 CFR 480.143 - QIO involvement in shared health data systems.

Code of Federal Regulations, 2013 CFR

2013-10-01

... HUMAN SERVICES (CONTINUED) QUALITY IMPROVEMENT ORGANIZATIONS ACQUISITION, PROTECTION, AND DISCLOSURE OF QUALITY IMPROVEMENT ORGANIZATION INFORMATION Utilization and Quality Control Quality Improvement Organizations (QIOs) Disclosure of Confidential Information § 480.143 QIO involvement in shared health data...

42 CFR 480.143 - QIO involvement in shared health data systems.

Code of Federal Regulations, 2012 CFR

2012-10-01

... HUMAN SERVICES (CONTINUED) QUALITY IMPROVEMENT ORGANIZATIONS ACQUISITION, PROTECTION, AND DISCLOSURE OF QUALITY IMPROVEMENT ORGANIZATION INFORMATION Utilization and Quality Control Quality Improvement Organizations (QIOs) Disclosure of Confidential Information § 480.143 QIO involvement in shared health data...

42 CFR 480.143 - QIO involvement in shared health data systems.

Code of Federal Regulations, 2014 CFR

2014-10-01

... HUMAN SERVICES (CONTINUED) QUALITY IMPROVEMENT ORGANIZATIONS ACQUISITION, PROTECTION, AND DISCLOSURE OF QUALITY IMPROVEMENT ORGANIZATION INFORMATION Utilization and Quality Control Quality Improvement Organizations (QIOs) Disclosure of Confidential Information § 480.143 QIO involvement in shared health data...

Cloud-Based Data Sharing Connects Emergency Managers

NASA Technical Reports Server (NTRS)

2014-01-01

Under an SBIR contract with Stennis Space Center, Baltimore-based StormCenter Communications Inc. developed an improved interoperable platform for sharing geospatial data over the Internet in real time-information that is critical for decision makers in emergency situations.

76 FR 30978 - Employment and Training Administration Program Year (PY) 2011 Workforce Investment Act (WIA...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-27

... area's relative share of farmworkers who are eligible for enrollment in the NFJP. The data used in the formula are comprised of a combination of data sets that were selected to yield the relative share... since their development in 1999, the data sets were last updated in 2005 with data from the 2000 Census...

Combining Cloud Networks and Course Management Systems for Enhanced Analysis in Teaching Laboratories

ERIC Educational Resources Information Center

Abrams, Neal M.

2012-01-01

A cloud network system is combined with standard computing applications and a course management system to provide a robust method for sharing data among students. This system provides a unique method to improve data analysis by easily increasing the amount of sampled data available for analysis. The data can be shared within one course as well as…

Developing patient-centered teams: The role of sharing stories about patients and patient care.

PubMed

Bennett, Ariana H; Hassinger, Jane A; Martin, Lisa A; Harris, Lisa H; Gold, Marji

2015-09-01

Research indicates that health care teams are good for staff, patients, and organizations. The characteristics that make teams effective include shared objectives, mutual respect, clarity of roles, communication, trust, and collaboration. We were interested in examining how teams develop these positive characteristics. This paper explores the role of sharing stories about patients in developing patient-centered teams. Data for this paper came from 1 primary care clinic as part of a larger Providers Share Workshop study conducted by the University of Michigan. Each workshop included 5 facilitated group sessions in which staff met to talk about their work. This paper analyzes qualitative data from the workshops. Through an iterative process, research team members identified major themes, developed a coding scheme, and coded transcripts for qualitative data analysis. One of the most powerful ways group members connected was through sharing stories about their patients. Sharing clinical cases and stories helped participants bond around their shared mission of patient-centered care, build supportive relationships, enhance compassion for patients, communicate and resolve conflict, better understand workflows and job roles, develop trust, and increase morale. These attributes highlighted by participants correspond to those documented in the literature as important elements of teambuilding and key indicators of team effectiveness. The sharing of stories about patients seems to be a promising tool for positive team development in a primary care clinical setting and should be investigated further. (c) 2015 APA, all rights reserved).

Needle and syringe sharing among Iranian drug injectors

PubMed Central

Rafiey, Hassan; Narenjiha, Hooman; Shirinbayan, Peymaneh; Noori, Roya; Javadipour, Morteza; Roshanpajouh, Mohsen; Samiei, Mercedeh; Assari, Shervin

2009-01-01

Objective The role of needle and syringe sharing behavior of injection drug users (IDUs) in spreading of blood-borne infections – specially HIV/AIDS – is well known. However, very little is known in this regard from Iran. The aim of our study was to determine the prevalence and associates of needle and syringe sharing among Iranian IDUs. Methods In a secondary analysis of a sample of drug dependents who were sampled from medical centers, prisons and streets of the capitals of 29 provinces in the Iran in 2007, 2091 male IDUs entered. Socio-demographic data, drug use data and high risk behaviors entered to a logistic regression to determine independent predictors of lifetime needle and syringe sharing. Results 749(35.8%) reported lifetime experience of needle and syringe sharing. The likelihood of lifetime needle and syringe sharing was increased by female gender, being jobless, having illegal income, drug use by family members, pleasure/enjoyment as causes of first injection, first injection in roofless and roofed public places, usual injection at groin, usual injection at scrotum, lifetime experience of nonfatal overdose, and history of arrest in past year and was decreased by being alone at most injections. Conclusion However this data has been extracted from cross-sectional design and we can not conclude causation, some of the introduced variables with association with needle and syringe sharing may be used in HIV prevention programs which target reducing syringe sharing among IDUs. PMID:19643014

Tracing the Potential Flow of Consumer Data: A Network Analysis of Prominent Health and Fitness Apps.

PubMed

Grundy, Quinn; Held, Fabian P; Bero, Lisa A

2017-06-28

A great deal of consumer data, collected actively through consumer reporting or passively through sensors, is shared among apps. Developers increasingly allow their programs to communicate with other apps, sensors, and Web-based services, which are promoted as features to potential users. However, health apps also routinely pose risks related to information leaks, information manipulation, and loss of information. There has been less investigation into the kinds of user data that developers are likely to collect, and who might have access to it. We sought to describe how consumer data generated from mobile health apps might be distributed and reused. We also aimed to outline risks to individual privacy and security presented by this potential for aggregating and combining user data across apps. We purposively sampled prominent health and fitness apps available in the United States, Canada, and Australia Google Play and iTunes app stores in November 2015. Two independent coders extracted data from app promotional materials on app and developer characteristics, and the developer-reported collection and sharing of user data. We conducted a descriptive analysis of app, developer, and user data collection characteristics. Using structural equivalence analysis, we conducted a network analysis of sampled apps' self-reported sharing of user-generated data. We included 297 unique apps published by 231 individual developers, which requested 58 different permissions (mean 7.95, SD 6.57). We grouped apps into 222 app families on the basis of shared ownership. Analysis of self-reported data sharing revealed a network of 359 app family nodes, with one connected central component of 210 app families (58.5%). Most (143/222, 64.4%) of the sampled app families did not report sharing any data and were therefore isolated from each other and from the core network. Fifteen app families assumed more central network positions as gatekeepers on the shortest paths that data would have to travel between other app families. This cross-sectional analysis highlights the possibilities for user data collection and potential paths that data is able to travel among a sample of prominent health and fitness apps. While individual apps may not collect personally identifiable information, app families and the partners with which they share data may be able to aggregate consumer data, thus achieving a much more comprehensive picture of the individual consumer. The organizations behind the centrally connected app families represent diverse industries, including apparel manufacturers and social media platforms that are not traditionally involved in health or fitness. This analysis highlights the potential for anticipated and voluntary but also possibly unanticipated and involuntary sharing of user data, validating privacy and security concerns in mobile health. ©Quinn Grundy, Fabian P Held, Lisa A Bero. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 28.06.2017.

Information-Sharing Application Standards for Integrated Government Systems

DTIC Science & Technology

2010-12-01

23 4. Federated Search and Role-Based Data Access ................ 24 G. LESSONS FROM HSIN...4. Federated Search and Role-Based Data Access One of the original purposes of HSIN was to facilitate information sharing...recent search paradigm, Federated Search , allows separate systems to feed external data requests without the need for a huge centralized database

Out of the archaeologist's desk drawer: communicating archaeological data online

NASA Astrophysics Data System (ADS)

Abate, D.; David, M.

2015-08-01

During archaeological field work a huge amount of data is collected, processed and elaborated for further studies and scientific publications. However, access and communication of linked data; associated tools for interrogation, analysis and sharing are often limited at the first stage of the archaeological research, mainly due to issues related to IPR. Information is often released months if not years after the fieldwork. Nowadays great deal of archaeological data is `born digital' in the field or lab. This means databases, pictures and 3D models of finds and excavation contexts could be available for public communication and sharing. Researchers usually restrict access to their data to a small group of people. It follows that data sharing is not so widespread among archaeologists, and dissemination of research is still mostly based on traditional pre-digital means like scientific papers, journal articles and books. This project has implemented a web approach for sharing and communication purposes, exploiting mainly open source technologies which allow a high level of interactivity. The case study presented is the newly Mithraeum excavated in Ostia Antica archaeological site in the framework of the Ostia Marina Project.

Technical and Policy Approaches to Balancing Patient Privacy and Data Sharing in Clinical and Translational Research

PubMed Central

Malin, Bradley; Karp, David; Scheuermann, Richard H.

2010-01-01

Clinical researchers need to share data to support scientific validation and information reuse, and to comply with a host of regulations and directives from funders. Various organizations are constructing informatics resources in the form of centralized databases to ensure widespread availability of data derived from sponsored research. The widespread use of such open databases is contingent on the protection of patient privacy. In this paper, we review several aspects of the privacy-related problems associated with data sharing for clinical research from technical and policy perspectives. We begin with a review of existing policies for secondary data sharing and privacy requirements in the context of data derived from research and clinical settings. In particular, we focus on policies specified by the U.S. National Institutes of Health and the Health Insurance Portability and Accountability Act and touch upon how these policies are related to current, as well as future, use of data stored in public database archives. Next, we address aspects of data privacy and “identifiability” from a more technical perspective, and review how biomedical databanks can be exploited and seemingly anonymous records can be “re-identified” using various resources without compromising or hacking into secure computer systems. We highlight which data features specified in clinical research data models are potentially vulnerable or exploitable. In the process, we recount a recent privacy-related concern associated with the publication of aggregate statistics from pooled genome-wide association studies that has had a significant impact on the data sharing policies of NIH-sponsored databanks. Finally, we conclude with a list of recommendations that cover various technical, legal, and policy mechanisms that open clinical databases can adopt to strengthen data privacy protections as they move toward wider deployment and adoption. PMID:20051768

Shared-Ride Taximeters : State-of-the-Art and Future Potential

DOT National Transportation Integrated Search

1982-05-01

This report describes shared-ride taximeter equipment and operating issues and then identifies the state-of-the-art and the future potential for shared-ride taximeter services. Data were collected as the evaluation contractor to the jointly sponsored...

The journey toward shared governance: the lived experience of nurse managers and staff nurses.

PubMed

Ott, Joyce; Ross, Carl

2014-09-01

The purpose of the study was to explore the lived experience of nurse managers and staff nurses in shared governance. Shared governance refers to systems and services aligned in partnership. The information gained by studying the lived experience of nurse managers and staff nurses in shared governance is valuable for providing knowledge of empowerment. A qualitative design was used. Data were collected through a semi-structured interview using five questions with 11 Registered Nurses. Data were analysed through thematic analysis. Four themes emerged from data analysis. Nurse managers identified the journey of patient satisfaction; journey of empowerment; journey of self-management and journey of wellness. Staff nurses identified the journey of development and implementation of best practice; journey to provide quality patient care, journey to a new culture of nursing; and journey of a variety of challenges. This study supports the idea that collaboration between nurse managers and staff nurses develops a journey toward shared governance. Nursing management can use findings to empower nurses to collaborate with nurse managers toward best practice. This adds to current knowledge that partnership of nurse managers and staff nurses, supports and encourages ownership in shared governance. © 2013 John Wiley & Sons Ltd.

Data Sharing Effect on Article Citation Rate in Paleoceanography

NASA Astrophysics Data System (ADS)

Sears, J. R.

2011-12-01

The validation of scientific results requires reproducible methods and data. Often, however, data sets supporting research articles are not openly accessible and interlinked. This analysis tests whether open sharing and linking of supporting data through the PANGAEA° data library measurably increases the citation rate of articles published between 1993 and 2010 in the journal Paleoceanography as reported in the Thomson Reuters Web of Science database. The 12.85% (171) of articles with publicly available supporting data sets received 19.94% (8,056) of the aggregate citations (40,409). Publicly available data were thus significantly (p=0.007, 95% confidence interval) associated with about 35% more citations per article than the average of all articles sampled over the 18-year study period (1,331), and the increase is fairly consistent over time (14 of 18 years). This relationship between openly available, curated data and increased citation rate may incentivize researchers to share their data.

Distributed Visualization Project

NASA Technical Reports Server (NTRS)

Craig, Douglas; Conroy, Michael; Kickbusch, Tracey; Mazone, Rebecca

2016-01-01

Distributed Visualization allows anyone, anywhere to see any simulation at any time. Development focuses on algorithms, software, data formats, data systems and processes to enable sharing simulation-based information across temporal and spatial boundaries without requiring stakeholders to possess highly-specialized and very expensive display systems. It also introduces abstraction between the native and shared data, which allows teams to share results without giving away proprietary or sensitive data. The initial implementation of this capability is the Distributed Observer Network (DON) version 3.1. DON 3.1 is available for public release in the NASA Software Store (https://software.nasa.gov/software/KSC-13775) and works with version 3.0 of the Model Process Control specification (an XML Simulation Data Representation and Communication Language) to display complex graphical information and associated Meta-Data.

Patients want granular privacy control over health information in electronic medical records.

PubMed

Caine, Kelly; Hanania, Rima

2013-01-01

To assess patients' desire for granular level privacy control over which personal health information should be shared, with whom, and for what purpose; and whether these preferences vary based on sensitivity of health information. A card task for matching health information with providers, questionnaire, and interview with 30 patients whose health information is stored in an electronic medical record system. Most patients' records contained sensitive health information. No patients reported that they would prefer to share all information stored in an electronic medical record (EMR) with all potential recipients. Sharing preferences varied by type of information (EMR data element) and recipient (eg, primary care provider), and overall sharing preferences varied by participant. Patients with and without sensitive records preferred less sharing of sensitive versus less-sensitive information. Patients expressed sharing preferences consistent with a desire for granular privacy control over which health information should be shared with whom and expressed differences in sharing preferences for sensitive versus less-sensitive EMR data. The pattern of results may be used by designers to generate privacy-preserving EMR systems including interfaces for patients to express privacy and sharing preferences. To maintain the level of privacy afforded by medical records and to achieve alignment with patients' preferences, patients should have granular privacy control over information contained in their EMR.

To Share or Not to Share? A Survey of Biomedical Researchers in the U.S. Southwest, an Ethnically Diverse Region.

PubMed

Oushy, Mai H; Palacios, Rebecca; Holden, Alan E C; Ramirez, Amelie G; Gallion, Kipling J; O'Connell, Mary A

2015-01-01

Cancer health disparities research depends on access to biospecimens from diverse racial/ethnic populations. This multimethodological study, using mixed methods for quantitative and qualitative analysis of survey results, assessed barriers, concerns, and practices for sharing biospecimens/data among researchers working with biospecimens from minority populations in a 5 state region of the United States (Arizona, Colorado, New Mexico, Oklahoma, and Texas). The ultimate goals of this research were to understand data sharing barriers among biomedical researchers; guide strategies to increase participation in biospecimen research; and strengthen collaborative opportunities among researchers. Email invitations to anonymous participants (n = 605 individuals identified by the NIH RePORT database), resulted in 112 responses. The survey assessed demographics, specimen collection data, and attitudes about virtual biorepositories. Respondents were primarily principal investigators at PhD granting institutions (91.1%) conducting basic (62.3%) research; most were non-Hispanic White (63.4%) and men (60.6%). The low response rate limited the statistical power of the analyses, further the number of respondents for each survey question was variable. Findings from this study identified barriers to biospecimen research, including lack of access to sufficient biospecimens, and limited availability of diverse tissue samples. Many of these barriers can be attributed to poor annotation of biospecimens, and researchers' unwillingness to share existing collections. Addressing these barriers to accessing biospecimens is essential to combating cancer in general and cancer health disparities in particular. This study confirmed researchers' willingness to participate in a virtual biorepository (n = 50 respondents agreed). However, researchers in this region listed clear specifications for establishing and using such a biorepository: specifications related to standardized procedures, funding, and protections of human subjects and intellectual property. The results help guide strategies to increase data sharing behaviors and to increase participation of researchers with multiethnic biospecimen collections in collaborative research endeavors. Data sharing by researchers is essential to leveraging knowledge and resources needed for the advancement of research on cancer health disparities. Although U.S. funding entities have guidelines for data and resource sharing, future efforts should address researcher preferences in order to promote collaboration to address cancer health disparities.

Publishing descriptions of non-public clinical datasets: proposed guidance for researchers, repositories, editors and funding organisations.

PubMed

Hrynaszkiewicz, Iain; Khodiyar, Varsha; Hufton, Andrew L; Sansone, Susanna-Assunta

2016-01-01

Sharing of experimental clinical research data usually happens between individuals or research groups rather than via public repositories, in part due to the need to protect research participant privacy. This approach to data sharing makes it difficult to connect journal articles with their underlying datasets and is often insufficient for ensuring access to data in the long term. Voluntary data sharing services such as the Yale Open Data Access (YODA) and Clinical Study Data Request (CSDR) projects have increased accessibility to clinical datasets for secondary uses while protecting patient privacy and the legitimacy of secondary analyses but these resources are generally disconnected from journal articles-where researchers typically search for reliable information to inform future research. New scholarly journal and article types dedicated to increasing accessibility of research data have emerged in recent years and, in general, journals are developing stronger links with data repositories. There is a need for increased collaboration between journals, data repositories, researchers, funders, and voluntary data sharing services to increase the visibility and reliability of clinical research. Using the journal Scientific Data as a case study, we propose and show examples of changes to the format and peer-review process for journal articles to more robustly link them to data that are only available on request. We also propose additional features for data repositories to better accommodate non-public clinical datasets, including Data Use Agreements (DUAs).

42 CFR 480.143 - QIO involvement in shared health data systems.

Code of Federal Regulations, 2011 CFR

2011-10-01

... HUMAN SERVICES (CONTINUED) QUALITY IMPROVEMENT ORGANIZATIONS ACQUISITION, PROTECTION, AND DISCLOSURE OF QUALITY IMPROVEMENT ORGANIZATION REVIEW INFORMATION Utilization and Quality Control Quality Improvement Organizations (QIOs) Disclosure of Confidential Information § 480.143 QIO involvement in shared health data...

42 CFR 480.143 - QIO involvement in shared health data systems.

Code of Federal Regulations, 2010 CFR

2010-10-01

... HUMAN SERVICES (CONTINUED) QUALITY IMPROVEMENT ORGANIZATIONS ACQUISITION, PROTECTION, AND DISCLOSURE OF QUALITY IMPROVEMENT ORGANIZATION REVIEW INFORMATION Utilization and Quality Control Quality Improvement Organizations (QIOs) Disclosure of Confidential Information § 480.143 QIO involvement in shared health data...

Petroleum market shares. Progress report on the retailing of gasoline

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1974-08-06

The report is comprised of three major sections: data currently available from industry; data comparisons; and descriptions and rationale for an FEA market share monitoring program. The latter part of this report is a rationale and description of FEA's development of capabilities to monitor changes of both petroleum marketing and distribution. The objective is to provide an ongoing system that reliably measures market shares. Included in the text are discussions of: Previously reported data on gasoline sales; survey of nonbranded independent marketers; company direct sales and independent marketers; gasoline and diesel fuel; and other petroleum products. (GRA)

Big data or bust: realizing the microbial genomics revolution.

PubMed

Raza, Sobia; Luheshi, Leila

2016-02-01

Pathogen genomics has the potential to transform the clinical and public health management of infectious diseases through improved diagnosis, detection and tracking of antimicrobial resistance and outbreak control. However, the wide-ranging benefits of this technology can only fully be realized through the timely collation, integration and sharing of genomic and clinical/epidemiological metadata by all those involved in the delivery of genomic-informed services. As part of our review on bringing pathogen genomics into 'health-service' practice, we undertook extensive stakeholder consultation to examine the factors integral to achieving effective data sharing and integration. Infrastructure tailored to the needs of clinical users, as well as practical support and policies to facilitate the timely and responsible sharing of data with relevant health authorities and beyond, are all essential. We propose a tiered data sharing and integration model to maximize the immediate and longer term utility of microbial genomics in healthcare. Realizing this model at the scale and sophistication necessary to support national and international infection management services is not uncomplicated. Yet the establishment of a clear data strategy is paramount if failures in containing disease spread due to inadequate knowledge sharing are to be averted, and substantial progress made in tackling the dangers posed by infectious diseases.

Effects of an educational programme on shared decision-making among Korean nurses.

PubMed

Jo, Kae-Hwa; An, Gyeong-Ju

2015-12-01

This study was conducted to examine the effects of an educational programme on shared decision-making on end-of-life care performance, moral sensitivity and attitude towards shared decision-making among Korean nurses. A quasi-experimental study with a non-equivalent control group pretest-posttest design was used. Forty-one clinical nurses were recruited as participants from two different university hospitals located in Daegu, Korea. Twenty nurses in the control group received no intervention, and 21 nurses in the experimental group received the educational programme on shared decision-making. Data were collected with a questionnaire covering end-of-life care performance, moral sensitivity and attitude towards shared decision-making. Analysis of the data was done with the chi-square test, t-test and Fisher's exact test using SPSS/Win 17.0 (SPSS, Inc., Chicago, IL, USA). The experimental group showed significantly higher scores in moral sensitivity and attitude towards shared decision-making after the intervention compared with the control group. This study suggests that the educational programme on shared decision-making was effective in increasing the moral sensitivity and attitude towards shared decision-making among Korean nurses. © 2014 Wiley Publishing Asia Pty Ltd.

Seven [Data] Habits of Highly Successful Researchers

NASA Astrophysics Data System (ADS)

Kinkade, D.; Shepherd, A.; Saito, M. A.; Wiebe, P. H.; Ake, H.; Biddle, M.; Copley, N. J.; Rauch, S.; Switzer, M. E.; York, A.

2017-12-01

Navigating the landscape of open science and data sharing can be daunting for the long-tail scientist. From satisfying funder requirements, and ensuring proper attribution for their work, to determining the best repository for data management and archive, there are several facets to be considered. Yet, there is no single source of guidance for investigators who may be using multiple research funding models. What role can existing repositories play to help facilitate a more effective data sharing workflow? The Biological and Chemical Oceanographic Data Management Office (BCO-DMO) is a domain-specific repository occupying the niche between funder and investigator. The office works closely with its stakeholders to develop and provide guidance, services, and tools that assist researchers in meeting their data sharing needs. From determining if BCO-DMO is the appropriate repository to manage an investigator's project data, to ensuring that investigator is able to fulfill funder requirements. The goal is to relieve the investigator of the more difficult aspects of data management and data sharing, while simultaneously educating them in better data management practices that will streamline the process of conducting open research in the future. This presentation will provide an overview of the BCO-DMO repository, highlighting some of the services and guidance the office provides to its community.

District decision-making for health in low-income settings: a case study of the potential of public and private sector data in India and Ethiopia

PubMed Central

Bhattacharyya, Sanghita; Berhanu, Della; Taddesse, Nolawi; Srivastava, Aradhana; Wickremasinghe, Deepthi; Schellenberg, Joanna

2016-01-01

Many low- and middle-income countries have pluralistic health systems where private for-profit and not-for-profit sectors complement the public sector: data shared across sectors can provide information for local decision-making. The third article in a series of four on district decision-making for health in low-income settings, this study shows the untapped potential of existing data through documenting the nature and type of data collected by the public and private health systems, data flow and sharing, use and inter-sectoral linkages in India and Ethiopia. In two districts in each country, semi-structured interviews were conducted with administrators and data managers to understand the type of data maintained and linkages with other sectors in terms of data sharing, flow and use. We created a database of all data elements maintained at district level, categorized by form and according to the six World Health Organization health system blocks. We used content analysis to capture the type of data available for different health system levels. Data flow in the public health sectors of both counties is sequential, formal and systematic. Although multiple sources of data exist outside the public health system, there is little formal sharing of data between sectors. Though not fully operational, Ethiopia has better developed formal structures for data sharing than India. In the private and public sectors, health data in both countries are collected in all six health system categories, with greatest focus on service delivery data and limited focus on supplies, health workforce, governance and contextual information. In the Indian private sector, there is a better balance than in the public sector of data across the six categories. In both India and Ethiopia the majority of data collected relate to maternal and child health. Both countries have huge potential for increased use of health data to guide district decision-making. PMID:27591203

Developing a Business Intelligence Process for a Training Module in SharePoint 2010

NASA Technical Reports Server (NTRS)

Schmidtchen, Bryce; Solano, Wanda M.; Albasini, Colby

2015-01-01

Prior to this project, training information for the employees of the National Center for Critical Processing and Storage (NCCIPS) was stored in an array of unrelated spreadsheets and SharePoint lists that had to be manually updated. By developing a content management system through a web application platform named SharePoint, this training system is now highly automated and provides a much less intensive method of storing training data and scheduling training courses. This system was developed by using SharePoint Designer and laying out the data structure for the interaction between different lists of data about the employees. The automation of data population inside of the lists was accomplished by implementing SharePoint workflows which essentially lay out the logic for how data is connected and calculated between certain lists. The resulting training system is constructed from a combination of five lists of data with a single list acting as the user-friendly interface. This interface is populated with the courses required for each employee and includes past and future information about course requirements. The employees of NCCIPS now have the ability to view, log, and schedule their training information and courses with much more ease. This system will relieve a significant amount of manual input and serve as a powerful informational resource for the employees of NCCIPS in the future.

Length Distributions of Identity by Descent Reveal Fine-Scale Demographic History

PubMed Central

Palamara, Pier Francesco; Lencz, Todd; Darvasi, Ariel; Pe’er, Itsik

2012-01-01

Data-driven studies of identity by descent (IBD) were recently enabled by high-resolution genomic data from large cohorts and scalable algorithms for IBD detection. Yet, haplotype sharing currently represents an underutilized source of information for population-genetics research. We present analytical results on the relationship between haplotype sharing across purportedly unrelated individuals and a population’s demographic history. We express the distribution of IBD sharing across pairs of individuals for segments of arbitrary length as a function of the population’s demography, and we derive an inference procedure to reconstruct such demographic history. The accuracy of the proposed reconstruction methodology was extensively tested on simulated data. We applied this methodology to two densely typed data sets: 500 Ashkenazi Jewish (AJ) individuals and 56 Kenyan Maasai (MKK) individuals (HapMap 3 data set). Reconstructing the demographic history of the AJ cohort, we recovered two subsequent population expansions, separated by a severe founder event, consistent with previous analysis of lower-throughput genetic data and historical accounts of AJ history. In the MKK cohort, high levels of cryptic relatedness were detected. The spectrum of IBD sharing is consistent with a demographic model in which several small-sized demes intermix through high migration rates and result in enrichment of shared long-range haplotypes. This scenario of historically structured demographies might explain the unexpected abundance of runs of homozygosity within several populations. PMID:23103233

The semantic web in translational medicine: current applications and future directions

PubMed Central

Machado, Catia M.; Rebholz-Schuhmann, Dietrich; Freitas, Ana T.; Couto, Francisco M.

2015-01-01

Semantic web technologies offer an approach to data integration and sharing, even for resources developed independently or broadly distributed across the web. This approach is particularly suitable for scientific domains that profit from large amounts of data that reside in the public domain and that have to be exploited in combination. Translational medicine is such a domain, which in addition has to integrate private data from the clinical domain with proprietary data from the pharmaceutical domain. In this survey, we present the results of our analysis of translational medicine solutions that follow a semantic web approach. We assessed these solutions in terms of their target medical use case; the resources covered to achieve their objectives; and their use of existing semantic web resources for the purposes of data sharing, data interoperability and knowledge discovery. The semantic web technologies seem to fulfill their role in facilitating the integration and exploration of data from disparate sources, but it is also clear that simply using them is not enough. It is fundamental to reuse resources, to define mappings between resources, to share data and knowledge. All these aspects allow the instantiation of translational medicine at the semantic web-scale, thus resulting in a network of solutions that can share resources for a faster transfer of new scientific results into the clinical practice. The envisioned network of translational medicine solutions is on its way, but it still requires resolving the challenges of sharing protected data and of integrating semantic-driven technologies into the clinical practice. PMID:24197933

The semantic web in translational medicine: current applications and future directions.

PubMed

Machado, Catia M; Rebholz-Schuhmann, Dietrich; Freitas, Ana T; Couto, Francisco M

2015-01-01

Semantic web technologies offer an approach to data integration and sharing, even for resources developed independently or broadly distributed across the web. This approach is particularly suitable for scientific domains that profit from large amounts of data that reside in the public domain and that have to be exploited in combination. Translational medicine is such a domain, which in addition has to integrate private data from the clinical domain with proprietary data from the pharmaceutical domain. In this survey, we present the results of our analysis of translational medicine solutions that follow a semantic web approach. We assessed these solutions in terms of their target medical use case; the resources covered to achieve their objectives; and their use of existing semantic web resources for the purposes of data sharing, data interoperability and knowledge discovery. The semantic web technologies seem to fulfill their role in facilitating the integration and exploration of data from disparate sources, but it is also clear that simply using them is not enough. It is fundamental to reuse resources, to define mappings between resources, to share data and knowledge. All these aspects allow the instantiation of translational medicine at the semantic web-scale, thus resulting in a network of solutions that can share resources for a faster transfer of new scientific results into the clinical practice. The envisioned network of translational medicine solutions is on its way, but it still requires resolving the challenges of sharing protected data and of integrating semantic-driven technologies into the clinical practice. © The Author 2013. Published by Oxford University Press.

Toward a Tiered Model to Share Clinical Trial Data and Samples in Precision Oncology.

PubMed

Broes, Stefanie; Lacombe, Denis; Verlinden, Michiel; Huys, Isabelle

2018-01-01

The recent revolution in science and technology applied to medical research has left in its wake a trial of biomedical data and human samples; however, its opportunities remain largely unfulfilled due to a number of legal, ethical, financial, strategic, and technical barriers. Precision oncology has been at the vanguard to leverage this potential of "Big data" and samples into meaningful solutions for patients, considering the need for new drug development approaches in this area (due to high costs, late-stage failures, and the molecular diversity of cancer). To harness the potential of the vast quantities of data and samples currently fragmented across databases and biobanks, it is critical to engage all stakeholders and share data and samples across research institutes. Here, we identified two general types of sharing strategies. First, open access models, characterized by the absence of any review panel or decision maker, and second controlled access model where some form of control is exercised by either the donor (i.e., patient), the data provider (i.e., initial organization), or an independent party. Further, we theoretically describe and provide examples of nine different strategies focused on greater sharing of patient data and material. These models provide varying levels of control, access to various data and/or samples, and different types of relationship between the donor, data provider, and data requester. We propose a tiered model to share clinical data and samples that takes into account privacy issues and respects sponsors' legitimate interests. Its implementation would contribute to maximize the value of existing datasets, enabling unraveling the complexity of tumor biology, identify novel biomarkers, and re-direct treatment strategies better, ultimately to help patients with cancer.

Technical and policy approaches to balancing patient privacy and data sharing in clinical and translational research.

PubMed

Malin, Bradley; Karp, David; Scheuermann, Richard H

2010-01-01

Clinical researchers need to share data to support scientific validation and information reuse and to comply with a host of regulations and directives from funders. Various organizations are constructing informatics resources in the form of centralized databases to ensure reuse of data derived from sponsored research. The widespread use of such open databases is contingent on the protection of patient privacy. We review privacy-related problems associated with data sharing for clinical research from technical and policy perspectives. We investigate existing policies for secondary data sharing and privacy requirements in the context of data derived from research and clinical settings. In particular, we focus on policies specified by the US National Institutes of Health and the Health Insurance Portability and Accountability Act and touch on how these policies are related to current and future use of data stored in public database archives. We address aspects of data privacy and identifiability from a technical, although approachable, perspective and summarize how biomedical databanks can be exploited and seemingly anonymous records can be reidentified using various resources without hacking into secure computer systems. We highlight which clinical and translational data features, specified in emerging research models, are potentially vulnerable or exploitable. In the process, we recount a recent privacy-related concern associated with the publication of aggregate statistics from pooled genome-wide association studies that have had a significant impact on the data sharing policies of National Institutes of Health-sponsored databanks. Based on our analysis and observations we provide a list of recommendations that cover various technical, legal, and policy mechanisms that open clinical databases can adopt to strengthen data privacy protection as they move toward wider deployment and adoption.

An i2b2-based, generalizable, open source, self-scaling chronic disease registry

PubMed Central

Quan, Justin; Ortiz, David M; Bousvaros, Athos; Ilowite, Norman T; Inman, Christi J; Marsolo, Keith; McMurry, Andrew J; Sandborg, Christy I; Schanberg, Laura E; Wallace, Carol A; Warren, Robert W; Weber, Griffin M; Mandl, Kenneth D

2013-01-01

Objective Registries are a well-established mechanism for obtaining high quality, disease-specific data, but are often highly project-specific in their design, implementation, and policies for data use. In contrast to the conventional model of centralized data contribution, warehousing, and control, we design a self-scaling registry technology for collaborative data sharing, based upon the widely adopted Integrating Biology & the Bedside (i2b2) data warehousing framework and the Shared Health Research Information Network (SHRINE) peer-to-peer networking software. Materials and methods Focusing our design around creation of a scalable solution for collaboration within multi-site disease registries, we leverage the i2b2 and SHRINE open source software to create a modular, ontology-based, federated infrastructure that provides research investigators full ownership and access to their contributed data while supporting permissioned yet robust data sharing. We accomplish these objectives via web services supporting peer-group overlays, group-aware data aggregation, and administrative functions. Results The 56-site Childhood Arthritis & Rheumatology Research Alliance (CARRA) Registry and 3-site Harvard Inflammatory Bowel Diseases Longitudinal Data Repository now utilize i2b2 self-scaling registry technology (i2b2-SSR). This platform, extensible to federation of multiple projects within and between research networks, encompasses >6000 subjects at sites throughout the USA. Discussion We utilize the i2b2-SSR platform to minimize technical barriers to collaboration while enabling fine-grained control over data sharing. Conclusions The implementation of i2b2-SSR for the multi-site, multi-stakeholder CARRA Registry has established a digital infrastructure for community-driven research data sharing in pediatric rheumatology in the USA. We envision i2b2-SSR as a scalable, reusable solution facilitating interdisciplinary research across diseases. PMID:22733975

An i2b2-based, generalizable, open source, self-scaling chronic disease registry.

PubMed

Natter, Marc D; Quan, Justin; Ortiz, David M; Bousvaros, Athos; Ilowite, Norman T; Inman, Christi J; Marsolo, Keith; McMurry, Andrew J; Sandborg, Christy I; Schanberg, Laura E; Wallace, Carol A; Warren, Robert W; Weber, Griffin M; Mandl, Kenneth D

2013-01-01

Registries are a well-established mechanism for obtaining high quality, disease-specific data, but are often highly project-specific in their design, implementation, and policies for data use. In contrast to the conventional model of centralized data contribution, warehousing, and control, we design a self-scaling registry technology for collaborative data sharing, based upon the widely adopted Integrating Biology & the Bedside (i2b2) data warehousing framework and the Shared Health Research Information Network (SHRINE) peer-to-peer networking software. Focusing our design around creation of a scalable solution for collaboration within multi-site disease registries, we leverage the i2b2 and SHRINE open source software to create a modular, ontology-based, federated infrastructure that provides research investigators full ownership and access to their contributed data while supporting permissioned yet robust data sharing. We accomplish these objectives via web services supporting peer-group overlays, group-aware data aggregation, and administrative functions. The 56-site Childhood Arthritis & Rheumatology Research Alliance (CARRA) Registry and 3-site Harvard Inflammatory Bowel Diseases Longitudinal Data Repository now utilize i2b2 self-scaling registry technology (i2b2-SSR). This platform, extensible to federation of multiple projects within and between research networks, encompasses >6000 subjects at sites throughout the USA. We utilize the i2b2-SSR platform to minimize technical barriers to collaboration while enabling fine-grained control over data sharing. The implementation of i2b2-SSR for the multi-site, multi-stakeholder CARRA Registry has established a digital infrastructure for community-driven research data sharing in pediatric rheumatology in the USA. We envision i2b2-SSR as a scalable, reusable solution facilitating interdisciplinary research across diseases.

Planning for Bike Share Connectivity to Rail Transit

PubMed Central

Griffin, Greg Phillip; Sener, Ipek Nese

2016-01-01

Bike sharing can play a role in providing access to transit stations and then to final destinations, but early implementation of these systems in North America has been opportunistic rather than strategic. This study evaluates local intermodal plan goals using trip data and associated infrastructure such as transit stops and bike share station locations in Austin, Texas, and Chicago, Illinois. Bike sharing use data from both cities suggest a weak relationship with existing rail stations that could be strengthened through collaborative, intermodal planning. The study suggests a planning framework and example language that could be tailored to help address the linkage between bike sharing and transit. Rather than an exhaustive study of the practice, this study provides evidence from these two cities that identify opportunities to improve intermodal planning. Cities that are planning or expanding a bike sharing system should consider carefully how to leverage this mode with existing modes of transport. Regardless of a city’s status in implementing a bike sharing system, planners can leverage information on existing transport systems for planning at regional and local levels. PMID:27872554

Supporting shared data structures on distributed memory architectures

NASA Technical Reports Server (NTRS)

Koelbel, Charles; Mehrotra, Piyush; Vanrosendale, John

1990-01-01

Programming nonshared memory systems is more difficult than programming shared memory systems, since there is no support for shared data structures. Current programming languages for distributed memory architectures force the user to decompose all data structures into separate pieces, with each piece owned by one of the processors in the machine, and with all communication explicitly specified by low-level message-passing primitives. A new programming environment is presented for distributed memory architectures, providing a global name space and allowing direct access to remote parts of data values. The analysis and program transformations required to implement this environment are described, and the efficiency of the resulting code on the NCUBE/7 and IPSC/2 hypercubes are described.

CloudMan as a platform for tool, data, and analysis distribution

PubMed Central

2012-01-01

Background Cloud computing provides an infrastructure that facilitates large scale computational analysis in a scalable, democratized fashion, However, in this context it is difficult to ensure sharing of an analysis environment and associated data in a scalable and precisely reproducible way. Results CloudMan (usecloudman.org) enables individual researchers to easily deploy, customize, and share their entire cloud analysis environment, including data, tools, and configurations. Conclusions With the enabled customization and sharing of instances, CloudMan can be used as a platform for collaboration. The presented solution improves accessibility of cloud resources, tools, and data to the level of an individual researcher and contributes toward reproducibility and transparency of research solutions. PMID:23181507

NSF Policies on Software and Data Sharing and their Implementation

NASA Astrophysics Data System (ADS)

Katz, Daniel

2014-01-01

Since January 2011, the National Science Foundation has required a Data Management plan to be submitted with all proposals. This plan should include a description of how the proposers will share the products of the research (http://www.nsf.gov/bfa/dias/policy/dmp.jsp). What constitutes such data will be determined by the community of interest through the process of peer review and program management. This may include, but is not limited to: data, publications, samples, physical collections, software and models. In particular, “investigators and grantees are encouraged to share software and inventions created under an award or otherwise make them or their products widely available and usable.”

Feasibility of Homomorphic Encryption for Sharing I2B2 Aggregate-Level Data in the Cloud

PubMed Central

Raisaro, Jean Louis; Klann, Jeffrey G; Wagholikar, Kavishwar B; Estiri, Hossein; Hubaux, Jean-Pierre; Murphy, Shawn N

2018-01-01

The biomedical community is lagging in the adoption of cloud computing for the management of medical data. The primary obstacles are concerns about privacy and security. In this paper, we explore the feasibility of using advanced privacy-enhancing technologies in order to enable the sharing of sensitive clinical data in a public cloud. Our goal is to facilitate sharing of clinical data in the cloud by minimizing the risk of unintended leakage of sensitive clinical information. In particular, we focus on homomorphic encryption, a specific type of encryption that offers the ability to run computation on the data while the data remains encrypted. This paper demonstrates that homomorphic encryption can be used efficiently to compute aggregating queries on the ciphertexts, along with providing end-to-end confidentiality of aggregate-level data from the i2b2 data model. PMID:29888067

Feasibility of Homomorphic Encryption for Sharing I2B2 Aggregate-Level Data in the Cloud.

PubMed

Raisaro, Jean Louis; Klann, Jeffrey G; Wagholikar, Kavishwar B; Estiri, Hossein; Hubaux, Jean-Pierre; Murphy, Shawn N

2018-01-01

The biomedical community is lagging in the adoption of cloud computing for the management of medical data. The primary obstacles are concerns about privacy and security. In this paper, we explore the feasibility of using advanced privacy-enhancing technologies in order to enable the sharing of sensitive clinical data in a public cloud. Our goal is to facilitate sharing of clinical data in the cloud by minimizing the risk of unintended leakage of sensitive clinical information. In particular, we focus on homomorphic encryption, a specific type of encryption that offers the ability to run computation on the data while the data remains encrypted. This paper demonstrates that homomorphic encryption can be used efficiently to compute aggregating queries on the ciphertexts, along with providing end-to-end confidentiality of aggregate-level data from the i2b2 data model.

This presentation will discuss how PLOS ONE collaborates with many different scientific communities to help create, share, and preserve the scholarly works produced by their researchers with emphasis on current common difficulties faced by communities, practical solutions, and a broader view of the importance of open data and reproducibility.

NASA Astrophysics Data System (ADS)

Kroffe, K.

2017-12-01

The mission of the Public Library of Science is to accelerate progress in science and medicine by leading a transformation in research communication. Researchers' ability to share their work without restriction is essential, but critical to sharing is open data, transparency in peer review, and an open approach to science assessment. In this session, we will discuss how PLOS ONE collaborates with many different scientific communities to help create, share, and preserve the scholarly works produced by their researchers with emphasis on current common difficulties faced by communities, practical solutions, and a broader view of the importance of open data and reproducibility.

Physician response to the United Mine Workers' cost-sharing program: the other side of the coin.

PubMed Central

Fahs, M C

1992-01-01

The effect of cost sharing on health services utilization is analyzed from a new perspective, that is, its effects on physician response to cost sharing. A primary data set was constructed using medical records and billing files from a large multispecialty group practice during the three-year period surrounding the introduction of cost sharing to the United Mine Workers Health and Retirement Fund. This same group practice also served an equally large number of patients covered by United Steelworkers' health benefit plans, for which similar utilization data were available. The questions addressed in this interinsurer study are: (1) to what extent does a physician's treatment of medically similar cases vary, following a drop in patient visits as a result of cost sharing? and (2) what is the impact, if any, on costs of care for other patients in the practice (e.g., "spillover effects" such as cost shifting)? Answers to these kinds of questions are necessary to predict the effects of cost sharing on overall health care costs. A fixed-effects model of physician service use was applied to data on episodes of treatment for all patients in a private group practice. This shows that the introduction of cost sharing to some patients in a practice does, in fact, increase the treatment costs to other patients in the same practice who remain under stable insurance plans. The analysis demonstrates that when the economic effects of cost sharing on physician service use are analyzed for all patients within a physician practice, the findings are remarkably different from those of an analysis limited to those patients directly affected by cost sharing. PMID:1563952

Alternative Fuels Data Center: Natural Gas Related Links

Science.gov Websites

, AGA provides services to member natural gas pipelines, marketers, gatherers, international gas Natural Gas Printable Version Share this resource Send a link to Alternative Fuels Data Center : Natural Gas Related Links to someone by E-mail Share Alternative Fuels Data Center: Natural Gas Related

Historical Development and Key Issues of Data Management Plan Requirements for National Science Foundation Grants: A Review

ERIC Educational Resources Information Center

Pasek, Judith E.

2017-01-01

Sharing scientific research data has become increasingly important for knowledge advancement in today's networked, digital world. This article describes the evolution of access to United States government information in relation to scientific research funded by federal grants. It analyzes the data sharing policy of the National Science Foundation,…

The Multiple-Institution Database for Investigating Engineering Longitudinal Development: An Experiential Case Study of Data Sharing and Reuse

ERIC Educational Resources Information Center

Ohland, Matthew W.; Long, Russell A.

2016-01-01

Sharing longitudinal student record data and merging data from different sources is critical to addressing important questions being asked of higher education. The Multiple-Institution Database for Investigating Engineering Longitudinal Development (MIDFIELD) is a multi-institution, longitudinal, student record level dataset that is used to answer…

Canadian Open Genetics Repository (COGR): a unified clinical genomics database as a community resource for standardising and sharing genetic interpretations.

PubMed

Lerner-Ellis, Jordan; Wang, Marina; White, Shana; Lebo, Matthew S

2015-07-01

The Canadian Open Genetics Repository is a collaborative effort for the collection, storage, sharing and robust analysis of variants reported by medical diagnostics laboratories across Canada. As clinical laboratories adopt modern genomics technologies, the need for this type of collaborative framework is increasingly important. A survey to assess existing protocols for variant classification and reporting was delivered to clinical genetics laboratories across Canada. Based on feedback from this survey, a variant assessment tool was made available to all laboratories. Each participating laboratory was provided with an instance of GeneInsight, a software featuring versioning and approval processes for variant assessments and interpretations and allowing for variant data to be shared between instances. Guidelines were established for sharing data among clinical laboratories and in the final outreach phase, data will be made readily available to patient advocacy groups for general use. The survey demonstrated the need for improved standardisation and data sharing across the country. A variant assessment template was made available to the community to aid with standardisation. Instances of the GeneInsight tool were provided to clinical diagnostic laboratories across Canada for the purpose of uploading, transferring, accessing and sharing variant data. As an ongoing endeavour and a permanent resource, the Canadian Open Genetics Repository aims to serve as a focal point for the collaboration of Canadian laboratories with other countries in the development of tools that take full advantage of laboratory data in diagnosing, managing and treating genetic diseases. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Peer Norms and Sharing of Injection Paraphernalia among Puerto Rican Injection Drug Users in New York and Puerto Rico

ERIC Educational Resources Information Center

Andia, Jonny F.; Deren, Sherry; Robles, Rafaela R.; Kang, Sung-Yeon; Colon, Hector M.

2008-01-01

This study examines the influence of peer norms on sharing of injection paraphernalia (e.g., indirect sharing behaviors, including sharing of cookers, cotton, rinse water and back/front loading) among Puerto Rican injection drug users (IDUs) in Bayamon, Puerto Rico, and East Harlem, New York City. Data were collected from 873 Puerto Rican IDUs…

Privacy Protection Standards for the Information Sharing Environment

DTIC Science & Technology

2009-09-01

enable ISE participants to share information and data (see ISE Implementation Plan, p. 51, ISE Enterprise Architecture Framework, pp. 67, 73–74 and...of frontiers. This article shall not prevent States from requiring the licensing of broadcasting, television or cinema enterprises. 2. The exercise...5 U.S.C. § 552a, as amended. Program Manager-Information Sharing Environment. (2008). Information Sharing Enterprise Architecture Framework

Combining Distributed and Shared Memory Models: Approach and Evolution of the Global Arrays Toolkit

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nieplocha, Jarek; Harrison, Robert J.; Kumar, Mukul

2002-07-29

Both shared memory and distributed memory models have advantages and shortcomings. Shared memory model is much easier to use but it ignores data locality/placement. Given the hierarchical nature of the memory subsystems in the modern computers this characteristic might have a negative impact on performance and scalability. Various techniques, such as code restructuring to increase data reuse and introducing blocking in data accesses, can address the problem and yield performance competitive with message passing[Singh], however at the cost of compromising the ease of use feature. Distributed memory models such as message passing or one-sided communication offer performance and scalability butmore » they compromise the ease-of-use. In this context, the message-passing model is sometimes referred to as?assembly programming for the scientific computing?. The Global Arrays toolkit[GA1, GA2] attempts to offer the best features of both models. It implements a shared-memory programming model in which data locality is managed explicitly by the programmer. This management is achieved by explicit calls to functions that transfer data between a global address space (a distributed array) and local storage. In this respect, the GA model has similarities to the distributed shared-memory models that provide an explicit acquire/release protocol. However, the GA model acknowledges that remote data is slower to access than local data and allows data locality to be explicitly specified and hence managed. The GA model exposes to the programmer the hierarchical memory of modern high-performance computer systems, and by recognizing the communication overhead for remote data transfer, it promotes data reuse and locality of reference. This paper describes the characteristics of the Global Arrays programming model, capabilities of the toolkit, and discusses its evolution.« less

Toward a Tiered Model to Share Clinical Trial Data and Samples in Precision Oncology

PubMed Central

Broes, Stefanie; Lacombe, Denis; Verlinden, Michiel; Huys, Isabelle

2018-01-01

The recent revolution in science and technology applied to medical research has left in its wake a trial of biomedical data and human samples; however, its opportunities remain largely unfulfilled due to a number of legal, ethical, financial, strategic, and technical barriers. Precision oncology has been at the vanguard to leverage this potential of “Big data” and samples into meaningful solutions for patients, considering the need for new drug development approaches in this area (due to high costs, late-stage failures, and the molecular diversity of cancer). To harness the potential of the vast quantities of data and samples currently fragmented across databases and biobanks, it is critical to engage all stakeholders and share data and samples across research institutes. Here, we identified two general types of sharing strategies. First, open access models, characterized by the absence of any review panel or decision maker, and second controlled access model where some form of control is exercised by either the donor (i.e., patient), the data provider (i.e., initial organization), or an independent party. Further, we theoretically describe and provide examples of nine different strategies focused on greater sharing of patient data and material. These models provide varying levels of control, access to various data and/or samples, and different types of relationship between the donor, data provider, and data requester. We propose a tiered model to share clinical data and samples that takes into account privacy issues and respects sponsors’ legitimate interests. Its implementation would contribute to maximize the value of existing datasets, enabling unraveling the complexity of tumor biology, identify novel biomarkers, and re-direct treatment strategies better, ultimately to help patients with cancer. PMID:29435448

Shared Governance and Regional Accreditation: Institutional Processes and Perceptions

ERIC Educational Resources Information Center

McGrane, Wendy L.

2013-01-01

This qualitative single-case research study was conducted to gain deeper understanding of the institutional processes to address shared governance accreditation criteria and to determine whether institutional processes altered stakeholder perceptions of shared governance. The data collection strategies were archival records and personal…

Comparison of two paradigms for distributed shared memory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Levelt, W.G.; Kaashoek, M.F.; Bal, H.E.

1990-08-01

The paper compares two paradigms for Distributed Shared Memory on loosely coupled computing systems: the shared data-object model as used in Orca, a programming language specially designed for loosely coupled computing systems and the Shared Virtual Memory model. For both paradigms the authors have implemented two systems, one using only point-to-point messages, the other using broadcasting as well. They briefly describe these two paradigms and their implementations. Then they compare their performance on four applications: the traveling salesman problem, alpha-beta search, matrix multiplication and the all pairs shortest paths problem. The measurements show that both paradigms can be used efficientlymore » for programming large-grain parallel applications. Significant speedups were obtained on all applications. The unstructured Shared Virtual Memory paradigm achieves the best absolute performance, although this is largely due to the preliminary nature of the Orca compiler used. The structured shared data-object model achieves the highest speedups and is much easier to program and to debug.« less

Data governance and data sharing agreements for community-wide health information exchange: lessons from the beacon communities.

PubMed

Allen, Claudia; Des Jardins, Terrisca R; Heider, Arvela; Lyman, Kristin A; McWilliams, Lee; Rein, Alison L; Schachter, Abigail A; Singh, Ranjit; Sorondo, Barbara; Topper, Joan; Turske, Scott A

2014-01-01

Unprecedented efforts are underway across the United States to electronically capture and exchange health information to improve health care and population health, and reduce costs. This increased collection and sharing of electronic patient data raises several governance issues, including privacy, security, liability, and market competition. Those engaged in such efforts have had to develop data sharing agreements (DSAs) among entities involved in information exchange, many of whom are "nontraditional" health care entities and/or new partners. This paper shares lessons learned based on the experiences of six federally funded communities participating in the Beacon Community Cooperative Agreement Program, and offers guidance for navigating data governance issues and developing DSAs to facilitate community-wide health information exchange. While all entities involved in electronic data sharing must address governance issues and create DSAs accordingly, until recently little formal guidance existed for doing so - particularly for community-based initiatives. Despite this lack of guidance, together the Beacon Communities' experiences highlight promising strategies for navigating complex governance issues, which may be useful to other entities or communities initiating information exchange efforts to support delivery system transformation. For the past three years, AcademyHealth has provided technical assistance to most of the 17 Beacon Communities, 6 of whom contributed to this collaborative writing effort. Though these communities varied widely in terms of their demographics, resources, and Beacon-driven priorities, common themes emerged as they described their approaches to data governance and DSA development. The 6 Beacon Communities confirmed that DSAs are necessary to satisfy legal and market-based concerns, and they identified several specific issues, many of which have been noted by others involved in network data sharing initiatives. More importantly, these communities identified several promising approaches to timely and effective DSA development, including: stakeholder engagement; identification and effective communication of value; adoption of a parsimonious approach; attention to market-based concerns; flexibility in adapting and expanding existing agreements and partnerships; and anticipation of required time and investment.

Cyberinfrastructure to Support Collaborative and Reproducible Computational Hydrologic Modeling

NASA Astrophysics Data System (ADS)

Goodall, J. L.; Castronova, A. M.; Bandaragoda, C.; Morsy, M. M.; Sadler, J. M.; Essawy, B.; Tarboton, D. G.; Malik, T.; Nijssen, B.; Clark, M. P.; Liu, Y.; Wang, S. W.

2017-12-01

Creating cyberinfrastructure to support reproducibility of computational hydrologic models is an important research challenge. Addressing this challenge requires open and reusable code and data with machine and human readable metadata, organized in ways that allow others to replicate results and verify published findings. Specific digital objects that must be tracked for reproducible computational hydrologic modeling include (1) raw initial datasets, (2) data processing scripts used to clean and organize the data, (3) processed model inputs, (4) model results, and (5) the model code with an itemization of all software dependencies and computational requirements. HydroShare is a cyberinfrastructure under active development designed to help users store, share, and publish digital research products in order to improve reproducibility in computational hydrology, with an architecture supporting hydrologic-specific resource metadata. Researchers can upload data required for modeling, add hydrology-specific metadata to these resources, and use the data directly within HydroShare.org for collaborative modeling using tools like CyberGIS, Sciunit-CLI, and JupyterHub that have been integrated with HydroShare to run models using notebooks, Docker containers, and cloud resources. Current research aims to implement the Structure For Unifying Multiple Modeling Alternatives (SUMMA) hydrologic model within HydroShare to support hypothesis-driven hydrologic modeling while also taking advantage of the HydroShare cyberinfrastructure. The goal of this integration is to create the cyberinfrastructure that supports hypothesis-driven model experimentation, education, and training efforts by lowering barriers to entry, reducing the time spent on informatics technology and software development, and supporting collaborative research within and across research groups.

77 FR 4277 - Proposed Data Sharing Activity

Federal Register 2010, 2011, 2012, 2013, 2014

2012-01-27

... DEPARTMENT OF COMMERCE Bureau of the Census [Docket Number 120103003-1757-01] Proposed Data Sharing Activity AGENCY: Bureau of the Census, Department of Commerce. ACTION: Notice and request for public comment. SUMMARY: The U.S. Bureau of the Census (Census Bureau) of the Department of Commerce...

Towards a global cancer knowledge network: dissecting the current international cancer genomic sequencing landscape.

PubMed

Vis, D J; Lewin, J; Liao, R G; Mao, M; Andre, F; Ward, R L; Calvo, F; Teh, B T; Camargo, A A; Knoppers, B M; Sawyers, C L; Wessels, L F A; Lawler, M; Siu, L L; Voest, E

2017-05-01

While next generation sequencing has enhanced our understanding of the biological basis of malignancy, current knowledge on global practices for sequencing cancer samples is limited. To address this deficiency, we developed a survey to provide a snapshot of current sequencing activities globally, identify barriers to data sharing and use this information to develop sustainable solutions for the cancer research community. A multi-item survey was conducted assessing demographics, clinical data collection, genomic platforms, privacy/ethics concerns, funding sources and data sharing barriers for sequencing initiatives globally. Additionally, respondents were asked as to provide the primary intent of their initiative (clinical diagnostic, research or combination). Of 107 initiatives invited to participate, 59 responded (response rate = 55%). Whole exome sequencing (P = 0.03) and whole genome sequencing (P = 0.01) were utilized less frequently in clinical diagnostic than in research initiatives. Procedures to identify cancer-specific variants were heterogeneous, with bioinformatics pipelines employing different mutation calling/variant annotation algorithms. Measurement of treatment efficacy varied amongst initiatives, with time on treatment (57%) and RECIST (53%) being the most common; however, other parameters were also employed. Whilst 72% of initiatives indicated data sharing, its scope varied, with a number of restrictions in place (e.g. transfer of raw data). The largest perceived barriers to data harmonization were the lack of financial support (P < 0.01) and bioinformatics concerns (e.g. lack of interoperability) (P = 0.02). Capturing clinical data was more likely to be perceived as a barrier to data sharing by larger initiatives than by smaller initiatives (P = 0.01). These results identify the main barriers, as perceived by the cancer sequencing community, to effective sharing of cancer genomic and clinical data. They highlight the need for greater harmonization of technical, ethical and data capture processes in cancer sample sequencing worldwide, in order to support effective and responsible data sharing for the benefit of patients. © The Author 2017. Published by Oxford University Press on behalf of the European Society for Medical Oncology.

A crystallographic perspective on sharing data and knowledge

NASA Astrophysics Data System (ADS)

Bruno, Ian J.; Groom, Colin R.

2014-10-01

The crystallographic community is in many ways an exemplar of the benefits and practices of sharing data. Since the inception of the technique, virtually every published crystal structure has been made available to others. This has been achieved through the establishment of several specialist data centres, including the Cambridge Crystallographic Data Centre, which produces the Cambridge Structural Database. Containing curated structures of small organic molecules, some containing a metal, the database has been produced for almost 50 years. This has required the development of complex informatics tools and an environment allowing expert human curation. As importantly, a financial model has evolved which has, to date, ensured the sustainability of the resource. However, the opportunities afforded by technological changes and changing attitudes to sharing data make it an opportune moment to review current practices.

Confidentiality and spatially explicit data: Concerns and challenges

PubMed Central

VanWey, Leah K.; Rindfuss, Ronald R.; Gutmann, Myron P.; Entwisle, Barbara; Balk, Deborah L.

2005-01-01

Recent theoretical, methodological, and technological advances in the spatial sciences create an opportunity for social scientists to address questions about the reciprocal relationship between context (spatial organization, environment, etc.) and individual behavior. This emerging research community has yet to adequately address the new threats to the confidentiality of respondent data in spatially explicit social survey or census data files, however. This paper presents four sometimes conflicting principles for the conduct of ethical and high-quality science using such data: protection of confidentiality, the social–spatial linkage, data sharing, and data preservation. The conflict among these four principles is particularly evident in the display of spatially explicit data through maps combined with the sharing of tabular data files. This paper reviews these two research activities and shows how current practices favor one of the principles over the others and do not satisfactorily resolve the conflict among them. Maps are indispensable for the display of results but also reveal information on the location of respondents and sampling clusters that can then be used in combination with shared data files to identify respondents. The current practice of sharing modified or incomplete data sets or using data enclaves is not ideal for either the advancement of science or the protection of confidentiality. Further basic research and open debate are needed to advance both understanding of and solutions to this dilemma. PMID:16230608

Public-private collaboration in spatial data infrastructure: Overview of exposure, acceptance and sharing platform in Malaysia

NASA Astrophysics Data System (ADS)

Othman, Raha binti; Bakar, Muhamad Shahbani Abu; Mahamud, Ku Ruhana Ku

2017-10-01

While Spatial Data Infrastructure (SDI) has been established in Malaysia, the full potential can be further realized. To a large degree, geospatial industry users are hopeful that they can easily get access to the system and start utilizing the data. Some users expect SDI to provide them with readily available data without the necessary steps of requesting the data from the data providers as well as the steps for them to process and to prepare the data for their use. Some further argued that the usability of the system can be improved if appropriate combination between data sharing and focused application is found within the services. In order to address the current challenges and to enhance the effectiveness of the SDI in Malaysia, there is possibility of establishing a collaborative business venture between public and private entities; thus can help addressing the issues and expectations. In this paper, we discussed the possibility of collaboration between these two entities. Interviews with seven entities are held to collect information on the exposure, acceptance and sharing of platform. The outcomes indicate that though the growth of GIS technology and the high level of technology acceptance provides a solid based for utilizing the geospatial data, the absence of concrete policy on data sharing, a quality geospatial data, an authority for coordinator agency, leaves a vacuum for the successful implementation of the SDI initiative.

The HydroServer Platform for Sharing Hydrologic Data

NASA Astrophysics Data System (ADS)

Tarboton, D. G.; Horsburgh, J. S.; Schreuders, K.; Maidment, D. R.; Zaslavsky, I.; Valentine, D. W.

2010-12-01

The CUAHSI Hydrologic Information System (HIS) is an internet based system that supports sharing of hydrologic data. HIS consists of databases connected using the Internet through Web services, as well as software for data discovery, access, and publication. The HIS system architecture is comprised of servers for publishing and sharing data, a centralized catalog to support cross server data discovery and a desktop client to access and analyze data. This paper focuses on HydroServer, the component developed for sharing and publishing space-time hydrologic datasets. A HydroServer is a computer server that contains a collection of databases, web services, tools, and software applications that allow data producers to store, publish, and manage the data from an experimental watershed or project site. HydroServer is designed to permit publication of data as part of a distributed national/international system, while still locally managing access to the data. We describe the HydroServer architecture and software stack, including tools for managing and publishing time series data for fixed point monitoring sites as well as spatially distributed, GIS datasets that describe a particular study area, watershed, or region. HydroServer adopts a standards based approach to data publication, relying on accepted and emerging standards for data storage and transfer. CUAHSI developed HydroServer code is free with community code development managed through the codeplex open source code repository and development system. There is some reliance on widely used commercial software for general purpose and standard data publication capability. The sharing of data in a common format is one way to stimulate interdisciplinary research and collaboration. It is anticipated that the growing, distributed network of HydroServers will facilitate cross-site comparisons and large scale studies that synthesize information from diverse settings, making the network as a whole greater than the sum of its parts in advancing hydrologic research. Details of the CUAHSI HIS can be found at http://his.cuahsi.org, and HydroServer codeplex site http://hydroserver.codeplex.com.

Cooperative storage of shared files in a parallel computing system with dynamic block size

DOEpatents

Bent, John M.; Faibish, Sorin; Grider, Gary

2015-11-10

Improved techniques are provided for parallel writing of data to a shared object in a parallel computing system. A method is provided for storing data generated by a plurality of parallel processes to a shared object in a parallel computing system. The method is performed by at least one of the processes and comprises: dynamically determining a block size for storing the data; exchanging a determined amount of the data with at least one additional process to achieve a block of the data having the dynamically determined block size; and writing the block of the data having the dynamically determined block size to a file system. The determined block size comprises, e.g., a total amount of the data to be stored divided by the number of parallel processes. The file system comprises, for example, a log structured virtual parallel file system, such as a Parallel Log-Structured File System (PLFS).

COINSTAC: Decentralizing the future of brain imaging analysis

PubMed Central

Ming, Jing; Verner, Eric; Sarwate, Anand; Kelly, Ross; Reed, Cory; Kahleck, Torran; Silva, Rogers; Panta, Sandeep; Turner, Jessica; Plis, Sergey; Calhoun, Vince

2017-01-01

In the era of Big Data, sharing neuroimaging data across multiple sites has become increasingly important. However, researchers who want to engage in centralized, large-scale data sharing and analysis must often contend with problems such as high database cost, long data transfer time, extensive manual effort, and privacy issues for sensitive data. To remove these barriers to enable easier data sharing and analysis, we introduced a new, decentralized, privacy-enabled infrastructure model for brain imaging data called COINSTAC in 2016. We have continued development of COINSTAC since this model was first introduced. One of the challenges with such a model is adapting the required algorithms to function within a decentralized framework. In this paper, we report on how we are solving this problem, along with our progress on several fronts, including additional decentralized algorithms implementation, user interface enhancement, decentralized regression statistic calculation, and complete pipeline specifications. PMID:29123643

Sharing Data to Build a Medical Information Commons: From Bermuda to the Global Alliance.

PubMed

Cook-Deegan, Robert; Ankeny, Rachel A; Maxson Jones, Kathryn

2017-08-31

The Human Genome Project modeled its open science ethos on nematode biology, most famously through daily release of DNA sequence data based on the 1996 Bermuda Principles. That open science philosophy persists, but daily, unfettered release of data has had to adapt to constraints occasioned by the use of data from individual people, broader use of data not only by scientists but also by clinicians and individuals, the global reach of genomic applications and diverse national privacy and research ethics laws, and the rising prominence of a diverse commercial genomics sector. The Global Alliance for Genomics and Health was established to enable the data sharing that is essential for making meaning of genomic variation. Data-sharing policies and practices will continue to evolve as researchers, health professionals, and individuals strive to construct a global medical and scientific information commons.

DataUp 2.0: Improving On a Tool For Helping Researchers Archive, Manage, and Share Their Tabular Data

NASA Astrophysics Data System (ADS)

Strasser, C.; Borda, S.; Cruse, P.; Kunze, J.

2013-12-01

There are many barriers to data management and sharing among earth and environmental scientists; among the most significant are a lack of knowledge about best practices for data management, metadata standards, or appropriate data repositories for archiving and sharing data. Last year we developed an open source web application, DataUp, to help researchers overcome these barriers. DataUp helps scientists to (1) determine whether their file is CSV compatible, (2) generate metadata in a standard format, (3) retrieve an identifier to facilitate data citation, and (4) deposit their data into a repository. With funding from the NSF via a supplemental grant to the DataONE project, we are working to improve upon DataUp. Our main goal for DataUp 2.0 is to ensure organizations and repositories are able to adopt and adapt DataUp to meet their unique needs, including connecting to analytical tools, adding new metadata schema, and expanding the list of connected data repositories. DataUp is a collaborative project between the California Digital Library, DataONE, the San Diego Supercomputing Center, and Microsoft Research Connections.

14 CFR 1274.205 - Consortia as recipients.

Code of Federal Regulations, 2012 CFR

2012-01-01

... better share the projects financial costs (e.g., the 50 percent recipient's cost share or other costs of... issues; (8) Internal and external reporting requirements; (9) Management structure of the consortium; (10... the consortia members (12) Agreements, if any, to share existing technology and data; (13) The firm...

14 CFR 1274.205 - Consortia as recipients.

Code of Federal Regulations, 2013 CFR

2013-01-01

... better share the projects financial costs (e.g., the 50 percent recipient's cost share or other costs of... issues; (8) Internal and external reporting requirements; (9) Management structure of the consortium; (10... the consortia members (12) Agreements, if any, to share existing technology and data; (13) The firm...

Trends in Institutional Financing. Practitioner Report.

ERIC Educational Resources Information Center

Brinkman, Paul

Data concerning higher education revenues during fiscal years 1973-1980 were collected. Four institutional perspectives were examined: market shares, sources of revenue, fund balances, and unit revenues. Six consumer-investor dimensions were also covered: the shares from federal, state, and local governments; private donor's share; the school's…

A Review of the Use of Script-Based Tracking in CALL Research for Data Sharing: Applications Providing Meaning Aids

ERIC Educational Resources Information Center

Hwu, Fenfang

2013-01-01

Using script-based tracking to gain insights into the way students learn or process language information can be traced as far back as to the 1980s. Nevertheless, researchers continue to face challenges in collecting and studying this type of data. The objective of this study is to propose data sharing through data repositories as a way to (a) ease…

An accessible, scalable ecosystem for enabling and sharing diverse mass spectrometry imaging analyses

DOE PAGES

Fischer, Curt R.; Ruebel, Oliver; Bowen, Benjamin P.

2015-09-11

Mass spectrometry imaging (MSI) is used in an increasing number of biological applications. Typical MSI datasets contain unique, high-resolution mass spectra from tens of thousands of spatial locations, resulting in raw data sizes of tens of gigabytes per sample. In this paper, we review technical progress that is enabling new biological applications and that is driving an increase in the complexity and size of MSI data. Handling such data often requires specialized computational infrastructure, software, and expertise. OpenMSI, our recently described platform, makes it easy to explore and share MSI datasets via the web – even when larger than 50more » GB. Here we describe the integration of OpenMSI with IPython notebooks for transparent, sharable, and replicable MSI research. An advantage of this approach is that users do not have to share raw data along with analyses; instead, data is retrieved via OpenMSI's web API. The IPython notebook interface provides a low-barrier entry point for data manipulation that is accessible for scientists without extensive computational training. Via these notebooks, analyses can be easily shared without requiring any data movement. We provide example notebooks for several common MSI analysis types including data normalization, plotting, clustering, and classification, and image registration.« less

Transforming Scientific Inquiry: Tapping Into Digital Data by Building a Culture of Transparency and Consent

PubMed Central

Smith, Robert J.; Grande, David; Merchant, Raina M.

2015-01-01

With over 1.7 billion individuals engaged in social media, patients and consumers share more about their lives than ever before through wearable devices, smart phone applications, and social media outlets. This cornucopia of data offers significant opportunity for health researchers and clinicians to track and explore how digital presence contributes to patients’ health outcomes and use of health care resources. While patients readily share their information with online communities, it is imperative that they maintain a sense of autonomy over who has access to such data. Recent data breaches of major insurance companies and retailers illustrate the challenges and vulnerabilities related to information safety and privacy. Many Websites and mobile apps require users to agree to data policies, but how those data are mined, protected, utilized, and externally shared is frequently non-transparent, resulting in a climate of fear and distrust around all forums of digital information sharing. While such skepticism is perhaps justified, it should not deter health researchers from attempting to collect and analyze these novel data for the purpose of designing unique health interventions. By clarifying intent around digital data acquisition, simplifying consent procedures, and affirming a commitment to privacy, the authors contend that health researchers can partner with patients to transform the boundaries of scientific inquiry. PMID:26630607

Transforming Scientific Inquiry: Tapping Into Digital Data by Building a Culture of Transparency and Consent.

PubMed

Smith, Robert J; Grande, David; Merchant, Raina M

2016-04-01

With over 1.7 billion individuals engaged in social media, patients and consumers share more about their lives than ever before through wearable devices, smartphone applications, and social media outlets. This cornucopia of data offers significant opportunity for health researchers and clinicians to track and explore how digital presence contributes to patients' health outcomes and use of health care resources. While patients readily share their information with online communities, it is imperative that they maintain a sense of autonomy over who has access to such data. Recent data breaches of major insurance companies and retailers illustrate the challenges and vulnerabilities related to information safety and privacy. Many Web sites and mobile apps require users to agree to data policies, but how those data are mined, protected, used, and externally shared is frequently nontransparent, resulting in a climate of fear and distrust around all forums of digital information sharing. Although such skepticism is perhaps justified, it should not deter health researchers from attempting to collect and analyze these novel data for the purpose of designing unique health interventions. By clarifying intent around digital data acquisition, simplifying consent procedures, and affirming a commitment to privacy, the authors contend that health researchers can partner with patients to transform the boundaries of scientific inquiry.

An accessible, scalable ecosystem for enabling and sharing diverse mass spectrometry imaging analyses.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fischer, CR; Ruebel, O; Bowen, BP

Mass spectrometry imaging (MSI) is used in an increasing number of biological applications. Typical MSI datasets contain unique, high-resolution mass spectra from tens of thousands of spatial locations, resulting in raw data sizes of tens of gigabytes per sample. In this paper, we review technical progress that is enabling new biological applications and that is driving an increase in the complexity and size of MSI data. Handling such data often requires specialized computational infrastructure, software, and expertise. OpenMSI, our recently described platform, makes it easy to explore and share MSI datasets via the web - even when larger than 50 GB.more » Here we describe the integration of OpenMSI with IPython notebooks for transparent, sharable, and replicable MSI research. An advantage of this approach is that users do not have to share raw data along with analyses; instead, data is retrieved via OpenMSI's web API. The IPython notebook interface provides a low-barrier entry point for data manipulation that is accessible for scientists without extensive computational training. Via these notebooks, analyses can be easily shared without requiring any data movement. We provide example notebooks for several common MSI analysis types including data normalization, plotting, clustering, and classification, and image registration.« less

An accessible, scalable ecosystem for enabling and sharing diverse mass spectrometry imaging analyses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fischer, Curt R.; Ruebel, Oliver; Bowen, Benjamin P.

Mass spectrometry imaging (MSI) is used in an increasing number of biological applications. Typical MSI datasets contain unique, high-resolution mass spectra from tens of thousands of spatial locations, resulting in raw data sizes of tens of gigabytes per sample. In this paper, we review technical progress that is enabling new biological applications and that is driving an increase in the complexity and size of MSI data. Handling such data often requires specialized computational infrastructure, software, and expertise. OpenMSI, our recently described platform, makes it easy to explore and share MSI datasets via the web – even when larger than 50more » GB. Here we describe the integration of OpenMSI with IPython notebooks for transparent, sharable, and replicable MSI research. An advantage of this approach is that users do not have to share raw data along with analyses; instead, data is retrieved via OpenMSI's web API. The IPython notebook interface provides a low-barrier entry point for data manipulation that is accessible for scientists without extensive computational training. Via these notebooks, analyses can be easily shared without requiring any data movement. We provide example notebooks for several common MSI analysis types including data normalization, plotting, clustering, and classification, and image registration.« less

The composition, heating value and renewable share of the energy content of mixed municipal solid waste in Finland

DOE Office of Scientific and Technical Information (OSTI.GOV)

Horttanainen, M., E-mail: mika.horttanainen@lut.fi; Teirasvuo, N.; Kapustina, V.

Highlights: • New experimental data of mixed MSW properties in a Finnish case region. • The share of renewable energy of mixed MSW. • The results were compared with earlier international studies. • The average share of renewable energy was 30% and the average LHVar 19 MJ/kg. • Well operating source separation decreases the renewable energy content of MSW. - Abstract: For the estimation of greenhouse gas emissions from waste incineration it is essential to know the share of the renewable energy content of the combusted waste. The composition and heating value information is generally available, but the renewable energymore » share or heating values of different fractions of waste have rarely been determined. In this study, data from Finnish studies concerning the composition and energy content of mixed MSW were collected, new experimental data on the compositions, heating values and renewable share of energy were presented and the results were compared to the estimations concluded from earlier international studies. In the town of Lappeenranta in south-eastern Finland, the share of renewable energy ranged between 25% and 34% in the energy content tests implemented for two sample trucks. The heating values of the waste and fractions of plastic waste were high in the samples compared to the earlier studies in Finland. These high values were caused by good source separation and led to a low share of renewable energy content in the waste. The results showed that in mixed municipal solid waste the renewable share of the energy content can be significantly lower than the general assumptions (50–60%) when the source separation of organic waste, paper and cardboard is carried out successfully. The number of samples was however small for making extensive conclusions on the results concerning the heating values and renewable share of energy and additional research is needed for this purpose.« less

Sharing data resources benefits owners as well as miners.

NASA Astrophysics Data System (ADS)

Smith, R. W.

2008-12-01

The most fundamental part of any research activity is the data created. Data are most frequently the result of physical measurements but, increasingly, also result from the operation of a computer code. Given that the methods of creation are properly executed and recorded, data have an intrinsic value regardless of the ensuing study in which they are used. Data are part of the intellectual property associated with the work of a scientist. Like any other form of property, the value to the cognizant community depends upon access and available usage. Data that remain on some hidden storage medium are like a bank account storing funds at with no interest accrual, an apparent waste of opportunity. Not sharing data with the cognizant community needs a justification like security risk or possible danger. The historically contentious issue associated with data as intellectual property is the protection of the owner's rights of first use. This paper contends that data sharing is the proper and most productive strategy for scientists to gain the most value from their work. The first example illustrating the point relates to the Alaska Climate Research Center (www.climate.gi.alaska.edu) operated by the Geophysical Institute (GI) where the data is shared on a website that gets 35,000 hits (2000 visits) per day. The data is a mixture of current weather and historical meteorological observations. The latter could be considered the property of the GI. Although most website hits are for the current weather, web inquiries for meteorological observations across the state, some dating back to 1820, are available for all to use. This kind of sharing brings the most volume and greatest value from the stored data. The second relates to the personal observations of GI faculty members who share their measurements directly on the web as soon as they are available. These data are the same as published in their personal work, and are also available for others to use based on some simple "rules of the road". This strategy broadens the applications of his work and results in more co-authorships along the way. Many federal granting agencies require a similar approach of rapid dissemination of data. The recent introduction of virtual observatories has strengthened this approach and also provides a formalism for the protection of data owners.

VLBI-resolution radio-map algorithms: Performance analysis of different levels of data-sharing on multi-socket, multi-core architectures

NASA Astrophysics Data System (ADS)

Tabik, S.; Romero, L. F.; Mimica, P.; Plata, O.; Zapata, E. L.

2012-09-01

A broad area in astronomy focuses on simulating extragalactic objects based on Very Long Baseline Interferometry (VLBI) radio-maps. Several algorithms in this scope simulate what would be the observed radio-maps if emitted from a predefined extragalactic object. This work analyzes the performance and scaling of this kind of algorithms on multi-socket, multi-core architectures. In particular, we evaluate a sharing approach, a privatizing approach and a hybrid approach on systems with complex memory hierarchy that includes shared Last Level Cache (LLC). In addition, we investigate which manual processes can be systematized and then automated in future works. The experiments show that the data-privatizing model scales efficiently on medium scale multi-socket, multi-core systems (up to 48 cores) while regardless of algorithmic and scheduling optimizations, the sharing approach is unable to reach acceptable scalability on more than one socket. However, the hybrid model with a specific level of data-sharing provides the best scalability over all used multi-socket, multi-core systems.

Image Sharing in Radiology-A Primer.

PubMed

Chatterjee, Arindam R; Stalcup, Seth; Sharma, Arjun; Sato, T Shawn; Gupta, Pushpender; Lee, Yueh Z; Malone, Christopher; McBee, Morgan; Hotaling, Elise L; Kansagra, Akash P

2017-03-01

By virtue of its information technology-oriented infrastructure, the specialty of radiology is uniquely positioned to be at the forefront of efforts to promote data sharing across the healthcare enterprise, including particularly image sharing. The potential benefits of image sharing for clinical, research, and educational applications in radiology are immense. In this work, our group-the Association of University Radiologists (AUR) Radiology Research Alliance Task Force on Image Sharing-reviews the benefits of implementing image sharing capability, introduces current image sharing platforms and details their unique requirements, and presents emerging platforms that may see greater adoption in the future. By understanding this complex ecosystem of image sharing solutions, radiologists can become important advocates for the successful implementation of these powerful image sharing resources. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Sharing information about cancer with one's family is associated with improved quality of life.

PubMed

Lai, Carlo; Borrelli, Beatrice; Ciurluini, Paola; Aceto, Paola

2017-10-01

The aim of this study was to investigate the association between cancer patients' ability to share information about their illness with their social network and attachment style dimensions, alexithymia, and quality of life. We hypothesised that ability to share information about one's cancer with family, friends, and medical teams would be positively associated with quality of life and secure attachment and negatively associated with alexithymia. Forty-five cancer patients were recruited from the Psycho-oncology Unit of the San Camillo-Forlanini Hospital in Rome. We collected anamnestic data and self-report data on social sharing ability, quality of life, alexithymia, and attachment. Sharing with family (B = 4.66; SE = 1.82; β = .52; SE = 0.20; t(41) = 2.6; P = .0143) was the only predictor of global health status, and attachment security was the only predictor of mean social sharing (B = 0.25; SE = 0.06; β = .63; SE = 0.14; t(41) = 4.4; P < .0001). Encouraging patients to share information about their experience of cancer may help to improve their quality of life. Attachment security seems to promote social sharing. Psychological assessments of cancer patients should cover both ability to share information about one's cancer with family and attachment security. Copyright © 2016 John Wiley & Sons, Ltd.

Improving the analysis, storage and sharing of neuroimaging data using relational databases and distributed computing.

PubMed

Hasson, Uri; Skipper, Jeremy I; Wilde, Michael J; Nusbaum, Howard C; Small, Steven L

2008-01-15

The increasingly complex research questions addressed by neuroimaging research impose substantial demands on computational infrastructures. These infrastructures need to support management of massive amounts of data in a way that affords rapid and precise data analysis, to allow collaborative research, and to achieve these aims securely and with minimum management overhead. Here we present an approach that overcomes many current limitations in data analysis and data sharing. This approach is based on open source database management systems that support complex data queries as an integral part of data analysis, flexible data sharing, and parallel and distributed data processing using cluster computing and Grid computing resources. We assess the strengths of these approaches as compared to current frameworks based on storage of binary or text files. We then describe in detail the implementation of such a system and provide a concrete description of how it was used to enable a complex analysis of fMRI time series data.

Improving the Analysis, Storage and Sharing of Neuroimaging Data using Relational Databases and Distributed Computing

PubMed Central

Hasson, Uri; Skipper, Jeremy I.; Wilde, Michael J.; Nusbaum, Howard C.; Small, Steven L.

2007-01-01

The increasingly complex research questions addressed by neuroimaging research impose substantial demands on computational infrastructures. These infrastructures need to support management of massive amounts of data in a way that affords rapid and precise data analysis, to allow collaborative research, and to achieve these aims securely and with minimum management overhead. Here we present an approach that overcomes many current limitations in data analysis and data sharing. This approach is based on open source database management systems that support complex data queries as an integral part of data analysis, flexible data sharing, and parallel and distributed data processing using cluster computing and Grid computing resources. We assess the strengths of these approaches as compared to current frameworks based on storage of binary or text files. We then describe in detail the implementation of such a system and provide a concrete description of how it was used to enable a complex analysis of fMRI time series data. PMID:17964812

Anonymizing and Sharing Medical Text Records

PubMed Central

Li, Xiao-Bai; Qin, Jialun

2017-01-01

Health information technology has increased accessibility of health and medical data and benefited medical research and healthcare management. However, there are rising concerns about patient privacy in sharing medical and healthcare data. A large amount of these data are in free text form. Existing techniques for privacy-preserving data sharing deal largely with structured data. Current privacy approaches for medical text data focus on detection and removal of patient identifiers from the data, which may be inadequate for protecting privacy or preserving data quality. We propose a new systematic approach to extract, cluster, and anonymize medical text records. Our approach integrates methods developed in both data privacy and health informatics fields. The key novel elements of our approach include a recursive partitioning method to cluster medical text records based on the similarity of the health and medical information and a value-enumeration method to anonymize potentially identifying information in the text data. An experimental study is conducted using real-world medical documents. The results of the experiments demonstrate the effectiveness of the proposed approach. PMID:29569650

e!DAL--a framework to store, share and publish research data.

PubMed

Arend, Daniel; Lange, Matthias; Chen, Jinbo; Colmsee, Christian; Flemming, Steffen; Hecht, Denny; Scholz, Uwe

2014-06-24

The life-science community faces a major challenge in handling "big data", highlighting the need for high quality infrastructures capable of sharing and publishing research data. Data preservation, analysis, and publication are the three pillars in the "big data life cycle". The infrastructures currently available for managing and publishing data are often designed to meet domain-specific or project-specific requirements, resulting in the repeated development of proprietary solutions and lower quality data publication and preservation overall. e!DAL is a lightweight software framework for publishing and sharing research data. Its main features are version tracking, metadata management, information retrieval, registration of persistent identifiers (DOI), an embedded HTTP(S) server for public data access, access as a network file system, and a scalable storage backend. e!DAL is available as an API for local non-shared storage and as a remote API featuring distributed applications. It can be deployed "out-of-the-box" as an on-site repository. e!DAL was developed based on experiences coming from decades of research data management at the Leibniz Institute of Plant Genetics and Crop Plant Research (IPK). Initially developed as a data publication and documentation infrastructure for the IPK's role as a data center in the DataCite consortium, e!DAL has grown towards being a general data archiving and publication infrastructure. The e!DAL software has been deployed into the Maven Central Repository. Documentation and Software are also available at: http://edal.ipk-gatersleben.de.

IP Sample Plan #4 | NCI Technology Transfer Center | TTC

Cancer.gov

Sample letter from Research Institutes and their principal investigator and consultants, describing a data and research tool sharing plan and procedures for sharing data, research materials, and patent and licensing of intellectual property. This letter is designed to be included as part of an application.

A case study : benefits associated with the sharing of ATMS-related video data in San Antonio, TX

DOT National Transportation Integrated Search

1998-08-11

This paper summarizes various findings relating to the integration of Advanced Traffic Management System (ATMS) components of video data in San Antonio, TX. Specifically, the paper examines the perceived benefits derived from the sharing of video dat...

Data sharing in the ag community - what are current challenges, benefits, and opportunities

USDA-ARS?s Scientific Manuscript database

The model for building agronomic science today and into the future to meet global food demands with limited resources will be through public-private data acquisition, sharing, and collaborative analysis. The public perspective focuses on preserving natural resources. The private perspective focuses ...

Sharing chemical structures with peer-reviewed publications. Are we there yet?

EPA Science Inventory

In the domain of chemistry one of the greatest benefits to publishing research is that data are shared. Unfortunately, the vast majority of chemical structure data remain locked up in document form, primarily as PDF files. Despite the explosive growth of online chemical databases...

The Socio-Technical Design of a Library and Information Science Collaboratory

ERIC Educational Resources Information Center

Lassi, Monica; Sonnenwald, Diane H.

2013-01-01

Introduction: We present a prototype collaboratory, a socio-technical platform to support sharing research data collection instruments in library and information science. No previous collaboratory has attempted to facilitate sharing digital research data collection instruments among library and information science researchers. Method: We have…

Shared decision-making in medical encounters regarding breast cancer treatment: the contribution of methodological triangulation.

PubMed

Durif-Bruckert, C; Roux, P; Morelle, M; Mignotte, H; Faure, C; Moumjid-Ferdjaoui, N

2015-07-01

The aim of this study on shared decision-making in the doctor-patient encounter about surgical treatment for early-stage breast cancer, conducted in a regional cancer centre in France, was to further the understanding of patient perceptions on shared decision-making. The study used methodological triangulation to collect data (both quantitative and qualitative) about patient preferences in the context of a clinical consultation in which surgeons followed a shared decision-making protocol. Data were analysed from a multi-disciplinary research perspective (social psychology and health economics). The triangulated data collection methods were questionnaires (n = 132), longitudinal interviews (n = 47) and observations of consultations (n = 26). Methodological triangulation revealed levels of divergence and complementarity between qualitative and quantitative results that suggest new perspectives on the three inter-related notions of decision-making, participation and information. Patients' responses revealed important differences between shared decision-making and participation per se. The authors note that subjecting patients to a normative behavioural model of shared decision-making in an era when paradigms of medical authority are shifting may undermine the patient's quest for what he or she believes is a more important right: a guarantee of the best care available. © 2014 John Wiley & Sons Ltd.

Local concurrent error detection and correction in data structures using virtual backpointers

NASA Technical Reports Server (NTRS)

Li, C. C.; Chen, P. P.; Fuchs, W. K.

1987-01-01

A new technique, based on virtual backpointers, for local concurrent error detection and correction in linked data structures is presented. Two new data structures, the Virtual Double Linked List, and the B-tree with Virtual Backpointers, are described. For these structures, double errors can be detected in 0(1) time and errors detected during forward moves can be corrected in 0(1) time. The application of a concurrent auditor process to data structure error detection and correction is analyzed, and an implementation is described, to determine the effect on mean time to failure of a multi-user shared database system. The implementation utilizes a Sequent shared memory multiprocessor system operating on a shared databased of Virtual Double Linked Lists.

Local concurrent error detection and correction in data structures using virtual backpointers

NASA Technical Reports Server (NTRS)

Li, Chung-Chi Jim; Chen, Paul Peichuan; Fuchs, W. Kent

1989-01-01

A new technique, based on virtual backpointers, for local concurrent error detection and correction in linked data strutures is presented. Two new data structures, the Virtual Double Linked List, and the B-tree with Virtual Backpointers, are described. For these structures, double errors can be detected in 0(1) time and errors detected during forward moves can be corrected in 0(1) time. The application of a concurrent auditor process to data structure error detection and correction is analyzed, and an implementation is described, to determine the effect on mean time to failure of a multi-user shared database system. The implementation utilizes a Sequent shared memory multiprocessor system operating on a shared database of Virtual Double Linked Lists.

New tools for Content Innovation and data sharing: Enhancing reproducibility and rigor in biomechanics research.

PubMed

Guilak, Farshid

2017-03-21

We are currently in one of the most exciting times for science and engineering as we witness unprecedented growth in our computational and experimental capabilities to generate new data and models. To facilitate data and model sharing, and to enhance reproducibility and rigor in biomechanics research, the Journal of Biomechanics has introduced a number of tools for Content Innovation to allow presentation, sharing, and archiving of methods, models, and data in our articles. The tools include an Interactive Plot Viewer, 3D Geometric Shape and Model Viewer, Virtual Microscope, Interactive MATLAB Figure Viewer, and Audioslides. Authors are highly encouraged to make use of these in upcoming journal submissions. Copyright © 2017 Elsevier Ltd. All rights reserved.

"Why Can't We Share?" after 9/11: The Critical Role of Stakeholders in the Process of Planning Inter-Organizational Information Integration System (IOIS) Change

ERIC Educational Resources Information Center

Stoltzfus, Kimberly Ann

2012-01-01

The problem of information sharing and coordination was made starkly evident by the September 11th attacks. September 11th illuminated the problems that justice agencies had in sharing information in a timely and collaborative nature without an interoperable data-sharing system. A number of government audits and justice agency leaders have sought…

A General Comparison of SharePoint 2007 and SharePoint 2010

DTIC Science & Technology

2012-10-01

rich as some dedicated Wiki offerings, e.g. Confluence, appropriately authorised users can collaboratively develop content. Unlike Wiki pages...Workspace 2010 uses Windows credentials instead of a Groove-specific logon for authenticating users, thus improving consistency with the rest of the Office...environment, such as authentication properties. In SharePoint 2010 the Business Data Connectivity service is the new version of SharePoint 2007’s Business

Optimization of knowledge sharing through multi-forum using cloud computing architecture

NASA Astrophysics Data System (ADS)

Madapusi Vasudevan, Sriram; Sankaran, Srivatsan; Muthuswamy, Shanmugasundaram; Ram, N. Sankar

2011-12-01

Knowledge sharing is done through various knowledge sharing forums which requires multiple logins through multiple browser instances. Here a single Multi-Forum knowledge sharing concept is introduced which requires only one login session which makes user to connect multiple forums and display the data in a single browser window. Also few optimization techniques are introduced here to speed up the access time using cloud computing architecture.

Genomes in the cloud: balancing privacy rights and the public good.

PubMed

Ohno-Machado, Lucila; Farcas, Claudiu; Kim, Jihoon; Wang, Shuang; Jiang, Xiaoqian

2013-01-01

The NIH-funded iDASH1 National Center for Biomedical Computing was created in 2010 with the goal of developing infrastructure, algorithms, and tools to integrate Data for Analysis, 'anonymization,' and SHaring. iDASH is based on the premise that, while a strong case for not sharing information to preserve individual privacy can be made, an equally compelling case for sharing genome information for the public good (i.e., to support new discoveries that promote health or alleviate the burden of disease) should also be made. In fact, these cases do not need to be mutually exclusive: genome data sharing on a cloud does not necessarily have to compromise individual privacy, although current practices need significant improvement. So far, protection of subject data from re-identification and misuse has been relying primarily on regulations such as HIPAA, the Common Rule, and GINA. However, protection of biometrics such as a genome requires specialized infrastructure and tools.

Preserving Patient Privacy When Sharing Same-Disease Data.

PubMed

Liu, Xiaoping; Li, Xiao-Bai; Motiwalla, Luvai; Li, Wenjun; Zheng, Hua; Franklin, Patricia D

2016-10-01

Medical and health data are often collected for studying a specific disease. For such same-disease microdata, a privacy disclosure occurs as long as an individual is known to be in the microdata. Individuals in same-disease microdata are thus subject to higher disclosure risk than those in microdata with different diseases. This important problem has been overlooked in data-privacy research and practice, and no prior study has addressed this problem. In this study, we analyze the disclosure risk for the individuals in same-disease microdata and propose a new metric that is appropriate for measuring disclosure risk in this situation. An efficient algorithm is designed and implemented for anonymizing same-disease data to minimize the disclosure risk while keeping data utility as good as possible. An experimental study was conducted on real patient and population data. Experimental results show that traditional reidentification risk measures underestimate the actual disclosure risk for the individuals in same-disease microdata and demonstrate that the proposed approach is very effective in reducing the actual risk for same-disease data. This study suggests that privacy protection policy and practice for sharing medical and health data should consider not only the individuals' identifying attributes but also the health and disease information contained in the data. It is recommended that data-sharing entities employ a statistical approach, instead of the HIPAA's Safe Harbor policy, when sharing same-disease microdata.

Preserving Patient Privacy When Sharing Same-Disease Data

PubMed Central

LIU, XIAOPING; LI, XIAO-BAI; MOTIWALLA, LUVAI; LI, WENJUN; ZHENG, HUA; FRANKLIN, PATRICIA D.

2016-01-01

Medical and health data are often collected for studying a specific disease. For such same-disease microdata, a privacy disclosure occurs as long as an individual is known to be in the microdata. Individuals in same-disease microdata are thus subject to higher disclosure risk than those in microdata with different diseases. This important problem has been overlooked in data-privacy research and practice, and no prior study has addressed this problem. In this study, we analyze the disclosure risk for the individuals in same-disease microdata and propose a new metric that is appropriate for measuring disclosure risk in this situation. An efficient algorithm is designed and implemented for anonymizing same-disease data to minimize the disclosure risk while keeping data utility as good as possible. An experimental study was conducted on real patient and population data. Experimental results show that traditional reidentification risk measures underestimate the actual disclosure risk for the individuals in same-disease microdata and demonstrate that the proposed approach is very effective in reducing the actual risk for same-disease data. This study suggests that privacy protection policy and practice for sharing medical and health data should consider not only the individuals’ identifying attributes but also the health and disease information contained in the data. It is recommended that data-sharing entities employ a statistical approach, instead of the HIPAA's Safe Harbor policy, when sharing same-disease microdata. PMID:27867450

ClipCard: Sharable, Searchable Visual Metadata Summaries on the Cloud to Render Big Data Actionable

NASA Astrophysics Data System (ADS)

Saripalli, P.; Davis, D.; Cunningham, R.

2013-12-01

Research firm IDC estimates that approximately 90 percent of the Enterprise Big Data go un-analyzed, as 'dark data' - an enormous corpus of undiscovered, untagged information residing on data warehouses, servers and Storage Area Networks (SAN). In the geosciences, these data range from unpublished model runs to vast survey data assets to raw sensor data. Many of these are now being collected instantaneously, at a greater volume and in new data formats. Not all of these data can be analyzed, nor processed in real time, and their features may not be well described at the time of collection. These dark data are a serious data management problem for science organizations of all types, especially ones with mandated or required data reporting and compliance requirements. Additionally, data curators and scientists are encouraged to quantify the impact of their data holdings as a way to measure research success. Deriving actionable insights is the foremost goal of Big Data Analytics (BDA), which is especially true with geoscience, given its direct impact on most of the pressing global issues. Clearly, there is a pressing need for innovative approaches to making dark data discoverable, measurable, and actionable. We report on ClipCard, a Cloud-based SaaS analytic platform for instant summarization, quick search, visualization and easy sharing of metadata summaries form the Dark Data at hierarchical levels of detail, thus rendering it 'white', i.e., actionable. We present a use case of the ClipCard platform, a cloud-based application which helps generate (abstracted) visual metadata summaries and meta-analytics for environmental data at hierarchical scales within and across big data containers. These summaries and analyses provide important new tools for managing big data and simplifying collaboration through easy to deploy sharing APIs. The ClipCard application solves a growing data management bottleneck by helping enterprises and large organizations to summarize, search, discover, and share the potential in their unused data and information assets. Using Cloud as the base platform enables wider reach, quick dissemination and easy sharing of the metadata summaries, without actually storing or sharing the original data assets per se.

Public and Biobank Participant Attitudes toward Genetic Research Participation and Data Sharing

PubMed Central

Lemke, A.A.; Wolf, W.A.; Hebert-Beirne, J.; Smith, M.E.

2010-01-01

Research assessing attitudes toward consent processes for high-throughput genomic-wide technologies and widespread sharing of data is limited. In order to develop a better understanding of stakeholder views toward these issues, this cross-sectional study assessed public and biorepository participant attitudes toward research participation and sharing of genetic research data. Forty-nine individuals participated in 6 focus groups; 28 in 3 public focus groups and 21 in 3 NUgene biorepository participant focus groups. In the public focus groups, 75% of participants were women, 75% had some college education or more, 46% were African-American and 29% were Hispanic. In the NUgene focus groups, 67% of participants were women, 95% had some college education or more, and the majority (76%) of participants was Caucasian. Five major themes were identified in the focus group data: (a) a wide spectrum of understanding of genetic research; (b) pros and cons of participation in genetic research; (c) influence of credibility and trust of the research institution; (d) concerns about sharing genetic research data and need for transparency in the Policy for Sharing of Data in National Institutes of Health-Supported or Conducted Genome-Wide Association Studies; (e) a need for more information and education about genetic research. In order to increase public understanding and address potential concerns about genetic research, future efforts should be aimed at involving the public in genetic research policy development and in identifying or developing appropriate educational strategies to meet the public's needs. PMID:20805700

Using Cryptography to Improve Conjunction Analysis

NASA Astrophysics Data System (ADS)

Hemenway, B.; Welser, B.; Baiocchi, D.

2012-09-01

Coordination of operations between satellite operators is becoming increasingly important to prevent collisions. Unfortunately, this coordination is often handicapped by a lack of trust. Coordination and cooperation between satellite operators can take many forms, however, one specific area where cooperation between operators would yield significant benefits is in the computation of conjunction analyses. Passively collected orbital are of generally of too low fidelity to be of use in conjunction analyses. Each operator, however, maintains high fidelity data about their own satellites. These high fidelity data are significantly more valuable in calculating conjunction analyses than the lower-fidelity data. If operators were to share their high fidelity data overall space situational awareness could be improved. At present, many operators do not share data and as a consequence space situational awareness suffers. Restrictive data sharing policies are primarily motivated by privacy concerns on the part of the satellite operators, as each operator is reluctant or unwilling to share data that might compromise its political or commercial interests. In order to perform the necessary conjunction analyses while still maintaining the privacy of their own data, a few operators have entered data sharing agreements. These operators provide their private data to a trusted outside party, who then performs the conjunction analyses and reports the results to the operators. These types of agreements are not an ideal solution as they require a degree of trust between the parties, and the cost of employing the trusted party can be large. In this work, we present and analyze cryptographic tools that would allow satellite operators to securely calculate conjunction analyses without the help of a trusted outside party, while provably maintaining the privacy of their own orbital information. For example, recent advances in cryptographic protocols, specifically in the area of secure Multiparty Computation (MPC) have the potential to allow satellite operators to perform the necessary conjunction analyses without the need to reveal their orbital information to anyone. This talk will describe how MPC works, and how we propose to use it to facilitate secure information sharing between satellite operators.

Linking social media and medical record data: a study of adults presenting to an academic, urban emergency department.

PubMed

Padrez, Kevin A; Ungar, Lyle; Schwartz, Hansen Andrew; Smith, Robert J; Hill, Shawndra; Antanavicius, Tadas; Brown, Dana M; Crutchley, Patrick; Asch, David A; Merchant, Raina M

2016-06-01

Social media may offer insight into the relationship between an individual's health and their everyday life, as well as attitudes towards health and the perceived quality of healthcare services. To determine the acceptability to patients and potential utility to researchers of a database linking patients' social media content with their electronic medical record (EMR) data. Adult Facebook/Twitter users who presented to an emergency department were queried about their willingness to share their social media data and EMR data with health researchers for the purpose of building a databank for research purposes. Shared posts were searched for select terms about health and healthcare. Of the 5256 patients approached, 2717 (52%) were Facebook and/or Twitter users. 1432 (53%) of those patients agreed to participate in the study. Of these participants, 1008 (71%) consented to share their social media data for the purposes of comparing it with their EMR. Social media data consisted of 1 395 720 posts/tweets to Facebook and Twitter. Participants sharing social media data were slightly younger (29.1±9.8 vs 31.9±10.4 years old; p<0.001), more likely to post at least once a day (42% vs 29%; p=0.003) and more likely to present to the emergency room via self-arrival mode and have private insurance. Of Facebook posts, 7.5% (95% CI 4.8% to 10.2%) were related to health. Individuals with a given diagnosis in their EMR were significantly more likely to use terms related to that diagnosis on Facebook than patients without that diagnosis in their EMR (p<0.0008). Many patients are willing to share and link their social media data with EMR data. Sharing patients have several demographic and clinical differences compared with non-sharers. A database that merges social media with EMR data has the potential to provide insights about individuals' health and health outcomes. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

dCache, Sync-and-Share for Big Data

NASA Astrophysics Data System (ADS)

Millar, AP; Fuhrmann, P.; Mkrtchyan, T.; Behrmann, G.; Bernardt, C.; Buchholz, Q.; Guelzow, V.; Litvintsev, D.; Schwank, K.; Rossi, A.; van der Reest, P.

2015-12-01

The availability of cheap, easy-to-use sync-and-share cloud services has split the scientific storage world into the traditional big data management systems and the very attractive sync-and-share services. With the former, the location of data is well understood while the latter is mostly operated in the Cloud, resulting in a rather complex legal situation. Beside legal issues, those two worlds have little overlap in user authentication and access protocols. While traditional storage technologies, popular in HEP, are based on X.509, cloud services and sync-and-share software technologies are generally based on username/password authentication or mechanisms like SAML or Open ID Connect. Similarly, data access models offered by both are somewhat different, with sync-and-share services often using proprietary protocols. As both approaches are very attractive, dCache.org developed a hybrid system, providing the best of both worlds. To avoid reinventing the wheel, dCache.org decided to embed another Open Source project: OwnCloud. This offers the required modern access capabilities but does not support the managed data functionality needed for large capacity data storage. With this hybrid system, scientists can share files and synchronize their data with laptops or mobile devices as easy as with any other cloud storage service. On top of this, the same data can be accessed via established mechanisms, like GridFTP to serve the Globus Transfer Service or the WLCG FTS3 tool, or the data can be made available to worker nodes or HPC applications via a mounted filesystem. As dCache provides a flexible authentication module, the same user can access its storage via different authentication mechanisms; e.g., X.509 and SAML. Additionally, users can specify the desired quality of service or trigger media transitions as necessary, thus tuning data access latency to the planned access profile. Such features are a natural consequence of using dCache. We will describe the design of the hybrid dCache/OwnCloud system, report on several months of operations experience running it at DESY, and elucidate the future road-map.

An open-source software platform for data management, visualisation, model building and model sharing in water, energy and other resource modelling domains.

NASA Astrophysics Data System (ADS)

Knox, S.; Meier, P.; Mohammed, K.; Korteling, B.; Matrosov, E. S.; Hurford, A.; Huskova, I.; Harou, J. J.; Rosenberg, D. E.; Thilmant, A.; Medellin-Azuara, J.; Wicks, J.

2015-12-01

Capacity expansion on resource networks is essential to adapting to economic and population growth and pressures such as climate change. Engineered infrastructure systems such as water, energy, or transport networks require sophisticated and bespoke models to refine management and investment strategies. Successful modeling of such complex systems relies on good data management and advanced methods to visualize and share data.Engineered infrastructure systems are often represented as networks of nodes and links with operating rules describing their interactions. Infrastructure system management and planning can be abstracted to simulating or optimizing new operations and extensions of the network. By separating the data storage of abstract networks from manipulation and modeling we have created a system where infrastructure modeling across various domains is facilitated.We introduce Hydra Platform, a Free Open Source Software designed for analysts and modelers to store, manage and share network topology and data. Hydra Platform is a Python library with a web service layer for remote applications, called Apps, to connect. Apps serve various functions including network or results visualization, data export (e.g. into a proprietary format) or model execution. This Client-Server architecture allows users to manipulate and share centrally stored data. XML templates allow a standardised description of the data structure required for storing network data such that it is compatible with specific models.Hydra Platform represents networks in an abstract way and is therefore not bound to a single modeling domain. It is the Apps that create domain-specific functionality. Using Apps researchers from different domains can incorporate different models within the same network enabling cross-disciplinary modeling while minimizing errors and streamlining data sharing. Separating the Python library from the web layer allows developers to natively expand the software or build web-based apps in other languages for remote functionality. Partner CH2M is developing a commercial user-interface for Hydra Platform however custom interfaces and visualization tools can be built. Hydra Platform is available on GitHub while Apps will be shared on a central repository.

14 CFR § 1274.205 - Consortia as recipients.

Code of Federal Regulations, 2014 CFR

2014-01-01

... better share the projects financial costs (e.g., the 50 percent recipient's cost share or other costs of... issues; (8) Internal and external reporting requirements; (9) Management structure of the consortium; (10... the consortia members (12) Agreements, if any, to share existing technology and data; (13) The firm...

Shared Understanding and Idiosyncratic Expression in Early Vocabularies

ERIC Educational Resources Information Center

Mayor, Julien; Plunkett, Kim

2014-01-01

To what extent do toddlers have shared vocabularies? We examined CDI data collected from 14,607 infants and toddlers in five countries and measured the amount of variability between individual lexicons during development for both comprehension and production. Early lexicons are highly overlapping. However, beyond 100 words, toddlers share more…

Building Shared Responsibility for Student Learning.

ERIC Educational Resources Information Center

Conzemius, Anne; O'Neill, Jan

Shared responsibility for student learning is neither a program nor a curriculum. It incorporates a set of principles and techniques that gives members of a school community the authority and responsibility to create what is needed, based on the data and culture of their particular school and school district. Sharing responsibility for student…

An adaptable XML based approach for scientific data management and integration

NASA Astrophysics Data System (ADS)

Wang, Fusheng; Thiel, Florian; Furrer, Daniel; Vergara-Niedermayr, Cristobal; Qin, Chen; Hackenberg, Georg; Bourgue, Pierre-Emmanuel; Kaltschmidt, David; Wang, Mo

2008-03-01

Increased complexity of scientific research poses new challenges to scientific data management. Meanwhile, scientific collaboration is becoming increasing important, which relies on integrating and sharing data from distributed institutions. We develop SciPort, a Web-based platform on supporting scientific data management and integration based on a central server based distributed architecture, where researchers can easily collect, publish, and share their complex scientific data across multi-institutions. SciPort provides an XML based general approach to model complex scientific data by representing them as XML documents. The documents capture not only hierarchical structured data, but also images and raw data through references. In addition, SciPort provides an XML based hierarchical organization of the overall data space to make it convenient for quick browsing. To provide generalization, schemas and hierarchies are customizable with XML-based definitions, thus it is possible to quickly adapt the system to different applications. While each institution can manage documents on a Local SciPort Server independently, selected documents can be published to a Central Server to form a global view of shared data across all sites. By storing documents in a native XML database, SciPort provides high schema extensibility and supports comprehensive queries through XQuery. By providing a unified and effective means for data modeling, data access and customization with XML, SciPort provides a flexible and powerful platform for sharing scientific data for scientific research communities, and has been successfully used in both biomedical research and clinical trials.

e!DAL - a framework to store, share and publish research data

PubMed Central

2014-01-01

Background The life-science community faces a major challenge in handling “big data”, highlighting the need for high quality infrastructures capable of sharing and publishing research data. Data preservation, analysis, and publication are the three pillars in the “big data life cycle”. The infrastructures currently available for managing and publishing data are often designed to meet domain-specific or project-specific requirements, resulting in the repeated development of proprietary solutions and lower quality data publication and preservation overall. Results e!DAL is a lightweight software framework for publishing and sharing research data. Its main features are version tracking, metadata management, information retrieval, registration of persistent identifiers (DOI), an embedded HTTP(S) server for public data access, access as a network file system, and a scalable storage backend. e!DAL is available as an API for local non-shared storage and as a remote API featuring distributed applications. It can be deployed “out-of-the-box” as an on-site repository. Conclusions e!DAL was developed based on experiences coming from decades of research data management at the Leibniz Institute of Plant Genetics and Crop Plant Research (IPK). Initially developed as a data publication and documentation infrastructure for the IPK’s role as a data center in the DataCite consortium, e!DAL has grown towards being a general data archiving and publication infrastructure. The e!DAL software has been deployed into the Maven Central Repository. Documentation and Software are also available at: http://edal.ipk-gatersleben.de. PMID:24958009

An Adaptable XML Based Approach for Scientific Data Management and Integration.

PubMed

Wang, Fusheng; Thiel, Florian; Furrer, Daniel; Vergara-Niedermayr, Cristobal; Qin, Chen; Hackenberg, Georg; Bourgue, Pierre-Emmanuel; Kaltschmidt, David; Wang, Mo

2008-02-20

Increased complexity of scientific research poses new challenges to scientific data management. Meanwhile, scientific collaboration is becoming increasing important, which relies on integrating and sharing data from distributed institutions. We develop SciPort, a Web-based platform on supporting scientific data management and integration based on a central server based distributed architecture, where researchers can easily collect, publish, and share their complex scientific data across multi-institutions. SciPort provides an XML based general approach to model complex scientific data by representing them as XML documents. The documents capture not only hierarchical structured data, but also images and raw data through references. In addition, SciPort provides an XML based hierarchical organization of the overall data space to make it convenient for quick browsing. To provide generalization, schemas and hierarchies are customizable with XML-based definitions, thus it is possible to quickly adapt the system to different applications. While each institution can manage documents on a Local SciPort Server independently, selected documents can be published to a Central Server to form a global view of shared data across all sites. By storing documents in a native XML database, SciPort provides high schema extensibility and supports comprehensive queries through XQuery. By providing a unified and effective means for data modeling, data access and customization with XML, SciPort provides a flexible and powerful platform for sharing scientific data for scientific research communities, and has been successfully used in both biomedical research and clinical trials.

An Experimental Study of the Effect of Shared Information on Pilot/Controller Re-Route Negotiation

NASA Technical Reports Server (NTRS)

Farley, Todd C.; Hansman, R. John

1999-01-01

Air-ground data link systems are being developed to enable pilots and air traffic controllers to share information more fully. The sharing of information is generally expected to enhance their shared situation awareness and foster more collaborative decision making. An exploratory, part-task simulator experiment is described which evaluates the extent to which shared information may lead pilots and controllers to cooperate or compete when negotiating route amendments. The results indicate an improvement in situation awareness for pilots and controllers and a willingness to work cooperatively. Independent of data link considerations, the experiment also demonstrates the value of providing controllers with a good-quality weather representation on their plan view displays. Observed improvements in situation awareness and separation assurance are discussed. It is argued that deployment of this relatively simple, low-risk addition to the plan view displays be accelerated.

Probability distribution of extreme share returns in Malaysia

NASA Astrophysics Data System (ADS)

Zin, Wan Zawiah Wan; Safari, Muhammad Aslam Mohd; Jaaman, Saiful Hafizah; Yie, Wendy Ling Shin

2014-09-01

The objective of this study is to investigate the suitable probability distribution to model the extreme share returns in Malaysia. To achieve this, weekly and monthly maximum daily share returns are derived from share prices data obtained from Bursa Malaysia over the period of 2000 to 2012. The study starts with summary statistics of the data which will provide a clue on the likely candidates for the best fitting distribution. Next, the suitability of six extreme value distributions, namely the Gumbel, Generalized Extreme Value (GEV), Generalized Logistic (GLO) and Generalized Pareto (GPA), the Lognormal (GNO) and the Pearson (PE3) distributions are evaluated. The method of L-moments is used in parameter estimation. Based on several goodness of fit tests and L-moment diagram test, the Generalized Pareto distribution and the Pearson distribution are found to be the best fitted distribution to represent the weekly and monthly maximum share returns in Malaysia stock market during the studied period, respectively.

Sharing knowledge of Planetary Datasets through the Web-Based PRoGIS

NASA Astrophysics Data System (ADS)

Giordano, M. G.; Morley, J. M.; Muller, J. P. M.; Barnes, R. B.; Tao, Y. T.

2015-10-01

The large amount of raw and derived data available from various planetary surface missions (e.g. Mars and Moon in our case) has been integrated withco-registered and geocoded orbital image data to provide rover traverses and camera site locations in universal global co-ordinates [1]. This then allows an integrated GIS to use these geocoded products for scientific applications: we aim to create a web interface, PRoGIS, with minimal controls focusing on the usability and visualisation of the data, to allow planetary geologists to share annotated surface observations. These observations in a common context are shared between different tools and software (PRoGIS, Pro3D, 3D point cloud viewer). Our aim is to use only Open Source components that integrate Open Web Services for planetary data to make available an universal platform with a WebGIS interface, as well as a 3D point cloud and a Panorama viewer to explore derived data. On top of these tools we are building capabilities to make and share annotations amongst users. We use Python and Django for the server-side framework and Open Layers 3 for the WebGIS client. For good performance previewing 3D data (point clouds, pictures on the surface and panoramas) we employ ThreeJS, a WebGL Javascript library. Additionally, user and group controls allow scientists to store and share their observations. PRoGIS not only displays data but also launches sophisticated 3D vision reprocessing (PRoVIP) and an immersive 3D analysis environment (PRo3D).

Bayesian analysis of longitudinal dyadic data with informative missing data using a dyadic shared-parameter model.

PubMed

Ahn, Jaeil; Morita, Satoshi; Wang, Wenyi; Yuan, Ying

2017-01-01

Analyzing longitudinal dyadic data is a challenging task due to the complicated correlations from repeated measurements and within-dyad interdependence, as well as potentially informative (or non-ignorable) missing data. We propose a dyadic shared-parameter model to analyze longitudinal dyadic data with ordinal outcomes and informative intermittent missing data and dropouts. We model the longitudinal measurement process using a proportional odds model, which accommodates the within-dyad interdependence using the concept of the actor-partner interdependence effects, as well as dyad-specific random effects. We model informative dropouts and intermittent missing data using a transition model, which shares the same set of random effects as the longitudinal measurement model. We evaluate the performance of the proposed method through extensive simulation studies. As our approach relies on some untestable assumptions on the missing data mechanism, we perform sensitivity analyses to evaluate how the analysis results change when the missing data mechanism is misspecified. We demonstrate our method using a longitudinal dyadic study of metastatic breast cancer.

Fair Shares and Sharing Fairly: A Survey of Public Views on Open Science, Informed Consent and Participatory Research in Biobanking.

PubMed

Joly, Yann; Dalpé, Gratien; So, Derek; Birko, Stanislav

2015-01-01

Biobanks are important resources which enable large-scale genomic research with human samples and data, raising significant ethical concerns about how participants' information is managed and shared. Three previous studies of the Canadian public's opinion about these topics have been conducted. Building on those results, an online survey representing the first study of public perceptions about biobanking spanning all Canadian provinces was conducted. Specifically, this study examined qualitative views about biobank objectives, governance structure, control and ownership of samples and data, benefit sharing, consent practices and data sharing norms, as well as additional questions and ethical concerns expressed by the public. Over half the respondents preferred to give a one-time general consent for the future sharing of their samples among researchers. Most expressed willingness for their data to be shared with the international scientific community rather than used by one or more Canadian institutions. Whereas more respondents indicated a preference for one-time general consent than any other model of consent, they constituted less than half of the total responses, revealing a lack of consensus among survey respondents regarding this question. Respondents identified biobank objectives, governance structure and accountability as the most important information to provide participants. Respondents' concerns about biobanking generally centred around the control and ownership of biological samples and data, especially with respect to potential misuse by insurers, the government and other third parties. Although almost half the respondents suggested that these should be managed by the researchers' institutions, results indicate that the public is interested in being well-informed about these projects and suggest the importance of increased involvement from participants. In conclusion, the study discusses the viability of several proposed models for informed consent, including e-governance, independent trustees and the use of exclusion clauses, in the context of these new findings about the views of the Canadian public.

Fair Shares and Sharing Fairly: A Survey of Public Views on Open Science, Informed Consent and Participatory Research in Biobanking

PubMed Central

Joly, Yann; Dalpé, Gratien; So, Derek; Birko, Stanislav

2015-01-01

Context Biobanks are important resources which enable large-scale genomic research with human samples and data, raising significant ethical concerns about how participants’ information is managed and shared. Three previous studies of the Canadian public’s opinion about these topics have been conducted. Building on those results, an online survey representing the first study of public perceptions about biobanking spanning all Canadian provinces was conducted. Specifically, this study examined qualitative views about biobank objectives, governance structure, control and ownership of samples and data, benefit sharing, consent practices and data sharing norms, as well as additional questions and ethical concerns expressed by the public. Results Over half the respondents preferred to give a one-time general consent for the future sharing of their samples among researchers. Most expressed willingness for their data to be shared with the international scientific community rather than used by one or more Canadian institutions. Whereas more respondents indicated a preference for one-time general consent than any other model of consent, they constituted less than half of the total responses, revealing a lack of consensus among survey respondents regarding this question. Respondents identified biobank objectives, governance structure and accountability as the most important information to provide participants. Respondents’ concerns about biobanking generally centred around the control and ownership of biological samples and data, especially with respect to potential misuse by insurers, the government and other third parties. Although almost half the respondents suggested that these should be managed by the researchers’ institutions, results indicate that the public is interested in being well-informed about these projects and suggest the importance of increased involvement from participants. In conclusion, the study discusses the viability of several proposed models for informed consent, including e-governance, independent trustees and the use of exclusion clauses, in the context of these new findings about the views of the Canadian public. PMID:26154134

Resource implications of preparing individual participant data from a clinical trial to share with external researchers.

PubMed

Tudur Smith, Catrin; Nevitt, Sarah; Appelbe, Duncan; Appleton, Richard; Dixon, Pete; Harrison, Janet; Marson, Anthony; Williamson, Paula; Tremain, Elizabeth

2017-07-17

Demands are increasingly being made for clinical trialists to actively share individual participant data (IPD) collected from clinical trials using responsible methods that protect the confidentiality and privacy of clinical trial participants. Clinical trialists, particularly those receiving public funding, are often concerned about the additional time and money that data-sharing activities will require, but few published empirical data are available to help inform these decisions. We sought to evaluate the activity and resources required to prepare anonymised IPD from a clinical trial in anticipation of a future data-sharing request. Data from two UK publicly funded clinical trials were used for this exercise: 2437 participants with epilepsy recruited from 90 hospital outpatient clinics in the SANAD trial and 146 children with neuro-developmental problems recruited from 18 hospitals in the MENDS trial. We calculated the time and resources required to prepare each anonymised dataset and assemble a data pack ready for sharing. The older SANAD trial (published 2007) required 50 hours of staff time with a total estimated associated cost of £3185 whilst the more recently completed MENDS trial (published 2012) required 39.5 hours of staff time with total estimated associated cost of £2540. Clinical trial researchers, funders and sponsors should consider appropriate resourcing and allow reasonable time for preparing IPD ready for subsequent sharing. This process would be most efficient if prospectively built into the standard operational design and conduct of a clinical trial. Further empirical examples exploring the resource requirements in other settings is recommended. SANAD: International Standard Randomised Controlled Trials Registry: ISRCTN38354748 . Registered on 25 April 2003. EU Clinical Trials Register Eudract 2006-004025-28 . Registered on 16 May 2007. International Standard Randomised Controlled Trials Registry: ISRCTN05534585 /MREC 07/MRE08/43. Registered on 26 January 2007.

Invasive species information networks: Collaboration at multiple scales for prevention, early detection, and rapid response to invasive alien species

USGS Publications Warehouse

Simpson, Annie; Jarnevich, Catherine S.; Madsen, John; Westbrooks, Randy G.; Fournier, Christine; Mehrhoff, Les; Browne, Michael; Graham, Jim; Sellers, Elizabeth A.

2009-01-01

Accurate analysis of present distributions and effective modeling of future distributions of invasive alien species (IAS) are both highly dependent on the availability and accessibility of occurrence data and natural history information about the species. Invasive alien species monitoring and detection networks (such as the Invasive Plant Atlas of New England and the Invasive Plant Atlas of the MidSouth) generate occurrence data at local and regional levels within the United States, which are shared through the US National Institute of Invasive Species Science. The Inter-American Biodiversity Information Network's Invasives Information Network (I3N), facilitates cooperation on sharing invasive species occurrence data throughout the Western Hemisphere. The I3N and other national and regional networks expose their data globally via the Global Invasive Species Information Network (GISIN). International and interdisciplinary cooperation on data sharing strengthens cooperation on strategies and responses to invasions. However, limitations to effective collaboration among invasive species networks leading to successful early detection and rapid response to invasive species include: lack of interoperability; data accessibility; funding; and technical expertise. This paper proposes various solutions to these obstacles at different geographic levels and briefly describes success stories from the invasive species information networks mentioned above. Using biological informatics to facilitate global information sharing is especially critical in invasive species science, as research has shown that one of the best indicators of the invasiveness of a species is whether it has been invasive elsewhere. Data must also be shared across disciplines because natural history information (e.g. diet, predators, habitat requirements, etc.) about a species in its native range is vital for effective prevention, detection, and rapid response to an invasion. Finally, it has been our experience that sharing information, including invasive species dispersal mechanisms and rates, impacts, and prevention and control strategies, enables resource managers and decision-makers to mount a more effective response to biological invasions.

Nurse manager perspective of staff participation in unit level shared governance.

PubMed

Cox Sullivan, Sheila; Norris, Mitzi R; Brown, Lana M; Scott, Karen J

2017-11-01

To examine the nurse manager perspective surrounding implementation of unit level shared governance in one Veterans Health Administration facility. Nursing shared governance is a formal model allowing nursing staff decision-making input into clinical practice, quality improvement, evidence-based practice and staff professional development. Unit level shared governance is a management process where decision authority is delegated to nursing staff at the unit level. Convenience sampling was used to recruit ten nurse managers who participated in face-to-face semi-structured interviews. Data were analysed using content analysis and constant comparison techniques. Demographic data were described using descriptive statistics. The participants included seven female and three male nurse managers with seven Caucasian and three African American. Participant quotes were clustered to identify sub-themes that were then grouped into four global themes to describe unit level shared governance. The global themes were: (1) motivation, (2) demotivation, (3) recommendations for success, and (4) outcomes. These research findings resonate with previous studies that shared governance may be associated with increased nurse empowerment, self-management, engagement, and satisfaction. These findings reflect the need for nurse managers to promote and recognize staff participation in unit level shared governance. © 2017 John Wiley & Sons Ltd.

20180318 - Sharing chemical structures with peer-reviewed publications. Are we there yet? (ACS Spring)

EPA Science Inventory

In the domain of chemistry one of the greatest benefits to publishing research is that data are shared. Unfortunately, the vast majority of chemical structure data remain locked up in document form, primarily as PDF files. Despite the explosive growth of online chemical databases...

Transparency in Teaching: Faculty Share Data and Improve Students' Learning

ERIC Educational Resources Information Center

Winkelmes, Mary-Ann

2013-01-01

The Illinois Initiative on Transparency in Learning and Teaching is a grassroots assessment project designed to promote students' conscious understanding of how they learn and to enable faculty to gather, share, and promptly benefit from data about students' learning by coordinating their efforts across disciplines, institutions, and countries.…

42 CFR 425.708 - Beneficiaries may decline data sharing.

Code of Federal Regulations, 2012 CFR

2012-10-01

... beneficiary for purposes of its care coordination and quality improvement work, and give the beneficiary... to decline data sharing as part of their first primary care service visit with an ACO participant... beneficiaries that have a primary care service office visit with an ACO participant who provides primary care...

42 CFR 425.708 - Beneficiaries may decline data sharing.

Code of Federal Regulations, 2014 CFR

2014-10-01

... beneficiary for purposes of its care coordination and quality improvement work, and give the beneficiary... to decline data sharing as part of their first primary care service visit with an ACO participant... beneficiaries that have a primary care service office visit with an ACO participant who provides primary care...

42 CFR 425.708 - Beneficiaries may decline data sharing.

Code of Federal Regulations, 2013 CFR

2013-10-01

... beneficiary for purposes of its care coordination and quality improvement work, and give the beneficiary... to decline data sharing as part of their first primary care service visit with an ACO participant... beneficiaries that have a primary care service office visit with an ACO participant who provides primary care...

Raising Concerns about Sharing and Reusing Large-Scale Mathematics Classroom Observation Video Data

ERIC Educational Resources Information Center

Ing, Marsha; Samkian, Artineh

2018-01-01

There are great opportunities and challenges to sharing large-scale mathematics classroom observation data. This Research Commentary describes the methodological opportunities and challenges and provides a specific example from a mathematics education research project to illustrate how the research questions and framework drove observational…

Data Sharing to Inform School-Based Asthma Services

ERIC Educational Resources Information Center

Portwood, Sharon G.; Nelson, Elissa B.

2013-01-01

Background: This article examines results and lessons learned from a collaborative project involving a large urban school district, its county health department, multiple community partners, and the local university to establish an effective system for data sharing to inform monitoring and evaluation of the Charlotte Mecklenburg Schools (CMS)…

Sharing Data between Mobile Devices, Connected Vehicles and Infrastructure Task 12 : D2X Hub Prototype Field Test, Evaluation Plan and Results.

DOT National Transportation Integrated Search

2017-10-25

Sharing Data between Mobile Devices, Connected Vehicles and Infrastructure was a U.S. DOT-sponsored research project to study the integration of mobile devices (such as smartphones) into the Connected Vehicle (CV) environment. Objectives includ...

Dynamic load-sharing characteristic analysis of face gear power-split gear system based on tooth contact characteristics

NASA Astrophysics Data System (ADS)

Dong, Hao; Hu, Yahui

2018-04-01

The bend-torsion coupling dynamics load-sharing model of the helicopter face gear split torque transmission system is established by using concentrated quality standard, to analyzing the dynamic load-sharing characteristic. The mathematical models include nonlinear support stiffness, time-varying meshing stiffness, damping, gear backlash. The results showed that the errors collectively influenced the load sharing characteristics, only reduce a certain error, it is never fully reached the perfect loading sharing characteristics. The system load-sharing performance can be improved through floating shaft support. The above-method will provide a theoretical basis and data support for its dynamic performance optimization design.

Secure medical information sharing in cloud computing.

PubMed

Shao, Zhiyi; Yang, Bo; Zhang, Wenzheng; Zhao, Yi; Wu, Zhenqiang; Miao, Meixia

2015-01-01

Medical information sharing is one of the most attractive applications of cloud computing, where searchable encryption is a fascinating solution for securely and conveniently sharing medical data among different medical organizers. However, almost all previous works are designed in symmetric key encryption environment. The only works in public key encryption do not support keyword trapdoor security, have long ciphertext related to the number of receivers, do not support receiver revocation without re-encrypting, and do not preserve the membership of receivers. In this paper, we propose a searchable encryption supporting multiple receivers for medical information sharing based on bilinear maps in public key encryption environment. In the proposed protocol, data owner stores only one copy of his encrypted file and its corresponding encrypted keywords on cloud for multiple designated receivers. The keyword ciphertext is significantly shorter and its length is constant without relation to the number of designated receivers, i.e., for n receivers the ciphertext length is only twice the element length in the group. Only the owner knows that with whom his data is shared, and the access to his data is still under control after having been put on the cloud. We formally prove the security of keyword ciphertext based on the intractability of Bilinear Diffie-Hellman problem and the keyword trapdoor based on Decisional Diffie-Hellman problem.

Cross-Jurisdictional Resource Sharing in Local Health Departments: Implications for Services, Quality, and Cost.

PubMed

Humphries, Debbie L; Hyde, Justeen; Hahn, Ethan; Atherly, Adam; O'Keefe, Elaine; Wilkinson, Geoffrey; Eckhouse, Seth; Huleatt, Steve; Wong, Samuel; Kertanis, Jennifer

2018-01-01

Forty one percent of local health departments in the U.S. serve jurisdictions with populations of 25,000 or less. Researchers, policymakers, and advocates have long questioned how to strengthen public health systems in smaller municipalities. Cross-jurisdictional sharing may increase quality of service, access to resources, and efficiency of resource use. To characterize perceived strengths and challenges of independent and comprehensive sharing approaches, and to assess cost, quality, and breadth of services provided by independent and sharing health departments in Connecticut (CT) and Massachusetts (MA). We interviewed local health directors or their designees from 15 comprehensive resource-sharing jurisdictions and 54 single-municipality jurisdictions in CT and MA using a semi-structured interview. Quantitative data were drawn from closed-ended questions in the semi-structured interviews; municipal demographic data were drawn from the American Community Survey and other public sources. Qualitative data were drawn from open-ended questions in the semi-structured interviews. The findings from this multistate study highlight advantages and disadvantages of two common public health service delivery models - independent and shared. Shared service jurisdictions provided more community health programs and services, and invested significantly more ($120 per thousand (1K) population vs. $69.5/1K population) on healthy food access activities. Sharing departments had more indicators of higher quality food safety inspections (FSIs), and there was a non-linear relationship between cost per FSI and number of FSI. Minimum cost per FSI was reached above the total number of FSI conducted by all but four of the jurisdictions sampled. Independent jurisdictions perceived their governing bodies to have greater understanding of the roles and responsibilities of local public health, while shared service jurisdictions had fewer staff per 1,000 population. There are trade-offs with sharing and remaining independent. Independent health departments serving small jurisdictions have limited resources but strong local knowledge. Multi-municipality departments have more resources but require more time and investment in governance and decision-making. When making decisions about the right service delivery model for a given municipality, careful consideration should be given to local culture and values. Some economies of scale may be achieved through resource sharing for municipalities <25,000 population.

The NIH BD2K center for big data in translational genomics

PubMed Central

Paten, Benedict; Diekhans, Mark; Druker, Brian J; Friend, Stephen; Guinney, Justin; Gassner, Nadine; Guttman, Mitchell; James Kent, W; Mantey, Patrick; Margolin, Adam A; Massie, Matt; Novak, Adam M; Nothaft, Frank; Pachter, Lior; Patterson, David; Smuga-Otto, Maciej; Stuart, Joshua M; Van’t Veer, Laura; Haussler, David

2015-01-01

The world’s genomics data will never be stored in a single repository – rather, it will be distributed among many sites in many countries. No one site will have enough data to explain genotype to phenotype relationships in rare diseases; therefore, sites must share data. To accomplish this, the genetics community must forge common standards and protocols to make sharing and computing data among many sites a seamless activity. Through the Global Alliance for Genomics and Health, we are pioneering the development of shared application programming interfaces (APIs) to connect the world’s genome repositories. In parallel, we are developing an open source software stack (ADAM) that uses these APIs. This combination will create a cohesive genome informatics ecosystem. Using containers, we are facilitating the deployment of this software in a diverse array of environments. Through benchmarking efforts and big data driver projects, we are ensuring ADAM’s performance and utility. PMID:26174866

To Share or Not to Share? A Survey of Biomedical Researchers in the U.S. Southwest, an Ethnically Diverse Region

PubMed Central

Oushy, Mai H.; Palacios, Rebecca; Holden, Alan E. C.; Ramirez, Amelie G.; Gallion, Kipling J.; O’Connell, Mary A.

2015-01-01

Background Cancer health disparities research depends on access to biospecimens from diverse racial/ethnic populations. This multimethodological study, using mixed methods for quantitative and qualitative analysis of survey results, assessed barriers, concerns, and practices for sharing biospecimens/data among researchers working with biospecimens from minority populations in a 5 state region of the United States (Arizona, Colorado, New Mexico, Oklahoma, and Texas). The ultimate goals of this research were to understand data sharing barriers among biomedical researchers; guide strategies to increase participation in biospecimen research; and strengthen collaborative opportunities among researchers. Methods and Population Email invitations to anonymous participants (n = 605 individuals identified by the NIH RePORT database), resulted in 112 responses. The survey assessed demographics, specimen collection data, and attitudes about virtual biorepositories. Respondents were primarily principal investigators at PhD granting institutions (91.1%) conducting basic (62.3%) research; most were non-Hispanic White (63.4%) and men (60.6%). The low response rate limited the statistical power of the analyses, further the number of respondents for each survey question was variable. Results Findings from this study identified barriers to biospecimen research, including lack of access to sufficient biospecimens, and limited availability of diverse tissue samples. Many of these barriers can be attributed to poor annotation of biospecimens, and researchers’ unwillingness to share existing collections. Addressing these barriers to accessing biospecimens is essential to combating cancer in general and cancer health disparities in particular. This study confirmed researchers’ willingness to participate in a virtual biorepository (n = 50 respondents agreed). However, researchers in this region listed clear specifications for establishing and using such a biorepository: specifications related to standardized procedures, funding, and protections of human subjects and intellectual property. The results help guide strategies to increase data sharing behaviors and to increase participation of researchers with multiethnic biospecimen collections in collaborative research endeavors Conclusions Data sharing by researchers is essential to leveraging knowledge and resources needed for the advancement of research on cancer health disparities. Although U.S. funding entities have guidelines for data and resource sharing, future efforts should address researcher preferences in order to promote collaboration to address cancer health disparities. PMID:26378445

Collaborative Data Publication Utilizing the Open Data Repository's Data Publisher

NASA Technical Reports Server (NTRS)

Stone, N.; Lafuente, B.; Bristow, T.; Keller, R. M.; Downs, R. T.; Blake, D.; Fonda, M.; Dateo, C.; Pires, A.

2017-01-01

For small communities in multidisciplinary fields such as astrobiology, publishing and sharing data can be challenging. While large, homogenous fields often have repositories and existing data standards, small groups of independent researchers have few options for publishing data that can be utilized within their community. In conjunction with teams at NASA Ames and the University of Arizona, a number of pilot studies are being conducted to assess the needs of these research groups and to guide the software development so that it allows them to publish and share their data collaboratively.