A Visual Analytics Approach to Structured Data Analysis to Enhance Nonproliferation and Arms Control Verification Activities

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

Gillen, David S.

Analysis activities for Nonproliferation and Arms Control verification require the use of many types of data. Tabular structured data, such as Excel spreadsheets and relational databases, have traditionally been used for data mining activities, where specific queries are issued against data to look for matching results. The application of visual analytics tools to structured data enables further exploration of datasets to promote discovery of previously unknown results. This paper discusses the application of a specific visual analytics tool to datasets related to the field of Arms Control and Nonproliferation to promote the use of visual analytics more broadly in thismore » domain. Visual analytics focuses on analytical reasoning facilitated by interactive visual interfaces (Wong and Thomas 2004). It promotes exploratory analysis of data, and complements data mining technologies where known patterns can be mined for. Also with a human in the loop, they can bring in domain knowledge and subject matter expertise. Visual analytics has not widely been applied to this domain. In this paper, we will focus on one type of data: structured data, and show the results of applying a specific visual analytics tool to answer questions in the Arms Control and Nonproliferation domain. We chose to use the T.Rex tool, a visual analytics tool developed at PNNL, which uses a variety of visual exploration patterns to discover relationships in structured datasets, including a facet view, graph view, matrix view, and timeline view. The facet view enables discovery of relationships between categorical information, such as countries and locations. The graph tool visualizes node-link relationship patterns, such as the flow of materials being shipped between parties. The matrix visualization shows highly correlated categories of information. The timeline view shows temporal patterns in data. In this paper, we will use T.Rex with two different datasets to demonstrate how interactive exploration of the data can aid an analyst with arms control and nonproliferation verification activities. Using a dataset from PIERS (PIERS 2014), we will show how container shipment imports and exports can aid an analyst in understanding the shipping patterns between two countries. We will also use T.Rex to examine a collection of research publications from the IAEA International Nuclear Information System (IAEA 2014) to discover collaborations of concern. We hope this paper will encourage the use of visual analytics structured data analytics in the field of nonproliferation and arms control verification. Our paper outlines some of the challenges that exist before broad adoption of these kinds of tools can occur and offers next steps to overcome these challenges.« less

Streaming Visual Analytics Workshop Report

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

Cook, Kristin A.; Burtner, Edwin R.; Kritzstein, Brian P.

How can we best enable users to understand complex emerging events and make appropriate assessments from streaming data? This was the central question addressed at a three-day workshop on streaming visual analytics. This workshop was organized by Pacific Northwest National Laboratory for a government sponsor. It brought together forty researchers and subject matter experts from government, industry, and academia. This report summarizes the outcomes from that workshop. It describes elements of the vision for a streaming visual analytic environment and set of important research directions needed to achieve this vision. Streaming data analysis is in many ways the analysis andmore » understanding of change. However, current visual analytics systems usually focus on static data collections, meaning that dynamically changing conditions are not appropriately addressed. The envisioned mixed-initiative streaming visual analytics environment creates a collaboration between the analyst and the system to support the analysis process. It raises the level of discourse from low-level data records to higher-level concepts. The system supports the analyst’s rapid orientation and reorientation as situations change. It provides an environment to support the analyst’s critical thinking. It infers tasks and interests based on the analyst’s interactions. The system works as both an assistant and a devil’s advocate, finding relevant data and alerts as well as considering alternative hypotheses. Finally, the system supports sharing of findings with others. Making such an environment a reality requires research in several areas. The workshop discussions focused on four broad areas: support for critical thinking, visual representation of change, mixed-initiative analysis, and the use of narratives for analysis and communication.« less

Towards Analytics for Wholistic School Improvement: Hierarchical Process Modelling and Evidence Visualization

ERIC Educational Resources Information Center

Crick, Ruth Deakin; Knight, Simon; Barr, Steven

2017-01-01

Central to the mission of most educational institutions is the task of preparing the next generation of citizens to contribute to society. Schools, colleges, and universities value a range of outcomes--e.g., problem solving, creativity, collaboration, citizenship, service to community--as well as academic outcomes in traditional subjects. Often…

AuthorSynth: a collaboration network and behaviorally-based visualization tool of activation reports from the neuroscience literature.

PubMed

Sochat, Vanessa V

2015-01-01

Targeted collaboration is becoming more challenging with the ever-increasing number of publications, conferences, and academic responsibilities that the modern-day researcher must synthesize. Specifically, the field of neuroimaging had roughly 10,000 new papers in PubMed for the year 2013, presenting tens of thousands of international authors, each a potential collaborator working on some sub-domain in the field. To remove the burden of synthesizing an entire corpus of publications, talks, and conference interactions to find and assess collaborations, we combine meta-analytical neuroimaging informatics methods with machine learning and network analysis toward this goal. We present "AuthorSynth," a novel application prototype that includes (1) a collaboration network to identify researchers with similar results reported in the literature; and (2) a 2D plot-"brain lattice"-to visually summarize a single author's contribution to the field, and allow for searching of authors based on behavioral terms. This method capitalizes on intelligent synthesis of the neuroimaging literature, and demonstrates that data-driven approaches can be used to confirm existing collaborations, reveal potential ones, and identify gaps in published knowledge. We believe this tool exemplifies how methods from neuroimaging informatics can better inform researchers about progress and knowledge in the field, and enhance the modern workflow of finding collaborations.

MemAxes: Visualization and Analytics for Characterizing Complex Memory Performance Behaviors.

PubMed

Gimenez, Alfredo; Gamblin, Todd; Jusufi, Ilir; Bhatele, Abhinav; Schulz, Martin; Bremer, Peer-Timo; Hamann, Bernd

2018-07-01

Memory performance is often a major bottleneck for high-performance computing (HPC) applications. Deepening memory hierarchies, complex memory management, and non-uniform access times have made memory performance behavior difficult to characterize, and users require novel, sophisticated tools to analyze and optimize this aspect of their codes. Existing tools target only specific factors of memory performance, such as hardware layout, allocations, or access instructions. However, today's tools do not suffice to characterize the complex relationships between these factors. Further, they require advanced expertise to be used effectively. We present MemAxes, a tool based on a novel approach for analytic-driven visualization of memory performance data. MemAxes uniquely allows users to analyze the different aspects related to memory performance by providing multiple visual contexts for a centralized dataset. We define mappings of sampled memory access data to new and existing visual metaphors, each of which enabling a user to perform different analysis tasks. We present methods to guide user interaction by scoring subsets of the data based on known performance problems. This scoring is used to provide visual cues and automatically extract clusters of interest. We designed MemAxes in collaboration with experts in HPC and demonstrate its effectiveness in case studies.

Toward Usable Interactive Analytics: Coupling Cognition and Computation

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

Endert, Alexander; North, Chris; Chang, Remco

Interactive analytics provide users a myriad of computational means to aid in extracting meaningful information from large and complex datasets. Much prior work focuses either on advancing the capabilities of machine-centric approaches by the data mining and machine learning communities, or human-driven methods by the visualization and CHI communities. However, these methods do not yet support a true human-machine symbiotic relationship where users and machines work together collaboratively and adapt to each other to advance an interactive analytic process. In this paper we discuss some of the inherent issues, outlining what we believe are the steps toward usable interactive analyticsmore » that will ultimately increase the effectiveness for both humans and computers to produce insights.« less

Bridging Theory with Practice: An Exploratory Study of Visualization Use and Design for Climate Model Comparison

DOE PAGES

Dasgupta, Aritra; Poco, Jorge; Wei, Yaxing; ...

2015-03-16

Evaluation methodologies in visualization have mostly focused on how well the tools and techniques cater to the analytical needs of the user. While this is important in determining the effectiveness of the tools and advancing the state-of-the-art in visualization research, a key area that has mostly been overlooked is how well established visualization theories and principles are instantiated in practice. This is especially relevant when domain experts, and not visualization researchers, design visualizations for analysis of their data or for broader dissemination of scientific knowledge. There is very little research on exploring the synergistic capabilities of cross-domain collaboration between domainmore » experts and visualization researchers. To fill this gap, in this paper we describe the results of an exploratory study of climate data visualizations conducted in tight collaboration with a pool of climate scientists. The study analyzes a large set of static climate data visualizations for identifying their shortcomings in terms of visualization design. The outcome of the study is a classification scheme that categorizes the design problems in the form of a descriptive taxonomy. The taxonomy is a first attempt for systematically categorizing the types, causes, and consequences of design problems in visualizations created by domain experts. We demonstrate the use of the taxonomy for a number of purposes, such as, improving the existing climate data visualizations, reflecting on the impact of the problems for enabling domain experts in designing better visualizations, and also learning about the gaps and opportunities for future visualization research. We demonstrate the applicability of our taxonomy through a number of examples and discuss the lessons learnt and implications of our findings.« less

Bridging Theory with Practice: An Exploratory Study of Visualization Use and Design for Climate Model Comparison

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

Dasgupta, Aritra; Poco, Jorge; Wei, Yaxing

Evaluation methodologies in visualization have mostly focused on how well the tools and techniques cater to the analytical needs of the user. While this is important in determining the effectiveness of the tools and advancing the state-of-the-art in visualization research, a key area that has mostly been overlooked is how well established visualization theories and principles are instantiated in practice. This is especially relevant when domain experts, and not visualization researchers, design visualizations for analysis of their data or for broader dissemination of scientific knowledge. There is very little research on exploring the synergistic capabilities of cross-domain collaboration between domainmore » experts and visualization researchers. To fill this gap, in this paper we describe the results of an exploratory study of climate data visualizations conducted in tight collaboration with a pool of climate scientists. The study analyzes a large set of static climate data visualizations for identifying their shortcomings in terms of visualization design. The outcome of the study is a classification scheme that categorizes the design problems in the form of a descriptive taxonomy. The taxonomy is a first attempt for systematically categorizing the types, causes, and consequences of design problems in visualizations created by domain experts. We demonstrate the use of the taxonomy for a number of purposes, such as, improving the existing climate data visualizations, reflecting on the impact of the problems for enabling domain experts in designing better visualizations, and also learning about the gaps and opportunities for future visualization research. We demonstrate the applicability of our taxonomy through a number of examples and discuss the lessons learnt and implications of our findings.« less

Multi-Intelligence Analytics for Next Generation Analysts (MIAGA)

NASA Astrophysics Data System (ADS)

Blasch, Erik; Waltz, Ed

2016-05-01

Current analysts are inundated with large volumes of data from which extraction, exploitation, and indexing are required. A future need for next-generation analysts is an appropriate balance between machine analytics from raw data and the ability of the user to interact with information through automation. Many quantitative intelligence tools and techniques have been developed which are examined towards matching analyst opportunities with recent technical trends such as big data, access to information, and visualization. The concepts and techniques summarized are derived from discussions with real analysts, documented trends of technical developments, and methods to engage future analysts with multiintelligence services. For example, qualitative techniques should be matched against physical, cognitive, and contextual quantitative analytics for intelligence reporting. Future trends include enabling knowledge search, collaborative situational sharing, and agile support for empirical decision-making and analytical reasoning.

IN13B-1660: Analytics and Visualization Pipelines for Big Data on the NASA Earth Exchange (NEX) and OpenNEX

NASA Technical Reports Server (NTRS)

Chaudhary, Aashish; Votava, Petr; Nemani, Ramakrishna R.; Michaelis, Andrew; Kotfila, Chris

2016-01-01

We are developing capabilities for an integrated petabyte-scale Earth science collaborative analysis and visualization environment. The ultimate goal is to deploy this environment within the NASA Earth Exchange (NEX) and OpenNEX in order to enhance existing science data production pipelines in both high-performance computing (HPC) and cloud environments. Bridging of HPC and cloud is a fairly new concept under active research and this system significantly enhances the ability of the scientific community to accelerate analysis and visualization of Earth science data from NASA missions, model outputs and other sources. We have developed a web-based system that seamlessly interfaces with both high-performance computing (HPC) and cloud environments, providing tools that enable science teams to develop and deploy large-scale analysis, visualization and QA pipelines of both the production process and the data products, and enable sharing results with the community. Our project is developed in several stages each addressing separate challenge - workflow integration, parallel execution in either cloud or HPC environments and big-data analytics or visualization. This work benefits a number of existing and upcoming projects supported by NEX, such as the Web Enabled Landsat Data (WELD), where we are developing a new QA pipeline for the 25PB system.

Analytics and Visualization Pipelines for Big ­Data on the NASA Earth Exchange (NEX) and OpenNEX

NASA Astrophysics Data System (ADS)

Chaudhary, A.; Votava, P.; Nemani, R. R.; Michaelis, A.; Kotfila, C.

2016-12-01

We are developing capabilities for an integrated petabyte-scale Earth science collaborative analysis and visualization environment. The ultimate goal is to deploy this environment within the NASA Earth Exchange (NEX) and OpenNEX in order to enhance existing science data production pipelines in both high-performance computing (HPC) and cloud environments. Bridging of HPC and cloud is a fairly new concept under active research and this system significantly enhances the ability of the scientific community to accelerate analysis and visualization of Earth science data from NASA missions, model outputs and other sources. We have developed a web-based system that seamlessly interfaces with both high-performance computing (HPC) and cloud environments, providing tools that enable science teams to develop and deploy large-scale analysis, visualization and QA pipelines of both the production process and the data products, and enable sharing results with the community. Our project is developed in several stages each addressing separate challenge - workflow integration, parallel execution in either cloud or HPC environments and big-data analytics or visualization. This work benefits a number of existing and upcoming projects supported by NEX, such as the Web Enabled Landsat Data (WELD), where we are developing a new QA pipeline for the 25PB system.

KNMI DataLab experiences in serving data-driven innovations

NASA Astrophysics Data System (ADS)

Noteboom, Jan Willem; Sluiter, Raymond

2016-04-01

Climate change research and innovations in weather forecasting rely more and more on (Big) data. Besides increasing data from traditional sources (such as observation networks, radars and satellites), the use of open data, crowd sourced data and the Internet of Things (IoT) is emerging. To deploy these sources of data optimally in our services and products, KNMI has established a DataLab to serve data-driven innovations in collaboration with public and private sector partners. Big data management, data integration, data analytics including machine learning and data visualization techniques are playing an important role in the DataLab. Cross-domain data-driven innovations that arise from public-private collaborative projects and research programmes can be explored, experimented and/or piloted by the KNMI DataLab. Furthermore, advice can be requested on (Big) data techniques and data sources. In support of collaborative (Big) data science activities, scalable environments are offered with facilities for data integration, data analysis and visualization. In addition, Data Science expertise is provided directly or from a pool of internal and external experts. At the EGU conference, gained experiences and best practices are presented in operating the KNMI DataLab to serve data-driven innovations for weather and climate applications optimally.

The World Spatiotemporal Analytics and Mapping Project (WSTAMP): Further Progress in Discovering, Exploring, and Mapping Spatiotemporal Patterns Across the World's Largest Open Source Data Sets

NASA Astrophysics Data System (ADS)

Piburn, J.; Stewart, R.; Myers, A.; Sorokine, A.; Axley, E.; Anderson, D.; Burdette, J.; Biddle, C.; Hohl, A.; Eberle, R.; Kaufman, J.; Morton, A.

2017-10-01

Spatiotemporal (ST) analytics applied to major data sources such as the World Bank and World Health Organization has shown tremendous value in shedding light on the evolution of cultural, health, economic, and geopolitical landscapes on a global level. WSTAMP engages this opportunity by situating analysts, data, and analytics together within a visually rich and computationally rigorous online analysis environment. Since introducing WSTAMP at the First International Workshop on Spatiotemporal Computing, several transformative advances have occurred. Collaboration with human computer interaction experts led to a complete interface redesign that deeply immerses the analyst within a ST context, significantly increases visual and textual content, provides navigational crosswalks for attribute discovery, substantially reduce mouse and keyboard actions, and supports user data uploads. Secondly, the database has been expanded to include over 16,000 attributes, 50 years of time, and 200+ nation states and redesigned to support non-annual, non-national, city, and interaction data. Finally, two new analytics are implemented for analyzing large portfolios of multi-attribute data and measuring the behavioral stability of regions along different dimensions. These advances required substantial new approaches in design, algorithmic innovations, and increased computational efficiency. We report on these advances and inform how others may freely access the tool.

Interactive Visual Analytics Approch for Exploration of Geochemical Model Simulations with Different Parameter Sets

NASA Astrophysics Data System (ADS)

Jatnieks, Janis; De Lucia, Marco; Sips, Mike; Dransch, Doris

2015-04-01

Many geoscience applications can benefit from testing many combinations of input parameters for geochemical simulation models. It is, however, a challenge to screen the input and output data from the model to identify the significant relationships between input parameters and output variables. For addressing this problem we propose a Visual Analytics approach that has been developed in an ongoing collaboration between computer science and geoscience researchers. Our Visual Analytics approach uses visualization methods of hierarchical horizontal axis, multi-factor stacked bar charts and interactive semi-automated filtering for input and output data together with automatic sensitivity analysis. This guides the users towards significant relationships. We implement our approach as an interactive data exploration tool. It is designed with flexibility in mind, so that a diverse set of tasks such as inverse modeling, sensitivity analysis and model parameter refinement can be supported. Here we demonstrate the capabilities of our approach by two examples for gas storage applications. For the first example our Visual Analytics approach enabled the analyst to observe how the element concentrations change around previously established baselines in response to thousands of different combinations of mineral phases. This supported combinatorial inverse modeling for interpreting observations about the chemical composition of the formation fluids at the Ketzin pilot site for CO2 storage. The results indicate that, within the experimental error range, the formation fluid cannot be considered at local thermodynamical equilibrium with the mineral assemblage of the reservoir rock. This is a valuable insight from the predictive geochemical modeling for the Ketzin site. For the second example our approach supports sensitivity analysis for a reaction involving the reductive dissolution of pyrite with formation of pyrrothite in presence of gaseous hydrogen. We determine that this reaction is thermodynamically favorable under a broad range of conditions. This includes low temperatures and absence of microbial catalysators. Our approach has potential for use in other applications that involve exploration of relationships in geochemical simulation model data.

Open cyberGIS software for geospatial research and education in the big data era

NASA Astrophysics Data System (ADS)

Wang, Shaowen; Liu, Yan; Padmanabhan, Anand

CyberGIS represents an interdisciplinary field combining advanced cyberinfrastructure, geographic information science and systems (GIS), spatial analysis and modeling, and a number of geospatial domains to improve research productivity and enable scientific breakthroughs. It has emerged as new-generation GIS that enable unprecedented advances in data-driven knowledge discovery, visualization and visual analytics, and collaborative problem solving and decision-making. This paper describes three open software strategies-open access, source, and integration-to serve various research and education purposes of diverse geospatial communities. These strategies have been implemented in a leading-edge cyberGIS software environment through three corresponding software modalities: CyberGIS Gateway, Toolkit, and Middleware, and achieved broad and significant impacts.

Comparing Learning Performance of Students Using Algorithm Visualizations Collaboratively on Different Engagement Levels

ERIC Educational Resources Information Center

Laakso, Mikko-Jussi; Myller, Niko; Korhonen, Ari

2009-01-01

In this paper, two emerging learning and teaching methods have been studied: collaboration in concert with algorithm visualization. When visualizations have been employed in collaborative learning, collaboration introduces new challenges for the visualization tools. In addition, new theories are needed to guide the development and research of the…

A collaborative visual analytics suite for protein folding research.

PubMed

Harvey, William; Park, In-Hee; Rübel, Oliver; Pascucci, Valerio; Bremer, Peer-Timo; Li, Chenglong; Wang, Yusu

2014-09-01

Molecular dynamics (MD) simulation is a crucial tool for understanding principles behind important biochemical processes such as protein folding and molecular interaction. With the rapidly increasing power of modern computers, large-scale MD simulation experiments can be performed regularly, generating huge amounts of MD data. An important question is how to analyze and interpret such massive and complex data. One of the (many) challenges involved in analyzing MD simulation data computationally is the high-dimensionality of such data. Given a massive collection of molecular conformations, researchers typically need to rely on their expertise and prior domain knowledge in order to retrieve certain conformations of interest. It is not easy to make and test hypotheses as the data set as a whole is somewhat "invisible" due to its high dimensionality. In other words, it is hard to directly access and examine individual conformations from a sea of molecular structures, and to further explore the entire data set. There is also no easy and convenient way to obtain a global view of the data or its various modalities of biochemical information. To this end, we present an interactive, collaborative visual analytics tool for exploring massive, high-dimensional molecular dynamics simulation data sets. The most important utility of our tool is to provide a platform where researchers can easily and effectively navigate through the otherwise "invisible" simulation data sets, exploring and examining molecular conformations both as a whole and at individual levels. The visualization is based on the concept of a topological landscape, which is a 2D terrain metaphor preserving certain topological and geometric properties of the high dimensional protein energy landscape. In addition to facilitating easy exploration of conformations, this 2D terrain metaphor also provides a platform where researchers can visualize and analyze various properties (such as contact density) overlayed on the top of the 2D terrain. Finally, the software provides a collaborative environment where multiple researchers can assemble observations and biochemical events into storyboards and share them in real time over the Internet via a client-server architecture. The software is written in Scala and runs on the cross-platform Java Virtual Machine. Binaries and source code are available at http://www.aylasoftware.org and have been released under the GNU General Public License. Copyright © 2014 Elsevier Inc. All rights reserved.

Technosocial Predictive Analytics in Support of Naturalistic Decision Making

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

Sanfilippo, Antonio P.; Cowell, Andrew J.; Malone, Elizabeth L.

2009-06-23

A main challenge we face in fostering sustainable growth is to anticipate outcomes through predictive and proactive across domains as diverse as energy, security, the environment, health and finance in order to maximize opportunities, influence outcomes and counter adversities. The goal of this paper is to present new methods for anticipatory analytical thinking which address this challenge through the development of a multi-perspective approach to predictive modeling as a core to a creative decision making process. This approach is uniquely multidisciplinary in that it strives to create decision advantage through the integration of human and physical models, and leverages knowledgemore » management and visual analytics to support creative thinking by facilitating the achievement of interoperable knowledge inputs and enhancing the user’s cognitive access. We describe a prototype system which implements this approach and exemplify its functionality with reference to a use case in which predictive modeling is paired with analytic gaming to support collaborative decision-making in the domain of agricultural land management.« less

Physics-based and human-derived information fusion for analysts

NASA Astrophysics Data System (ADS)

Blasch, Erik; Nagy, James; Scott, Steve; Okoth, Joshua; Hinman, Michael

2017-05-01

Recent trends in physics-based and human-derived information fusion (PHIF) have amplified the capabilities of analysts; however with the big data opportunities there is a need for open architecture designs, methods of distributed team collaboration, and visualizations. In this paper, we explore recent trends in the information fusion to support user interaction and machine analytics. Challenging scenarios requiring PHIF include combing physics-based video data with human-derived text data for enhanced simultaneous tracking and identification. A driving effort would be to provide analysts with applications, tools, and interfaces that afford effective and affordable solutions for timely decision making. Fusion at scale should be developed to allow analysts to access data, call analytics routines, enter solutions, update models, and store results for distributed decision making.

An extreme events laboratory to provide network centric collaborative situation assessment and decision making

NASA Astrophysics Data System (ADS)

Panulla, Brian J.; More, Loretta D.; Shumaker, Wade R.; Jones, Michael D.; Hooper, Robert; Vernon, Jeffrey M.; Aungst, Stanley G.

2009-05-01

Rapid improvements in communications infrastructure and sophistication of commercial hand-held devices provide a major new source of information for assessing extreme situations such as environmental crises. In particular, ad hoc collections of humans can act as "soft sensors" to augment data collected by traditional sensors in a net-centric environment (in effect, "crowd-sourcing" observational data). A need exists to understand how to task such soft sensors, characterize their performance and fuse the data with traditional data sources. In order to quantitatively study such situations, as well as study distributed decision-making, we have developed an Extreme Events Laboratory (EEL) at The Pennsylvania State University. This facility provides a network-centric, collaborative situation assessment and decision-making capability by supporting experiments involving human observers, distributed decision making and cognition, and crisis management. The EEL spans the information chain from energy detection via sensors, human observations, signal and image processing, pattern recognition, statistical estimation, multi-sensor data fusion, visualization and analytics, and modeling and simulation. The EEL command center combines COTS and custom collaboration tools in innovative ways, providing capabilities such as geo-spatial visualization and dynamic mash-ups of multiple data sources. This paper describes the EEL and several on-going human-in-the-loop experiments aimed at understanding the new collective observation and analysis landscape.

Progressive Visual Analytics: User-Driven Visual Exploration of In-Progress Analytics.

PubMed

Stolper, Charles D; Perer, Adam; Gotz, David

2014-12-01

As datasets grow and analytic algorithms become more complex, the typical workflow of analysts launching an analytic, waiting for it to complete, inspecting the results, and then re-Iaunching the computation with adjusted parameters is not realistic for many real-world tasks. This paper presents an alternative workflow, progressive visual analytics, which enables an analyst to inspect partial results of an algorithm as they become available and interact with the algorithm to prioritize subspaces of interest. Progressive visual analytics depends on adapting analytical algorithms to produce meaningful partial results and enable analyst intervention without sacrificing computational speed. The paradigm also depends on adapting information visualization techniques to incorporate the constantly refining results without overwhelming analysts and provide interactions to support an analyst directing the analytic. The contributions of this paper include: a description of the progressive visual analytics paradigm; design goals for both the algorithms and visualizations in progressive visual analytics systems; an example progressive visual analytics system (Progressive Insights) for analyzing common patterns in a collection of event sequences; and an evaluation of Progressive Insights and the progressive visual analytics paradigm by clinical researchers analyzing electronic medical records.

The role of 3-D interactive visualization in blind surveys of H I in galaxies

NASA Astrophysics Data System (ADS)

Punzo, D.; van der Hulst, J. M.; Roerdink, J. B. T. M.; Oosterloo, T. A.; Ramatsoku, M.; Verheijen, M. A. W.

2015-09-01

Upcoming H I surveys will deliver large datasets, and automated processing using the full 3-D information (two positional dimensions and one spectral dimension) to find and characterize H I objects is imperative. In this context, visualization is an essential tool for enabling qualitative and quantitative human control on an automated source finding and analysis pipeline. We discuss how Visual Analytics, the combination of automated data processing and human reasoning, creativity and intuition, supported by interactive visualization, enables flexible and fast interaction with the 3-D data, helping the astronomer to deal with the analysis of complex sources. 3-D visualization, coupled to modeling, provides additional capabilities helping the discovery and analysis of subtle structures in the 3-D domain. The requirements for a fully interactive visualization tool are: coupled 1-D/2-D/3-D visualization, quantitative and comparative capabilities, combined with supervised semi-automated analysis. Moreover, the source code must have the following characteristics for enabling collaborative work: open, modular, well documented, and well maintained. We review four state of-the-art, 3-D visualization packages assessing their capabilities and feasibility for use in the case of 3-D astronomical data.

Process Improvement Through Tool Integration in Aero-Mechanical Design

NASA Technical Reports Server (NTRS)

Briggs, Clark

2010-01-01

Emerging capabilities in commercial design tools promise to significantly improve the multi-disciplinary and inter-disciplinary design and analysis coverage for aerospace mechanical engineers. This paper explores the analysis process for two example problems of a wing and flap mechanical drive system and an aircraft landing gear door panel. The examples begin with the design solid models and include various analysis disciplines such as structural stress and aerodynamic loads. Analytical methods include CFD, multi-body dynamics with flexible bodies and structural analysis. Elements of analysis data management, data visualization and collaboration are also included.

Not Just a Game … When We Play Together, We Learn Together: Interactive Virtual Environments and Gaming Engines for Geospatial Visualization

NASA Astrophysics Data System (ADS)

Shipman, J. S.; Anderson, J. W.

2017-12-01

An ideal tool for ecologists and land managers to investigate the impacts of both projected environmental changes and policy alternatives is the creation of immersive, interactive, virtual landscapes. As a new frontier in visualizing and understanding geospatial data, virtual landscapes require a new toolbox for data visualization that includes traditional GIS tools and uncommon tools such as the Unity3d game engine. Game engines provide capabilities to not only explore data but to build and interact with dynamic models collaboratively. These virtual worlds can be used to display and illustrate data that is often more understandable and plausible to both stakeholders and policy makers than is achieved using traditional maps.Within this context we will present funded research that has been developed utilizing virtual landscapes for geographic visualization and decision support among varied stakeholders. We will highlight the challenges and lessons learned when developing interactive virtual environments that require large multidisciplinary team efforts with varied competences. The results will emphasize the importance of visualization and interactive virtual environments and the link with emerging research disciplines within Visual Analytics.

CasCADe: A Novel 4D Visualization System for Virtual Construction Planning.

PubMed

Ivson, Paulo; Nascimento, Daniel; Celes, Waldemar; Barbosa, Simone Dj

2018-01-01

Building Information Modeling (BIM) provides an integrated 3D environment to manage large-scale engineering projects. The Architecture, Engineering and Construction (AEC) industry explores 4D visualizations over these datasets for virtual construction planning. However, existing solutions lack adequate visual mechanisms to inspect the underlying schedule and make inconsistencies readily apparent. The goal of this paper is to apply best practices of information visualization to improve 4D analysis of construction plans. We first present a review of previous work that identifies common use cases and limitations. We then consulted with AEC professionals to specify the main design requirements for such applications. These guided the development of CasCADe, a novel 4D visualization system where task sequencing and spatio-temporal simultaneity are immediately apparent. This unique framework enables the combination of diverse analytical features to create an information-rich analysis environment. We also describe how engineering collaborators used CasCADe to review the real-world construction plans of an Oil & Gas process plant. The system made evident schedule uncertainties, identified work-space conflicts and helped analyze other constructability issues. The results and contributions of this paper suggest new avenues for future research in information visualization for the AEC industry.

The Human is the Loop: New Directions for Visual Analytics

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

Endert, Alexander; Hossain, Shahriar H.; Ramakrishnan, Naren

2014-01-28

Visual analytics is the science of marrying interactive visualizations and analytic algorithms to support exploratory knowledge discovery in large datasets. We argue for a shift from a ‘human in the loop’ philosophy for visual analytics to a ‘human is the loop’ viewpoint, where the focus is on recognizing analysts’ work processes, and seamlessly fitting analytics into that existing interactive process. We survey a range of projects that provide visual analytic support contextually in the sensemaking loop, and outline a research agenda along with future challenges.

Collaborative interactive visualization: exploratory concept

NASA Astrophysics Data System (ADS)

Mokhtari, Marielle; Lavigne, Valérie; Drolet, Frédéric

2015-05-01

Dealing with an ever increasing amount of data is a challenge that military intelligence analysts or team of analysts face day to day. Increased individual and collective comprehension goes through collaboration between people. Better is the collaboration, better will be the comprehension. Nowadays, various technologies support and enhance collaboration by allowing people to connect and collaborate in settings as varied as across mobile devices, over networked computers, display walls, tabletop surfaces, to name just a few. A powerful collaboration system includes traditional and multimodal visualization features to achieve effective human communication. Interactive visualization strengthens collaboration because this approach is conducive to incrementally building a mental assessment of the data meaning. The purpose of this paper is to present an overview of the envisioned collaboration architecture and the interactive visualization concepts underlying the Sensemaking Support System prototype developed to support analysts in the context of the Joint Intelligence Collection and Analysis Capability project at DRDC Valcartier. It presents the current version of the architecture, discusses future capabilities to help analyst(s) in the accomplishment of their tasks and finally recommends collaboration and visualization technologies allowing to go a step further both as individual and as a team.

HydroShare: A Platform for Collaborative Data and Model Sharing in Hydrology

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 its use as a virtual environment supporting education and research. HydroShare has components that support: (1) resource storage, (2) resource exploration, and (3) web apps for actions on resources. The HydroShare data discovery, sharing and publishing functions as well as HydroShare web apps provide the capability to analyze data and execute models completely in the cloud (servers remote from the user) overcoming desktop platform limitations. The HydroShare GIS app provides a basic capability to visualize spatial data. The HydroShare JupyterHub Notebook app provides flexible and documentable execution of Python code snippets for analysis and modeling in a way that results can be shared among HydroShare users and groups to support research collaboration and education. We will discuss how these developments can be used to support different types of educational efforts in Hydrology where being completely web based is of value in an educational setting as students can all have access to the same functionality regardless of their computer.

Real-Time Process Analytics in Emergency Healthcare.

PubMed

Koufi, Vassiliki; Malamateniou, Flora; Prentza, Adrianna; Vassilacopoulos, George

2017-01-01

Emergency medical systems (EMS) are considered to be amongst the most crucial systems as they involve a variety of activities which are performed from the time of a call to an ambulance service till the time of patient's discharge from the emergency department of a hospital. These activities are closely interrelated so that collaboration and coordination becomes a vital issue for patients and for emergency healthcare service performance. The utilization of standard workflow technology in the context of Service Oriented Architecture can provide an appropriate technological infrastructure for defining and automating EMS processes that span organizational boundaries so that to create and empower collaboration and coordination among the participating organizations. In such systems, the utilization of leading-edge analytics tools can prove important as it can facilitate real-time extraction and visualization of useful insights from the mountains of generated data pertaining to emergency case management. This paper presents a framework which provides healthcare professionals with just-in-time insight within and across emergency healthcare processes by performing real-time analysis on process-related data in order to better support decision making and identify potential critical risks that may affect the provision of emergency care to patients.

'Big Data' Collaboration: Exploring, Recording and Sharing Enterprise Knowledge

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

Sukumar, Sreenivas R; Ferrell, Regina Kay

2013-01-01

As data sources and data size proliferate, knowledge discovery from "Big Data" is starting to pose several challenges. In this paper, we address a specific challenge in the practice of enterprise knowledge management while extracting actionable nuggets from diverse data sources of seemingly-related information. In particular, we address the challenge of archiving knowledge gained through collaboration, dissemination and visualization as part of the data analysis, inference and decision-making lifecycle. We motivate the implementation of an enterprise data-discovery and knowledge recorder tool, called SEEKER based on real world case-study. We demonstrate SEEKER capturing schema and data-element relationships, tracking the data elementsmore » of value based on the queries and the analytical artifacts that are being created by analysts as they use the data. We show how the tool serves as digital record of institutional domain knowledge and a documentation for the evolution of data elements, queries and schemas over time. As a knowledge management service, a tool like SEEKER saves enterprise resources and time by avoiding analytic silos, expediting the process of multi-source data integration and intelligently documenting discoveries from fellow analysts.« less

VAST Challenge 2016: Streaming Visual Analytics

DTIC Science & Technology

2016-10-25

understand rapidly evolving situations. To support such tasks, visual analytics solutions must move well beyond systems that simply provide real-time...received. Mini-Challenge 1: Design Challenge Mini-Challenge 1 focused on systems to support security and operational analytics at the Euybia...Challenge 1 was to solicit novel approaches for streaming visual analytics that push the boundaries for what constitutes a visual analytics system , and to

Collaborative volume visualization with applications to underwater acoustic signal processing

NASA Astrophysics Data System (ADS)

Jarvis, Susan; Shane, Richard T.

2000-08-01

Distributed collaborative visualization systems represent a technology whose time has come. Researchers at the Fraunhofer Center for Research in Computer Graphics have been working in the areas of collaborative environments and high-end visualization systems for several years. The medical application. TeleInVivo, is an example of a system which marries visualization and collaboration. With TeleInvivo, users can exchange and collaboratively interact with volumetric data sets in geographically distributed locations. Since examination of many physical phenomena produce data that are naturally volumetric, the visualization frameworks used by TeleInVivo have been extended for non-medical applications. The system can now be made compatible with almost any dataset that can be expressed in terms of magnitudes within a 3D grid. Coupled with advances in telecommunications, telecollaborative visualization is now possible virtually anywhere. Expert data quality assurance and analysis can occur remotely and interactively without having to send all the experts into the field. Building upon this point-to-point concept of collaborative visualization, one can envision a larger pooling of resources to form a large overview of a region of interest from contributions of numerous distributed members.

Collaborative Visualization for Large-Scale Accelerator Electromagnetic Modeling (Final Report)

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

William J. Schroeder

2011-11-13

This report contains the comprehensive summary of the work performed on the SBIR Phase II, Collaborative Visualization for Large-Scale Accelerator Electromagnetic Modeling at Kitware Inc. in collaboration with Stanford Linear Accelerator Center (SLAC). The goal of the work was to develop collaborative visualization tools for large-scale data as illustrated in the figure below. The solutions we proposed address the typical problems faced by geographicallyand organizationally-separated research and engineering teams, who produce large data (either through simulation or experimental measurement) and wish to work together to analyze and understand their data. Because the data is large, we expect that it cannotmore » be easily transported to each team member's work site, and that the visualization server must reside near the data. Further, we also expect that each work site has heterogeneous resources: some with large computing clients, tiled (or large) displays and high bandwidth; others sites as simple as a team member on a laptop computer. Our solution is based on the open-source, widely used ParaView large-data visualization application. We extended this tool to support multiple collaborative clients who may locally visualize data, and then periodically rejoin and synchronize with the group to discuss their findings. Options for managing session control, adding annotation, and defining the visualization pipeline, among others, were incorporated. We also developed and deployed a Web visualization framework based on ParaView that enables the Web browser to act as a participating client in a collaborative session. The ParaView Web Visualization framework leverages various Web technologies including WebGL, JavaScript, Java and Flash to enable interactive 3D visualization over the web using ParaView as the visualization server. We steered the development of this technology by teaming with the SLAC National Accelerator Laboratory. SLAC has a computationally-intensive problem important to the nations scientific progress as described shortly. Further, SLAC researchers routinely generate massive amounts of data, and frequently collaborate with other researchers located around the world. Thus SLAC is an ideal teammate through which to develop, test and deploy this technology. The nature of the datasets generated by simulations performed at SLAC presented unique visualization challenges especially when dealing with higher-order elements that were addressed during this Phase II. During this Phase II, we have developed a strong platform for collaborative visualization based on ParaView. We have developed and deployed a ParaView Web Visualization framework that can be used for effective collaboration over the Web. Collaborating and visualizing over the Web presents the community with unique opportunities for sharing and accessing visualization and HPC resources that hitherto with either inaccessible or difficult to use. The technology we developed in here will alleviate both these issues as it becomes widely deployed and adopted.« less

Developing Guidelines for Assessing Visual Analytics Environments

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

Scholtz, Jean

2011-07-01

In this paper, we develop guidelines for evaluating visual analytic environments based on a synthesis of reviews for the entries to the 2009 Visual Analytics Science and Technology (VAST) Symposium Challenge and from a user study with professional intelligence analysts. By analyzing the 2009 VAST Challenge reviews we gained a better understanding of what is important to our reviewers, both visualization researchers and professional analysts. We also report on a small user study with professional analysts to determine the important factors that they use in evaluating visual analysis systems. We then looked at guidelines developed by researchers in various domainsmore » and synthesized these into an initial set for use by others in the community. In a second part of the user study, we looked at guidelines for a new aspect of visual analytic systems – the generation of reports. Future visual analytic systems have been challenged to help analysts generate their reports. In our study we worked with analysts to understand the criteria they used to evaluate the quality of analytic reports. We propose that this knowledge will be useful as researchers look at systems to automate some of the report generation.1 Based on these efforts, we produced some initial guidelines for evaluating visual analytic environment and for evaluation of analytic reports. It is important to understand that these guidelines are initial drafts and are limited in scope because of the type of tasks for which the visual analytic systems used in the studies in this paper were designed. More research and refinement is needed by the Visual Analytics Community to provide additional evaluation guidelines for different types of visual analytic environments.« less

Using Learning Analytics to Support Engagement in Collaborative Writing

ERIC Educational Resources Information Center

Liu, Ming; Pardo, Abelardo; Liu, Li

2017-01-01

Online collaborative writing tools provide an efficient way to complete a writing task. However, existing tools only focus on technological affordances and ignore the importance of social affordances in a collaborative learning environment. This article describes a learning analytic system that analyzes writing behaviors, and creates…

Visualization Forms in the Cross-Cultural Collaborative Activities of Design and Development of a Digital Resource for Education

ERIC Educational Resources Information Center

Quan, Guolong; Gu, Xiaoqing

2018-01-01

Recent studies have demonstrated the integration of visualization technology to support collaboration and stimulate learning performance. The use of visualization tools during the collaborative activities of international students is a worthy topic for further exploration. Based on grounded and activity theories, this research uses observation and…

VAMPS: a website for visualization and analysis of microbial population structures.

PubMed

Huse, Susan M; Mark Welch, David B; Voorhis, Andy; Shipunova, Anna; Morrison, Hilary G; Eren, A Murat; Sogin, Mitchell L

2014-02-05

The advent of next-generation DNA sequencing platforms has revolutionized molecular microbial ecology by making the detailed analysis of complex communities over time and space a tractable research pursuit for small research groups. However, the ability to generate 10⁵-10⁸ reads with relative ease brings with it many downstream complications. Beyond the computational resources and skills needed to process and analyze data, it is difficult to compare datasets in an intuitive and interactive manner that leads to hypothesis generation and testing. We developed the free web service VAMPS (Visualization and Analysis of Microbial Population Structures, http://vamps.mbl.edu) to address these challenges and to facilitate research by individuals or collaborating groups working on projects with large-scale sequencing data. Users can upload marker gene sequences and associated metadata; reads are quality filtered and assigned to both taxonomic structures and to taxonomy-independent clusters. A simple point-and-click interface allows users to select for analysis any combination of their own or their collaborators' private data and data from public projects, filter these by their choice of taxonomic and/or abundance criteria, and then explore these data using a wide range of analytic methods and visualizations. Each result is extensively hyperlinked to other analysis and visualization options, promoting data exploration and leading to a greater understanding of data relationships. VAMPS allows researchers using marker gene sequence data to analyze the diversity of microbial communities and the relationships between communities, to explore these analyses in an intuitive visual context, and to download data, results, and images for publication. VAMPS obviates the need for individual research groups to make the considerable investment in computational infrastructure and bioinformatic support otherwise necessary to process, analyze, and interpret massive amounts of next-generation sequence data. Any web-capable device can be used to upload, process, explore, and extract data and results from VAMPS. VAMPS encourages researchers to share sequence and metadata, and fosters collaboration between researchers of disparate biomes who recognize common patterns in shared data.

Web GIS in practice IX: a demonstration of geospatial visual analytics using Microsoft Live Labs Pivot technology and WHO mortality data

PubMed Central

2011-01-01

The goal of visual analytics is to facilitate the discourse between the user and the data by providing dynamic displays and versatile visual interaction opportunities with the data that can support analytical reasoning and the exploration of data from multiple user-customisable aspects. This paper introduces geospatial visual analytics, a specialised subtype of visual analytics, and provides pointers to a number of learning resources about the subject, as well as some examples of human health, surveillance, emergency management and epidemiology-related geospatial visual analytics applications and examples of free software tools that readers can experiment with, such as Google Public Data Explorer. The authors also present a practical demonstration of geospatial visual analytics using partial data for 35 countries from a publicly available World Health Organization (WHO) mortality dataset and Microsoft Live Labs Pivot technology, a free, general purpose visual analytics tool that offers a fresh way to visually browse and arrange massive amounts of data and images online and also supports geographic and temporal classifications of datasets featuring geospatial and temporal components. Interested readers can download a Zip archive (included with the manuscript as an additional file) containing all files, modules and library functions used to deploy the WHO mortality data Pivot collection described in this paper. PMID:21410968

Web GIS in practice IX: a demonstration of geospatial visual analytics using Microsoft Live Labs Pivot technology and WHO mortality data.

PubMed

Kamel Boulos, Maged N; Viangteeravat, Teeradache; Anyanwu, Matthew N; Ra Nagisetty, Venkateswara; Kuscu, Emin

2011-03-16

The goal of visual analytics is to facilitate the discourse between the user and the data by providing dynamic displays and versatile visual interaction opportunities with the data that can support analytical reasoning and the exploration of data from multiple user-customisable aspects. This paper introduces geospatial visual analytics, a specialised subtype of visual analytics, and provides pointers to a number of learning resources about the subject, as well as some examples of human health, surveillance, emergency management and epidemiology-related geospatial visual analytics applications and examples of free software tools that readers can experiment with, such as Google Public Data Explorer. The authors also present a practical demonstration of geospatial visual analytics using partial data for 35 countries from a publicly available World Health Organization (WHO) mortality dataset and Microsoft Live Labs Pivot technology, a free, general purpose visual analytics tool that offers a fresh way to visually browse and arrange massive amounts of data and images online and also supports geographic and temporal classifications of datasets featuring geospatial and temporal components. Interested readers can download a Zip archive (included with the manuscript as an additional file) containing all files, modules and library functions used to deploy the WHO mortality data Pivot collection described in this paper.

Evaluation of Visual Analytics Environments: The Road to the Visual Analytics Science and Technology Challenge Evaluation Methodology

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

Scholtz, Jean; Plaisant, Catherine; Whiting, Mark A.

The evaluation of visual analytics environments was a topic in Illuminating the Path [Thomas 2005] as a critical aspect of moving research into practice. For a thorough understanding of the utility of the systems available, evaluation not only involves assessing the visualizations, interactions or data processing algorithms themselves, but also the complex processes that a tool is meant to support (such as exploratory data analysis and reasoning, communication through visualization, or collaborative data analysis [Lam 2012; Carpendale 2007]). Researchers and practitioners in the field have long identified many of the challenges faced when planning, conducting, and executing an evaluation ofmore » a visualization tool or system [Plaisant 2004]. Evaluation is needed to verify that algorithms and software systems work correctly and that they represent improvements over the current infrastructure. Additionally to effectively transfer new software into a working environment, it is necessary to ensure that the software has utility for the end-users and that the software can be incorporated into the end-user’s infrastructure and work practices. Evaluation test beds require datasets, tasks, metrics and evaluation methodologies. As noted in [Thomas 2005] it is difficult and expensive for any one researcher to setup an evaluation test bed so in many cases evaluation is setup for communities of researchers or for various research projects or programs. Examples of successful community evaluations can be found [Chinchor 1993; Voorhees 2007; FRGC 2012]. As visual analytics environments are intended to facilitate the work of human analysts, one aspect of evaluation needs to focus on the utility of the software to the end-user. This requires representative users, representative tasks, and metrics that measure the utility to the end-user. This is even more difficult as now one aspect of the test methodology is access to representative end-users to participate in the evaluation. In many cases the sensitive nature of data and tasks and difficult access to busy analysts puts even more of a burden on researchers to complete this type of evaluation. User-centered design goes beyond evaluation and starts with the user [Beyer 1997, Shneiderman 2009]. Having some knowledge of the type of data, tasks, and work practices helps researchers and developers know the correct paths to pursue in their work. When access to the end-users is problematic at best and impossible at worst, user-centered design becomes difficult. Researchers are unlikely to go to work on the type of problems faced by inaccessible users. Commercial vendors have difficulties evaluating and improving their products when they cannot observe real users working with their products. In well-established fields such as web site design or office software design, user-interface guidelines have been developed based on the results of empirical studies or the experience of experts. Guidelines can speed up the design process and replace some of the need for observation of actual users [heuristics review references]. In 2006 when the visual analytics community was initially getting organized, no such guidelines existed. Therefore, we were faced with the problem of developing an evaluation framework for the field of visual analytics that would provide representative situations and datasets, representative tasks and utility metrics, and finally a test methodology which would include a surrogate for representative users, increase interest in conducting research in the field, and provide sufficient feedback to the researchers so that they could improve their systems.« less

Supporting tactical intelligence using collaborative environments and social networking

NASA Astrophysics Data System (ADS)

Wollocko, Arthur B.; Farry, Michael P.; Stark, Robert F.

2013-05-01

Modern military environments place an increased emphasis on the collection and analysis of intelligence at the tactical level. The deployment of analytical tools at the tactical level helps support the Warfighter's need for rapid collection, analysis, and dissemination of intelligence. However, given the lack of experience and staffing at the tactical level, most of the available intelligence is not exploited. Tactical environments are staffed by a new generation of intelligence analysts who are well-versed in modern collaboration environments and social networking. An opportunity exists to enhance tactical intelligence analysis by exploiting these personnel strengths, but is dependent on appropriately designed information sharing technologies. Existing social information sharing technologies enable users to publish information quickly, but do not unite or organize information in a manner that effectively supports intelligence analysis. In this paper, we present an alternative approach to structuring and supporting tactical intelligence analysis that combines the benefits of existing concepts, and provide detail on a prototype system embodying that approach. Since this approach employs familiar collaboration support concepts from social media, it enables new-generation analysts to identify the decision-relevant data scattered among databases and the mental models of other personnel, increasing the timeliness of collaborative analysis. Also, the approach enables analysts to collaborate visually to associate heterogeneous and uncertain data within the intelligence analysis process, increasing the robustness of collaborative analyses. Utilizing this familiar dynamic collaboration environment, we hope to achieve a significant reduction of time and skill required to glean actionable intelligence in these challenging operational environments.

Data Analytics and Visualization for Large Army Testing Data

DTIC Science & Technology

2013-09-01

and relationships in the data that would otherwise remain hidden. 7 Bibliography 1. Goodall , J. R.; Tesone, D. R. Visual Analytics for Network...Software Visualization, 2003, pp 143–149. 3. Goodall , J. R.; Sowul, M. VIAssist: Visual Analytics for Cyber Defense, IEEE Conference on Technologies

Understanding the International Space Station Crew Perspective following Long-Duration Missions through Data Analytics & Visualization of Crew Feedback

NASA Technical Reports Server (NTRS)

Bryant, Cody; Meza, David; Schoenstein, Nicole; Schuh, Susan

2017-01-01

The International Space Station (ISS) first became a home and research laboratory for NASA and International Partner crewmembers over 16 years ago. Each ISS mission lasts approximately 6 months and consists of three to six crewmembers. After returning to Earth, most crewmembers participate in an extensive series of 30+ debriefs intended to further understand life onboard ISS and allow crews to reflect on their experiences. Examples of debrief data collected include ISS crew feedback about sleep, dining, payload science, scheduling and time planning, health & safety, and maintenance. The Flight Crew Integration (FCI) Operational Habitability (OpsHab) team, based at Johnson Space Center (JSC), is a small group of Human Factors engineers and one stenographer that has worked collaboratively with the NASA Astronaut office and ISS Program to collect, maintain, disseminate and analyze this data. The database provides an exceptional and unique resource for understanding the "crew perspective" on long duration space missions. Data is formatted and categorized to allow for ease of search, reporting, and ultimately trending, in order to understand lessons learned, recurring issues and efficiencies gained over time. Recently, the FCI OpsHab team began collaborating with the NASA JSC Knowledge Management team to provide analytical analysis and visualization of these over 75,000 crew comments in order to better ascertain the crew's perspective on long duration spaceflight and gain insight on changes over time. In this initial phase of study, a text mining framework was used to cluster similar comments and develop measures of similarity useful for identifying relevant topics affecting crew health or performance, locating similar comments when a particular issue or item of operational interest is identified, and providing search capabilities to identify information pertinent to future spaceflight systems and processes for things like procedure development and training. In addition, the comments were scored for sentiment using a polarity scoring algorithm to identify both positive and negative comments for particular groups and clusters, allowing the team to make analytically informed decisions regarding future hardware and operating procedures. The use of polarity scoring with time series analysis was used to provide insight into how crew health and habitability is changing throughout various spaceflight increments or the station lifecycle as a whole. Finally, a visualization framework was developed to address the needs of the end users to search for and analyze comments by user, category or mission. This paper will discuss how the use of an analytical framework in conjunction with the current human interface, improved the understanding of crew perspective and shortened the time for analysis allowing for more informed decisions and rapid development of improvements. These methods are significantly optimizing the way that this valuable data can be assessed and applied to current and future spaceflight design and development. This collaboration allows the FCI OpsHab team to effectively analyze and share data in a more automated and timely fashion. Trends are no longer derived manually and can be illustrated effectively and accurately with these evolving techniques to an ever growing group of human spaceflight end users.

Innovative Visualization Techniques applied to a Flood Scenario

NASA Astrophysics Data System (ADS)

Falcão, António; Ho, Quan; Lopes, Pedro; Malamud, Bruce D.; Ribeiro, Rita; Jern, Mikael

2013-04-01

The large and ever-increasing amounts of multi-dimensional, time-varying and geospatial digital information from multiple sources represent a major challenge for today's analysts. We present a set of visualization techniques that can be used for the interactive analysis of geo-referenced and time sampled data sets, providing an integrated mechanism and that aids the user to collaboratively explore, present and communicate visually complex and dynamic data. Here we present these concepts in the context of a 4 hour flood scenario from Lisbon in 2010, with data that includes measures of water column (flood height) every 10 minutes at a 4.5 m x 4.5 m resolution, topography, building damage, building information, and online base maps. Techniques we use include web-based linked views, multiple charts, map layers and storytelling. We explain two of these in more detail that are not currently in common use for visualization of data: storytelling and web-based linked views. Visual storytelling is a method for providing a guided but interactive process of visualizing data, allowing more engaging data exploration through interactive web-enabled visualizations. Within storytelling, a snapshot mechanism helps the author of a story to highlight data views of particular interest and subsequently share or guide others within the data analysis process. This allows a particular person to select relevant attributes for a snapshot, such as highlighted regions for comparisons, time step, class values for colour legend, etc. and provide a snapshot of the current application state, which can then be provided as a hyperlink and recreated by someone else. Since data can be embedded within this snapshot, it is possible to interactively visualize and manipulate it. The second technique, web-based linked views, includes multiple windows which interactively respond to the user selections, so that when selecting an object and changing it one window, it will automatically update in all the other windows. These concepts can be part of a collaborative platform, where multiple people share and work together on the data, via online access, which also allows its remote usage from a mobile platform. Storytelling augments analysis and decision-making capabilities allowing to assimilate complex situations and reach informed decisions, in addition to helping the public visualize information. In our visualization scenario, developed in the context of the VA-4D project for the European Space Agency (see http://www.ca3-uninova.org/project_va4d), we make use of the GAV (GeoAnalytics Visualization) framework, a web-oriented visual analytics application based on multiple interactive views. The final visualization that we produce includes multiple interactive views, including a dynamic multi-layer map surrounded by other visualizations such as bar charts, time graphs and scatter plots. The map provides flood and building information, on top of a base city map (street maps and/or satellite imagery provided by online map services such as Google Maps, Bing Maps etc.). Damage over time for selected buildings, damage for all buildings at a chosen time period, correlation between damage and water depth can be analysed in the other views. This interactive web-based visualization that incorporates the ideas of storytelling, web-based linked views, and other visualization techniques, for a 4 hour flood event in Lisbon in 2010, can be found online at http://www.ncomva.se/flash/projects/esa/flooding/.

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

Karakaya, Mahmut; Qi, Hairong

This paper addresses the communication and energy efficiency in collaborative visual sensor networks (VSNs) for people localization, a challenging computer vision problem of its own. We focus on the design of a light-weight and energy efficient solution where people are localized based on distributed camera nodes integrating the so-called certainty map generated at each node, that records the target non-existence information within the camera s field of view. We first present a dynamic itinerary for certainty map integration where not only each sensor node transmits a very limited amount of data but that a limited number of camera nodes ismore » involved. Then, we perform a comprehensive analytical study to evaluate communication and energy efficiency between different integration schemes, i.e., centralized and distributed integration. Based on results obtained from analytical study and real experiments, the distributed method shows effectiveness in detection accuracy as well as energy and bandwidth efficiency.« less

Multimedia Analysis plus Visual Analytics = Multimedia Analytics

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

Chinchor, Nancy; Thomas, James J.; Wong, Pak C.

2010-10-01

Multimedia analysis has focused on images, video, and to some extent audio and has made progress in single channels excluding text. Visual analytics has focused on the user interaction with data during the analytic process plus the fundamental mathematics and has continued to treat text as did its precursor, information visualization. The general problem we address in this tutorial is the combining of multimedia analysis and visual analytics to deal with multimedia information gathered from different sources, with different goals or objectives, and containing all media types and combinations in common usage.

Visual Analytics 101

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

Scholtz, Jean; Burtner, Edwin R.; Cook, Kristin A.

This course will introduce the field of Visual Analytics to HCI researchers and practitioners highlighting the contributions they can make to this field. Topics will include a definition of visual analytics along with examples of current systems, types of tasks and end users, issues in defining user requirements, design of visualizations and interactions, guidelines and heuristics, the current state of user-centered evaluations, and metrics for evaluation. We encourage designers, HCI researchers, and HCI practitioners to attend to learn how their skills can contribute to advancing the state of the art of visual analytics

Using Interactive Data Visualizations for Exploratory Analysis in Undergraduate Genomics Coursework: Field Study Findings and Guidelines

NASA Astrophysics Data System (ADS)

Mirel, Barbara; Kumar, Anuj; Nong, Paige; Su, Gang; Meng, Fan

2016-02-01

Life scientists increasingly use visual analytics to explore large data sets and generate hypotheses. Undergraduate biology majors should be learning these same methods. Yet visual analytics is one of the most underdeveloped areas of undergraduate biology education. This study sought to determine the feasibility of undergraduate biology majors conducting exploratory analysis using the same interactive data visualizations as practicing scientists. We examined 22 upper level undergraduates in a genomics course as they engaged in a case-based inquiry with an interactive heat map. We qualitatively and quantitatively analyzed students' visual analytic behaviors, reasoning and outcomes to identify student performance patterns, commonly shared efficiencies and task completion. We analyzed students' successes and difficulties in applying knowledge and skills relevant to the visual analytics case and related gaps in knowledge and skill to associated tool designs. Findings show that undergraduate engagement in visual analytics is feasible and could be further strengthened through tool usability improvements. We identify these improvements. We speculate, as well, on instructional considerations that our findings suggested may also enhance visual analytics in case-based modules.

Using Interactive Data Visualizations for Exploratory Analysis in Undergraduate Genomics Coursework: Field Study Findings and Guidelines

PubMed Central

Kumar, Anuj; Nong, Paige; Su, Gang; Meng, Fan

2016-01-01

Life scientists increasingly use visual analytics to explore large data sets and generate hypotheses. Undergraduate biology majors should be learning these same methods. Yet visual analytics is one of the most underdeveloped areas of undergraduate biology education. This study sought to determine the feasibility of undergraduate biology majors conducting exploratory analysis using the same interactive data visualizations as practicing scientists. We examined 22 upper level undergraduates in a genomics course as they engaged in a case-based inquiry with an interactive heat map. We qualitatively and quantitatively analyzed students’ visual analytic behaviors, reasoning and outcomes to identify student performance patterns, commonly shared efficiencies and task completion. We analyzed students’ successes and difficulties in applying knowledge and skills relevant to the visual analytics case and related gaps in knowledge and skill to associated tool designs. Findings show that undergraduate engagement in visual analytics is feasible and could be further strengthened through tool usability improvements. We identify these improvements. We speculate, as well, on instructional considerations that our findings suggested may also enhance visual analytics in case-based modules. PMID:26877625

Analyzing Earth Science Research Networking through Visualizations

NASA Astrophysics Data System (ADS)

Hasnain, S.; Stephan, R.; Narock, T.

2017-12-01

Using D3.js we visualize collaboration amongst several geophysical science organizations, such as the American Geophysical Union (AGU) and the Federation of Earth Science Information Partners (ESIP). We look at historical trends in Earth Science research topics, cross-domain collaboration, and topics of interest to the general population. The visualization techniques used provide an effective way for non-experts to easily explore distributed and heterogeneous Big Data. Analysis of these visualizations provides stakeholders with insights into optimizing meetings, performing impact evaluation, structuring outreach efforts, and identifying new opportunities for collaboration.

Changes in Visual/Spatial and Analytic Strategy Use in Organic Chemistry with the Development of Expertise

ERIC Educational Resources Information Center

Vlacholia, Maria; Vosniadou, Stella; Roussos, Petros; Salta, Katerina; Kazi, Smaragda; Sigalas, Michael; Tzougraki, Chryssa

2017-01-01

We present two studies that investigated the adoption of visual/spatial and analytic strategies by individuals at different levels of expertise in the area of organic chemistry, using the Visual Analytic Chemistry Task (VACT). The VACT allows the direct detection of analytic strategy use without drawing inferences about underlying mental…

Human image tracking technique applied to remote collaborative environments

NASA Astrophysics Data System (ADS)

Nagashima, Yoshio; Suzuki, Gen

1993-10-01

To support various kinds of collaborations over long distances by using visual telecommunication, it is necessary to transmit visual information related to the participants and topical materials. When people collaborate in the same workspace, they use visual cues such as facial expressions and eye movement. The realization of coexistence in a collaborative workspace requires the support of these visual cues. Therefore, it is important that the facial images be large enough to be useful. During collaborations, especially dynamic collaborative activities such as equipment operation or lectures, the participants often move within the workspace. When the people move frequently or over a wide area, the necessity for automatic human tracking increases. Using the movement area of the human being or the resolution of the extracted area, we have developed a memory tracking method and a camera tracking method for automatic human tracking. Experimental results using a real-time tracking system show that the extracted area fairly moves according to the movement of the human head.

A Tool Supporting Collaborative Data Analytics Workflow Design and Management

NASA Astrophysics Data System (ADS)

Zhang, J.; Bao, Q.; Lee, T. J.

2016-12-01

Collaborative experiment design could significantly enhance the sharing and adoption of the data analytics algorithms and models emerged in Earth science. Existing data-oriented workflow tools, however, are not suitable to support collaborative design of such a workflow, to name a few, to support real-time co-design; to track how a workflow evolves over time based on changing designs contributed by multiple Earth scientists; and to capture and retrieve collaboration knowledge on workflow design (discussions that lead to a design). To address the aforementioned challenges, we have designed and developed a technique supporting collaborative data-oriented workflow composition and management, as a key component toward supporting big data collaboration through the Internet. Reproducibility and scalability are two major targets demanding fundamental infrastructural support. One outcome of the project os a software tool, supporting an elastic number of groups of Earth scientists to collaboratively design and compose data analytics workflows through the Internet. Instead of recreating the wheel, we have extended an existing workflow tool VisTrails into an online collaborative environment as a proof of concept.

User-Centered Evaluation of Visual Analytics

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

Scholtz, Jean C.

Visual analytics systems are becoming very popular. More domains now use interactive visualizations to analyze the ever-increasing amount and heterogeneity of data. More novel visualizations are being developed for more tasks and users. We need to ensure that these systems can be evaluated to determine that they are both useful and usable. A user-centered evaluation for visual analytics needs to be developed for these systems. While many of the typical human-computer interaction (HCI) evaluation methodologies can be applied as is, others will need modification. Additionally, new functionality in visual analytics systems needs new evaluation methodologies. There is a difference betweenmore » usability evaluations and user-centered evaluations. Usability looks at the efficiency, effectiveness, and user satisfaction of users carrying out tasks with software applications. User-centered evaluation looks more specifically at the utility provided to the users by the software. This is reflected in the evaluations done and in the metrics used. In the visual analytics domain this is very challenging as users are most likely experts in a particular domain, the tasks they do are often not well defined, the software they use needs to support large amounts of different kinds of data, and often the tasks last for months. These difficulties are discussed more in the section on User-centered Evaluation. Our goal is to provide a discussion of user-centered evaluation practices for visual analytics, including existing practices that can be carried out and new methodologies and metrics that need to be developed and agreed upon by the visual analytics community. The material provided here should be of use for both researchers and practitioners in the field of visual analytics. Researchers and practitioners in HCI and interested in visual analytics will find this information useful as well as a discussion on changes that need to be made to current HCI practices to make them more suitable to visual analytics. A history of analysis and analysis techniques and problems is provided as well as an introduction to user-centered evaluation and various evaluation techniques for readers from different disciplines. The understanding of these techniques is imperative if we wish to support analysis in the visual analytics software we develop. Currently the evaluations that are conducted and published for visual analytics software are very informal and consist mainly of comments from users or potential users. Our goal is to help researchers in visual analytics to conduct more formal user-centered evaluations. While these are time-consuming and expensive to carryout, the outcomes of these studies will have a defining impact on the field of visual analytics and help point the direction for future features and visualizations to incorporate. While many researchers view work in user-centered evaluation as a less-than-exciting area to work, the opposite is true. First of all, the goal is user-centered evaluation is to help visual analytics software developers, researchers, and designers improve their solutions and discover creative ways to better accommodate their users. Working with the users is extremely rewarding as well. While we use the term “users” in almost all situations there are a wide variety of users that all need to be accommodated. Moreover, the domains that use visual analytics are varied and expanding. Just understanding the complexities of a number of these domains is exciting. Researchers are trying out different visualizations and interactions as well. And of course, the size and variety of data are expanding rapidly. User-centered evaluation in this context is rapidly changing. There are no standard processes and metrics and thus those of us working on user-centered evaluation must be creative in our work with both the users and with the researchers and developers.« less

A study on haptic collaborative game in shared virtual environment

NASA Astrophysics Data System (ADS)

Lu, Keke; Liu, Guanyang; Liu, Lingzhi

2013-03-01

A study on collaborative game in shared virtual environment with haptic feedback over computer networks is introduced in this paper. A collaborative task was used where the players located at remote sites and played the game together. The player can feel visual and haptic feedback in virtual environment compared to traditional networked multiplayer games. The experiment was desired in two conditions: visual feedback only and visual-haptic feedback. The goal of the experiment is to assess the impact of force feedback on collaborative task performance. Results indicate that haptic feedback is beneficial for performance enhancement for collaborative game in shared virtual environment. The outcomes of this research can have a powerful impact on the networked computer games.

The case for visual analytics of arsenic concentrations in foods.

PubMed

Johnson, Matilda O; Cohly, Hari H P; Isokpehi, Raphael D; Awofolu, Omotayo R

2010-05-01

Arsenic is a naturally occurring toxic metal and its presence in food could be a potential risk to the health of both humans and animals. Prolonged ingestion of arsenic contaminated water may result in manifestations of toxicity in all systems of the body. Visual Analytics is a multidisciplinary field that is defined as the science of analytical reasoning facilitated by interactive visual interfaces. The concentrations of arsenic vary in foods making it impractical and impossible to provide regulatory limit for each food. This review article presents a case for the use of visual analytics approaches to provide comparative assessment of arsenic in various foods. The topics covered include (i) metabolism of arsenic in the human body; (ii) arsenic concentrations in various foods; (ii) factors affecting arsenic uptake in plants; (ii) introduction to visual analytics; and (iv) benefits of visual analytics for comparative assessment of arsenic concentration in foods. Visual analytics can provide an information superstructure of arsenic in various foods to permit insightful comparative risk assessment of the diverse and continually expanding data on arsenic in food groups in the context of country of study or origin, year of study, method of analysis and arsenic species.

The Case for Visual Analytics of Arsenic Concentrations in Foods

PubMed Central

Johnson, Matilda O.; Cohly, Hari H.P.; Isokpehi, Raphael D.; Awofolu, Omotayo R.

2010-01-01

Arsenic is a naturally occurring toxic metal and its presence in food could be a potential risk to the health of both humans and animals. Prolonged ingestion of arsenic contaminated water may result in manifestations of toxicity in all systems of the body. Visual Analytics is a multidisciplinary field that is defined as the science of analytical reasoning facilitated by interactive visual interfaces. The concentrations of arsenic vary in foods making it impractical and impossible to provide regulatory limit for each food. This review article presents a case for the use of visual analytics approaches to provide comparative assessment of arsenic in various foods. The topics covered include (i) metabolism of arsenic in the human body; (ii) arsenic concentrations in various foods; (ii) factors affecting arsenic uptake in plants; (ii) introduction to visual analytics; and (iv) benefits of visual analytics for comparative assessment of arsenic concentration in foods. Visual analytics can provide an information superstructure of arsenic in various foods to permit insightful comparative risk assessment of the diverse and continually expanding data on arsenic in food groups in the context of country of study or origin, year of study, method of analysis and arsenic species. PMID:20623005

Scalable Visual Analytics of Massive Textual Datasets

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

Krishnan, Manoj Kumar; Bohn, Shawn J.; Cowley, Wendy E.

2007-04-01

This paper describes the first scalable implementation of text processing engine used in Visual Analytics tools. These tools aid information analysts in interacting with and understanding large textual information content through visual interfaces. By developing parallel implementation of the text processing engine, we enabled visual analytics tools to exploit cluster architectures and handle massive dataset. The paper describes key elements of our parallelization approach and demonstrates virtually linear scaling when processing multi-gigabyte data sets such as Pubmed. This approach enables interactive analysis of large datasets beyond capabilities of existing state-of-the art visual analytics tools.

A collaborative interaction and visualization multi-modal environment for surgical planning.

PubMed

Foo, Jung Leng; Martinez-Escobar, Marisol; Peloquin, Catherine; Lobe, Thom; Winer, Eliot

2009-01-01

The proliferation of virtual reality visualization and interaction technologies has changed the way medical image data is analyzed and processed. This paper presents a multi-modal environment that combines a virtual reality application with a desktop application for collaborative surgical planning. Both visualization applications can function independently but can also be synced over a network connection for collaborative work. Any changes to either application is immediately synced and updated to the other. This is an efficient collaboration tool that allows multiple teams of doctors with only an internet connection to visualize and interact with the same patient data simultaneously. With this multi-modal environment framework, one team working in the VR environment and another team from a remote location working on a desktop machine can both collaborate in the examination and discussion for procedures such as diagnosis, surgical planning, teaching and tele-mentoring.

Utility assessment of a map-based online geo-collaboration tool.

PubMed

Sidlar, Christopher L; Rinner, Claus

2009-05-01

Spatial group decision-making processes often include both informal and analytical components. Discussions among stakeholders or planning experts are an example of an informal component. When participants discuss spatial planning projects they typically express concerns and comments by pointing to places on a map. The Argumentation Map model provides a conceptual basis for collaborative tools that enable explicit linkages of arguments to the places to which they refer. These tools allow for the input of explicitly geo-referenced arguments as well as the visual access to arguments through a map interface. In this paper, we will review previous utility studies in geo-collaboration and evaluate a case study of a Web-based Argumentation Map application. The case study was conducted in the summer of 2005 when student participants discussed planning issues on the University of Toronto St. George campus. During a one-week unmoderated discussion phase, 11 participants wrote 60 comments on issues such as safety, facilities, parking, and building aesthetics. By measuring the participants' use of geographic references, we draw conclusions on how well the software tool supported the potential of the underlying concept. This research aims to contribute to a scientific approach to geo-collaboration in which the engineering of novel spatial decision support methods is complemented by a critical assessment of their utility in controlled, realistic experiments.

Beyond Control Panels: Direct Manipulation for Visual Analytics

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

Endert, Alexander; Bradel, Lauren; North, Chris

2013-07-19

Information Visualization strives to provide visual representations through which users can think about and gain insight into information. By leveraging the visual and cognitive systems of humans, complex relationships and phenomena occurring within datasets can be uncovered by exploring information visually. Interaction metaphors for such visualizations are designed to enable users direct control over the filters, queries, and other parameters controlling how the data is visually represented. Through the evolution of information visualization, more complex mathematical and data analytic models are being used to visualize relationships and patterns in data – creating the field of Visual Analytics. However, the expectationsmore » for how users interact with these visualizations has remained largely unchanged – focused primarily on the direct manipulation of parameters of the underlying mathematical models. In this article we present an opportunity to evolve the methodology for user interaction from the direct manipulation of parameters through visual control panels, to interactions designed specifically for visual analytic systems. Instead of focusing on traditional direct manipulation of mathematical parameters, the evolution of the field can be realized through direct manipulation within the visual representation – where users can not only gain insight, but also interact. This article describes future directions and research challenges that fundamentally change the meaning of direct manipulation with regards to visual analytics, advancing the Science of Interaction.« less

Multi-Resolution Climate Ensemble Parameter Analysis with Nested Parallel Coordinates Plots.

PubMed

Wang, Junpeng; Liu, Xiaotong; Shen, Han-Wei; Lin, Guang

2017-01-01

Due to the uncertain nature of weather prediction, climate simulations are usually performed multiple times with different spatial resolutions. The outputs of simulations are multi-resolution spatial temporal ensembles. Each simulation run uses a unique set of values for multiple convective parameters. Distinct parameter settings from different simulation runs in different resolutions constitute a multi-resolution high-dimensional parameter space. Understanding the correlation between the different convective parameters, and establishing a connection between the parameter settings and the ensemble outputs are crucial to domain scientists. The multi-resolution high-dimensional parameter space, however, presents a unique challenge to the existing correlation visualization techniques. We present Nested Parallel Coordinates Plot (NPCP), a new type of parallel coordinates plots that enables visualization of intra-resolution and inter-resolution parameter correlations. With flexible user control, NPCP integrates superimposition, juxtaposition and explicit encodings in a single view for comparative data visualization and analysis. We develop an integrated visual analytics system to help domain scientists understand the connection between multi-resolution convective parameters and the large spatial temporal ensembles. Our system presents intricate climate ensembles with a comprehensive overview and on-demand geographic details. We demonstrate NPCP, along with the climate ensemble visualization system, based on real-world use-cases from our collaborators in computational and predictive science.

Interaction Junk: User Interaction-Based Evaluation of Visual Analytic Systems

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

Endert, Alexander; North, Chris

2012-10-14

With the growing need for visualization to aid users in understanding large, complex datasets, the ability for users to interact and explore these datasets is critical. As visual analytic systems have advanced to leverage powerful computational models and data analytics capabilities, the modes by which users engage and interact with the information are limited. Often, users are taxed with directly manipulating parameters of these models through traditional GUIs (e.g., using sliders to directly manipulate the value of a parameter). However, the purpose of user interaction in visual analytic systems is to enable visual data exploration – where users can focusmore » on their task, as opposed to the tool or system. As a result, users can engage freely in data exploration and decision-making, for the purpose of gaining insight. In this position paper, we discuss how evaluating visual analytic systems can be approached through user interaction analysis, where the goal is to minimize the cognitive translation between the visual metaphor and the mode of interaction (i.e., reducing the “Interactionjunk”). We motivate this concept through a discussion of traditional GUIs used in visual analytics for direct manipulation of model parameters, and the importance of designing interactions the support visual data exploration.« less

Use of the self-organising map network (SOMNet) as a decision support system for regional mental health planning.

PubMed

Chung, Younjin; Salvador-Carulla, Luis; Salinas-Pérez, José A; Uriarte-Uriarte, Jose J; Iruin-Sanz, Alvaro; García-Alonso, Carlos R

2018-04-25

Decision-making in mental health systems should be supported by the evidence-informed knowledge transfer of data. Since mental health systems are inherently complex, involving interactions between its structures, processes and outcomes, decision support systems (DSS) need to be developed using advanced computational methods and visual tools to allow full system analysis, whilst incorporating domain experts in the analysis process. In this study, we use a DSS model developed for interactive data mining and domain expert collaboration in the analysis of complex mental health systems to improve system knowledge and evidence-informed policy planning. We combine an interactive visual data mining approach, the self-organising map network (SOMNet), with an operational expert knowledge approach, expert-based collaborative analysis (EbCA), to develop a DSS model. The SOMNet was applied to the analysis of healthcare patterns and indicators of three different regional mental health systems in Spain, comprising 106 small catchment areas and providing healthcare for over 9 million inhabitants. Based on the EbCA, the domain experts in the development team guided and evaluated the analytical processes and results. Another group of 13 domain experts in mental health systems planning and research evaluated the model based on the analytical information of the SOMNet approach for processing information and discovering knowledge in a real-world context. Through the evaluation, the domain experts assessed the feasibility and technology readiness level (TRL) of the DSS model. The SOMNet, combined with the EbCA, effectively processed evidence-based information when analysing system outliers, explaining global and local patterns, and refining key performance indicators with their analytical interpretations. The evaluation results showed that the DSS model was feasible by the domain experts and reached level 7 of the TRL (system prototype demonstration in operational environment). This study supports the benefits of combining health systems engineering (SOMNet) and expert knowledge (EbCA) to analyse the complexity of health systems research. The use of the SOMNet approach contributes to the demonstration of DSS for mental health planning in practice.

Guided Text Search Using Adaptive Visual Analytics

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

Steed, Chad A; Symons, Christopher T; Senter, James K

This research demonstrates the promise of augmenting interactive visualizations with semi- supervised machine learning techniques to improve the discovery of significant associations and insights in the search and analysis of textual information. More specifically, we have developed a system called Gryffin that hosts a unique collection of techniques that facilitate individualized investigative search pertaining to an ever-changing set of analytical questions over an indexed collection of open-source documents related to critical national infrastructure. The Gryffin client hosts dynamic displays of the search results via focus+context record listings, temporal timelines, term-frequency views, and multiple coordinate views. Furthermore, as the analyst interactsmore » with the display, the interactions are recorded and used to label the search records. These labeled records are then used to drive semi-supervised machine learning algorithms that re-rank the unlabeled search records such that potentially relevant records are moved to the top of the record listing. Gryffin is described in the context of the daily tasks encountered at the US Department of Homeland Security s Fusion Center, with whom we are collaborating in its development. The resulting system is capable of addressing the analysts information overload that can be directly attributed to the deluge of information that must be addressed in the search and investigative analysis of textual information.« less

Visual Analytics for Law Enforcement: Deploying a Service-Oriented Analytic Framework for Web-based Visualization

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

Dowson, Scott T.; Bruce, Joseph R.; Best, Daniel M.

2009-04-14

This paper presents key components of the Law Enforcement Information Framework (LEIF) that provides communications, situational awareness, and visual analytics tools in a service-oriented architecture supporting web-based desktop and handheld device users. LEIF simplifies interfaces and visualizations of well-established visual analytical techniques to improve usability. Advanced analytics capability is maintained by enhancing the underlying processing to support the new interface. LEIF development is driven by real-world user feedback gathered through deployments at three operational law enforcement organizations in the US. LEIF incorporates a robust information ingest pipeline supporting a wide variety of information formats. LEIF also insulates interface and analyticalmore » components from information sources making it easier to adapt the framework for many different data repositories.« less

Examining the Use of a Visual Analytics System for Sensemaking Tasks: Case Studies with Domain Experts.

PubMed

Kang, Youn-Ah; Stasko, J

2012-12-01

While the formal evaluation of systems in visual analytics is still relatively uncommon, particularly rare are case studies of prolonged system use by domain analysts working with their own data. Conducting case studies can be challenging, but it can be a particularly effective way to examine whether visual analytics systems are truly helping expert users to accomplish their goals. We studied the use of a visual analytics system for sensemaking tasks on documents by six analysts from a variety of domains. We describe their application of the system along with the benefits, issues, and problems that we uncovered. Findings from the studies identify features that visual analytics systems should emphasize as well as missing capabilities that should be addressed. These findings inform design implications for future systems.

The forensic validity of visual analytics

NASA Astrophysics Data System (ADS)

Erbacher, Robert F.

2008-01-01

The wider use of visualization and visual analytics in wide ranging fields has led to the need for visual analytics capabilities to be legally admissible, especially when applied to digital forensics. This brings the need to consider legal implications when performing visual analytics, an issue not traditionally examined in visualization and visual analytics techniques and research. While digital data is generally admissible under the Federal Rules of Evidence [10][21], a comprehensive validation of the digital evidence is considered prudent. A comprehensive validation requires validation of the digital data under rules for authentication, hearsay, best evidence rule, and privilege. Additional issues with digital data arise when exploring digital data related to admissibility and the validity of what information was examined, to what extent, and whether the analysis process was sufficiently covered by a search warrant. For instance, a search warrant generally covers very narrow requirements as to what law enforcement is allowed to examine and acquire during an investigation. When searching a hard drive for child pornography, how admissible is evidence of an unrelated crime, i.e. drug dealing. This is further complicated by the concept of "in plain view". When performing an analysis of a hard drive what would be considered "in plain view" when analyzing a hard drive. The purpose of this paper is to discuss the issues of digital forensics and the related issues as they apply to visual analytics and identify how visual analytics techniques fit into the digital forensics analysis process, how visual analytics techniques can improve the legal admissibility of digital data, and identify what research is needed to further improve this process. The goal of this paper is to open up consideration of legal ramifications among the visualization community; the author is not a lawyer and the discussions are not meant to be inclusive of all differences in laws between states and countries.

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.

Web-based Visual Analytics for Extreme Scale Climate Science

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

Steed, Chad A; Evans, Katherine J; Harney, John F

In this paper, we introduce a Web-based visual analytics framework for democratizing advanced visualization and analysis capabilities pertinent to large-scale earth system simulations. We address significant limitations of present climate data analysis tools such as tightly coupled dependencies, ineffi- cient data movements, complex user interfaces, and static visualizations. Our Web-based visual analytics framework removes critical barriers to the widespread accessibility and adoption of advanced scientific techniques. Using distributed connections to back-end diagnostics, we minimize data movements and leverage HPC platforms. We also mitigate system dependency issues by employing a RESTful interface. Our framework embraces the visual analytics paradigm via newmore » visual navigation techniques for hierarchical parameter spaces, multi-scale representations, and interactive spatio-temporal data mining methods that retain details. Although generalizable to other science domains, the current work focuses on improving exploratory analysis of large-scale Community Land Model (CLM) and Community Atmosphere Model (CAM) simulations.« less

An Analysis of Machine- and Human-Analytics in Classification.

PubMed

Tam, Gary K L; Kothari, Vivek; Chen, Min

2017-01-01

In this work, we present a study that traces the technical and cognitive processes in two visual analytics applications to a common theoretic model of soft knowledge that may be added into a visual analytics process for constructing a decision-tree model. Both case studies involved the development of classification models based on the "bag of features" approach. Both compared a visual analytics approach using parallel coordinates with a machine-learning approach using information theory. Both found that the visual analytics approach had some advantages over the machine learning approach, especially when sparse datasets were used as the ground truth. We examine various possible factors that may have contributed to such advantages, and collect empirical evidence for supporting the observation and reasoning of these factors. We propose an information-theoretic model as a common theoretic basis to explain the phenomena exhibited in these two case studies. Together we provide interconnected empirical and theoretical evidence to support the usefulness of visual analytics.

Visual Analytics in Public Safety: Example Capabilities for Example Government Agencies

DTIC Science & Technology

2011-10-01

is not limited to: the Police Records Information Management Environment for British Columbia (PRIME-BC), the Police Reporting and Occurrence System...and filtering for rapid identification of relevant documents - Graphical environment for visual evidence marshaling - Interactive linking and...analytical reasoning facilitated by interactive visual interfaces and integration with computational analytics. Indeed, a wide variety of technologies

The Earth Science Research Network as Seen Through Network Analysis of the AGU

NASA Astrophysics Data System (ADS)

Narock, T.; Hasnain, S.; Stephan, R.

2017-12-01

Scientometrics is the science of science. Scientometric research includes measurements of impact, mapping of scientific fields, and the production of indicators for use in policy and management. We have leveraged network analysis in a scientometric study of the American Geophysical Union (AGU). Data from the AGU's Linked Data Abstract Browser was used to create a visualization and analytics tools to explore the Earth science's research network. Our application applies network theory to look at network structure within the various AGU sections, identify key individuals and communities related to Earth science topics, and examine multi-disciplinary collaboration across sections. Opportunities to optimize Earth science output, as well as policy and outreach applications, are discussed.

Development of collaborative-creative learning model using virtual laboratory media for instrumental analytical chemistry lectures

NASA Astrophysics Data System (ADS)

Zurweni, Wibawa, Basuki; Erwin, Tuti Nurian

2017-08-01

The framework for teaching and learning in the 21st century was prepared with 4Cs criteria. Learning providing opportunity for the development of students' optimal creative skills is by implementing collaborative learning. Learners are challenged to be able to compete, work independently to bring either individual or group excellence and master the learning material. Virtual laboratory is used for the media of Instrumental Analytical Chemistry (Vis, UV-Vis-AAS etc) lectures through simulations computer application and used as a substitution for the laboratory if the equipment and instruments are not available. This research aims to design and develop collaborative-creative learning model using virtual laboratory media for Instrumental Analytical Chemistry lectures, to know the effectiveness of this design model adapting the Dick & Carey's model and Hannafin & Peck's model. The development steps of this model are: needs analyze, design collaborative-creative learning, virtual laboratory media using macromedia flash, formative evaluation and test of learning model effectiveness. While, the development stages of collaborative-creative learning model are: apperception, exploration, collaboration, creation, evaluation, feedback. Development of collaborative-creative learning model using virtual laboratory media can be used to improve the quality learning in the classroom, overcome the limitation of lab instruments for the real instrumental analysis. Formative test results show that the Collaborative-Creative Learning Model developed meets the requirements. The effectiveness test of students' pretest and posttest proves significant at 95% confidence level, t-test higher than t-table. It can be concluded that this learning model is effective to use for Instrumental Analytical Chemistry lectures.

The social computing room: a multi-purpose collaborative visualization environment

NASA Astrophysics Data System (ADS)

Borland, David; Conway, Michael; Coposky, Jason; Ginn, Warren; Idaszak, Ray

2010-01-01

The Social Computing Room (SCR) is a novel collaborative visualization environment for viewing and interacting with large amounts of visual data. The SCR consists of a square room with 12 projectors (3 per wall) used to display a single 360-degree desktop environment that provides a large physical real estate for arranging visual information. The SCR was designed to be cost-effective, collaborative, configurable, widely applicable, and approachable for naive users. Because the SCR displays a single desktop, a wide range of applications is easily supported, making it possible for a variety of disciplines to take advantage of the room. We provide a technical overview of the room and highlight its application to scientific visualization, arts and humanities projects, research group meetings, and virtual worlds, among other uses.

TimeBench: a data model and software library for visual analytics of time-oriented data.

PubMed

Rind, Alexander; Lammarsch, Tim; Aigner, Wolfgang; Alsallakh, Bilal; Miksch, Silvia

2013-12-01

Time-oriented data play an essential role in many Visual Analytics scenarios such as extracting medical insights from collections of electronic health records or identifying emerging problems and vulnerabilities in network traffic. However, many software libraries for Visual Analytics treat time as a flat numerical data type and insufficiently tackle the complexity of the time domain such as calendar granularities and intervals. Therefore, developers of advanced Visual Analytics designs need to implement temporal foundations in their application code over and over again. We present TimeBench, a software library that provides foundational data structures and algorithms for time-oriented data in Visual Analytics. Its expressiveness and developer accessibility have been evaluated through application examples demonstrating a variety of challenges with time-oriented data and long-term developer studies conducted in the scope of research and student projects.

Visualization analysis of author collaborations in schizophrenia research.

PubMed

Wu, Ying; Duan, Zhiguang

2015-02-19

Schizophrenia is a serious mental illness that levies a heavy medical toll and cost burden throughout the world. Scientific collaborations are necessary for progress in psychiatric research. However, there have been few publications on scientific collaborations in schizophrenia. The aim of this study was to investigate the extent of author collaborations in schizophrenia research. This study used 58,107 records on schizophrenia from 2003 to 2012 which were downloaded from Science Citation Index Expanded (SCI Expanded) via Web of Science. CiteSpace III, an information visualization and analysis software, was used to make a visual analysis. Collaborative author networks within the field of schizophrenia were determined using published documents. We found that external author collaboration networks were more scattered while potential author collaboration networks were more compact. Results from hierarchical clustering analysis showed that the main collaborative field was genetic research in schizophrenia. Based on the results, authors belonging to different institutions and in different countries should be encouraged to collaborate in schizophrenia research. This will help researchers focus their studies on key issues, and allow each other to offer reasonable suggestions for making polices and providing scientific evidence to effectively diagnose, prevent, and cure schizophrenia.

Musician Map: visualizing music collaborations over time

NASA Astrophysics Data System (ADS)

Yim, Ji-Dong; Shaw, Chris D.; Bartram, Lyn

2009-01-01

In this paper we introduce Musician Map, a web-based interactive tool for visualizing relationships among popular musicians who have released recordings since 1950. Musician Map accepts search terms from the user, and in turn uses these terms to retrieve data from MusicBrainz.org and AudioScrobbler.net, and visualizes the results. Musician Map visualizes relationships of various kinds between music groups and individual musicians, such as band membership, musical collaborations, and linkage to other artists that are generally regarded as being similar in musical style. These relationships are plotted between artists using a new timeline-based visualization where a node in a traditional node-link diagram has been transformed into a Timeline-Node, which allows the visualization of an evolving entity over time, such as the membership in a band. This allows the user to pursue social trend queries such as "Do Hip-Hop artists collaborate differently than Rock artists".

Rethinking Visual Analytics for Streaming Data Applications

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

Crouser, R. Jordan; Franklin, Lyndsey; Cook, Kris

In the age of data science, the use of interactive information visualization techniques has become increasingly ubiquitous. From online scientific journals to the New York Times graphics desk, the utility of interactive visualization for both storytelling and analysis has become ever more apparent. As these techniques have become more readily accessible, the appeal of combining interactive visualization with computational analysis continues to grow. Arising out of a need for scalable, human-driven analysis, primary objective of visual analytics systems is to capitalize on the complementary strengths of human and machine analysis, using interactive visualization as a medium for communication between themore » two. These systems leverage developments from the fields of information visualization, computer graphics, machine learning, and human-computer interaction to support insight generation in areas where purely computational analyses fall short. Over the past decade, visual analytics systems have generated remarkable advances in many historically challenging analytical contexts. These include areas such as modeling political systems [Crouser et al. 2012], detecting financial fraud [Chang et al. 2008], and cybersecurity [Harrison et al. 2012]. In each of these contexts, domain expertise and human intuition is a necessary component of the analysis. This intuition is essential to building trust in the analytical products, as well as supporting the translation of evidence into actionable insight. In addition, each of these examples also highlights the need for scalable analysis. In each case, it is infeasible for a human analyst to manually assess the raw information unaided, and the communication overhead to divide the task between a large number of analysts makes simple parallelism intractable. Regardless of the domain, visual analytics tools strive to optimize the allocation of human analytical resources, and to streamline the sensemaking process on data that is massive, complex, incomplete, and uncertain in scenarios requiring human judgment.« less

Visual and Analytic Strategies in Geometry

ERIC Educational Resources Information Center

Kospentaris, George; Vosniadou, Stella; Kazic, Smaragda; Thanou, Emilian

2016-01-01

We argue that there is an increasing reliance on analytic strategies compared to visuospatial strategies, which is related to geometry expertise and not on individual differences in cognitive style. A Visual/Analytic Strategy Test (VAST) was developed to investigate the use of visuo-spatial and analytic strategies in geometry in 30 mathematics…

Social Network Analysis of Biomedical Research Collaboration Networks in a CTSA Institution

PubMed Central

Bian, Jiang; Xie, Mengjun; Topaloglu, Umit; Hudson, Teresa; Eswaran, Hari; Hogan, William

2014-01-01

BACKGROUND The popularity of social networks has triggered a number of research efforts on network analyses of research collaborations in the Clinical and Translational Science Award (CTSA) community. Those studies mainly focus on the general understanding of collaboration networks by measuring common network metrics. More fundamental questions about collaborations still remain unanswered such as recognizing “influential” nodes and identifying potential new collaborations that are most rewarding. METHODS We analyzed biomedical research collaboration networks (RCNs) constructed from a dataset of research grants collected at a CTSA institution (i.e. University of Arkansas for Medical Sciences (UAMS)) in a comprehensive and systematic manner. First, our analysis covers the full spectrum of a RCN study: from network modeling to network characteristics measurement, from key nodes recognition to potential links (collaborations) suggestion. Second, our analysis employs non-conventional model and techniques including a weighted network model for representing collaboration strength, rank aggregation for detecting important nodes, and Random Walk with Restart (RWR) for suggesting new research collaborations. RESULTS By applying our models and techniques to RCNs at UAMS prior to and after the CTSA, we have gained valuable insights that not only reveal the temporal evolution of the network dynamics but also assess the effectiveness of the CTSA and its impact on a research institution. We find that collaboration networks at UAMS are not scale-free but small-world. Quantitative measures have been obtained to evident that the RCNs at UAMS are moving towards favoring multidisciplinary research. Moreover, our link prediction model creates the basis of collaboration recommendations with an impressive accuracy (AUC: 0.990, MAP@3: 1.48 and MAP@5: 1.522). Last but not least, an open-source visual analytical tool for RCNs is being developed and released through Github. CONCLUSIONS Through this study, we have developed a set of techniques and tools for analyzing research collaboration networks and conducted a comprehensive case study focusing on a CTSA institution. Our findings demonstrate the promising future of these techniques and tools in understanding the generative mechanisms of research collaborations and helping identify beneficial collaborations to members in the research community. PMID:24560679

A case study of collaborative facilities use in engineering design

NASA Astrophysics Data System (ADS)

Monroe, Laura; Pugmire, David

2010-01-01

In this paper we describe the use of visualization tools and facilities in the collaborative design of a replacement weapons system, the Reliable Replacement Warhead (RRW). We used not only standard collaboration methods but also a range of visualization software and facilities to bring together domain specialists from laboratories across the country to collaborate on the design and integrate this disparate input early in the design. This was the first time in U.S. weapons history that a weapon had been designed in this collaborative manner. Benefits included projected cost savings, design improvements and increased understanding across the project.

Lack of habituation of evoked visual potentials in analytic information processing style: evidence in healthy subjects.

PubMed

Buonfiglio, Marzia; Toscano, M; Puledda, F; Avanzini, G; Di Clemente, L; Di Sabato, F; Di Piero, V

2015-03-01

Habituation is considered one of the most basic mechanisms of learning. Habituation deficit to several sensory stimulations has been defined as a trait of migraine brain and also observed in other disorders. On the other hand, analytic information processing style is characterized by the habit of continually evaluating stimuli and it has been associated with migraine. We investigated a possible correlation between lack of habituation of evoked visual potentials and analytic cognitive style in healthy subjects. According to Sternberg-Wagner self-assessment inventory, 15 healthy volunteers (HV) with high analytic score and 15 HV with high global score were recruited. Both groups underwent visual evoked potentials recordings after psychological evaluation. We observed significant lack of habituation in analytical individuals compared to global group. In conclusion, a reduced habituation of visual evoked potentials has been observed in analytic subjects. Our results suggest that further research should be undertaken regarding the relationship between analytic cognitive style and lack of habituation in both physiological and pathophysiological conditions.

D3: A Collaborative Infrastructure for Aerospace Design

NASA Technical Reports Server (NTRS)

Walton, Joan; Filman, Robert E.; Knight, Chris; Korsmeyer, David J.; Lee, Diana D.; Clancy, Daniel (Technical Monitor)

2001-01-01

DARWIN is a NASA developed, Internet-based system for enabling aerospace researchers to securely and remotely access and collaborate on the analysis of aerospace vehicle design data, primarily the results of wind-tunnel testing and numeric (e.g., computational fluid dynamics) model executions. DARWIN captures, stores and indexes data, manages derived knowledge (such as visualizations across multiple data sets) and provides an environment for designers to collaborate in the analysis of the results of testing. DARWIN is an interesting application because it supports high volumes of data, integrates multiple modalities of data display (e.g. images and data visualizations), and provides non-trivial access control mechanisms. DARWIN enables collaboration by allowing not only sharing visualizations of data, but also commentary about and view of data.

Mixed Initiative Visual Analytics Using Task-Driven Recommendations

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

Cook, Kristin A.; Cramer, Nicholas O.; Israel, David

2015-12-07

Visual data analysis is composed of a collection of cognitive actions and tasks to decompose, internalize, and recombine data to produce knowledge and insight. Visual analytic tools provide interactive visual interfaces to data to support tasks involved in discovery and sensemaking, including forming hypotheses, asking questions, and evaluating and organizing evidence. Myriad analytic models can be incorporated into visual analytic systems, at the cost of increasing complexity in the analytic discourse between user and system. Techniques exist to increase the usability of interacting with such analytic models, such as inferring data models from user interactions to steer the underlying modelsmore » of the system via semantic interaction, shielding users from having to do so explicitly. Such approaches are often also referred to as mixed-initiative systems. Researchers studying the sensemaking process have called for development of tools that facilitate analytic sensemaking through a combination of human and automated activities. However, design guidelines do not exist for mixed-initiative visual analytic systems to support iterative sensemaking. In this paper, we present a candidate set of design guidelines and introduce the Active Data Environment (ADE) prototype, a spatial workspace supporting the analytic process via task recommendations invoked by inferences on user interactions within the workspace. ADE recommends data and relationships based on a task model, enabling users to co-reason with the system about their data in a single, spatial workspace. This paper provides an illustrative use case, a technical description of ADE, and a discussion of the strengths and limitations of the approach.« less

GeoChronos: An On-line Collaborative Platform for Earth Observation Scientists

NASA Astrophysics Data System (ADS)

Gamon, J. A.; Kiddle, C.; Curry, R.; Markatchev, N.; Zonta-Pastorello, G., Jr.; Rivard, B.; Sanchez-Azofeifa, G. A.; Simmonds, R.; Tan, T.

2009-12-01

Recent advances in cyberinfrastructure are offering new solutions to the growing challenges of managing and sharing large data volumes. Web 2.0 and social networking technologies, provide the means for scientists to collaborate and share information more effectively. Cloud computing technologies can provide scientists with transparent and on-demand access to applications served over the Internet in a dynamic and scalable manner. Semantic Web technologies allow for data to be linked together in a manner understandable by machines, enabling greater automation. Combining all of these technologies together can enable the creation of very powerful platforms. GeoChronos (http://geochronos.org/), part of a CANARIE Network Enabled Platforms project, is an online collaborative platform that incorporates these technologies to enable members of the earth observation science community to share data and scientific applications and to collaborate more effectively. The GeoChronos portal is built on an open source social networking platform called Elgg. Elgg provides a full set of social networking functionalities similar to Facebook including blogs, tags, media/document sharing, wikis, friends/contacts, groups, discussions, message boards, calendars, status, activity feeds and more. An underlying cloud computing infrastructure enables scientists to access dynamically provisioned applications via the portal for visualizing and analyzing data. Users are able to access and run the applications from any computer that has a Web browser and Internet connectivity and do not need to manage and maintain the applications themselves. Semantic Web Technologies, such as the Resource Description Framework (RDF) are being employed for relating and linking together spectral, satellite, meteorological and other data. Social networking functionality plays an integral part in facilitating the sharing of data and applications. Examples of recent GeoChronos users during the early testing phase have included the IAI International Wireless Sensor Networking Summer School at the University of Alberta, and the IAI Tropi-Dry community. Current GeoChronos activities include the development of a web-based spectral library and related analytical and visualization tools, in collaboration with members of the SpecNet community. The GeoChronos portal will be open to all members of the earth observation science community when the project nears completion at the end of 2010.

A graph algebra for scalable visual analytics.

PubMed

Shaverdian, Anna A; Zhou, Hao; Michailidis, George; Jagadish, Hosagrahar V

2012-01-01

Visual analytics (VA), which combines analytical techniques with advanced visualization features, is fast becoming a standard tool for extracting information from graph data. Researchers have developed many tools for this purpose, suggesting a need for formal methods to guide these tools' creation. Increased data demands on computing requires redesigning VA tools to consider performance and reliability in the context of analysis of exascale datasets. Furthermore, visual analysts need a way to document their analyses for reuse and results justification. A VA graph framework encapsulated in a graph algebra helps address these needs. Its atomic operators include selection and aggregation. The framework employs a visual operator and supports dynamic attributes of data to enable scalable visual exploration of data.

Data visualisation in surveillance for injury prevention and control: conceptual bases and case studies

PubMed Central

Martinez, Ramon; Ordunez, Pedro; Soliz, Patricia N; Ballesteros, Michael F

2016-01-01

Background The complexity of current injury-related health issues demands the usage of diverse and massive data sets for comprehensive analyses, and application of novel methods to communicate data effectively to the public health community, decision-makers and the public. Recent advances in information visualisation, availability of new visual analytic methods and tools, and progress on information technology provide an opportunity for shaping the next generation of injury surveillance. Objective To introduce data visualisation conceptual bases, and propose a visual analytic and visualisation platform in public health surveillance for injury prevention and control. Methods The paper introduces data visualisation conceptual bases, describes a visual analytic and visualisation platform, and presents two real-world case studies illustrating their application in public health surveillance for injury prevention and control. Results Application of visual analytic and visualisation platform is presented as solution for improved access to heterogeneous data sources, enhance data exploration and analysis, communicate data effectively, and support decision-making. Conclusions Applications of data visualisation concepts and visual analytic platform could play a key role to shape the next generation of injury surveillance. Visual analytic and visualisation platform could improve data use, the analytic capacity, and ability to effectively communicate findings and key messages. The public health surveillance community is encouraged to identify opportunities to develop and expand its use in injury prevention and control. PMID:26728006

Integrated remote sensing and visualization (IRSV) system for transportation infrastructure operations and management, phase two, volume 4 : web-based bridge information database--visualization analytics and distributed sensing.

DOT National Transportation Integrated Search

2012-03-01

This report introduces the design and implementation of a Web-based bridge information visual analytics system. This : project integrates Internet, multiple databases, remote sensing, and other visualization technologies. The result : combines a GIS ...

Visualisation and Analytic Strategies for Anticipating the Folding of Nets

ERIC Educational Resources Information Center

Wright, Vince

2016-01-01

Visual and analytic strategies are features of students' schemes for spatial tasks. The strategies used by six students to anticipate the folding of nets were investigated. Evidence suggested that visual and analytic strategies were strongly connected in competent performance.

Visual analytics of brain networks.

PubMed

Li, Kaiming; Guo, Lei; Faraco, Carlos; Zhu, Dajiang; Chen, Hanbo; Yuan, Yixuan; Lv, Jinglei; Deng, Fan; Jiang, Xi; Zhang, Tuo; Hu, Xintao; Zhang, Degang; Miller, L Stephen; Liu, Tianming

2012-05-15

Identification of regions of interest (ROIs) is a fundamental issue in brain network construction and analysis. Recent studies demonstrate that multimodal neuroimaging approaches and joint analysis strategies are crucial for accurate, reliable and individualized identification of brain ROIs. In this paper, we present a novel approach of visual analytics and its open-source software for ROI definition and brain network construction. By combining neuroscience knowledge and computational intelligence capabilities, visual analytics can generate accurate, reliable and individualized ROIs for brain networks via joint modeling of multimodal neuroimaging data and an intuitive and real-time visual analytics interface. Furthermore, it can be used as a functional ROI optimization and prediction solution when fMRI data is unavailable or inadequate. We have applied this approach to an operation span working memory fMRI/DTI dataset, a schizophrenia DTI/resting state fMRI (R-fMRI) dataset, and a mild cognitive impairment DTI/R-fMRI dataset, in order to demonstrate the effectiveness of visual analytics. Our experimental results are encouraging. Copyright © 2012 Elsevier Inc. All rights reserved.

Ultrascale collaborative visualization using a display-rich global cyberinfrastructure.

PubMed

Jeong, Byungil; Leigh, Jason; Johnson, Andrew; Renambot, Luc; Brown, Maxine; Jagodic, Ratko; Nam, Sungwon; Hur, Hyejung

2010-01-01

The scalable adaptive graphics environment (SAGE) is high-performance graphics middleware for ultrascale collaborative visualization using a display-rich global cyberinfrastructure. Dozens of sites worldwide use this cyberinfrastructure middleware, which connects high-performance-computing resources over high-speed networks to distributed ultraresolution displays.

The global lambda visualization facility: An international ultra-high-definition wide-area visualization collaboratory

USGS Publications Warehouse

Leigh, J.; Renambot, L.; Johnson, Aaron H.; Jeong, B.; Jagodic, R.; Schwarz, N.; Svistula, D.; Singh, R.; Aguilera, J.; Wang, X.; Vishwanath, V.; Lopez, B.; Sandin, D.; Peterka, T.; Girado, J.; Kooima, R.; Ge, J.; Long, L.; Verlo, A.; DeFanti, T.A.; Brown, M.; Cox, D.; Patterson, R.; Dorn, P.; Wefel, P.; Levy, S.; Talandis, J.; Reitzer, J.; Prudhomme, T.; Coffin, T.; Davis, B.; Wielinga, P.; Stolk, B.; Bum, Koo G.; Kim, J.; Han, S.; Corrie, B.; Zimmerman, T.; Boulanger, P.; Garcia, M.

2006-01-01

The research outlined in this paper marks an initial global cooperative effort between visualization and collaboration researchers to build a persistent virtual visualization facility linked by ultra-high-speed optical networks. The goal is to enable the comprehensive and synergistic research and development of the necessary hardware, software and interaction techniques to realize the next generation of end-user tools for scientists to collaborate on the global Lambda Grid. This paper outlines some of the visualization research projects that were demonstrated at the iGrid 2005 workshop in San Diego, California.

High Performance Visualization using Query-Driven Visualizationand Analytics

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

Bethel, E. Wes; Campbell, Scott; Dart, Eli

2006-06-15

Query-driven visualization and analytics is a unique approach for high-performance visualization that offers new capabilities for knowledge discovery and hypothesis testing. The new capabilities akin to finding needles in haystacks are the result of combining technologies from the fields of scientific visualization and scientific data management. This approach is crucial for rapid data analysis and visualization in the petascale regime. This article describes how query-driven visualization is applied to a hero-sized network traffic analysis problem.

Opportunities for GEOGLAM to contribute to Food Systems Sustainability

NASA Astrophysics Data System (ADS)

LeZaks, D.; Jahn, M.

2013-12-01

Since the GEO Global Agricultural Monitoring (GEO-GLAM) community of practice was formed, there has been much interest in how this community can be leveraged to address a series of challenges that has received recognition from a variety of stakeholder groups across acacemia, government, the private sector and multilateral international organizations. This talk will review the collaborative network that has formed around the on-going and planned activities of GEOGLAM, and how future research and development activities within and around GEOGLAM can contribute to the innovation ecosystem around agricultural monitoring and how monitoring activities can contribute to informing decision processes from stakeholders ranging from farmers to policy-makers and other key stakeholders. These collaborative activities revolve around sharing data, information, knowledge, analytics, improved reflections of risks, and opportunities related to humanity's sustainable provisioning at the land/water/energy nexus. The goal of extending GEOGLAMs collaborative activities is to mobilize aligned assets and commitments to set up more ordered approaches to describing and managing the dynamics of food systems, viewed more holistically as sets of nested geospatially and temporally explicit processes. A special focus will be given to how information assets originating from within GEOGLAM can be used to support a coherent visualization of the world's food systems along with improving representation of the resource bases upon which our survival depends

Data visualisation in surveillance for injury prevention and control: conceptual bases and case studies.

PubMed

Martinez, Ramon; Ordunez, Pedro; Soliz, Patricia N; Ballesteros, Michael F

2016-04-01

The complexity of current injury-related health issues demands the usage of diverse and massive data sets for comprehensive analyses, and application of novel methods to communicate data effectively to the public health community, decision-makers and the public. Recent advances in information visualisation, availability of new visual analytic methods and tools, and progress on information technology provide an opportunity for shaping the next generation of injury surveillance. To introduce data visualisation conceptual bases, and propose a visual analytic and visualisation platform in public health surveillance for injury prevention and control. The paper introduces data visualisation conceptual bases, describes a visual analytic and visualisation platform, and presents two real-world case studies illustrating their application in public health surveillance for injury prevention and control. Application of visual analytic and visualisation platform is presented as solution for improved access to heterogeneous data sources, enhance data exploration and analysis, communicate data effectively, and support decision-making. Applications of data visualisation concepts and visual analytic platform could play a key role to shape the next generation of injury surveillance. Visual analytic and visualisation platform could improve data use, the analytic capacity, and ability to effectively communicate findings and key messages. The public health surveillance community is encouraged to identify opportunities to develop and expand its use in injury prevention and control. 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/

Comparing art-science collaboration efforts to highlight changes in the marine environment of Arctic Alaska

NASA Astrophysics Data System (ADS)

Lee, O. A.

2016-12-01

Significant changes to the Arctic marine environment is anticipated as a result of decreasing sea ice and increasing anthropogenic activity that may occur with increasing access to ice-free waters. Two different collaboration efforts between scientists and artists on projects related to changes in the Alaskan Arctic waters are compared to present different outcomes from two collaboration strategies. The first collaboration involved a funded project to develop visualizations of change on the North Slope as part of an outreach effort for the North Slope Science Initiative Scenarios project. The second collaboration was a voluntary art-science collaboration to develop artwork about changing sea ice habitat for walrus as one contribution to a featured art show during the 2016 Arctic Science Summit Week. Both collaboration opportunities resulted in compelling visualizations. However the funded collaboration provided for more iterative discussions between the scientist and the collaborators for the film and animation products throughout the duration of the project. This ensured that the science remained an important focal point. In contrast, the product of the voluntary collaboration effort was primarily driven by the artist's perspective, although the discussions with the scientist played a role in connecting the content of the three panels in the final art and sculpture piece. This comparison of different levels of scientist-involvement and resources used to develop the visualizations highlights the importance of defining the intended audience and expectations for all collaborators early.

PAVA: Physiological and Anatomical Visual Analytics for Mapping of Tissue-Specific Concentration and Time-Course Data

EPA Science Inventory

We describe the development and implementation of a Physiological and Anatomical Visual Analytics tool (PAVA), a web browser-based application, used to visualize experimental/simulated chemical time-course data (dosimetry), epidemiological data and Physiologically-Annotated Data ...

A Visual Analytics Paradigm Enabling Trillion-Edge Graph Exploration

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

Wong, Pak C.; Haglin, David J.; Gillen, David S.

We present a visual analytics paradigm and a system prototype for exploring web-scale graphs. A web-scale graph is described as a graph with ~one trillion edges and ~50 billion vertices. While there is an aggressive R&D effort in processing and exploring web-scale graphs among internet vendors such as Facebook and Google, visualizing a graph of that scale still remains an underexplored R&D area. The paper describes a nontraditional peek-and-filter strategy that facilitates the exploration of a graph database of unprecedented size for visualization and analytics. We demonstrate that our system prototype can 1) preprocess a graph with ~25 billion edgesmore » in less than two hours and 2) support database query and visualization on the processed graph database afterward. Based on our computational performance results, we argue that we most likely will achieve the one trillion edge mark (a computational performance improvement of 40 times) for graph visual analytics in the near future.« less

Visual analytics in medical education: impacting analytical reasoning and decision making for quality improvement.

PubMed

Vaitsis, Christos; Nilsson, Gunnar; Zary, Nabil

2015-01-01

The medical curriculum is the main tool representing the entire undergraduate medical education. Due to its complexity and multilayered structure it is of limited use to teachers in medical education for quality improvement purposes. In this study we evaluated three visualizations of curriculum data from a pilot course, using teachers from an undergraduate medical program and applying visual analytics methods. We found that visual analytics can be used to positively impacting analytical reasoning and decision making in medical education through the realization of variables capable to enhance human perception and cognition on complex curriculum data. The positive results derived from our evaluation of a medical curriculum and in a small scale, signify the need to expand this method to an entire medical curriculum. As our approach sustains low levels of complexity it opens a new promising direction in medical education informatics research.

ESIP Earth Sciences Data Analytics (ESDA) Cluster - Work in Progress

NASA Technical Reports Server (NTRS)

Kempler, Steven

2015-01-01

The purpose of this poster is to promote a common understanding of the usefulness of, and activities that pertain to, Data Analytics and more broadly, the Data Scientist; Facilitate collaborations to better understand the cross usage of heterogeneous datasets and to provide accommodating data analytics expertise, now and as the needs evolve into the future; Identify gaps that, once filled, will further collaborative activities. Objectives Provide a forum for Academic discussions that provides ESIP members a better understanding of the various aspects of Earth Science Data Analytics Bring in guest speakers to describe external efforts, and further teach us about the broader use of Data Analytics. Perform activities that:- Compile use cases generated from specific community needs to cross analyze heterogeneous data- Compile sources of analytics tools, in particular, to satisfy the needs of the above data users- Examine gaps between needs and sources- Examine gaps between needs and community expertise- Document specific data analytics expertise needed to perform Earth science data analytics Seek graduate data analytics Data Science student internship opportunities.

An optimized web-based approach for collaborative stereoscopic medical visualization

PubMed Central

Kaspar, Mathias; Parsad, Nigel M; Silverstein, Jonathan C

2013-01-01

Objective Medical visualization tools have traditionally been constrained to tethered imaging workstations or proprietary client viewers, typically part of hospital radiology systems. To improve accessibility to real-time, remote, interactive, stereoscopic visualization and to enable collaboration among multiple viewing locations, we developed an open source approach requiring only a standard web browser with no added client-side software. Materials and Methods Our collaborative, web-based, stereoscopic, visualization system, CoWebViz, has been used successfully for the past 2 years at the University of Chicago to teach immersive virtual anatomy classes. It is a server application that streams server-side visualization applications to client front-ends, comprised solely of a standard web browser with no added software. Results We describe optimization considerations, usability, and performance results, which make CoWebViz practical for broad clinical use. We clarify technical advances including: enhanced threaded architecture, optimized visualization distribution algorithms, a wide range of supported stereoscopic presentation technologies, and the salient theoretical and empirical network parameters that affect our web-based visualization approach. Discussion The implementations demonstrate usability and performance benefits of a simple web-based approach for complex clinical visualization scenarios. Using this approach overcomes technical challenges that require third-party web browser plug-ins, resulting in the most lightweight client. Conclusions Compared to special software and hardware deployments, unmodified web browsers enhance remote user accessibility to interactive medical visualization. Whereas local hardware and software deployments may provide better interactivity than remote applications, our implementation demonstrates that a simplified, stable, client approach using standard web browsers is sufficient for high quality three-dimensional, stereoscopic, collaborative and interactive visualization. PMID:23048008

Applying Pragmatics Principles for Interaction with Visual Analytics.

PubMed

Hoque, Enamul; Setlur, Vidya; Tory, Melanie; Dykeman, Isaac

2018-01-01

Interactive visual data analysis is most productive when users can focus on answering the questions they have about their data, rather than focusing on how to operate the interface to the analysis tool. One viable approach to engaging users in interactive conversations with their data is a natural language interface to visualizations. These interfaces have the potential to be both more expressive and more accessible than other interaction paradigms. We explore how principles from language pragmatics can be applied to the flow of visual analytical conversations, using natural language as an input modality. We evaluate the effectiveness of pragmatics support in our system Evizeon, and present design considerations for conversation interfaces to visual analytics tools.

Transformation of an uncertain video search pipeline to a sketch-based visual analytics loop.

PubMed

Legg, Philip A; Chung, David H S; Parry, Matthew L; Bown, Rhodri; Jones, Mark W; Griffiths, Iwan W; Chen, Min

2013-12-01

Traditional sketch-based image or video search systems rely on machine learning concepts as their core technology. However, in many applications, machine learning alone is impractical since videos may not be semantically annotated sufficiently, there may be a lack of suitable training data, and the search requirements of the user may frequently change for different tasks. In this work, we develop a visual analytics systems that overcomes the shortcomings of the traditional approach. We make use of a sketch-based interface to enable users to specify search requirement in a flexible manner without depending on semantic annotation. We employ active machine learning to train different analytical models for different types of search requirements. We use visualization to facilitate knowledge discovery at the different stages of visual analytics. This includes visualizing the parameter space of the trained model, visualizing the search space to support interactive browsing, visualizing candidature search results to support rapid interaction for active learning while minimizing watching videos, and visualizing aggregated information of the search results. We demonstrate the system for searching spatiotemporal attributes from sports video to identify key instances of the team and player performance.

Lateral flow devices

DOEpatents

Mazumdar, Debapriya; Liu, Juewen; Lu, Yi

2010-09-21

An analytical test for an analyte comprises (a) a base, having a reaction area and a visualization area, (b) a capture species, on the base in the visualization area, comprising nucleic acid, and (c) analysis chemistry reagents, on the base in the reaction area. The analysis chemistry reagents comprise (i) a substrate comprising nucleic acid and a first label, and (ii) a reactor comprising nucleic acid. The analysis chemistry reagents can react with a sample comprising the analyte and water, to produce a visualization species comprising nucleic acid and the first label, and the capture species can bind the visualization species.

CI-KNOW: Cyberinfrastructure Knowledge Networks on the Web. A Social Network Enabled Recommender System for Locating Resources in Cyberinfrastructures

NASA Astrophysics Data System (ADS)

Green, H. D.; Contractor, N. S.; Yao, Y.

2006-12-01

A knowledge network is a multi-dimensional network created from the interactions and interconnections among the scientists, documents, data, analytic tools, and interactive collaboration spaces (like forums and wikis) associated with a collaborative environment. CI-KNOW is a suite of software tools that leverages automated data collection, social network theories, analysis techniques and algorithms to infer an individual's interests and expertise based on their interactions and activities within a knowledge network. The CI-KNOW recommender system mines the knowledge network associated with a scientific community's use of cyberinfrastructure tools and uses relational metadata to record connections among entities in the knowledge network. Recent developments in social network theories and methods provide the backbone for a modular system that creates recommendations from relational metadata. A network navigation portlet allows users to locate colleagues, documents, data or analytic tools in the knowledge network and to explore their networks through a visual, step-wise process. An internal auditing portlet offers administrators diagnostics to assess the growth and health of the entire knowledge network. The first instantiation of the prototype CI-KNOW system is part of the Environmental Cyberinfrastructure Demonstration project at the National Center for Supercomputing Applications, which supports the activities of hydrologic and environmental science communities (CLEANER and CUAHSI) under the umbrella of the WATERS network environmental observatory planning activities (http://cleaner.ncsa.uiuc.edu). This poster summarizes the key aspects of the CI-KNOW system, highlighting the key inputs, calculation mechanisms, and output modalities.

VisSearch: A Collaborative Web Searching Environment

ERIC Educational Resources Information Center

Lee, Young-Jin

2005-01-01

VisSearch is a collaborative Web searching environment intended for sharing Web search results among people with similar interests, such as college students taking the same course. It facilitates students' Web searches by visualizing various Web searching processes. It also collects the visualized Web search results and applies an association rule…

Using Visualization to Motivate Student Participation in Collaborative Online Learning Environments

ERIC Educational Resources Information Center

Jin, Sung-Hee

2017-01-01

Online participation in collaborative online learning environments is instrumental in motivating students to learn and promoting their learning satisfaction, but there has been little research on the technical supports for motivating students' online participation. The purpose of this study was to develop a visualization tool to motivate learners…

Collaborative Rhetorical Structure: A Discourse Analysis Method for Analyzing Student Collaborative Inquiry via Computer Conferencing

ERIC Educational Resources Information Center

Kou, Xiaojing

2011-01-01

Various formats of online discussion have proven valuable for enhancing learning and collaboration in distance and blended learning contexts. However, despite their capacity to reveal essential processes in collaborative inquiry, current mainstream analytical frameworks, such as the cognitive presence framework (Garrison, Anderson, & Archer,…

Visual Analytics and Storytelling through Video

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

Wong, Pak C.; Perrine, Kenneth A.; Mackey, Patrick S.

2005-10-31

This paper supplements a video clip submitted to the Video Track of IEEE Symposium on Information Visualization 2005. The original video submission applies a two-way storytelling approach to demonstrate the visual analytics capabilities of a new visualization technique. The paper presents our video production philosophy, describes the plot of the video, explains the rationale behind the plot, and finally, shares our production experiences with our readers.

Integrated remote sensing and visualization (IRSV) system for transportation infrastructure operations and management, phase one, volume 4 : use of knowledge integrated visual analytics system in supporting bridge management.

DOT National Transportation Integrated Search

2009-12-01

The goals of integration should be: Supporting domain oriented data analysis through the use of : knowledge augmented visual analytics system. In this project, we focus on: : Providing interactive data exploration for bridge managements. : ...

VRML and Collaborative Environments: New Tools for Networked Visualization

NASA Astrophysics Data System (ADS)

Crutcher, R. M.; Plante, R. L.; Rajlich, P.

We present two new applications that engage the network as a tool for astronomical research and/or education. The first is a VRML server which allows users over the Web to interactively create three-dimensional visualizations of FITS images contained in the NCSA Astronomy Digital Image Library (ADIL). The server's Web interface allows users to select images from the ADIL, fill in processing parameters, and create renderings featuring isosurfaces, slices, contours, and annotations; the often extensive computations are carried out on an NCSA SGI supercomputer server without the user having an individual account on the system. The user can then download the 3D visualizations as VRML files, which may be rotated and manipulated locally on virtually any class of computer. The second application is the ADILBrowser, a part of the NCSA Horizon Image Data Browser Java package. ADILBrowser allows a group of participants to browse images from the ADIL within a collaborative session. The collaborative environment is provided by the NCSA Habanero package which includes text and audio chat tools and a white board. The ADILBrowser is just an example of a collaborative tool that can be built with the Horizon and Habanero packages. The classes provided by these packages can be assembled to create custom collaborative applications that visualize data either from local disk or from anywhere on the network.

Accelerate Healthcare Data Analytics: An Agile Practice to Perform Collaborative and Reproducible Analyses.

PubMed

Hao, Bibo; Sun, Wen; Yu, Yiqin; Li, Jing; Hu, Gang; Xie, Guotong

2016-01-01

Recent advances in cloud computing and machine learning made it more convenient for researchers to gain insights from massive healthcare data, while performing analyses on healthcare data in current practice still lacks efficiency for researchers. What's more, collaborating among different researchers and sharing analysis results are challenging issues. In this paper, we developed a practice to make analytics process collaborative and analysis results reproducible by exploiting and extending Jupyter Notebook. After applying this practice in our use cases, we can perform analyses and deliver results with less efforts in shorter time comparing to our previous practice.

Error-analysis and comparison to analytical models of numerical waveforms produced by the NRAR Collaboration

NASA Astrophysics Data System (ADS)

Hinder, Ian; Buonanno, Alessandra; Boyle, Michael; Etienne, Zachariah B.; Healy, James; Johnson-McDaniel, Nathan K.; Nagar, Alessandro; Nakano, Hiroyuki; Pan, Yi; Pfeiffer, Harald P.; Pürrer, Michael; Reisswig, Christian; Scheel, Mark A.; Schnetter, Erik; Sperhake, Ulrich; Szilágyi, Bela; Tichy, Wolfgang; Wardell, Barry; Zenginoğlu, Anıl; Alic, Daniela; Bernuzzi, Sebastiano; Bode, Tanja; Brügmann, Bernd; Buchman, Luisa T.; Campanelli, Manuela; Chu, Tony; Damour, Thibault; Grigsby, Jason D.; Hannam, Mark; Haas, Roland; Hemberger, Daniel A.; Husa, Sascha; Kidder, Lawrence E.; Laguna, Pablo; London, Lionel; Lovelace, Geoffrey; Lousto, Carlos O.; Marronetti, Pedro; Matzner, Richard A.; Mösta, Philipp; Mroué, Abdul; Müller, Doreen; Mundim, Bruno C.; Nerozzi, Andrea; Paschalidis, Vasileios; Pollney, Denis; Reifenberger, George; Rezzolla, Luciano; Shapiro, Stuart L.; Shoemaker, Deirdre; Taracchini, Andrea; Taylor, Nicholas W.; Teukolsky, Saul A.; Thierfelder, Marcus; Witek, Helvi; Zlochower, Yosef

2013-01-01

The Numerical-Relativity-Analytical-Relativity (NRAR) collaboration is a joint effort between members of the numerical relativity, analytical relativity and gravitational-wave data analysis communities. The goal of the NRAR collaboration is to produce numerical-relativity simulations of compact binaries and use them to develop accurate analytical templates for the LIGO/Virgo Collaboration to use in detecting gravitational-wave signals and extracting astrophysical information from them. We describe the results of the first stage of the NRAR project, which focused on producing an initial set of numerical waveforms from binary black holes with moderate mass ratios and spins, as well as one non-spinning binary configuration which has a mass ratio of 10. All of the numerical waveforms are analysed in a uniform and consistent manner, with numerical errors evaluated using an analysis code created by members of the NRAR collaboration. We compare previously-calibrated, non-precessing analytical waveforms, notably the effective-one-body (EOB) and phenomenological template families, to the newly-produced numerical waveforms. We find that when the binary's total mass is ˜100-200M⊙, current EOB and phenomenological models of spinning, non-precessing binary waveforms have overlaps above 99% (for advanced LIGO) with all of the non-precessing-binary numerical waveforms with mass ratios ⩽4, when maximizing over binary parameters. This implies that the loss of event rate due to modelling error is below 3%. Moreover, the non-spinning EOB waveforms previously calibrated to five non-spinning waveforms with mass ratio smaller than 6 have overlaps above 99.7% with the numerical waveform with a mass ratio of 10, without even maximizing on the binary parameters.

Art-Science-Technology collaboration through immersive, interactive 3D visualization

NASA Astrophysics Data System (ADS)

Kellogg, L. H.

2014-12-01

At the W. M. Keck Center for Active Visualization in Earth Sciences (KeckCAVES), a group of geoscientists and computer scientists collaborate to develop and use of interactive, immersive, 3D visualization technology to view, manipulate, and interpret data for scientific research. The visual impact of immersion in a CAVE environment can be extremely compelling, and from the outset KeckCAVES scientists have collaborated with artists to bring this technology to creative works, including theater and dance performance, installations, and gamification. The first full-fledged collaboration designed and produced a performance called "Collapse: Suddenly falling down", choreographed by Della Davidson, which investigated the human and cultural response to natural and man-made disasters. Scientific data (lidar scans of disaster sites, such as landslides and mine collapses) were fully integrated into the performance by the Sideshow Physical Theatre. This presentation will discuss both the technological and creative characteristics of, and lessons learned from the collaboration. Many parallels between the artistic and scientific process emerged. We observed that both artists and scientists set out to investigate a topic, solve a problem, or answer a question. Refining that question or problem is an essential part of both the creative and scientific workflow. Both artists and scientists seek understanding (in this case understanding of natural disasters). Differences also emerged; the group noted that the scientists sought clarity (including but not limited to quantitative measurements) as a means to understanding, while the artists embraced ambiguity, also as a means to understanding. Subsequent art-science-technology collaborations have responded to evolving technology for visualization and include gamification as a means to explore data, and use of augmented reality for informal learning in museum settings.

Mapping longitudinal scientific progress, collaboration and impact of the Alzheimer's disease neuroimaging initiative.

PubMed

Yao, Xiaohui; Yan, Jingwen; Ginda, Michael; Börner, Katy; Saykin, Andrew J; Shen, Li

2017-01-01

Alzheimer's disease neuroimaging initiative (ADNI) is a landmark imaging and omics study in AD. ADNI research literature has increased substantially over the past decade, which poses challenges for effectively communicating information about the results and impact of ADNI-related studies. In this work, we employed advanced information visualization techniques to perform a comprehensive and systematic mapping of the ADNI scientific growth and impact over a period of 12 years. Citation information of ADNI-related publications from 01/01/2003 to 05/12/2015 were downloaded from the Scopus database. Five fields, including authors, years, affiliations, sources (journals), and keywords, were extracted and preprocessed. Statistical analyses were performed on basic publication data as well as journal and citations information. Science mapping workflows were conducted using the Science of Science (Sci2) Tool to generate geospatial, topical, and collaboration visualizations at the micro (individual) to macro (global) levels such as geospatial layouts of institutional collaboration networks, keyword co-occurrence networks, and author collaboration networks evolving over time. During the studied period, 996 ADNI manuscripts were published across 233 journals and conference proceedings. The number of publications grew linearly from 2008 to 2015, so did the number of involved institutions. ADNI publications received much more citations than typical papers from the same set of journals. Collaborations were visualized at multiple levels, including authors, institutions, and research areas. The evolution of key ADNI research topics was also plotted over the studied period. Both statistical and visualization results demonstrate the increasing attention of ADNI research, strong citation impact of ADNI publications, the expanding collaboration networks among researchers, institutions and ADNI core areas, and the dynamic evolution of ADNI research topics. The visualizations presented here can help improve daily decision making based on a deep understanding of existing patterns and trends using proven and replicable data analysis and visualization methods. They have great potential to provide new insights and actionable knowledge for helping translational research in AD.

Mapping longitudinal scientific progress, collaboration and impact of the Alzheimer’s disease neuroimaging initiative

PubMed Central

Yao, Xiaohui; Yan, Jingwen; Ginda, Michael; Börner, Katy; Saykin, Andrew J.

2017-01-01

Background Alzheimer’s disease neuroimaging initiative (ADNI) is a landmark imaging and omics study in AD. ADNI research literature has increased substantially over the past decade, which poses challenges for effectively communicating information about the results and impact of ADNI-related studies. In this work, we employed advanced information visualization techniques to perform a comprehensive and systematic mapping of the ADNI scientific growth and impact over a period of 12 years. Methods Citation information of ADNI-related publications from 01/01/2003 to 05/12/2015 were downloaded from the Scopus database. Five fields, including authors, years, affiliations, sources (journals), and keywords, were extracted and preprocessed. Statistical analyses were performed on basic publication data as well as journal and citations information. Science mapping workflows were conducted using the Science of Science (Sci2) Tool to generate geospatial, topical, and collaboration visualizations at the micro (individual) to macro (global) levels such as geospatial layouts of institutional collaboration networks, keyword co-occurrence networks, and author collaboration networks evolving over time. Results During the studied period, 996 ADNI manuscripts were published across 233 journals and conference proceedings. The number of publications grew linearly from 2008 to 2015, so did the number of involved institutions. ADNI publications received much more citations than typical papers from the same set of journals. Collaborations were visualized at multiple levels, including authors, institutions, and research areas. The evolution of key ADNI research topics was also plotted over the studied period. Conclusions Both statistical and visualization results demonstrate the increasing attention of ADNI research, strong citation impact of ADNI publications, the expanding collaboration networks among researchers, institutions and ADNI core areas, and the dynamic evolution of ADNI research topics. The visualizations presented here can help improve daily decision making based on a deep understanding of existing patterns and trends using proven and replicable data analysis and visualization methods. They have great potential to provide new insights and actionable knowledge for helping translational research in AD. PMID:29095836

Open-source web-enabled data management, analyses, and visualization of very large data in geosciences using Jupyter, Apache Spark, and community tools

NASA Astrophysics Data System (ADS)

Chaudhary, A.

2017-12-01

Current simulation models and sensors are producing high-resolution, high-velocity data in geosciences domain. Knowledge discovery from these complex and large size datasets require tools that are capable of handling very large data and providing interactive data analytics features to researchers. To this end, Kitware and its collaborators are producing open-source tools GeoNotebook, GeoJS, Gaia, and Minerva for geosciences that are using hardware accelerated graphics and advancements in parallel and distributed processing (Celery and Apache Spark) and can be loosely coupled to solve real-world use-cases. GeoNotebook (https://github.com/OpenGeoscience/geonotebook) is co-developed by Kitware and NASA-Ames and is an extension to the Jupyter Notebook. It provides interactive visualization and python-based analysis of geospatial data and depending the backend (KTile or GeoPySpark) can handle data sizes of Hundreds of Gigabytes to Terabytes. GeoNotebook uses GeoJS (https://github.com/OpenGeoscience/geojs) to render very large geospatial data on the map using WebGL and Canvas2D API. GeoJS is more than just a GIS library as users can create scientific plots such as vector and contour and can embed InfoVis plots using D3.js. GeoJS aims for high-performance visualization and interactive data exploration of scientific and geospatial location aware datasets and supports features such as Point, Line, Polygon, and advanced features such as Pixelmap, Contour, Heatmap, and Choropleth. Our another open-source tool Minerva ((https://github.com/kitware/minerva) is a geospatial application that is built on top of open-source web-based data management system Girder (https://github.com/girder/girder) which provides an ability to access data from HDFS or Amazon S3 buckets and provides capabilities to perform visualization and analyses on geosciences data in a web environment using GDAL and GeoPandas wrapped in a unified API provided by Gaia (https://github.com/OpenDataAnalytics/gaia). In this presentation, we will discuss core features of each of these tools and will present lessons learned on handling large data in the context of data management, analyses and visualization.

Human Factors in Streaming Data Analysis: Challenges and Opportunities for Information Visualization

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

Dasgupta, Aritra; Arendt, Dustin L.; Franklin, Lyndsey

State-of-the-art visual analytics models and frameworks mostly assume a static snapshot of the data, while in many cases it is a stream with constant updates and changes. Exploration of streaming data poses unique challenges as machine-level computations and abstractions need to be synchronized with the visual representation of the data and the temporally evolving human insights. In the visual analytics literature, we lack a thorough characterization of streaming data and analysis of the challenges associated with task abstraction, visualization design, and adaptation of the role of human-in-the-loop for exploration of data streams. We aim to fill this gap by conductingmore » a survey of the state-of-the-art in visual analytics of streaming data for systematically describing the contributions and shortcomings of current techniques and analyzing the research gaps that need to be addressed in the future. Our contributions are: i) problem characterization for identifying challenges that are unique to streaming data analysis tasks, ii) a survey and analysis of the state-of-the-art in streaming data visualization research with a focus on the visualization design space for dynamic data and the role of the human-in-the-loop, and iii) reflections on the design-trade-offs for streaming visual analytics techniques and their practical applicability in real-world application scenarios.« less

Promoting Creative Tension within Collaborative Writing Groups.

ERIC Educational Resources Information Center

Ewald, Helen Rothschild; MacCallum, Virginia

1990-01-01

Describes a collaborative writing assignment which features a series of interconnected business messages arising out of a case study and including inhouse memos and an analytical report. Shows how the design of a collaborative writing assignment can foster creative rather than debilitative tension. (RS)

The generation of criteria for selecting analytical tools for landscape management

Treesearch

Marilyn Duffey-Armstrong

1979-01-01

This paper presents an approach to generating criteria for selecting the analytical tools used to assess visual resources for various landscape management tasks. The approach begins by first establishing the overall parameters for the visual assessment task, and follows by defining the primary requirements of the various sets of analytical tools to be used. Finally,...

Chemistry in Second Life

PubMed Central

Lang, Andrew SID; Bradley, Jean-Claude

2009-01-01

This review will focus on the current level on chemistry research, education, and visualization possible within the multi-user virtual environment of Second Life. We discuss how Second Life has been used as a platform for the interactive and collaborative visualization of data from molecules and proteins to spectra and experimental data. We then review how these visualizations can be scripted for immersive educational activities and real-life collaborative research. We also discuss the benefits of the social networking affordances of Second Life for both chemists and chemistry students. PMID:19852781

Chemistry in second life.

PubMed

Lang, Andrew S I D; Bradley, Jean-Claude

2009-10-23

This review will focus on the current level on chemistry research, education, and visualization possible within the multi-user virtual environment of Second Life. We discuss how Second Life has been used as a platform for the interactive and collaborative visualization of data from molecules and proteins to spectra and experimental data. We then review how these visualizations can be scripted for immersive educational activities and real-life collaborative research. We also discuss the benefits of the social networking affordances of Second Life for both chemists and chemistry students.

The Role of Teamwork in the Analysis of Big Data: A Study of Visual Analytics and Box Office Prediction.

PubMed

Buchanan, Verica; Lu, Yafeng; McNeese, Nathan; Steptoe, Michael; Maciejewski, Ross; Cooke, Nancy

2017-03-01

Historically, domains such as business intelligence would require a single analyst to engage with data, develop a model, answer operational questions, and predict future behaviors. However, as the problems and domains become more complex, organizations are employing teams of analysts to explore and model data to generate knowledge. Furthermore, given the rapid increase in data collection, organizations are struggling to develop practices for intelligence analysis in the era of big data. Currently, a variety of machine learning and data mining techniques are available to model data and to generate insights and predictions, and developments in the field of visual analytics have focused on how to effectively link data mining algorithms with interactive visuals to enable analysts to explore, understand, and interact with data and data models. Although studies have explored the role of single analysts in the visual analytics pipeline, little work has explored the role of teamwork and visual analytics in the analysis of big data. In this article, we present an experiment integrating statistical models, visual analytics techniques, and user experiments to study the role of teamwork in predictive analytics. We frame our experiment around the analysis of social media data for box office prediction problems and compare the prediction performance of teams, groups, and individuals. Our results indicate that a team's performance is mediated by the team's characteristics such as openness of individual members to others' positions and the type of planning that goes into the team's analysis. These findings have important implications for how organizations should create teams in order to make effective use of information from their analytic models.

Using Interactive Data Visualizations for Exploratory Analysis in Undergraduate Genomics Coursework: Field Study Findings and Guidelines

ERIC Educational Resources Information Center

Mirel, Barbara; Kumar, Anuj; Nong, Paige; Su, Gang; Meng, Fan

2016-01-01

Life scientists increasingly use visual analytics to explore large data sets and generate hypotheses. Undergraduate biology majors should be learning these same methods. Yet visual analytics is one of the most underdeveloped areas of undergraduate biology education. This study sought to determine the feasibility of undergraduate biology majors…

Panoptes: web-based exploration of large scale genome variation data.

PubMed

Vauterin, Paul; Jeffery, Ben; Miles, Alistair; Amato, Roberto; Hart, Lee; Wright, Ian; Kwiatkowski, Dominic

2017-10-15

The size and complexity of modern large-scale genome variation studies demand novel approaches for exploring and sharing the data. In order to unlock the potential of these data for a broad audience of scientists with various areas of expertise, a unified exploration framework is required that is accessible, coherent and user-friendly. Panoptes is an open-source software framework for collaborative visual exploration of large-scale genome variation data and associated metadata in a web browser. It relies on technology choices that allow it to operate in near real-time on very large datasets. It can be used to browse rich, hybrid content in a coherent way, and offers interactive visual analytics approaches to assist the exploration. We illustrate its application using genome variation data of Anopheles gambiae, Plasmodium falciparum and Plasmodium vivax. Freely available at https://github.com/cggh/panoptes, under the GNU Affero General Public License. paul.vauterin@gmail.com. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Using a Semantic Diagram to Structure a Collaborative Problem Solving Process in the Classroom

ERIC Educational Resources Information Center

Cai, Huiying; Lin, Lin; Gu, Xiaoqing

2016-01-01

This study provides an in-depth look into the implementation process of visualization-based tools for structuring collaborative problem solving (CPS) in the classroom. A visualization-based learning platform--the semantic diagram for structuring CPS in a real classroom was designed and implemented. Metafora, the preliminary vehicle of the semantic…

Literature and Product Review of Visual Analytics for Maritime Awareness

DTIC Science & Technology

2009-10-28

the user’s knowledge and experience. • Riveiro et al [107] provide a useful discussion of the cognitive process of anomaly detection based on...changes over time can be seen visually. • Wilkinson et al [140] suggests that we need visual analytics for three principal purposes: checking raw data...Predictions within the Current Plot • Yue et al [146] describe an AI blackboard-based agent that leverages interactive visualization and mixed

Big data in medical informatics: improving education through visual analytics.

PubMed

Vaitsis, Christos; Nilsson, Gunnar; Zary, Nabil

2014-01-01

A continuous effort to improve healthcare education today is currently driven from the need to create competent health professionals able to meet healthcare demands. Limited research reporting how educational data manipulation can help in healthcare education improvement. The emerging research field of visual analytics has the advantage to combine big data analysis and manipulation techniques, information and knowledge representation, and human cognitive strength to perceive and recognise visual patterns. The aim of this study was therefore to explore novel ways of representing curriculum and educational data using visual analytics. Three approaches of visualization and representation of educational data were presented. Five competencies at undergraduate medical program level addressed in courses were identified to inaccurately correspond to higher education board competencies. Different visual representations seem to have a potential in impacting on the ability to perceive entities and connections in the curriculum data.

The How and Why of Academic Collaboration: Disciplinary Differences and Policy Implications

ERIC Educational Resources Information Center

Lewis, Jenny M.; Ross, Sandy; Holden, Thomas

2012-01-01

This paper examines how and why academics in different parts of the academy collaborate. In this paper we argue that: (1) There is a useful analytical distinction to be made between collaboration (fluid and expressive) and Collaboration (concrete and instrumental); (2) These two are not mutually exclusive and their use varies between disciplines;…

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.

Industrial Internet of Things-Based Collaborative Sensing Intelligence: Framework and Research Challenges.

PubMed

Chen, Yuanfang; Lee, Gyu Myoung; Shu, Lei; Crespi, Noel

2016-02-06

The development of an efficient and cost-effective solution to solve a complex problem (e.g., dynamic detection of toxic gases) is an important research issue in the industrial applications of the Internet of Things (IoT). An industrial intelligent ecosystem enables the collection of massive data from the various devices (e.g., sensor-embedded wireless devices) dynamically collaborating with humans. Effectively collaborative analytics based on the collected massive data from humans and devices is quite essential to improve the efficiency of industrial production/service. In this study, we propose a collaborative sensing intelligence (CSI) framework, combining collaborative intelligence and industrial sensing intelligence. The proposed CSI facilitates the cooperativity of analytics with integrating massive spatio-temporal data from different sources and time points. To deploy the CSI for achieving intelligent and efficient industrial production/service, the key challenges and open issues are discussed, as well.

Industrial Internet of Things-Based Collaborative Sensing Intelligence: Framework and Research Challenges

PubMed Central

Chen, Yuanfang; Lee, Gyu Myoung; Shu, Lei; Crespi, Noel

2016-01-01

The development of an efficient and cost-effective solution to solve a complex problem (e.g., dynamic detection of toxic gases) is an important research issue in the industrial applications of the Internet of Things (IoT). An industrial intelligent ecosystem enables the collection of massive data from the various devices (e.g., sensor-embedded wireless devices) dynamically collaborating with humans. Effectively collaborative analytics based on the collected massive data from humans and devices is quite essential to improve the efficiency of industrial production/service. In this study, we propose a collaborative sensing intelligence (CSI) framework, combining collaborative intelligence and industrial sensing intelligence. The proposed CSI facilitates the cooperativity of analytics with integrating massive spatio-temporal data from different sources and time points. To deploy the CSI for achieving intelligent and efficient industrial production/service, the key challenges and open issues are discussed, as well. PMID:26861345

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.

Physiological and Anatomical Visual Analytics (PAVA) Background

EPA Pesticide Factsheets

The need to efficiently analyze human chemical disposition data from in vivo studies or in silico PBPK modeling efforts, and to see complex disposition data in a logical manner, has created a unique opportunity for visual analytics applid to PAD.

Mobile collaborative medical display system.

PubMed

Park, Sanghun; Kim, Wontae; Ihm, Insung

2008-03-01

Because of recent advances in wireless communication technologies, the world of mobile computing is flourishing with a variety of applications. In this study, we present an integrated architecture for a personal digital assistant (PDA)-based mobile medical display system that supports collaborative work between remote users. We aim to develop a system that enables users in different regions to share a working environment for collaborative visualization with the potential for exploring huge medical datasets. Our system consists of three major components: mobile client, gateway, and parallel rendering server. The mobile client serves as a front end and enables users to choose the visualization and control parameters interactively and cooperatively. The gateway handles requests and responses between mobile clients and the rendering server for efficient communication. Through the gateway, it is possible to share working environments between users, allowing them to work together in computer supported cooperative work (CSCW) mode. Finally, the parallel rendering server is responsible for performing heavy visualization tasks. Our experience indicates that some features currently available to our mobile clients for collaborative scientific visualization are limited due to the poor performance of mobile devices and the low bandwidth of wireless connections. However, as mobile devices and wireless network systems are experiencing considerable elevation in their capabilities, we believe that our methodology will be utilized effectively in building quite responsive, useful mobile collaborative medical systems in the very near future.

Classroom Guitar and Students with Visual Impairments: A Positive Approach to Music Learning and Artistry

ERIC Educational Resources Information Center

Coleman, Jeremy M.

2016-01-01

In 2011, a collaborative effort began between the Texas School for the Blind and Visually Impaired (TSBVI) and Austin Classical Guitar (ACG), a local 501(c) nonprofit music organization. The idea behind this collaboration was to start a small guitar program that would provide TSBVI students with quality classroom guitar instruction. At that time,…

Developing Teachers' Work for Improving Teaching and Learning of Children with Visual Impairment Accommodated in Ordinary Primary Schools

ERIC Educational Resources Information Center

Mnyanyi, Cosmas B. F.

2009-01-01

The study investigated how to facilitate teachers in developing their work in improving the teaching and learning of children with visual impairment (CVI) accommodated in ordinary classrooms. The study takes the form of collaborative action research where the researcher works in collaboration with the teachers. The project is being conducted in…

Bridging the Gap between Physical Therapy and Orientation and Mobility in Schools: Using a Collaborative Team Approach for Students with Visual Impairments

ERIC Educational Resources Information Center

Szabo, Joanne; Panikkar, Rajiv K.

2017-01-01

This article explores transdisciplinary collaboration and role-release strategies that would allow physical therapists and orientation and mobility (O&M) specialists to more effectively support students with visual impairments (that is, those who are blind or have low vision) and additional disabilities with their expanded core curriculum…

WebViz:A Web-based Collaborative Interactive Visualization System for large-Scale Data Sets

NASA Astrophysics Data System (ADS)

Yuen, D. A.; McArthur, E.; Weiss, R. M.; Zhou, J.; Yao, B.

2010-12-01

WebViz is a web-based application designed to conduct collaborative, interactive visualizations of large data sets for multiple users, allowing researchers situated all over the world to utilize the visualization services offered by the University of Minnesota’s Laboratory for Computational Sciences and Engineering (LCSE). This ongoing project has been built upon over the last 3 1/2 years .The motivation behind WebViz lies primarily with the need to parse through an increasing amount of data produced by the scientific community as a result of larger and faster multicore and massively parallel computers coming to the market, including the use of general purpose GPU computing. WebViz allows these large data sets to be visualized online by anyone with an account. The application allows users to save time and resources by visualizing data ‘on the fly’, wherever he or she may be located. By leveraging AJAX via the Google Web Toolkit (http://code.google.com/webtoolkit/), we are able to provide users with a remote, web portal to LCSE's (http://www.lcse.umn.edu) large-scale interactive visualization system already in place at the University of Minnesota. LCSE’s custom hierarchical volume rendering software provides high resolution visualizations on the order of 15 million pixels and has been employed for visualizing data primarily from simulations in astrophysics to geophysical fluid dynamics . In the current version of WebViz, we have implemented a highly extensible back-end framework built around HTTP "server push" technology. The web application is accessible via a variety of devices including netbooks, iPhones, and other web and javascript-enabled cell phones. Features in the current version include the ability for users to (1) securely login (2) launch multiple visualizations (3) conduct collaborative visualization sessions (4) delegate control aspects of a visualization to others and (5) engage in collaborative chats with other users within the user interface of the web application. These features are all in addition to a full range of essential visualization functions including 3-D camera and object orientation, position manipulation, time-stepping control, and custom color/alpha mapping.

Supporting Patient-Provider Collaboration to Identify Individual Triggers using Food and Symptom Journals

PubMed Central

Schroeder, Jessica; Hoffswell, Jane; Chung, Chia-Fang; Fogarty, James; Munson, Sean; Zia, Jasmine

2017-01-01

Patient-generated data can allow patients and providers to collaboratively develop accurate diagnoses and actionable treatment plans. Unfortunately, patients and providers often lack effective support to make use of such data. We examine patient-provider collaboration to interpret patient-generated data. We focus on irritable bowel syndrome (IBS), a chronic illness in which particular foods can exacerbate symptoms. IBS management often requires patient-provider collaboration using a patient’s food and symptom journal to identify the patient’s triggers. We contribute interactive visualizations to support exploration of such journals, as well as an examination of patient-provider collaboration in interpreting the journals. Drawing upon individual and collaborative interviews with patients and providers, we find that collaborative review helps improve data comprehension and build mutual trust. We also find a desire to use tools like our interactive visualizations within and beyond clinic appointments. We discuss these findings and present guidance for the design of future tools. PMID:28516172

IBM Watson Analytics: Automating Visualization, Descriptive, and Predictive Statistics

PubMed Central

2016-01-01

Background We live in an era of explosive data generation that will continue to grow and involve all industries. One of the results of this explosion is the need for newer and more efficient data analytics procedures. Traditionally, data analytics required a substantial background in statistics and computer science. In 2015, International Business Machines Corporation (IBM) released the IBM Watson Analytics (IBMWA) software that delivered advanced statistical procedures based on the Statistical Package for the Social Sciences (SPSS). The latest entry of Watson Analytics into the field of analytical software products provides users with enhanced functions that are not available in many existing programs. For example, Watson Analytics automatically analyzes datasets, examines data quality, and determines the optimal statistical approach. Users can request exploratory, predictive, and visual analytics. Using natural language processing (NLP), users are able to submit additional questions for analyses in a quick response format. This analytical package is available free to academic institutions (faculty and students) that plan to use the tools for noncommercial purposes. Objective To report the features of IBMWA and discuss how this software subjectively and objectively compares to other data mining programs. Methods The salient features of the IBMWA program were examined and compared with other common analytical platforms, using validated health datasets. Results Using a validated dataset, IBMWA delivered similar predictions compared with several commercial and open source data mining software applications. The visual analytics generated by IBMWA were similar to results from programs such as Microsoft Excel and Tableau Software. In addition, assistance with data preprocessing and data exploration was an inherent component of the IBMWA application. Sensitivity and specificity were not included in the IBMWA predictive analytics results, nor were odds ratios, confidence intervals, or a confusion matrix. Conclusions IBMWA is a new alternative for data analytics software that automates descriptive, predictive, and visual analytics. This program is very user-friendly but requires data preprocessing, statistical conceptual understanding, and domain expertise. PMID:27729304

IBM Watson Analytics: Automating Visualization, Descriptive, and Predictive Statistics.

PubMed

Hoyt, Robert Eugene; Snider, Dallas; Thompson, Carla; Mantravadi, Sarita

2016-10-11

We live in an era of explosive data generation that will continue to grow and involve all industries. One of the results of this explosion is the need for newer and more efficient data analytics procedures. Traditionally, data analytics required a substantial background in statistics and computer science. In 2015, International Business Machines Corporation (IBM) released the IBM Watson Analytics (IBMWA) software that delivered advanced statistical procedures based on the Statistical Package for the Social Sciences (SPSS). The latest entry of Watson Analytics into the field of analytical software products provides users with enhanced functions that are not available in many existing programs. For example, Watson Analytics automatically analyzes datasets, examines data quality, and determines the optimal statistical approach. Users can request exploratory, predictive, and visual analytics. Using natural language processing (NLP), users are able to submit additional questions for analyses in a quick response format. This analytical package is available free to academic institutions (faculty and students) that plan to use the tools for noncommercial purposes. To report the features of IBMWA and discuss how this software subjectively and objectively compares to other data mining programs. The salient features of the IBMWA program were examined and compared with other common analytical platforms, using validated health datasets. Using a validated dataset, IBMWA delivered similar predictions compared with several commercial and open source data mining software applications. The visual analytics generated by IBMWA were similar to results from programs such as Microsoft Excel and Tableau Software. In addition, assistance with data preprocessing and data exploration was an inherent component of the IBMWA application. Sensitivity and specificity were not included in the IBMWA predictive analytics results, nor were odds ratios, confidence intervals, or a confusion matrix. IBMWA is a new alternative for data analytics software that automates descriptive, predictive, and visual analytics. This program is very user-friendly but requires data preprocessing, statistical conceptual understanding, and domain expertise.

Just-in-time Time Data Analytics and Visualization of Climate Simulations using the Bellerophon Framework

NASA Astrophysics Data System (ADS)

Anantharaj, V. G.; Venzke, J.; Lingerfelt, E.; Messer, B.

2015-12-01

Climate model simulations are used to understand the evolution and variability of earth's climate. Unfortunately, high-resolution multi-decadal climate simulations can take days to weeks to complete. Typically, the simulation results are not analyzed until the model runs have ended. During the course of the simulation, the output may be processed periodically to ensure that the model is preforming as expected. However, most of the data analytics and visualization are not performed until the simulation is finished. The lengthy time period needed for the completion of the simulation constrains the productivity of climate scientists. Our implementation of near real-time data visualization analytics capabilities allows scientists to monitor the progress of their simulations while the model is running. Our analytics software executes concurrently in a co-scheduling mode, monitoring data production. When new data are generated by the simulation, a co-scheduled data analytics job is submitted to render visualization artifacts of the latest results. These visualization output are automatically transferred to Bellerophon's data server located at ORNL's Compute and Data Environment for Science (CADES) where they are processed and archived into Bellerophon's database. During the course of the experiment, climate scientists can then use Bellerophon's graphical user interface to view animated plots and their associated metadata. The quick turnaround from the start of the simulation until the data are analyzed permits research decisions and projections to be made days or sometimes even weeks sooner than otherwise possible! The supercomputer resources used to run the simulation are unaffected by co-scheduling the data visualization jobs, so the model runs continuously while the data are visualized. Our just-in-time data visualization software looks to increase climate scientists' productivity as climate modeling moves into exascale era of computing.

Teacher Collaboration, Mentorship, and Intergenerational Gap in Post-Soviet Ukrainian Schools

ERIC Educational Resources Information Center

Kutsyuruba, Benjamin

2011-01-01

This article examines the interconnections between mentoring and teacher collaboration in view of the intergenerational gap between experienced and novice educators in the post-Soviet Ukraine. The conceptual framework utilized a constructive postmodern perspective as an analytical lens and examined mentorship as a collaborative form of teacher…

A Day in the Professional Life of a Collaborative Biostatistician Deconstructed: Implications for Curriculum Design

ERIC Educational Resources Information Center

Samsa, Gregory P.

2018-01-01

Collaborative biostatistics is the creative application of statistical tools to biomedical problems. The relatively modest literature about the traits of effective collaborative biostatisticians focuses on four core competencies: (a) technical and analytical; (b) substance-matter knowledge; (c) communication; and (d) problem solving and problem…

Assisting Instructional Assessment of Undergraduate Collaborative Wiki and SVN Activities

ERIC Educational Resources Information Center

Kim, Jihie; Shaw, Erin; Xu, Hao; Adarsh, G. V.

2012-01-01

In this paper we examine the collaborative performance of undergraduate engineering students who used shared project documents (Wikis, Google documents) and a software version control system (SVN) to support project collaboration. We present an initial implementation of TeamAnalytics, an instructional tool that facilitates the analyses of the…

SeeDB: Efficient Data-Driven Visualization Recommendations to Support Visual Analytics

PubMed Central

Vartak, Manasi; Rahman, Sajjadur; Madden, Samuel; Parameswaran, Aditya; Polyzotis, Neoklis

2015-01-01

Data analysts often build visualizations as the first step in their analytical workflow. However, when working with high-dimensional datasets, identifying visualizations that show relevant or desired trends in data can be laborious. We propose SeeDB, a visualization recommendation engine to facilitate fast visual analysis: given a subset of data to be studied, SeeDB intelligently explores the space of visualizations, evaluates promising visualizations for trends, and recommends those it deems most “useful” or “interesting”. The two major obstacles in recommending interesting visualizations are (a) scale: evaluating a large number of candidate visualizations while responding within interactive time scales, and (b) utility: identifying an appropriate metric for assessing interestingness of visualizations. For the former, SeeDB introduces pruning optimizations to quickly identify high-utility visualizations and sharing optimizations to maximize sharing of computation across visualizations. For the latter, as a first step, we adopt a deviation-based metric for visualization utility, while indicating how we may be able to generalize it to other factors influencing utility. We implement SeeDB as a middleware layer that can run on top of any DBMS. Our experiments show that our framework can identify interesting visualizations with high accuracy. Our optimizations lead to multiple orders of magnitude speedup on relational row and column stores and provide recommendations at interactive time scales. Finally, we demonstrate via a user study the effectiveness of our deviation-based utility metric and the value of recommendations in supporting visual analytics. PMID:26779379

SeeDB: Efficient Data-Driven Visualization Recommendations to Support Visual Analytics.

PubMed

Vartak, Manasi; Rahman, Sajjadur; Madden, Samuel; Parameswaran, Aditya; Polyzotis, Neoklis

2015-09-01

Data analysts often build visualizations as the first step in their analytical workflow. However, when working with high-dimensional datasets, identifying visualizations that show relevant or desired trends in data can be laborious. We propose SeeDB, a visualization recommendation engine to facilitate fast visual analysis: given a subset of data to be studied, SeeDB intelligently explores the space of visualizations, evaluates promising visualizations for trends, and recommends those it deems most "useful" or "interesting". The two major obstacles in recommending interesting visualizations are (a) scale : evaluating a large number of candidate visualizations while responding within interactive time scales, and (b) utility : identifying an appropriate metric for assessing interestingness of visualizations. For the former, SeeDB introduces pruning optimizations to quickly identify high-utility visualizations and sharing optimizations to maximize sharing of computation across visualizations. For the latter, as a first step, we adopt a deviation-based metric for visualization utility, while indicating how we may be able to generalize it to other factors influencing utility. We implement SeeDB as a middleware layer that can run on top of any DBMS. Our experiments show that our framework can identify interesting visualizations with high accuracy. Our optimizations lead to multiple orders of magnitude speedup on relational row and column stores and provide recommendations at interactive time scales. Finally, we demonstrate via a user study the effectiveness of our deviation-based utility metric and the value of recommendations in supporting visual analytics.

Does the Medium Matter in Collaboration? Using Visually Supported Collaboration Technology in an Interior Design Studio

ERIC Educational Resources Information Center

Cho, Ji Young; Cho, Moon-Heum; Kozinets, Nadya

2016-01-01

With the recognition of the importance of collaboration in a design studio and the advancement of technology, increasing numbers of design students collaborate with others in a technology-mediated learning environment (TMLE); however, not all students have positive experiences in TMLEs. One possible reason for unsatisfactory collaboration…

Effects of Using Dynamic Mathematics Software on Preservice Mathematics Teachers' Spatial Visualization Skills: The Case of Spatial Analytic Geometry

ERIC Educational Resources Information Center

Kösa, Temel

2016-01-01

The purpose of this study was to investigate the effects of using dynamic geometry software on preservice mathematics teachers' spatial visualization skills and to determine whether spatial visualization skills can be a predictor of success in learning analytic geometry of space. The study used a quasi-experimental design with a control group.…

Visual Information for the Desktop, version 1.0

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

2006-03-29

VZIN integrates visual analytics capabilities into popular desktop tools to aid a user in searching and understanding an information space. VZIN allows users to Drag-Drop-Visualize-Explore-Organize information within tools such as Microsoft Office, Windows Explorer, Excel, and Outlook. VZIN is tailorable to specific client or industry requirements. VZIN follows the desktop metaphors so that advanced analytical capabilities are available with minimal user training.

Web-based Collaboration and Visualization in the ANDRILL Program

NASA Astrophysics Data System (ADS)

Reed, J.; Rack, F. R.; Huffman, L. T.; Cattadori, M.

2009-12-01

ANDRILL has embraced the web as a platform for facilitating collaboration and communicating science with educators, students and researchers alike. Two recent ANDRILL education and outreach projects, Project Circle 2008 and the Climate Change Student Summit, brought together classrooms from around the world to participate in cutting edge science. A large component of each project was the online collaboration achieved through project websites, blogs, and the GroupHub--a secure online environment where students could meet to send messages, exchange presentations and pictures, and even chat live. These technologies enabled students from different countries and time zones to connect and participate in a shared 'conversation' about climate change research. ANDRILL has also developed several interactive, web-based visualizations to make scientific drilling data more engaging and accessible to the science community and the public. Each visualization is designed around three core concepts that enable the Web 2.0 platform, namely, that they are: (1) customizable - a user can customize the visualization to display the exact data she is interested in; (2) linkable - each view in the visualization has a distinct URL that the user can share with her friends via sites like Facebook and Twitter; and (3) mashable - the user can take the visualization, mash it up with data from other sites or her own research, and embed it in her blog or website. The web offers an ideal environment for visualization and collaboration because it requires no special software and works across all computer platforms, which allows organizations and research projects to engage much larger audiences. In this presentation we will describe past challenges and successes, as well as future plans.

An Examination of the Effects of Collaborative Scientific Visualization via Model-Based Reasoning on Science, Technology, Engineering, and Mathematics (STEM) Learning within an Immersive 3D World

ERIC Educational Resources Information Center

Soleimani, Ali

2013-01-01

Immersive 3D worlds can be designed to effectively engage students in peer-to-peer collaborative learning activities, supported by scientific visualization, to help with understanding complex concepts associated with learning science, technology, engineering, and mathematics (STEM). Previous research studies have shown STEM learning benefits…

Empirical Analysis of the Subjective Impressions and Objective Measures of Domain Scientists’ Visual Analytic Judgments

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

Dasgupta, Aritra; Burrows, Susannah M.; Han, Kyungsik

2017-05-08

Scientists often use specific data analysis and presentation methods familiar within their domain. But does high familiarity drive better analytical judgment? This question is especially relevant when familiar methods themselves can have shortcomings: many visualizations used conventionally for scientific data analysis and presentation do not follow established best practices. This necessitates new methods that might be unfamiliar yet prove to be more effective. But there is little empirical understanding of the relationships between scientists’ subjective impressions about familiar and unfamiliar visualizations and objective measures of their visual analytic judgments. To address this gap and to study these factors, we focusmore » on visualizations used for comparison of climate model performance. We report on a comprehensive survey-based user study with 47 climate scientists and present an analysis of : i) relationships among scientists’ familiarity, their perceived lev- els of comfort, confidence, accuracy, and objective measures of accuracy, and ii) relationships among domain experience, visualization familiarity, and post-study preference.« less

Distributed Generation Interconnection Collaborative | NREL

Science.gov Websites

, reduce paperwork, and improve customer service. Analytical Methods for Interconnection Many utilities and jurisdictions are seeking the right screening and analytical methods and tools to meet their reliability

Evaluating How the Computer-Supported Collaborative Learning Community Fosters Critical Reflective Practices

ERIC Educational Resources Information Center

Ma, Ada W.W.

2013-01-01

In recent research, little attention has been paid to issues of methodology and analysis methods to evaluate the quality of the collaborative learning community. To address such issues, an attempt is made to adopt the Activity System Model as an analytical framework to examine the relationship between computer supported collaborative learning…

AMOEBA: Designing for Collaboration in Computer Science Classrooms through Live Learning Analytics

ERIC Educational Resources Information Center

Berland, Matthew; Davis, Don; Smith, Carmen Petrick

2015-01-01

AMOEBA is a unique tool to support teachers' orchestration of collaboration among novice programmers in a non-traditional programming environment. The AMOEBA tool was designed and utilized to facilitate collaboration in a classroom setting in real time among novice middle school and high school programmers utilizing the IPRO programming…

Measuring Knowledge Elaboration Based on a Computer-Assisted Knowledge Map Analytical Approach to Collaborative Learning

ERIC Educational Resources Information Center

Zheng, Lanqin; Huang, Ronghuai; Hwang, Gwo-Jen; Yang, Kaicheng

2015-01-01

The purpose of this study is to quantitatively measure the level of knowledge elaboration and explore the relationships between prior knowledge of a group, group performance, and knowledge elaboration in collaborative learning. Two experiments were conducted to investigate the level of knowledge elaboration. The collaborative learning objective in…

Cyberhubs: Virtual Research Environments for Astronomy

NASA Astrophysics Data System (ADS)

Herwig, Falk; Andrassy, Robert; Annau, Nic; Clarkson, Ondrea; Côté, Benoit; D’Sa, Aaron; Jones, Sam; Moa, Belaid; O’Connell, Jericho; Porter, David; Ritter, Christian; Woodward, Paul

2018-05-01

Collaborations in astronomy and astrophysics are faced with numerous cyber-infrastructure challenges, such as large data sets, the need to combine heterogeneous data sets, and the challenge to effectively collaborate on those large, heterogeneous data sets with significant processing requirements and complex science software tools. The cyberhubs system is an easy-to-deploy package for small- to medium-sized collaborations based on the Jupyter and Docker technology, which allows web-browser-enabled, remote, interactive analytic access to shared data. It offers an initial step to address these challenges. The features and deployment steps of the system are described, as well as the requirements collection through an account of the different approaches to data structuring, handling, and available analytic tools for the NuGrid and PPMstar collaborations. NuGrid is an international collaboration that creates stellar evolution and explosion physics and nucleosynthesis simulation data. The PPMstar collaboration performs large-scale 3D stellar hydrodynamics simulations of interior convection in the late phases of stellar evolution. Examples of science that is currently performed on cyberhubs, in the areas of 3D stellar hydrodynamic simulations, stellar evolution and nucleosynthesis, and Galactic chemical evolution, are presented.

Enabling Reanalysis Intercomparison with the CREATE-IP and CREATE-V Projects

NASA Astrophysics Data System (ADS)

Carriere, L.; Potter, G. L.; Hertz, J.; Shen, Y.; Britzolakis, G.; Peters, J.; Maxwell, T. P.; Li, J.; Strong, S.; Schnase, J. L.

2016-12-01

NASA Goddard Space Flight Center's Office of Computational and Information Sciences and Technology, the NASA Center for Climate Simulation (NCCS), and the Earth System Grid Federation (ESGF) are working together to build a uniform environment for the comparative study and use of a group of reanalysis datasets of particular importance to the research community. This effort is called the Collaborative REAnalysis Technical Environment (CREATE) and it contains two components: the CREATE-Intercomparison Project (CREATE-IP) and CREATE-V. For CREATE-IP, our target reanalyses include ECMWF ERA-Interim, NASA/GMAO MERRA and MERRA2, NOAA/NCEP CFSR, NOAA/ESRL 20CR and 20CRv2, JMA JRA25, and JRA55. Each dataset is reformatted similarly to the models in the CMIP5 archive. By repackaging the reanalysis data into a common structure and format, it simplifies access, subsetting, and reanalysis comparison. Both monthly average data and a selection of high frequency data (6-hr) relevant to investigations such as the 2016 El Niño are provided. Much of the processing workflow has been automated and new data appear on a regular basis. In collaboration with the CLIVAR Global Synthesis and Observations Panel (GSOP), we are also processing and publishing eight ocean reanalyses, from 1980 to the present. Here, the data are regridded to a common 1° x 1° grid, vertically interpolated to the World Ocean Atlas 09 (WOA09) depths, and an ensemble is generated. CREATE-V is a web based visualization tool that allows the user to simultaneously view four reanalyses to facilitate comparison. The addition of a backend analytics engine, based on UV-CDAT and Scala provides the ability to generate a time series and anomaly for any given location on a map. The system enables scientists to identify data of interest and visualize, subset, and compare data without the need for download large volumes of data for local visualization.

Visualization and Analytics Software Tools for Peregrine System |

Science.gov Websites

R is a language and environment for statistical computing and graphics. Go to the R web site for System Visualization and Analytics Software Tools for Peregrine System Learn about the available visualization for OpenGL-based applications. For more information, please go to the FastX page. ParaView An open

Coordinating Cognition: The Costs and Benefits of Shared Gaze during Collaborative Search

ERIC Educational Resources Information Center

Brennan, Susan E.; Chen, Xin; Dickinson, Christopher A.; Neider, Mark B.; Zelinsky, Gregory J.

2008-01-01

Collaboration has its benefits, but coordination has its costs. We explored the potential for remotely located pairs of people to collaborate during visual search, using shared gaze and speech. Pairs of searchers wearing eyetrackers jointly performed an O-in-Qs search task alone, or in one of three collaboration conditions: shared gaze (with one…

Visual Analytics for MOOC Data.

PubMed

Qu, Huamin; Chen, Qing

2015-01-01

With the rise of massive open online courses (MOOCs), tens of millions of learners can now enroll in more than 1,000 courses via MOOC platforms such as Coursera and edX. As a result, a huge amount of data has been collected. Compared with traditional education records, the data from MOOCs has much finer granularity and also contains new pieces of information. It is the first time in history that such comprehensive data related to learning behavior has become available for analysis. What roles can visual analytics play in this MOOC movement? The authors survey the current practice and argue that MOOCs provide an opportunity for visualization researchers and that visual analytics systems for MOOCs can benefit a range of end users such as course instructors, education researchers, students, university administrators, and MOOC providers.

CREATE-IP and CREATE-V: Data and Services Update

NASA Astrophysics Data System (ADS)

Carriere, L.; Potter, G. L.; Hertz, J.; Peters, J.; Maxwell, T. P.; Strong, S.; Shute, J.; Shen, Y.; Duffy, D.

2017-12-01

The NASA Center for Climate Simulation (NCCS) at the Goddard Space Flight Center and the Earth System Grid Federation (ESGF) are working together to build a uniform environment for the comparative study and use of a group of reanalysis datasets of particular importance to the research community. This effort is called the Collaborative REAnalysis Technical Environment (CREATE) and it contains two components: the CREATE-Intercomparison Project (CREATE-IP) and CREATE-V. This year's efforts included generating and publishing an atmospheric reanalysis ensemble mean and spread and improving the analytics available through CREATE-V. Related activities included adding access to subsets of the reanalysis data through ArcGIS and expanding the visualization tool to GMAO forecast data. This poster will present the access mechanisms to this data and use cases including example Jupyter Notebook code. The reanalysis ensemble was generated using two methods, first using standard Python tools for regridding, extracting levels and creating the ensemble mean and spread on a virtual server in the NCCS environment. The second was using a new analytics software suite, the Earth Data Analytics Services (EDAS), coupled with a high-performance Data Analytics and Storage System (DASS) developed at the NCCS. Results were compared to validate the EDAS methodologies, and the results, including time to process, will be presented. The ensemble includes selected 6 hourly and monthly variables, regridded to 1.25 degrees, with 24 common levels used for the 3D variables. Use cases for the new data and services will be presented, including the use of EDAS for the backend analytics on CREATE-V, the use of the GMAO forecast aerosol and cloud data in CREATE-V, and the ability to connect CREATE-V data to NCCS ArcGIS services.

Toward Collaboration Sensing

ERIC Educational Resources Information Center

Schneider, Bertrand; Pea, Roy

2014-01-01

We describe preliminary applications of network analysis techniques to eye-tracking data collected during a collaborative learning activity. This paper makes three contributions: first, we visualize collaborative eye-tracking data as networks, where the nodes of the graph represent fixations and edges represent saccades. We found that those…

Toward visual user interfaces supporting collaborative multimedia content management

NASA Astrophysics Data System (ADS)

Husein, Fathi; Leissler, Martin; Hemmje, Matthias

2000-12-01

Supporting collaborative multimedia content management activities, as e.g., image and video acquisition, exploration, and access dialogues between naive users and multi media information systems is a non-trivial task. Although a wide variety of experimental and prototypical multimedia storage technologies as well as corresponding indexing and retrieval engines are available, most of them lack appropriate support for collaborative end-user oriented user interface front ends. The development of advanced user adaptable interfaces is necessary for building collaborative multimedia information- space presentations based upon advanced tools for information browsing, searching, filtering, and brokering to be applied on potentially very large and highly dynamic multimedia collections with a large number of users and user groups. Therefore, the development of advanced and at the same time adaptable and collaborative computer graphical information presentation schemes that allow to easily apply adequate visual metaphors for defined target user stereotypes has to become a key focus within ongoing research activities trying to support collaborative information work with multimedia collections.

Collaborations in art/science: Renaissance teams.

PubMed

Cox, D J

1991-01-01

A Renaissance Team is a group of specialists who collaborate and provide synergism in the quest for knowledge and information. Artists can participate in Renaissance Teams with scientists and computer specialists for scientific visualization projects. Some projects are described in which the author functioned as programmer and color expert, as interface designer, as visual paradigm maker, as animator, and as producer. Examples are provided for each of these five projects.

IdentityMap Visualization of the Super Identity Model

ScienceCinema

None

2018-06-08

The Super Identity Model is a collaboration with six United Kingdom universities to develop use cases used to piece together a person's identity across biological, cyber, psychological, and biographical domains. PNNL visualized the model in a web-based application called IdentityMap. This is the first step in a promising new field of research. Interested future collaborators are welcome to find out more by emailing superid@pnnl.gov.

IdentityMap Visualization of the Super Identity Model

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

None

The Super Identity Model is a collaboration with six United Kingdom universities to develop use cases used to piece together a person's identity across biological, cyber, psychological, and biographical domains. PNNL visualized the model in a web-based application called IdentityMap. This is the first step in a promising new field of research. Interested future collaborators are welcome to find out more by emailing superid@pnnl.gov.

Rocinante, a virtual collaborative visualizer

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

McDonald, M.J.; Ice, L.G.

1996-12-31

With the goal of improving the ability of people around the world to share the development and use of intelligent systems, Sandia National Laboratories` Intelligent Systems and Robotics Center is developing new Virtual Collaborative Engineering (VCE) and Virtual Collaborative Control (VCC) technologies. A key area of VCE and VCC research is in shared visualization of virtual environments. This paper describes a Virtual Collaborative Visualizer (VCV), named Rocinante, that Sandia developed for VCE and VCC applications. Rocinante allows multiple participants to simultaneously view dynamic geometrically-defined environments. Each viewer can exclude extraneous detail or include additional information in the scene as desired.more » Shared information can be saved and later replayed in a stand-alone mode. Rocinante automatically scales visualization requirements with computer system capabilities. Models with 30,000 polygons and 4 Megabytes of texture display at 12 to 15 frames per second (fps) on an SGI Onyx and at 3 to 8 fps (without texture) on Indigo 2 Extreme computers. In its networked mode, Rocinante synchronizes its local geometric model with remote simulators and sensory systems by monitoring data transmitted through UDP packets. Rocinante`s scalability and performance make it an ideal VCC tool. Users throughout the country can monitor robot motions and the thinking behind their motion planners and simulators.« less

Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT)

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

Williams, Dean N.

2011-07-20

This report summarizes work carried out by the Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT) Team for the period of January 1, 2011 through June 30, 2011. It discusses highlights, overall progress, period goals, and collaborations and lists papers and presentations. To learn more about our project, please visit our UV-CDAT website (URL: http://uv-cdat.org). This report will be forwarded to the program manager for the Department of Energy (DOE) Office of Biological and Environmental Research (BER), national and international collaborators and stakeholders, and to researchers working on a wide range of other climate model, reanalysis, and observation evaluation activities. Themore » UV-CDAT executive committee consists of Dean N. Williams of Lawrence Livermore National Laboratory (LLNL); Dave Bader and Galen Shipman of Oak Ridge National Laboratory (ORNL); Phil Jones and James Ahrens of Los Alamos National Laboratory (LANL), Claudio Silva of Polytechnic Institute of New York University (NYU-Poly); and Berk Geveci of Kitware, Inc. The UV-CDAT team consists of researchers and scientists with diverse domain knowledge whose home institutions also include the National Aeronautics and Space Administration (NASA) and the University of Utah. All work is accomplished under DOE open-source guidelines and in close collaboration with the project's stakeholders, domain researchers, and scientists. Working directly with BER climate science analysis projects, this consortium will develop and deploy data and computational resources useful to a wide variety of stakeholders, including scientists, policymakers, and the general public. Members of this consortium already collaborate with other institutions and universities in researching data discovery, management, visualization, workflow analysis, and provenance. The UV-CDAT team will address the following high-level visualization requirements: (1) Alternative parallel streaming statistics and analysis pipelines - Data parallelism, Task parallelism, Visualization parallelism; (2) Optimized parallel input/output (I/O); (3) Remote interactive execution; (4) Advanced intercomparison visualization; (5) Data provenance processing and capture; and (6) Interfaces for scientists - Workflow data analysis and visualization construction tools, and Visualization interfaces.« less

Supporting awareness through collaborative brushing and linking of tabular data.

PubMed

Hajizadeh, Amir Hossein; Tory, Melanie; Leung, Rock

2013-12-01

Maintaining an awareness of collaborators' actions is critical during collaborative work, including during collaborative visualization activities. Particularly when collaborators are located at a distance, it is important to know what everyone is working on in order to avoid duplication of effort, share relevant results in a timely manner and build upon each other's results. Can a person's brushing actions provide an indication of their queries and interests in a data set? Can these actions be revealed to a collaborator without substantially disrupting their own independent work? We designed a study to answer these questions in the context of distributed collaborative visualization of tabular data. Participants in our study worked independently to answer questions about a tabular data set, while simultaneously viewing brushing actions of a fictitious collaborator, shown directly within a shared workspace. We compared three methods of presenting the collaborator's actions: brushing & linking (i.e. highlighting exactly what the collaborator would see), selection (i.e. showing only a selected item), and persistent selection (i.e. showing only selected items but having them persist for some time). Our results demonstrated that persistent selection enabled some awareness of the collaborator's activities while causing minimal interference with independent work. Other techniques were less effective at providing awareness, and brushing & linking caused substantial interference. These findings suggest promise for the idea of exploiting natural brushing actions to provide awareness in collaborative work.

Bibliometric mapping: eight decades of analytical chemistry, with special focus on the use of mass spectrometry.

PubMed

Waaijer, Cathelijn J F; Palmblad, Magnus

2015-01-01

In this Feature we use automatic bibliometric mapping tools to visualize the history of analytical chemistry from the 1920s until the present. In particular, we have focused on the application of mass spectrometry in different fields. The analysis shows major shifts in research focus and use of mass spectrometry. We conclude by discussing the application of bibliometric mapping and visualization tools in analytical chemists' research.

Neural network based visualization of collaborations in a citizen science project

NASA Astrophysics Data System (ADS)

Morais, Alessandra M. M.; Santos, Rafael D. C.; Raddick, M. Jordan

2014-05-01

Citizen science projects are those in which volunteers are asked to collaborate in scientific projects, usually by volunteering idle computer time for distributed data processing efforts or by actively labeling or classifying information - shapes of galaxies, whale sounds, historical records are all examples of citizen science projects in which users access a data collecting system to label or classify images and sounds. In order to be successful, a citizen science project must captivate users and keep them interested on the project and on the science behind it, increasing therefore the time the users spend collaborating with the project. Understanding behavior of citizen scientists and their interaction with the data collection systems may help increase the involvement of the users, categorize them accordingly to different parameters, facilitate their collaboration with the systems, design better user interfaces, and allow better planning and deployment of similar projects and systems. Users behavior can be actively monitored or derived from their interaction with the data collection systems. Records of the interactions can be analyzed using visualization techniques to identify patterns and outliers. In this paper we present some results on the visualization of more than 80 million interactions of almost 150 thousand users with the Galaxy Zoo I citizen science project. Visualization of the attributes extracted from their behaviors was done with a clustering neural network (the Self-Organizing Map) and a selection of icon- and pixel-based techniques. These techniques allows the visual identification of groups of similar behavior in several different ways.

Metadata management for high content screening in OMERO

PubMed Central

Li, Simon; Besson, Sébastien; Blackburn, Colin; Carroll, Mark; Ferguson, Richard K.; Flynn, Helen; Gillen, Kenneth; Leigh, Roger; Lindner, Dominik; Linkert, Melissa; Moore, William J.; Ramalingam, Balaji; Rozbicki, Emil; Rustici, Gabriella; Tarkowska, Aleksandra; Walczysko, Petr; Williams, Eleanor; Allan, Chris; Burel, Jean-Marie; Moore, Josh; Swedlow, Jason R.

2016-01-01

High content screening (HCS) experiments create a classic data management challenge—multiple, large sets of heterogeneous structured and unstructured data, that must be integrated and linked to produce a set of “final” results. These different data include images, reagents, protocols, analytic output, and phenotypes, all of which must be stored, linked and made accessible for users, scientists, collaborators and where appropriate the wider community. The OME Consortium has built several open source tools for managing, linking and sharing these different types of data. The OME Data Model is a metadata specification that supports the image data and metadata recorded in HCS experiments. Bio-Formats is a Java library that reads recorded image data and metadata and includes support for several HCS screening systems. OMERO is an enterprise data management application that integrates image data, experimental and analytic metadata and makes them accessible for visualization, mining, sharing and downstream analysis. We discuss how Bio-Formats and OMERO handle these different data types, and how they can be used to integrate, link and share HCS experiments in facilities and public data repositories. OME specifications and software are open source and are available at https://www.openmicroscopy.org. PMID:26476368

Metadata management for high content screening in OMERO.

PubMed

Li, Simon; Besson, Sébastien; Blackburn, Colin; Carroll, Mark; Ferguson, Richard K; Flynn, Helen; Gillen, Kenneth; Leigh, Roger; Lindner, Dominik; Linkert, Melissa; Moore, William J; Ramalingam, Balaji; Rozbicki, Emil; Rustici, Gabriella; Tarkowska, Aleksandra; Walczysko, Petr; Williams, Eleanor; Allan, Chris; Burel, Jean-Marie; Moore, Josh; Swedlow, Jason R

2016-03-01

High content screening (HCS) experiments create a classic data management challenge-multiple, large sets of heterogeneous structured and unstructured data, that must be integrated and linked to produce a set of "final" results. These different data include images, reagents, protocols, analytic output, and phenotypes, all of which must be stored, linked and made accessible for users, scientists, collaborators and where appropriate the wider community. The OME Consortium has built several open source tools for managing, linking and sharing these different types of data. The OME Data Model is a metadata specification that supports the image data and metadata recorded in HCS experiments. Bio-Formats is a Java library that reads recorded image data and metadata and includes support for several HCS screening systems. OMERO is an enterprise data management application that integrates image data, experimental and analytic metadata and makes them accessible for visualization, mining, sharing and downstream analysis. We discuss how Bio-Formats and OMERO handle these different data types, and how they can be used to integrate, link and share HCS experiments in facilities and public data repositories. OME specifications and software are open source and are available at https://www.openmicroscopy.org. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Achievement of Joint Perception in a Computer Supported Collaborative Learning Environment: A Case Study

ERIC Educational Resources Information Center

Afacan Adanir, Gulgun

2017-01-01

The case study focuses on the interactional mechanisms through which online collaborative teams co-construct a shared understanding of an analytical geometry problem by using dynamic geometry representations. The collaborative study consisted of an assignment on which the learners worked together in groups to solve a ship navigation problem as…

Real-Time Mutual Gaze Perception Enhances Collaborative Learning and Collaboration Quality

ERIC Educational Resources Information Center

Schneider, Bertrand; Pea, Roy

2013-01-01

In this paper we present the results of an eye-tracking study on collaborative problem-solving dyads. Dyads remotely collaborated to learn from contrasting cases involving basic concepts about how the human brain processes visual information. In one condition, dyads saw the eye gazes of their partner on the screen; in a control group, they did not…

Semantic Interaction for Sensemaking: Inferring Analytical Reasoning for Model Steering.

PubMed

Endert, A; Fiaux, P; North, C

2012-12-01

Visual analytic tools aim to support the cognitively demanding task of sensemaking. Their success often depends on the ability to leverage capabilities of mathematical models, visualization, and human intuition through flexible, usable, and expressive interactions. Spatially clustering data is one effective metaphor for users to explore similarity and relationships between information, adjusting the weighting of dimensions or characteristics of the dataset to observe the change in the spatial layout. Semantic interaction is an approach to user interaction in such spatializations that couples these parametric modifications of the clustering model with users' analytic operations on the data (e.g., direct document movement in the spatialization, highlighting text, search, etc.). In this paper, we present results of a user study exploring the ability of semantic interaction in a visual analytic prototype, ForceSPIRE, to support sensemaking. We found that semantic interaction captures the analytical reasoning of the user through keyword weighting, and aids the user in co-creating a spatialization based on the user's reasoning and intuition.

Big data and visual analytics in anaesthesia and health care.

PubMed

Simpao, A F; Ahumada, L M; Rehman, M A

2015-09-01

Advances in computer technology, patient monitoring systems, and electronic health record systems have enabled rapid accumulation of patient data in electronic form (i.e. big data). Organizations such as the Anesthesia Quality Institute and Multicenter Perioperative Outcomes Group have spearheaded large-scale efforts to collect anaesthesia big data for outcomes research and quality improvement. Analytics--the systematic use of data combined with quantitative and qualitative analysis to make decisions--can be applied to big data for quality and performance improvements, such as predictive risk assessment, clinical decision support, and resource management. Visual analytics is the science of analytical reasoning facilitated by interactive visual interfaces, and it can facilitate performance of cognitive activities involving big data. Ongoing integration of big data and analytics within anaesthesia and health care will increase demand for anaesthesia professionals who are well versed in both the medical and the information sciences. © The Author 2015. Published by Oxford University Press on behalf of the British Journal of Anaesthesia. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Visual analytics in healthcare education: exploring novel ways to analyze and represent big data in undergraduate medical education

PubMed Central

Nilsson, Gunnar; Zary, Nabil

2014-01-01

Introduction. The big data present in the medical curriculum that informs undergraduate medical education is beyond human abilities to perceive and analyze. The medical curriculum is the main tool used by teachers and directors to plan, design, and deliver teaching and assessment activities and student evaluations in medical education in a continuous effort to improve it. Big data remains largely unexploited for medical education improvement purposes. The emerging research field of visual analytics has the advantage of combining data analysis and manipulation techniques, information and knowledge representation, and human cognitive strength to perceive and recognize visual patterns. Nevertheless, there is a lack of research on the use and benefits of visual analytics in medical education. Methods. The present study is based on analyzing the data in the medical curriculum of an undergraduate medical program as it concerns teaching activities, assessment methods and learning outcomes in order to explore visual analytics as a tool for finding ways of representing big data from undergraduate medical education for improvement purposes. Cytoscape software was employed to build networks of the identified aspects and visualize them. Results. After the analysis of the curriculum data, eleven aspects were identified. Further analysis and visualization of the identified aspects with Cytoscape resulted in building an abstract model of the examined data that presented three different approaches; (i) learning outcomes and teaching methods, (ii) examination and learning outcomes, and (iii) teaching methods, learning outcomes, examination results, and gap analysis. Discussion. This study identified aspects of medical curriculum that play an important role in how medical education is conducted. The implementation of visual analytics revealed three novel ways of representing big data in the undergraduate medical education context. It appears to be a useful tool to explore such data with possible future implications on healthcare education. It also opens a new direction in medical education informatics research. PMID:25469323

Visual analytics in healthcare education: exploring novel ways to analyze and represent big data in undergraduate medical education.

PubMed

Vaitsis, Christos; Nilsson, Gunnar; Zary, Nabil

2014-01-01

Introduction. The big data present in the medical curriculum that informs undergraduate medical education is beyond human abilities to perceive and analyze. The medical curriculum is the main tool used by teachers and directors to plan, design, and deliver teaching and assessment activities and student evaluations in medical education in a continuous effort to improve it. Big data remains largely unexploited for medical education improvement purposes. The emerging research field of visual analytics has the advantage of combining data analysis and manipulation techniques, information and knowledge representation, and human cognitive strength to perceive and recognize visual patterns. Nevertheless, there is a lack of research on the use and benefits of visual analytics in medical education. Methods. The present study is based on analyzing the data in the medical curriculum of an undergraduate medical program as it concerns teaching activities, assessment methods and learning outcomes in order to explore visual analytics as a tool for finding ways of representing big data from undergraduate medical education for improvement purposes. Cytoscape software was employed to build networks of the identified aspects and visualize them. Results. After the analysis of the curriculum data, eleven aspects were identified. Further analysis and visualization of the identified aspects with Cytoscape resulted in building an abstract model of the examined data that presented three different approaches; (i) learning outcomes and teaching methods, (ii) examination and learning outcomes, and (iii) teaching methods, learning outcomes, examination results, and gap analysis. Discussion. This study identified aspects of medical curriculum that play an important role in how medical education is conducted. The implementation of visual analytics revealed three novel ways of representing big data in the undergraduate medical education context. It appears to be a useful tool to explore such data with possible future implications on healthcare education. It also opens a new direction in medical education informatics research.

Big data analytics as a service infrastructure: challenges, desired properties and solutions

NASA Astrophysics Data System (ADS)

Martín-Márquez, Manuel

2015-12-01

CERN's accelerator complex generates a very large amount of data. A large volumen of heterogeneous data is constantly generated from control equipment and monitoring agents. These data must be stored and analysed. Over the decades, CERN's researching and engineering teams have applied different approaches, techniques and technologies for this purpose. This situation has minimised the necessary collaboration and, more relevantly, the cross data analytics over different domains. These two factors are essential to unlock hidden insights and correlations between the underlying processes, which enable better and more efficient daily-based accelerator operations and more informed decisions. The proposed Big Data Analytics as a Service Infrastructure aims to: (1) integrate the existing developments; (2) centralise and standardise the complex data analytics needs for CERN's research and engineering community; (3) deliver real-time, batch data analytics and information discovery capabilities; and (4) provide transparent access and Extract, Transform and Load (ETL), mechanisms to the various and mission-critical existing data repositories. This paper presents the desired objectives and properties resulting from the analysis of CERN's data analytics requirements; the main challenges: technological, collaborative and educational and; potential solutions.

SOCRAT Platform Design: A Web Architecture for Interactive Visual Analytics Applications

PubMed Central

Kalinin, Alexandr A.; Palanimalai, Selvam; Dinov, Ivo D.

2018-01-01

The modern web is a successful platform for large scale interactive web applications, including visualizations. However, there are no established design principles for building complex visual analytics (VA) web applications that could efficiently integrate visualizations with data management, computational transformation, hypothesis testing, and knowledge discovery. This imposes a time-consuming design and development process on many researchers and developers. To address these challenges, we consider the design requirements for the development of a module-based VA system architecture, adopting existing practices of large scale web application development. We present the preliminary design and implementation of an open-source platform for Statistics Online Computational Resource Analytical Toolbox (SOCRAT). This platform defines: (1) a specification for an architecture for building VA applications with multi-level modularity, and (2) methods for optimizing module interaction, re-usage, and extension. To demonstrate how this platform can be used to integrate a number of data management, interactive visualization, and analysis tools, we implement an example application for simple VA tasks including raw data input and representation, interactive visualization and analysis. PMID:29630069

SOCRAT Platform Design: A Web Architecture for Interactive Visual Analytics Applications.

PubMed

Kalinin, Alexandr A; Palanimalai, Selvam; Dinov, Ivo D

2017-04-01

The modern web is a successful platform for large scale interactive web applications, including visualizations. However, there are no established design principles for building complex visual analytics (VA) web applications that could efficiently integrate visualizations with data management, computational transformation, hypothesis testing, and knowledge discovery. This imposes a time-consuming design and development process on many researchers and developers. To address these challenges, we consider the design requirements for the development of a module-based VA system architecture, adopting existing practices of large scale web application development. We present the preliminary design and implementation of an open-source platform for Statistics Online Computational Resource Analytical Toolbox (SOCRAT). This platform defines: (1) a specification for an architecture for building VA applications with multi-level modularity, and (2) methods for optimizing module interaction, re-usage, and extension. To demonstrate how this platform can be used to integrate a number of data management, interactive visualization, and analysis tools, we implement an example application for simple VA tasks including raw data input and representation, interactive visualization and analysis.

Avatar-Mediated Networking: Increasing Social Presence and Interpersonal Trust in Net-Based Collaborations

ERIC Educational Resources Information Center

Bente, Gary; Ruggenberg, Sabine; Kramer, Nicole C.; Eschenburg, Felix

2008-01-01

This study analyzes the influence of avatars on social presence, interpersonal trust, perceived communication quality, nonverbal behavior, and visual attention in Net-based collaborations using a comparative approach. A real-time communication window including a special avatar interface was integrated into a shared collaborative workspace.…

Immersive Visual Analytics for Transformative Neutron Scattering Science

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

Steed, Chad A; Daniel, Jamison R; Drouhard, Margaret

The ORNL Spallation Neutron Source (SNS) provides the most intense pulsed neutron beams in the world for scientific research and development across a broad range of disciplines. SNS experiments produce large volumes of complex data that are analyzed by scientists with varying degrees of experience using 3D visualization and analysis systems. However, it is notoriously difficult to achieve proficiency with 3D visualizations. Because 3D representations are key to understanding the neutron scattering data, scientists are unable to analyze their data in a timely fashion resulting in inefficient use of the limited and expensive SNS beam time. We believe a moremore » intuitive interface for exploring neutron scattering data can be created by combining immersive virtual reality technology with high performance data analytics and human interaction. In this paper, we present our initial investigations of immersive visualization concepts as well as our vision for an immersive visual analytics framework that could lower the barriers to 3D exploratory data analysis of neutron scattering data at the SNS.« less

A Software Developer’s Guide to Informal Evaluation of Visual Analytics Environments Using VAST Challenge Information

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

Cook, Kristin A.; Scholtz, Jean; Whiting, Mark A.

The VAST Challenge has been a popular venue for academic and industry participants for over ten years. Many participants comment that the majority of their time in preparing VAST Challenge entries is discovering elements in their software environments that need to be redesigned in order to solve the given task. Fortunately, there is no need to wait until the VAST Challenge is announced to test out software systems. The Visual Analytics Benchmark Repository contains all past VAST Challenge tasks, data, solutions and submissions. This paper details the various types of evaluations that may be conducted using the Repository information. Inmore » this paper we describe how developers can do informal evaluations of various aspects of their visual analytics environments using VAST Challenge information. Aspects that can be evaluated include the appropriateness of the software for various tasks, the various data types and formats that can be accommodated, the effectiveness and efficiency of the process supported by the software, and the intuitiveness of the visualizations and interactions. Researchers can compare their visualizations and interactions to those submitted to determine novelty. In addition, the paper provides pointers to various guidelines that software teams can use to evaluate the usability of their software. While these evaluations are not a replacement for formal evaluation methods, this information can be extremely useful during the development of visual analytics environments.« less

SmartAdP: Visual Analytics of Large-scale Taxi Trajectories for Selecting Billboard Locations.

PubMed

Liu, Dongyu; Weng, Di; Li, Yuhong; Bao, Jie; Zheng, Yu; Qu, Huamin; Wu, Yingcai

2017-01-01

The problem of formulating solutions immediately and comparing them rapidly for billboard placements has plagued advertising planners for a long time, owing to the lack of efficient tools for in-depth analyses to make informed decisions. In this study, we attempt to employ visual analytics that combines the state-of-the-art mining and visualization techniques to tackle this problem using large-scale GPS trajectory data. In particular, we present SmartAdP, an interactive visual analytics system that deals with the two major challenges including finding good solutions in a huge solution space and comparing the solutions in a visual and intuitive manner. An interactive framework that integrates a novel visualization-driven data mining model enables advertising planners to effectively and efficiently formulate good candidate solutions. In addition, we propose a set of coupled visualizations: a solution view with metaphor-based glyphs to visualize the correlation between different solutions; a location view to display billboard locations in a compact manner; and a ranking view to present multi-typed rankings of the solutions. This system has been demonstrated using case studies with a real-world dataset and domain-expert interviews. Our approach can be adapted for other location selection problems such as selecting locations of retail stores or restaurants using trajectory data.

Big Data Analytics and Machine Intelligence Capability Development at NASA Langley Research Center: Strategy, Roadmap, and Progress

NASA Technical Reports Server (NTRS)

Ambur, Manjula Y.; Yagle, Jeremy J.; Reith, William; McLarney, Edward

2016-01-01

In 2014, a team of researchers, engineers and information technology specialists at NASA Langley Research Center developed a Big Data Analytics and Machine Intelligence Strategy and Roadmap as part of Langley's Comprehensive Digital Transformation Initiative, with the goal of identifying the goals, objectives, initiatives, and recommendations need to develop near-, mid- and long-term capabilities for data analytics and machine intelligence in aerospace domains. Since that time, significant progress has been made in developing pilots and projects in several research, engineering, and scientific domains by following the original strategy of collaboration between mission support organizations, mission organizations, and external partners from universities and industry. This report summarizes the work to date in Data Intensive Scientific Discovery, Deep Content Analytics, and Deep Q&A projects, as well as the progress made in collaboration, outreach, and education. Recommendations for continuing this success into future phases of the initiative are also made.

Overview of Human-Centric Space Situational Awareness (SSA) Science and Technology (S&T)

NASA Astrophysics Data System (ADS)

Ianni, J.; Aleva, D.; Ellis, S.

2012-09-01

A number of organizations, within the government, industry, and academia, are researching ways to help humans understand and react to events in space. The problem is both helped and complicated by the fact that there are numerous data sources that need to be planned (i.e., tasked), collected, processed, analyzed, and disseminated. A large part of the research is in support of the Joint Space Operational Center (JSpOC), National Air and Space Intelligence Center (NASIC), and similar organizations. Much recent research has been specifically targeting the JSpOC Mission System (JMS) which has provided a unifying software architecture. This paper will first outline areas of science and technology (S&T) related to human-centric space situational awareness (SSA) and space command and control (C2) including: 1. Object visualization - especially data fused from disparate sources. Also satellite catalog visualizations that convey the physical relationships between space objects. 2. Data visualization - improve data trend analysis as in visual analytics and interactive visualization; e.g., satellite anomaly trends over time, space weather visualization, dynamic visualizations 3. Workflow support - human-computer interfaces that encapsulate multiple computer services (i.e., algorithms, programs, applications) into a 4. Command and control - e.g., tools that support course of action (COA) development and selection, tasking for satellites and sensors, etc. 5. Collaboration - improve individuals or teams ability to work with others; e.g., video teleconferencing, shared virtual spaces, file sharing, virtual white-boards, chat, and knowledge search. 6. Hardware/facilities - e.g., optimal layouts for operations centers, ergonomic workstations, immersive displays, interaction technologies, and mobile computing. Secondly we will provide a survey of organizations working these areas and suggest where more attention may be needed. Although no detailed master plan exists for human-centric SSA and C2, we see little redundancy among the groups supporting SSA human factors at this point.

The Role of Visual Learning in Improving Students' High-Order Thinking Skills

ERIC Educational Resources Information Center

Raiyn, Jamal

2016-01-01

Various concepts have been introduced to improve students' analytical thinking skills based on problem based learning (PBL). This paper introduces a new concept to increase student's analytical thinking skills based on a visual learning strategy. Such a strategy has three fundamental components: a teacher, a student, and a learning process. The…

Education and Community: The Collaborative Solution. Proceedings of the International Conference Linking Research and Practice (Toronto, Ontario, Canada, March 3-5, 1994).

ERIC Educational Resources Information Center

Lawton, Stephen B., Ed.; Tanenzapt, Elaine, Ed.; Townsend, Richard G., Ed.

These proceedings are divided into two sections that explore collaboration between schools and communities. In Part I, the first four papers, analytic frameworks are described that provide different perspectives on collaboration. In Part II, descriptions of concrete programs and advice for developing better school-community relations are offered.…

A Graphics Design Framework to Visualize Multi-Dimensional Economic Datasets

ERIC Educational Resources Information Center

Chandramouli, Magesh; Narayanan, Badri; Bertoline, Gary R.

2013-01-01

This study implements a prototype graphics visualization framework to visualize multidimensional data. This graphics design framework serves as a "visual analytical database" for visualization and simulation of economic models. One of the primary goals of any kind of visualization is to extract useful information from colossal volumes of…

Unlocking Proteomic Heterogeneity in Complex Diseases through Visual Analytics

PubMed Central

Bhavnani, Suresh K.; Dang, Bryant; Bellala, Gowtham; Divekar, Rohit; Visweswaran, Shyam; Brasier, Allan; Kurosky, Alex

2015-01-01

Despite years of preclinical development, biological interventions designed to treat complex diseases like asthma often fail in phase III clinical trials. These failures suggest that current methods to analyze biomedical data might be missing critical aspects of biological complexity such as the assumption that cases and controls come from homogeneous distributions. Here we discuss why and how methods from the rapidly evolving field of visual analytics can help translational teams (consisting of biologists, clinicians, and bioinformaticians) to address the challenge of modeling and inferring heterogeneity in the proteomic and phenotypic profiles of patients with complex diseases. Because a primary goal of visual analytics is to amplify the cognitive capacities of humans for detecting patterns in complex data, we begin with an overview of the cognitive foundations for the field of visual analytics. Next, we organize the primary ways in which a specific form of visual analytics called networks have been used to model and infer biological mechanisms, which help to identify the properties of networks that are particularly useful for the discovery and analysis of proteomic heterogeneity in complex diseases. We describe one such approach called subject-protein networks, and demonstrate its application on two proteomic datasets. This demonstration provides insights to help translational teams overcome theoretical, practical, and pedagogical hurdles for the widespread use of subject-protein networks for analyzing molecular heterogeneities, with the translational goal of designing biomarker-based clinical trials, and accelerating the development of personalized approaches to medicine. PMID:25684269

Application of Data Provenance in Healthcare Analytics Software: Information Visualisation of User Activities

PubMed Central

Xu, Shen; Rogers, Toby; Fairweather, Elliot; Glenn, Anthony; Curran, James; Curcin, Vasa

2018-01-01

Data provenance is a technique that describes the history of digital objects. In health data settings, it can be used to deliver auditability and transparency, and to achieve trust in a software system. However, implementing data provenance in analytics software at an enterprise level presents a different set of challenges from the research environments where data provenance was originally devised. In this paper, the challenges of reporting provenance information to the user is presented. Provenance captured from analytics software can be large and complex and visualizing a series of tasks over a long period can be overwhelming even for a domain expert, requiring visual aggregation mechanisms that fit with complex human cognitive activities involved in the process. This research studied how provenance-based reporting can be integrated into a health data analytics software, using the example of Atmolytics visual reporting tool. PMID:29888084

The science of visual analysis at extreme scale

NASA Astrophysics Data System (ADS)

Nowell, Lucy T.

2011-01-01

Driven by market forces and spanning the full spectrum of computational devices, computer architectures are changing in ways that present tremendous opportunities and challenges for data analysis and visual analytic technologies. Leadership-class high performance computing system will have as many as a million cores by 2020 and support 10 billion-way concurrency, while laptop computers are expected to have as many as 1,000 cores by 2015. At the same time, data of all types are increasing exponentially and automated analytic methods are essential for all disciplines. Many existing analytic technologies do not scale to make full use of current platforms and fewer still are likely to scale to the systems that will be operational by the end of this decade. Furthermore, on the new architectures and for data at extreme scales, validating the accuracy and effectiveness of analytic methods, including visual analysis, will be increasingly important.

Developing Visual Thinking in the Electronic Health Record.

PubMed

Boyd, Andrew D; Young, Christine D; Amatayakul, Margret; Dieter, Michael G; Pawola, Lawrence M

2017-01-01

The purpose of this vision paper is to identify how data visualization could transform healthcare. Electronic Health Records (EHRs) are maturing with new technology and tools being applied. Researchers are reaping the benefits of data visualization to better access compilations of EHR data for enhanced clinical research. Data visualization, while still primarily the domain of clinical researchers, is beginning to show promise for other stakeholders. A non-exhaustive review of the literature indicates that respective to the growth and development of the EHR, the maturity of data visualization in healthcare is in its infancy. Visual analytics has been only cursorily applied to healthcare. A fundamental issue contributing to fragmentation and poor coordination of healthcare delivery is that each member of the healthcare team, including patients, has a different view. Summarizing all of this care comprehensively for any member of the healthcare team is a "wickedly hard" visual analytics and data visualization problem to solve.

Matisse: A Visual Analytics System for Exploring Emotion Trends in Social Media Text Streams

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

Steed, Chad A; Drouhard, Margaret MEG G; Beaver, Justin M

Dynamically mining textual information streams to gain real-time situational awareness is especially challenging with social media systems where throughput and velocity properties push the limits of a static analytical approach. In this paper, we describe an interactive visual analytics system, called Matisse, that aids with the discovery and investigation of trends in streaming text. Matisse addresses the challenges inherent to text stream mining through the following technical contributions: (1) robust stream data management, (2) automated sentiment/emotion analytics, (3) interactive coordinated visualizations, and (4) a flexible drill-down interaction scheme that accesses multiple levels of detail. In addition to positive/negative sentiment prediction,more » Matisse provides fine-grained emotion classification based on Valence, Arousal, and Dominance dimensions and a novel machine learning process. Information from the sentiment/emotion analytics are fused with raw data and summary information to feed temporal, geospatial, term frequency, and scatterplot visualizations using a multi-scale, coordinated interaction model. After describing these techniques, we conclude with a practical case study focused on analyzing the Twitter sample stream during the week of the 2013 Boston Marathon bombings. The case study demonstrates the effectiveness of Matisse at providing guided situational awareness of significant trends in social media streams by orchestrating computational power and human cognition.« less

Remote Visualization and Remote Collaboration On Computational Fluid Dynamics

NASA Technical Reports Server (NTRS)

Watson, Val; Lasinski, T. A. (Technical Monitor)

1995-01-01

A new technology has been developed for remote visualization that provides remote, 3D, high resolution, dynamic, interactive viewing of scientific data (such as fluid dynamics simulations or measurements). Based on this technology, some World Wide Web sites on the Internet are providing fluid dynamics data for educational or testing purposes. This technology is also being used for remote collaboration in joint university, industry, and NASA projects in computational fluid dynamics and wind tunnel testing. Previously, remote visualization of dynamic data was done using video format (transmitting pixel information) such as video conferencing or MPEG movies on the Internet. The concept for this new technology is to send the raw data (e.g., grids, vectors, and scalars) along with viewing scripts over the Internet and have the pixels generated by a visualization tool running on the viewer's local workstation. The visualization tool that is currently used is FAST (Flow Analysis Software Toolkit).

Visualization and characterization of users in a citizen science project

NASA Astrophysics Data System (ADS)

Morais, Alessandra M. M.; Raddick, Jordan; Coelho dos Santos, Rafael D.

2013-05-01

Recent technological advances allowed the creation and use of internet-based systems where many users can collaborate gathering and sharing information for specific or general purposes: social networks, e-commerce review systems, collaborative knowledge systems, etc. Since most of the data collected in these systems is user-generated, understanding of the motivations and general behavior of users is a very important issue. Of particular interest are citizen science projects, where users without scientific training are asked for collaboration labeling and classifying information (either automatically by giving away idle computer time or manually by actually seeing data and providing information about it). Understanding behavior of users of those types of data collection systems may help increase the involvement of the users, categorize users accordingly to different parameters, facilitate their collaboration with the systems, design better user interfaces, and allow better planning and deployment of similar projects and systems. Behavior of those users could be estimated through analysis of their collaboration track: registers of which user did what and when can be easily and unobtrusively collected in several different ways, the simplest being a log of activities. In this paper we present some results on the visualization and characterization of almost 150.000 users with more than 80.000.000 collaborations with a citizen science project - Galaxy Zoo I, which asked users to classify galaxies' images. Basic visualization techniques are not applicable due to the number of users, so techniques to characterize users' behavior based on feature extraction and clustering are used.

SmartR: an open-source platform for interactive visual analytics for translational research data

PubMed Central

Herzinger, Sascha; Gu, Wei; Satagopam, Venkata; Eifes, Serge; Rege, Kavita; Barbosa-Silva, Adriano; Schneider, Reinhard

2017-01-01

Abstract Summary: In translational research, efficient knowledge exchange between the different fields of expertise is crucial. An open platform that is capable of storing a multitude of data types such as clinical, pre-clinical or OMICS data combined with strong visual analytical capabilities will significantly accelerate the scientific progress by making data more accessible and hypothesis generation easier. The open data warehouse tranSMART is capable of storing a variety of data types and has a growing user community including both academic institutions and pharmaceutical companies. tranSMART, however, currently lacks interactive and dynamic visual analytics and does not permit any post-processing interaction or exploration. For this reason, we developed SmartR, a plugin for tranSMART, that equips the platform not only with several dynamic visual analytical workflows, but also provides its own framework for the addition of new custom workflows. Modern web technologies such as D3.js or AngularJS were used to build a set of standard visualizations that were heavily improved with dynamic elements. Availability and Implementation: The source code is licensed under the Apache 2.0 License and is freely available on GitHub: https://github.com/transmart/SmartR. Contact: reinhard.schneider@uni.lu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28334291

SmartR: an open-source platform for interactive visual analytics for translational research data.

PubMed

Herzinger, Sascha; Gu, Wei; Satagopam, Venkata; Eifes, Serge; Rege, Kavita; Barbosa-Silva, Adriano; Schneider, Reinhard

2017-07-15

In translational research, efficient knowledge exchange between the different fields of expertise is crucial. An open platform that is capable of storing a multitude of data types such as clinical, pre-clinical or OMICS data combined with strong visual analytical capabilities will significantly accelerate the scientific progress by making data more accessible and hypothesis generation easier. The open data warehouse tranSMART is capable of storing a variety of data types and has a growing user community including both academic institutions and pharmaceutical companies. tranSMART, however, currently lacks interactive and dynamic visual analytics and does not permit any post-processing interaction or exploration. For this reason, we developed SmartR , a plugin for tranSMART, that equips the platform not only with several dynamic visual analytical workflows, but also provides its own framework for the addition of new custom workflows. Modern web technologies such as D3.js or AngularJS were used to build a set of standard visualizations that were heavily improved with dynamic elements. The source code is licensed under the Apache 2.0 License and is freely available on GitHub: https://github.com/transmart/SmartR . reinhard.schneider@uni.lu. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Early Alert of Academically At-Risk Students: An Open Source Analytics Initiative

ERIC Educational Resources Information Center

Jayaprakash, Sandeep M.; Moody, Erik W.; Lauría, Eitel J. M.; Regan, James R.; Baron, Joshua D.

2014-01-01

The Open Academic Analytics Initiative (OAAI) is a collaborative, multi-year grant program aimed at researching issues related to the scaling up of learning analytics technologies and solutions across all of higher education. The paper describes the goals and objectives of the OAAI, depicts the process and challenges of collecting, organizing and…

How Pictorial Knowledge Representations Mediate Collaborative Knowledge Construction in Groups

ERIC Educational Resources Information Center

Naykki, Piia; Jarvela, Sanna

2008-01-01

This study investigates the process of collaborative knowledge construction when technology and pictorial knowledge representations are used for visualizing individual and groups' shared ideas. The focus of the study is on how teacher-students contribute to the group's collaborative knowledge construction and use each other's ideas and tools as an…

The Importance of Earth Observations and Data Collaboration within Environmental Intelligence Supporting Arctic Research

NASA Technical Reports Server (NTRS)

Casas, Joseph

2017-01-01

Within the IARPC Collaboration Team activities of 2016, Arctic in-situ and remote earth observations advanced topics such as :1) exploring the role for new and innovative autonomous observing technologies in the Arctic; 2) advancing catalytic national and international community based observing efforts in support of the National Strategy for the Arctic Region; and 3) enhancing the use of discovery tools for observing system collaboration such as the U.S. National Oceanic and Atmospheric Administration (NOAA) Arctic Environmental Response Management Application (ERMA) and the U.S. National Aeronautics and Space Administration (NASA) Arctic Collaborative Environment (ACE) project geo reference visualization decision support and exploitation internet based tools. Critical to the success of these earth observations for both in-situ and remote systems is the emerging of new and innovative data collection technologies and comprehensive modeling as well as enhanced communications and cyber infrastructure capabilities which effectively assimilate and dissemination many environmental intelligence products in a timely manner. The Arctic Collaborative Environment (ACE) project is well positioned to greatly enhance user capabilities for accessing, organizing, visualizing, sharing and producing collaborative knowledge for the Arctic.

Intelligent platforms for disease assessment: novel approaches in functional echocardiography.

PubMed

Sengupta, Partho P

2013-11-01

Accelerating trends in the dynamic digital era (from 2004 onward) has resulted in the emergence of novel parametric imaging tools that allow easy and accurate extraction of quantitative information from cardiac images. This review principally attempts to heighten the awareness of newer emerging paradigms that may advance acquisition, visualization and interpretation of the large functional data sets obtained during cardiac ultrasound imaging. Incorporation of innovative cognitive software that allow advanced pattern recognition and disease forecasting will likely transform the human-machine interface and interpretation process to achieve a more efficient and effective work environment. Novel technologies for automation and big data analytics that are already active in other fields need to be rapidly adapted to the health care environment with new academic-industry collaborations to enrich and accelerate the delivery of newer decision making tools for enhancing patient care. Copyright © 2013. Published by Elsevier Inc.

Visual Analytics of Surveillance Data on Foodborne Vibriosis, United States, 1973–2010

PubMed Central

Sims, Jennifer N.; Isokpehi, Raphael D.; Cooper, Gabrielle A.; Bass, Michael P.; Brown, Shyretha D.; St John, Alison L.; Gulig, Paul A.; Cohly, Hari H.P.

2011-01-01

Foodborne illnesses caused by microbial and chemical contaminants in food are a substantial health burden worldwide. In 2007, human vibriosis (non-cholera Vibrio infections) became a notifiable disease in the United States. In addition, Vibrio species are among the 31 major known pathogens transmitted through food in the United States. Diverse surveillance systems for foodborne pathogens also track outbreaks, illnesses, hospitalization and deaths due to non-cholera vibrios. Considering the recognition of vibriosis as a notifiable disease in the United States and the availability of diverse surveillance systems, there is a need for the development of easily deployed visualization and analysis approaches that can combine diverse data sources in an interactive manner. Current efforts to address this need are still limited. Visual analytics is an iterative process conducted via visual interfaces that involves collecting information, data preprocessing, knowledge representation, interaction, and decision making. We have utilized public domain outbreak and surveillance data sources covering 1973 to 2010, as well as visual analytics software to demonstrate integrated and interactive visualizations of data on foodborne outbreaks and surveillance of Vibrio species. Through the data visualization, we were able to identify unique patterns and/or novel relationships within and across datasets regarding (i) causative agent; (ii) foodborne outbreaks and illness per state; (iii) location of infection; (iv) vehicle (food) of infection; (v) anatomical site of isolation of Vibrio species; (vi) patients and complications of vibriosis; (vii) incidence of laboratory-confirmed vibriosis and V. parahaemolyticus outbreaks. The additional use of emerging visual analytics approaches for interaction with data on vibriosis, including non-foodborne related disease, can guide disease control and prevention as well as ongoing outbreak investigations. PMID:22174586

Self-contained image mapping of placental vasculature in 3D ultrasound-guided fetoscopy.

PubMed

Yang, Liangjing; Wang, Junchen; Ando, Takehiro; Kubota, Akihiro; Yamashita, Hiromasa; Sakuma, Ichiro; Chiba, Toshio; Kobayashi, Etsuko

2016-09-01

Surgical navigation technology directed at fetoscopic procedures is relatively underdeveloped compared with other forms of endoscopy. The narrow fetoscopic field of views and the vast vascular network on the placenta make examination and photocoagulation treatment of twin-to-twin transfusion syndrome challenging. Though ultrasonography is used for intraoperative guidance, its navigational ability is not fully exploited. This work aims to integrate 3D ultrasound imaging and endoscopic vision seamlessly for placental vasculature mapping through a self-contained framework without external navigational devices. This is achieved through development, integration, and experimentation of novel navigational modules. Firstly, a framework design that addresses the current limitations based on identified gaps is conceptualized. Secondly, integration of navigational modules including (1) ultrasound-based localization, (2) image alignment, and (3) vision-based tracking to update the scene texture map is implemented. This updated texture map is projected to an ultrasound-constructed 3D model for photorealistic texturing of the 3D scene creating a panoramic view of the moving fetoscope. In addition, a collaborative scheme for the integration of the modular workflow system is proposed to schedule updates in a systematic fashion. Finally, experiments are carried out to evaluate each modular variation and an integrated collaborative scheme of the framework. The modules and the collaborative scheme are evaluated through a series of phantom experiments with controlled trajectories for repeatability. The collaborative framework demonstrated the best accuracy (5.2 % RMS error) compared with all the three single-module variations during the experiment. Validation on an ex vivo monkey placenta shows visual continuity of the freehand fetoscopic panorama. The proposed developed collaborative framework and the evaluation study of the framework variations provide analytical insights for effective integration of ultrasonography and endoscopy. This contributes to the development of navigation techniques in fetoscopic procedures and can potentially be extended to other applications in intraoperative imaging.

Live Storybook Outcomes of Pilot Multidisciplinary Elementary Earth Science Collaborative Project

NASA Astrophysics Data System (ADS)

Soeffing, C.; Pierson, R.

2017-12-01

Live Storybook Outcomes of pilot multidisciplinary elementary earth science collaborative project Anchoring phenomena leading to student led investigations are key to applying the NGSS standards in the classroom. This project employs the GLOBE elementary storybook, Discoveries at Willow Creek, as an inspiration and operational framework for a collaborative pilot project engaging 4th grade students in asking questions, collecting relevant data, and using analytical tools to document and understand natural phenomena. The Institute of Global Environmental Strategies (IGES), a GLOBE Partner, the Outdoor Campus, an informal educational outdoor learning facility managed by South Dakota Game, Fish and Parks, University of Sioux Falls, and All City Elementary, Sioux Falls are collaborating partners in this project. The Discoveries at Willow Creek storyline introduces young students to the scientific process, and models how they can apply science and engineering practices (SEPs) to discover and understand the Earth system in which they live. One innovation associated with this project is the formal engagement of elementary students in a global citizen science program (for all ages), GLOBE Observer, and engaging them in data collection using GLOBE Observer's Cloud and Mosquito Habitat Mapper apps. As modeled by the fictional students from Willow Creek, the 4th grade students will identify their 3 study sites at the Outdoor Campus, keep a journal, and record observations. The students will repeat their investigations at the Outdoor Campus to document and track change over time. Students will be introduced to "big data" in a manageable way, as they see their observations populate GLOBE's map-based data visualization and . Our research design recognizes the comfort and familiarity factor of literacy activities in the elementary classroom for students and teachers alike, and postulates that connecting a science education project to an engaging storybook text will contribute to a successful implementation and measurable learning outcomes. We will report on the Fall 2017 pilot metrics of success, along with a discussion of multi partner collaborations, project scale-up and sustainability.

How the study of online collaborative learning can guide teachers and predict students' performance in a medical course.

PubMed

Saqr, Mohammed; Fors, Uno; Tedre, Matti

2018-02-06

Collaborative learning facilitates reflection, diversifies understanding and stimulates skills of critical and higher-order thinking. Although the benefits of collaborative learning have long been recognized, it is still rarely studied by social network analysis (SNA) in medical education, and the relationship of parameters that can be obtained via SNA with students' performance remains largely unknown. The aim of this work was to assess the potential of SNA for studying online collaborative clinical case discussions in a medical course and to find out which activities correlate with better performance and help predict final grade or explain variance in performance. Interaction data were extracted from the learning management system (LMS) forum module of the Surgery course in Qassim University, College of Medicine. The data were analyzed using social network analysis. The analysis included visual as well as a statistical analysis. Correlation with students' performance was calculated, and automatic linear regression was used to predict students' performance. By using social network analysis, we were able to analyze a large number of interactions in online collaborative discussions and gain an overall insight of the course social structure, track the knowledge flow and the interaction patterns, as well as identify the active participants and the prominent discussion moderators. When augmented with calculated network parameters, SNA offered an accurate view of the course network, each user's position, and level of connectedness. Results from correlation coefficients, linear regression, and logistic regression indicated that a student's position and role in information relay in online case discussions, combined with the strength of that student's network (social capital), can be used as predictors of performance in relevant settings. By using social network analysis, researchers can analyze the social structure of an online course and reveal important information about students' and teachers' interactions that can be valuable in guiding teachers, improve students' engagement, and contribute to learning analytics insights.

Ciência & Saúde Coletiva: scientific production analysis and collaborative research networks.

PubMed

Conner, Norma; Provedel, Attilio; Maciel, Ethel Leonor Noia

2017-03-01

The purpose of this metric and descriptive study was to identify the most productive authors and their collaborative research networks from articles published in Ciência & Saúde Coletiva between, 2005, and 2014. Authors meeting the cutoff criteria of at least 10 articles were considered the most productive authors. VOSviewer and Network Workbench technologies were applied for visual representations of collaborative research networks involving the most productive authors in the period. Initial analysis recovered 2511 distinct articles, with 8920 total authors with an average of 3.55 authors per article. Author analysis revealed 6288 distinct authors, 24 of these authors were identified as the most productive. These 24 authors generated 287 articles with an average of 4.31 authors per article, and represented 8 separate collaborative partnerships, the largest of which had 14 authors, indicating a significant degree of collaboration among these authors. This analysis provides a visual representation of networks of knowledge development in public health and demonstrates the usefulness of VOSviewer and Network Workbench technologies in future research.

Scalable Adaptive Graphics Environment (SAGE) Software for the Visualization of Large Data Sets on a Video Wall

NASA Technical Reports Server (NTRS)

Jedlovec, Gary; Srikishen, Jayanthi; Edwards, Rita; Cross, David; Welch, Jon; Smith, Matt

2013-01-01

The use of collaborative scientific visualization systems for the analysis, visualization, and sharing of "big data" available from new high resolution remote sensing satellite sensors or four-dimensional numerical model simulations is propelling the wider adoption of ultra-resolution tiled display walls interconnected by high speed networks. These systems require a globally connected and well-integrated operating environment that provides persistent visualization and collaboration services. This abstract and subsequent presentation describes a new collaborative visualization system installed for NASA's Shortterm Prediction Research and Transition (SPoRT) program at Marshall Space Flight Center and its use for Earth science applications. The system consists of a 3 x 4 array of 1920 x 1080 pixel thin bezel video monitors mounted on a wall in a scientific collaboration lab. The monitors are physically and virtually integrated into a 14' x 7' for video display. The display of scientific data on the video wall is controlled by a single Alienware Aurora PC with a 2nd Generation Intel Core 4.1 GHz processor, 32 GB memory, and an AMD Fire Pro W600 video card with 6 mini display port connections. Six mini display-to-dual DVI cables are used to connect the 12 individual video monitors. The open source Scalable Adaptive Graphics Environment (SAGE) windowing and media control framework, running on top of the Ubuntu 12 Linux operating system, allows several users to simultaneously control the display and storage of high resolution still and moving graphics in a variety of formats, on tiled display walls of any size. The Ubuntu operating system supports the open source Scalable Adaptive Graphics Environment (SAGE) software which provides a common environment, or framework, enabling its users to access, display and share a variety of data-intensive information. This information can be digital-cinema animations, high-resolution images, high-definition video-teleconferences, presentation slides, documents, spreadsheets or laptop screens. SAGE is cross-platform, community-driven, open-source visualization and collaboration middleware that utilizes shared national and international cyberinfrastructure for the advancement of scientific research and education.

Scalable Adaptive Graphics Environment (SAGE) Software for the Visualization of Large Data Sets on a Video Wall

NASA Astrophysics Data System (ADS)

Jedlovec, G.; Srikishen, J.; Edwards, R.; Cross, D.; Welch, J. D.; Smith, M. R.

2013-12-01

The use of collaborative scientific visualization systems for the analysis, visualization, and sharing of 'big data' available from new high resolution remote sensing satellite sensors or four-dimensional numerical model simulations is propelling the wider adoption of ultra-resolution tiled display walls interconnected by high speed networks. These systems require a globally connected and well-integrated operating environment that provides persistent visualization and collaboration services. This abstract and subsequent presentation describes a new collaborative visualization system installed for NASA's Short-term Prediction Research and Transition (SPoRT) program at Marshall Space Flight Center and its use for Earth science applications. The system consists of a 3 x 4 array of 1920 x 1080 pixel thin bezel video monitors mounted on a wall in a scientific collaboration lab. The monitors are physically and virtually integrated into a 14' x 7' for video display. The display of scientific data on the video wall is controlled by a single Alienware Aurora PC with a 2nd Generation Intel Core 4.1 GHz processor, 32 GB memory, and an AMD Fire Pro W600 video card with 6 mini display port connections. Six mini display-to-dual DVI cables are used to connect the 12 individual video monitors. The open source Scalable Adaptive Graphics Environment (SAGE) windowing and media control framework, running on top of the Ubuntu 12 Linux operating system, allows several users to simultaneously control the display and storage of high resolution still and moving graphics in a variety of formats, on tiled display walls of any size. The Ubuntu operating system supports the open source Scalable Adaptive Graphics Environment (SAGE) software which provides a common environment, or framework, enabling its users to access, display and share a variety of data-intensive information. This information can be digital-cinema animations, high-resolution images, high-definition video-teleconferences, presentation slides, documents, spreadsheets or laptop screens. SAGE is cross-platform, community-driven, open-source visualization and collaboration middleware that utilizes shared national and international cyberinfrastructure for the advancement of scientific research and education.

Patterns of cooperation: fairness and coordination in networks of interacting agents

NASA Astrophysics Data System (ADS)

Do, Anne-Ly; Rudolf, Lars; Gross, Thilo

2010-06-01

We study the self-assembly of a complex network of collaborations among self-interested agents. The agents can maintain different levels of cooperation with different partners. Further, they continuously, selectively and independently adapt the amount of resources allocated to each of their collaborations in order to maximize the obtained payoff. We show analytically that the system approaches a state in which the agents make identical investments, and links produce identical benefits. Despite this high degree of social coordination, some agents manage to secure privileged topological positions in the network, enabling them to extract high payoffs. Our analytical investigations provide a rationale for the emergence of unidirectional non-reciprocal collaborations and different responses to the withdrawal of a partner from an interaction that have been reported in the psychological literature.

SnapShot: Visualization to Propel Ice Hockey Analytics.

PubMed

Pileggi, H; Stolper, C D; Boyle, J M; Stasko, J T

2012-12-01

Sports analysts live in a world of dynamic games flattened into tables of numbers, divorced from the rinks, pitches, and courts where they were generated. Currently, these professional analysts use R, Stata, SAS, and other statistical software packages for uncovering insights from game data. Quantitative sports consultants seek a competitive advantage both for their clients and for themselves as analytics becomes increasingly valued by teams, clubs, and squads. In order for the information visualization community to support the members of this blossoming industry, it must recognize where and how visualization can enhance the existing analytical workflow. In this paper, we identify three primary stages of today's sports analyst's routine where visualization can be beneficially integrated: 1) exploring a dataspace; 2) sharing hypotheses with internal colleagues; and 3) communicating findings to stakeholders.Working closely with professional ice hockey analysts, we designed and built SnapShot, a system to integrate visualization into the hockey intelligence gathering process. SnapShot employs a variety of information visualization techniques to display shot data, yet given the importance of a specific hockey statistic, shot length, we introduce a technique, the radial heat map. Through a user study, we received encouraging feedback from several professional analysts, both independent consultants and professional team personnel.

Project UNITY: Cross Domain Visualization Collaboration

NASA Astrophysics Data System (ADS)

Moore, J.; Havig, P.

UNITY is an International Cooperative Research and Development (ICR&D) project between the United States and Great Britain under the Research and Development Projects (RDP) Memorandum of Agreement (MOA). UNITYs objectives are to develop and evaluate the operational concepts and requirements for undertaking combined operations: a) pursuant to the interests of mission partners, b) develop, experiment, and demonstrate, transitionable emergent technologies, capabilities, or concepts, which facilitate the sharing of information and products between mission partners, and c) identify and define additional emerging technologies that may need to be developed to support current and future military information sharing. Collaboration between coalition partners is essentially for accurate and timely decision making in the ever increasing nature and tempo of global security. The purpose for this project is to develop engineering solutions in order to further investigate the human factors issues that arise while sharing information in a collaborative environment where security is an issue. The biggest difference between existing available solutions are in the presentation and interaction with the interface on both ends of the collaboration in order to preserve the expressed intent of shared situation awareness while also enabling markups and content on one screen that the other collaborator does not see and vice versa. The UNITY project stresses collaboration differently than all known realtime collaboration software in production, aka groupware, on the market today. The tradition of What You See Is What I See (WYSIWIS) as in typical implementations of shared whiteboards simply do not address the need for local and private information to be displayed in context with shareable data. This paper addresses the concerns, problems, and some solutions for shared 3D visualization and 2D tabular visualizations which are explored and presented within the space situation awareness problem set.

CM-DataONE: A Framework for collaborative analysis of climate model output

NASA Astrophysics Data System (ADS)

Xu, Hao; Bai, Yuqi; Li, Sha; Dong, Wenhao; Huang, Wenyu; Xu, Shiming; Lin, Yanluan; Wang, Bin

2015-04-01

CM-DataONE is a distributed collaborative analysis framework for climate model data which aims to break through the data access barriers of increasing file size and to accelerate research process. As data size involved in project such as the fifth Coupled Model Intercomparison Project (CMIP5) has reached petabytes, conventional methods for analysis and diagnosis of model outputs have been rather time-consuming and redundant. CM-DataONE is developed for data publishers and researchers from relevant areas. It can enable easy access to distributed data and provide extensible analysis functions based on tools such as NCAR Command Language, NetCDF Operators (NCO) and Climate Data Operators (CDO). CM-DataONE can be easily installed, configured, and maintained. The main web application has two separate parts which communicate with each other through APIs based on HTTP protocol. The analytic server is designed to be installed in each data node while a data portal can be configured anywhere and connect to a nearest node. Functions such as data query, analytic task submission, status monitoring, visualization and product downloading are provided to end users by data portal. Data conform to CMIP5 Model Output Format in each peer node can be scanned by the server and mapped to a global information database. A scheduler included in the server is responsible for task decomposition, distribution and consolidation. Analysis functions are always executed where data locate. Analysis function package included in the server has provided commonly used functions such as EOF analysis, trend analysis and time series. Functions are coupled with data by XML descriptions and can be easily extended. Various types of results can be obtained by users for further studies. This framework has significantly decreased the amount of data to be transmitted and improved efficiency in model intercomparison jobs by supporting online analysis and multi-node collaboration. To end users, data query is therefore accelerated and the size of data to be downloaded is reduced. Methodology can be easily shared among scientists, avoiding unnecessary replication. Currently, a prototype of CM-DataONE has been deployed on two data nodes of Tsinghua University.

Towards a Web-Enabled Geovisualization and Analytics Platform for the Energy and Water Nexus

NASA Astrophysics Data System (ADS)

Sanyal, J.; Chandola, V.; Sorokine, A.; Allen, M.; Berres, A.; Pang, H.; Karthik, R.; Nugent, P.; McManamay, R.; Stewart, R.; Bhaduri, B. L.

2017-12-01

Interactive data analytics are playing an increasingly vital role in the generation of new, critical insights regarding the complex dynamics of the energy/water nexus (EWN) and its interactions with climate variability and change. Integration of impacts, adaptation, and vulnerability (IAV) science with emerging, and increasingly critical, data science capabilities offers a promising potential to meet the needs of the EWN community. To enable the exploration of pertinent research questions, a web-based geospatial visualization platform is being built that integrates a data analysis toolbox with advanced data fusion and data visualization capabilities to create a knowledge discovery framework for the EWN. The system, when fully built out, will offer several geospatial visualization capabilities including statistical visual analytics, clustering, principal-component analysis, dynamic time warping, support uncertainty visualization and the exploration of data provenance, as well as support machine learning discoveries to render diverse types of geospatial data and facilitate interactive analysis. Key components in the system architecture includes NASA's WebWorldWind, the Globus toolkit, postgresql, as well as other custom built software modules.

Visualization techniques for computer network defense

NASA Astrophysics Data System (ADS)

Beaver, Justin M.; Steed, Chad A.; Patton, Robert M.; Cui, Xiaohui; Schultz, Matthew

2011-06-01

Effective visual analysis of computer network defense (CND) information is challenging due to the volume and complexity of both the raw and analyzed network data. A typical CND is comprised of multiple niche intrusion detection tools, each of which performs network data analysis and produces a unique alerting output. The state-of-the-practice in the situational awareness of CND data is the prevalent use of custom-developed scripts by Information Technology (IT) professionals to retrieve, organize, and understand potential threat events. We propose a new visual analytics framework, called the Oak Ridge Cyber Analytics (ORCA) system, for CND data that allows an operator to interact with all detection tool outputs simultaneously. Aggregated alert events are presented in multiple coordinated views with timeline, cluster, and swarm model analysis displays. These displays are complemented with both supervised and semi-supervised machine learning classifiers. The intent of the visual analytics framework is to improve CND situational awareness, to enable an analyst to quickly navigate and analyze thousands of detected events, and to combine sophisticated data analysis techniques with interactive visualization such that patterns of anomalous activities may be more easily identified and investigated.

Using a commodity high-definition television for collaborative structural biology

PubMed Central

Yennamalli, Ragothaman; Arangarasan, Raj; Bryden, Aaron; Gleicher, Michael; Phillips, George N.

2014-01-01

Visualization of protein structures using stereoscopic systems is frequently needed by structural biologists working to understand a protein’s structure–function relationships. Often several scientists are working as a team and need simultaneous interaction with each other and the graphics representations. Most existing molecular visualization tools support single-user tasks, which are not suitable for a collaborative group. Expensive caves, domes or geowalls have been developed, but the availability and low cost of high-definition televisions (HDTVs) and game controllers in the commodity entertainment market provide an economically attractive option to achieve a collaborative environment. This paper describes a low-cost environment, using standard consumer game controllers and commercially available stereoscopic HDTV monitors with appropriate signal converters for structural biology collaborations employing existing binary distributions of commonly used software packages like Coot, PyMOL, Chimera, VMD, O, Olex2 and others. PMID:24904249

Overview of Human-Centric Space Situational Awareness Science and Technology

DTIC Science & Technology

2012-09-01

AGI), the developers of Satellite Tool Kit ( STK ), has provided demonstrations of innovative SSA visualization concepts that take advantage of the...needs inherent with SSA. RH has conducted CTAs and developed work-centered human-computer interfaces, visualizations , and collaboration technologies...all end users. RH’s Battlespace Visualization Branch researches methods to exploit the visual channel primarily to improve decision making and

GeoBuilder: a geometric algorithm visualization and debugging system for 2D and 3D geometric computing.

PubMed

Wei, Jyh-Da; Tsai, Ming-Hung; Lee, Gen-Cher; Huang, Jeng-Hung; Lee, Der-Tsai

2009-01-01

Algorithm visualization is a unique research topic that integrates engineering skills such as computer graphics, system programming, database management, computer networks, etc., to facilitate algorithmic researchers in testing their ideas, demonstrating new findings, and teaching algorithm design in the classroom. Within the broad applications of algorithm visualization, there still remain performance issues that deserve further research, e.g., system portability, collaboration capability, and animation effect in 3D environments. Using modern technologies of Java programming, we develop an algorithm visualization and debugging system, dubbed GeoBuilder, for geometric computing. The GeoBuilder system features Java's promising portability, engagement of collaboration in algorithm development, and automatic camera positioning for tracking 3D geometric objects. In this paper, we describe the design of the GeoBuilder system and demonstrate its applications.

How Can Visual Analytics Assist Investigative Analysis? Design Implications from an Evaluation.

PubMed

Youn-Ah Kang; Görg, Carsten; Stasko, John

2011-05-01

Despite the growing number of systems providing visual analytic support for investigative analysis, few empirical studies of the potential benefits of such systems have been conducted, particularly controlled, comparative evaluations. Determining how such systems foster insight and sensemaking is important for their continued growth and study, however. Furthermore, studies that identify how people use such systems and why they benefit (or not) can help inform the design of new systems in this area. We conducted an evaluation of the visual analytics system Jigsaw employed in a small investigative sensemaking exercise, and compared its use to three other more traditional methods of analysis. Sixteen participants performed a simulated intelligence analysis task under one of the four conditions. Experimental results suggest that Jigsaw assisted participants to analyze the data and identify an embedded threat. We describe different analysis strategies used by study participants and how computational support (or the lack thereof) influenced the strategies. We then illustrate several characteristics of the sensemaking process identified in the study and provide design implications for investigative analysis tools based thereon. We conclude with recommendations on metrics and techniques for evaluating visual analytics systems for investigative analysis.

A Paper-Based Electrochromic Array for Visualized Electrochemical Sensing.

PubMed

Zhang, Fengling; Cai, Tianyi; Ma, Liang; Zhan, Liyuan; Liu, Hong

2017-01-31

We report a battery-powered, paper-based electrochromic array for visualized electrochemical sensing. The paper-based sensing system consists of six parallel electrochemical cells, which are powered by an aluminum-air battery. Each single electrochemical cell uses a Prussian Blue spot electrodeposited on an indium-doped tin oxide thin film as the electrochromic indicator. Each electrochemical cell is preloaded with increasing amounts of analyte. The sample activates the battery for the sensing. Both the preloaded analyte and the analyte in the sample initiate the color change of Prussian Blue to Prussian White. With a reaction time of 60 s, the number of electrochemical cells with complete color changes is correlated to the concentration of analyte in the sample. As a proof-of-concept analyte, lactic acid was detected semi-quantitatively using the naked eye.

Insight solutions are correct more often than analytic solutions

PubMed Central

Salvi, Carola; Bricolo, Emanuela; Kounios, John; Bowden, Edward; Beeman, Mark

2016-01-01

How accurate are insights compared to analytical solutions? In four experiments, we investigated how participants’ solving strategies influenced their solution accuracies across different types of problems, including one that was linguistic, one that was visual and two that were mixed visual-linguistic. In each experiment, participants’ self-judged insight solutions were, on average, more accurate than their analytic ones. We hypothesised that insight solutions have superior accuracy because they emerge into consciousness in an all-or-nothing fashion when the unconscious solving process is complete, whereas analytic solutions can be guesses based on conscious, prematurely terminated, processing. This hypothesis is supported by the finding that participants’ analytic solutions included relatively more incorrect responses (i.e., errors of commission) than timeouts (i.e., errors of omission) compared to their insight responses. PMID:27667960

Delving into Teacher Collaboration: Untangling Problems and Solutions for Leadership

ERIC Educational Resources Information Center

Gates, Gordon; Robinson, Sharon

2009-01-01

This article offers description and interpretation for understanding the exercise of leadership in teacher collaboration. Data gathered in two urban high schools through observations and interviews were coded and categorized following Miles and Huberman's modified analytic induction technique. The analysis contributes to emerging theory on…

Structure and Management of European R&D Projects: A View from Industrial Liaison Organizations

ERIC Educational Resources Information Center

Arranz, N.; de Arroyabe, J. C. Fdez.

2009-01-01

Collaboration between economic agents, especially in technological areas, is characterized by ambiguity in terminology, multiple analytical approaches, a diversity of objectives and multiple organizational forms, among which the network constitutes the most important example of "common organization" in international collaboration. This…

Review: visual analytics of climate networks

NASA Astrophysics Data System (ADS)

Nocke, T.; Buschmann, S.; Donges, J. F.; Marwan, N.; Schulz, H.-J.; Tominski, C.

2015-09-01

Network analysis has become an important approach in studying complex spatiotemporal behaviour within geophysical observation and simulation data. This new field produces increasing numbers of large geo-referenced networks to be analysed. Particular focus lies currently on the network analysis of the complex statistical interrelationship structure within climatological fields. The standard procedure for such network analyses is the extraction of network measures in combination with static standard visualisation methods. Existing interactive visualisation methods and tools for geo-referenced network exploration are often either not known to the analyst or their potential is not fully exploited. To fill this gap, we illustrate how interactive visual analytics methods in combination with geovisualisation can be tailored for visual climate network investigation. Therefore, the paper provides a problem analysis relating the multiple visualisation challenges to a survey undertaken with network analysts from the research fields of climate and complex systems science. Then, as an overview for the interested practitioner, we review the state-of-the-art in climate network visualisation and provide an overview of existing tools. As a further contribution, we introduce the visual network analytics tools CGV and GTX, providing tailored solutions for climate network analysis, including alternative geographic projections, edge bundling, and 3-D network support. Using these tools, the paper illustrates the application potentials of visual analytics for climate networks based on several use cases including examples from global, regional, and multi-layered climate networks.

Review: visual analytics of climate networks

NASA Astrophysics Data System (ADS)

Nocke, T.; Buschmann, S.; Donges, J. F.; Marwan, N.; Schulz, H.-J.; Tominski, C.

2015-04-01

Network analysis has become an important approach in studying complex spatiotemporal behaviour within geophysical observation and simulation data. This new field produces increasing amounts of large geo-referenced networks to be analysed. Particular focus lies currently on the network analysis of the complex statistical interrelationship structure within climatological fields. The standard procedure for such network analyses is the extraction of network measures in combination with static standard visualisation methods. Existing interactive visualisation methods and tools for geo-referenced network exploration are often either not known to the analyst or their potential is not fully exploited. To fill this gap, we illustrate how interactive visual analytics methods in combination with geovisualisation can be tailored for visual climate network investigation. Therefore, the paper provides a problem analysis, relating the multiple visualisation challenges with a survey undertaken with network analysts from the research fields of climate and complex systems science. Then, as an overview for the interested practitioner, we review the state-of-the-art in climate network visualisation and provide an overview of existing tools. As a further contribution, we introduce the visual network analytics tools CGV and GTX, providing tailored solutions for climate network analysis, including alternative geographic projections, edge bundling, and 3-D network support. Using these tools, the paper illustrates the application potentials of visual analytics for climate networks based on several use cases including examples from global, regional, and multi-layered climate networks.

Reusable Client-Side JavaScript Modules for Immersive Web-Based Real-Time Collaborative Neuroimage Visualization.

PubMed

Bernal-Rusiel, Jorge L; Rannou, Nicolas; Gollub, Randy L; Pieper, Steve; Murphy, Shawn; Robertson, Richard; Grant, Patricia E; Pienaar, Rudolph

2017-01-01

In this paper we present a web-based software solution to the problem of implementing real-time collaborative neuroimage visualization. In both clinical and research settings, simple and powerful access to imaging technologies across multiple devices is becoming increasingly useful. Prior technical solutions have used a server-side rendering and push-to-client model wherein only the server has the full image dataset. We propose a rich client solution in which each client has all the data and uses the Google Drive Realtime API for state synchronization. We have developed a small set of reusable client-side object-oriented JavaScript modules that make use of the XTK toolkit, a popular open-source JavaScript library also developed by our team, for the in-browser rendering and visualization of brain image volumes. Efficient realtime communication among the remote instances is achieved by using just a small JSON object, comprising a representation of the XTK image renderers' state, as the Google Drive Realtime collaborative data model. The developed open-source JavaScript modules have already been instantiated in a web-app called MedView , a distributed collaborative neuroimage visualization application that is delivered to the users over the web without requiring the installation of any extra software or browser plugin. This responsive application allows multiple physically distant physicians or researchers to cooperate in real time to reach a diagnosis or scientific conclusion. It also serves as a proof of concept for the capabilities of the presented technological solution.

Framework for Deploying a Virtualized Computing Environment for Collaborative and Secure Data Analytics

PubMed Central

Meyer, Adrian; Green, Laura; Faulk, Ciearro; Galla, Stephen; Meyer, Anne-Marie

2016-01-01

Introduction: Large amounts of health data generated by a wide range of health care applications across a variety of systems have the potential to offer valuable insight into populations and health care systems, but robust and secure computing and analytic systems are required to leverage this information. Framework: We discuss our experiences deploying a Secure Data Analysis Platform (SeDAP), and provide a framework to plan, build and deploy a virtual desktop infrastructure (VDI) to enable innovation, collaboration and operate within academic funding structures. It outlines 6 core components: Security, Ease of Access, Performance, Cost, Tools, and Training. Conclusion: A platform like SeDAP is not simply successful through technical excellence and performance. It’s adoption is dependent on a collaborative environment where researchers and users plan and evaluate the requirements of all aspects. PMID:27683665

An Experimental Introduction to Interlaboratory Exercises in Analytical Chemistry

ERIC Educational Resources Information Center

Puignou, L.; Llaurado, M.

2005-01-01

An experimental exercise on analytical proficiency studies in collaborative trials is proposed. This practical provides students in advanced undergraduate courses in chemistry, pharmacy, and biochemistry, with the opportunity to improve their quality assurance skills. It involves an environmental analysis, determining the concentration of a…

VIGOR: Interactive Visual Exploration of Graph Query Results.

PubMed

Pienta, Robert; Hohman, Fred; Endert, Alex; Tamersoy, Acar; Roundy, Kevin; Gates, Chris; Navathe, Shamkant; Chau, Duen Horng

2018-01-01

Finding patterns in graphs has become a vital challenge in many domains from biological systems, network security, to finance (e.g., finding money laundering rings of bankers and business owners). While there is significant interest in graph databases and querying techniques, less research has focused on helping analysts make sense of underlying patterns within a group of subgraph results. Visualizing graph query results is challenging, requiring effective summarization of a large number of subgraphs, each having potentially shared node-values, rich node features, and flexible structure across queries. We present VIGOR, a novel interactive visual analytics system, for exploring and making sense of query results. VIGOR uses multiple coordinated views, leveraging different data representations and organizations to streamline analysts sensemaking process. VIGOR contributes: (1) an exemplar-based interaction technique, where an analyst starts with a specific result and relaxes constraints to find other similar results or starts with only the structure (i.e., without node value constraints), and adds constraints to narrow in on specific results; and (2) a novel feature-aware subgraph result summarization. Through a collaboration with Symantec, we demonstrate how VIGOR helps tackle real-world problems through the discovery of security blindspots in a cybersecurity dataset with over 11,000 incidents. We also evaluate VIGOR with a within-subjects study, demonstrating VIGOR's ease of use over a leading graph database management system, and its ability to help analysts understand their results at higher speed and make fewer errors.

A Cross-Cultural Collaboration: Using Visual Culture for the Creation of a Socially Relevant Mural in Mexico

ERIC Educational Resources Information Center

Hubbard, Kathy

2010-01-01

In this article, the author describes how high school and university students in Georgia and members of a small weaving pueblo in Oaxaca, Mexico, collaborated in designing and creating a mural in the central market ("mercado") of the pueblo. A number of lessons emerged from this multi-cultural collaboration. First they learned that using…

Open Access to Multi-Domain Collaborative Analysis of Geospatial Data Through the Internet

NASA Astrophysics Data System (ADS)

Turner, A.

2009-12-01

The internet has provided us with a high bandwidth, low latency, globally connected network in which to rapidly share realtime data from sensors, reports, and imagery. In addition, the availability of this data is even easier to obtain, consume and analyze. Another aspect of the internet has been the increased approachability of complex systems through lightweight interfaces - with additional complex services able to provide more advanced connections into data services. These analyses and discussions have primarily been siloed within single domains, or kept out of the reach of amateur scientists and interested citizens. However, through more open access to analytical tools and data, experts can collaborate with citizens to gather information, provide interfaces for experimenting and querying results, and help make improved insights and feedback for further investigation. For example, farmers in Uganda are able to use their mobile phones to query, analyze, and be alerted to banana crop disease based on agriculture and climatological data. In the U.S., local groups use online social media sharing sites to gather data on storm-water runoff and stream siltation in order to alert wardens and environmental agencies. This talk will present various web-based geospatial visualization and analysis techniques and tools such as Google Earth and GeoCommons that have emerged that provide for a collaboration between experts of various domains as well as between experts, government, and citizen scientists. Through increased communication and the sharing of data and tools, it is possible to gain broad insight and development of joint, working solutions to a variety of difficult scientific and policy related questions.

Using a Collaborative Critiquing Technique to Develop Chemistry Students' Technical Writing Skills

ERIC Educational Resources Information Center

Carr, Jeremy M.

2013-01-01

The technique, termed "collaborative critiquing", was developed to teach fundamental technical writing skills to analytical chemistry students for the preparation of laboratory reports. This exercise, which can be completed prior to peer-review activities, is novel, highly interactive, and allows students to take responsibility for their…

Developing Visual Literacy: Historical and Manipulated Photography in the Social Studies Classroom

ERIC Educational Resources Information Center

Cruz, Bárbara C.; Ellerbrock, Cheryl R.

2015-01-01

The importance of visual literacy development is demonstrated using social studies examples from an innovative, collaborative arts program. Discussion of the Visual Thinking Strategies approach, connections to the Common Core State Standards, prompts for higher-order critical thinking, and the application of historical and social science ideas in…

Belle2VR: A Virtual-Reality Visualization of Subatomic Particle Physics in the Belle II Experiment.

PubMed

Duer, Zach; Piilonen, Leo; Glasson, George

2018-05-01

Belle2VR is an interactive virtual-reality visualization of subatomic particle physics, designed by an interdisciplinary team as an educational tool for learning about and exploring subatomic particle collisions. This article describes the tool, discusses visualization design decisions, and outlines our process for collaborative development.

Leveraging multidisciplinarity in a visual analytics graduate course.

PubMed

Elmqvist, Niklas; Ebert, David S

2012-01-01

Demand is growing in engineering, business, science, research, and industry for students with visual analytics expertise. However, teaching VA is challenging owing to the multidisciplinary nature of the topic, students' diverse backgrounds, and the corresponding requirements for instructors. This article reports best practices from a VA graduate course at Purdue University, where instructors leveraged these challenges to their advantage instead of trying to mitigate them.

Shopping For Danger: E-commerce techniques applied to collaboration in cyber security

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

Bruce, Joseph R.; Fink, Glenn A.

Collaboration among cyber security analysts is essential to a successful protection strategy on the Internet today, but it is uncommonly practiced or encouraged in operating environments. Barriers to productive collaboration often include data sensitivity, time and effort to communicate, institutional policy, and protection of domain knowledge. We propose an ambient collaboration framework, Vulcan, designed to remove the barriers of time and effort and mitigate the others. Vulcan automated data collection, collaborative filtering, and asynchronous dissemination, eliminating the effort implied by explicit collaboration among peers. We instrumented two analytic applications and performed a mock analysis session to build a dataset andmore » test the output of the system.« less

Information-Pooling Bias in Collaborative Security Incident Correlation Analysis.

PubMed

Rajivan, Prashanth; Cooke, Nancy J

2018-03-01

Incident correlation is a vital step in the cybersecurity threat detection process. This article presents research on the effect of group-level information-pooling bias on collaborative incident correlation analysis in a synthetic task environment. Past research has shown that uneven information distribution biases people to share information that is known to most team members and prevents them from sharing any unique information available with them. The effect of such biases on security team collaborations are largely unknown. Thirty 3-person teams performed two threat detection missions involving information sharing and correlating security incidents. Incidents were predistributed to each person in the team based on the hidden profile paradigm. Participant teams, randomly assigned to three experimental groups, used different collaboration aids during Mission 2. Communication analysis revealed that participant teams were 3 times more likely to discuss security incidents commonly known to the majority. Unaided team collaboration was inefficient in finding associations between security incidents uniquely available to each member of the team. Visualizations that augment perceptual processing and recognition memory were found to mitigate the bias. The data suggest that (a) security analyst teams, when conducting collaborative correlation analysis, could be inefficient in pooling unique information from their peers; (b) employing off-the-shelf collaboration tools in cybersecurity defense environments is inadequate; and (c) collaborative security visualization tools developed considering the human cognitive limitations of security analysts is necessary. Potential applications of this research include development of team training procedures and collaboration tool development for security analysts.

Analytical Thinking, Analytical Action: Using Prelab Video Demonstrations and e-Quizzes to Improve Undergraduate Preparedness for Analytical Chemistry Practical Classes

ERIC Educational Resources Information Center

Jolley, Dianne F.; Wilson, Stephen R.; Kelso, Celine; O'Brien, Glennys; Mason, Claire E.

2016-01-01

This project utilizes visual and critical thinking approaches to develop a higher-education synergistic prelab training program for a large second-year undergraduate analytical chemistry class, directing more of the cognitive learning to the prelab phase. This enabled students to engage in more analytical thinking prior to engaging in the…

Constraint-Referenced Analytics of Algebra Learning

ERIC Educational Resources Information Center

Sutherland, Scot M.; White, Tobin F.

2016-01-01

The development of the constraint-referenced analytics tool for monitoring algebra learning activities presented here came from the desire to firstly, take a more quantitative look at student responses in collaborative algebra activities, and secondly, to situate those activities in a more traditional introductory algebra setting focusing on…

Understanding Digital Note-Taking Practice for Visualization.

PubMed

Willett, Wesley; Goffin, Pascal; Isenberg, Petra

2015-05-13

We present results and design implications from a study of digital note-taking practice to examine how visualization can support revisitation, reflection, and collaboration around notes. As digital notebooks become common forms of external memory, keeping track of volumes of content is increasingly difficult. Information visualization tools can help give note-takers an overview of their content and allow them to explore diverse sets of notes, find and organize related content, and compare their notes with their collaborators. To ground the design of such tools, we conducted a detailed mixed-methods study of digital note-taking practice. We identify a variety of different editing, organization, and sharing methods used by digital note-takers, many of which result in notes becoming "lost in the pile''. These findings form the basis for our design considerations that examine how visualization can support the revisitation, organization, and sharing of digital notes.

The Matsu Wheel: A Cloud-Based Framework for Efficient Analysis and Reanalysis of Earth Satellite Imagery

NASA Technical Reports Server (NTRS)

Patterson, Maria T.; Anderson, Nicholas; Bennett, Collin; Bruggemann, Jacob; Grossman, Robert L.; Handy, Matthew; Ly, Vuong; Mandl, Daniel J.; Pederson, Shane; Pivarski, James;

Potential of Cognitive Computing and Cognitive Systems

NASA Astrophysics Data System (ADS)

Noor, Ahmed K.

2015-01-01

Cognitive computing and cognitive technologies are game changers for future engineering systems, as well as for engineering practice and training. They are major drivers for knowledge automation work, and the creation of cognitive products with higher levels of intelligence than current smart products. This paper gives a brief review of cognitive computing and some of the cognitive engineering systems activities. The potential of cognitive technologies is outlined, along with a brief description of future cognitive environments, incorporating cognitive assistants - specialized proactive intelligent software agents designed to follow and interact with humans and other cognitive assistants across the environments. The cognitive assistants engage, individually or collectively, with humans through a combination of adaptive multimodal interfaces, and advanced visualization and navigation techniques. The realization of future cognitive environments requires the development of a cognitive innovation ecosystem for the engineering workforce. The continuously expanding major components of the ecosystem include integrated knowledge discovery and exploitation facilities (incorporating predictive and prescriptive big data analytics); novel cognitive modeling and visual simulation facilities; cognitive multimodal interfaces; and cognitive mobile and wearable devices. The ecosystem will provide timely, engaging, personalized / collaborative, learning and effective decision making. It will stimulate creativity and innovation, and prepare the participants to work in future cognitive enterprises and develop new cognitive products of increasing complexity. http://www.aee.odu.edu/cognitivecomp

A Visual Analytics Approach for Station-Based Air Quality Data

PubMed Central

Du, Yi; Ma, Cuixia; Wu, Chao; Xu, Xiaowei; Guo, Yike; Zhou, Yuanchun; Li, Jianhui

2016-01-01

With the deployment of multi-modality and large-scale sensor networks for monitoring air quality, we are now able to collect large and multi-dimensional spatio-temporal datasets. For these sensed data, we present a comprehensive visual analysis approach for air quality analysis. This approach integrates several visual methods, such as map-based views, calendar views, and trends views, to assist the analysis. Among those visual methods, map-based visual methods are used to display the locations of interest, and the calendar and the trends views are used to discover the linear and periodical patterns. The system also provides various interaction tools to combine the map-based visualization, trends view, calendar view and multi-dimensional view. In addition, we propose a self-adaptive calendar-based controller that can flexibly adapt the changes of data size and granularity in trends view. Such a visual analytics system would facilitate big-data analysis in real applications, especially for decision making support. PMID:28029117

A Visual Analytics Approach for Station-Based Air Quality Data.

PubMed

Du, Yi; Ma, Cuixia; Wu, Chao; Xu, Xiaowei; Guo, Yike; Zhou, Yuanchun; Li, Jianhui

2016-12-24

With the deployment of multi-modality and large-scale sensor networks for monitoring air quality, we are now able to collect large and multi-dimensional spatio-temporal datasets. For these sensed data, we present a comprehensive visual analysis approach for air quality analysis. This approach integrates several visual methods, such as map-based views, calendar views, and trends views, to assist the analysis. Among those visual methods, map-based visual methods are used to display the locations of interest, and the calendar and the trends views are used to discover the linear and periodical patterns. The system also provides various interaction tools to combine the map-based visualization, trends view, calendar view and multi-dimensional view. In addition, we propose a self-adaptive calendar-based controller that can flexibly adapt the changes of data size and granularity in trends view. Such a visual analytics system would facilitate big-data analysis in real applications, especially for decision making support.

Visualization Techniques for Computer Network Defense

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

Beaver, Justin M; Steed, Chad A; Patton, Robert M

2011-01-01

Effective visual analysis of computer network defense (CND) information is challenging due to the volume and complexity of both the raw and analyzed network data. A typical CND is comprised of multiple niche intrusion detection tools, each of which performs network data analysis and produces a unique alerting output. The state-of-the-practice in the situational awareness of CND data is the prevalent use of custom-developed scripts by Information Technology (IT) professionals to retrieve, organize, and understand potential threat events. We propose a new visual analytics framework, called the Oak Ridge Cyber Analytics (ORCA) system, for CND data that allows an operatormore » to interact with all detection tool outputs simultaneously. Aggregated alert events are presented in multiple coordinated views with timeline, cluster, and swarm model analysis displays. These displays are complemented with both supervised and semi-supervised machine learning classifiers. The intent of the visual analytics framework is to improve CND situational awareness, to enable an analyst to quickly navigate and analyze thousands of detected events, and to combine sophisticated data analysis techniques with interactive visualization such that patterns of anomalous activities may be more easily identified and investigated.« less

TopicLens: Efficient Multi-Level Visual Topic Exploration of Large-Scale Document Collections.

PubMed

Kim, Minjeong; Kang, Kyeongpil; Park, Deokgun; Choo, Jaegul; Elmqvist, Niklas

2017-01-01

Topic modeling, which reveals underlying topics of a document corpus, has been actively adopted in visual analytics for large-scale document collections. However, due to its significant processing time and non-interactive nature, topic modeling has so far not been tightly integrated into a visual analytics workflow. Instead, most such systems are limited to utilizing a fixed, initial set of topics. Motivated by this gap in the literature, we propose a novel interaction technique called TopicLens that allows a user to dynamically explore data through a lens interface where topic modeling and the corresponding 2D embedding are efficiently computed on the fly. To support this interaction in real time while maintaining view consistency, we propose a novel efficient topic modeling method and a semi-supervised 2D embedding algorithm. Our work is based on improving state-of-the-art methods such as nonnegative matrix factorization and t-distributed stochastic neighbor embedding. Furthermore, we have built a web-based visual analytics system integrated with TopicLens. We use this system to measure the performance and the visualization quality of our proposed methods. We provide several scenarios showcasing the capability of TopicLens using real-world datasets.

gQTL: A Web Application for QTL Analysis Using the Collaborative Cross Mouse Genetic Reference Population.

PubMed

Konganti, Kranti; Ehrlich, Andre; Rusyn, Ivan; Threadgill, David W

2018-06-07

Multi-parental recombinant inbred populations, such as the Collaborative Cross (CC) mouse genetic reference population, are increasingly being used for analysis of quantitative trait loci (QTL). However specialized analytic software for these complex populations is typically built in R that works only on command-line, which limits the utility of these powerful resources for many users. To overcome analytic limitations, we developed gQTL, a web accessible, simple graphical user interface application based on the DOQTL platform in R to perform QTL mapping using data from CC mice. Copyright © 2018, G3: Genes, Genomes, Genetics.

The oral-systemic connection: role of salivary diagnostics

NASA Astrophysics Data System (ADS)

Malamud, Daniel

2013-05-01

Utilizing saliva instead of blood for diagnosis of both local and systemic health is a rapidly emerging field. Recognition of oral-systemic interrelationships for many diseases has fostered collaborations between medicine and dentistry, and many of these collaborations rely on salivary diagnostics. The oral cavity is easily accessed and contains most of the analytes present in blood. Saliva and mucosal transudate are generally utilized for oral diagnostics, but gingival crevicular fluid, buccal swabs, dental plaque and volatiles may also be useful depending on the analyte being studied. Examples of point-of-care devices capable of detecting HIV, TB, and Malaria targets are being developed and discussed in this overview.

A results-based process for evaluation of diverse visual analytics tools

NASA Astrophysics Data System (ADS)

Rubin, Gary; Berger, David H.

2013-05-01

With the pervasiveness of still and full-motion imagery in commercial and military applications, the need to ingest and analyze these media has grown rapidly in recent years. Additionally, video hosting and live camera websites provide a near real-time view of our changing world with unprecedented spatial coverage. To take advantage of these controlled and crowd-sourced opportunities, sophisticated visual analytics (VA) tools are required to accurately and efficiently convert raw imagery into usable information. Whether investing in VA products or evaluating algorithms for potential development, it is important for stakeholders to understand the capabilities and limitations of visual analytics tools. Visual analytics algorithms are being applied to problems related to Intelligence, Surveillance, and Reconnaissance (ISR), facility security, and public safety monitoring, to name a few. The diversity of requirements means that a onesize- fits-all approach to performance assessment will not work. We present a process for evaluating the efficacy of algorithms in real-world conditions, thereby allowing users and developers of video analytics software to understand software capabilities and identify potential shortcomings. The results-based approach described in this paper uses an analysis of end-user requirements and Concept of Operations (CONOPS) to define Measures of Effectiveness (MOEs), test data requirements, and evaluation strategies. We define metrics that individually do not fully characterize a system, but when used together, are a powerful way to reveal both strengths and weaknesses. We provide examples of data products, such as heatmaps, performance maps, detection timelines, and rank-based probability-of-detection curves.

Analytical Essay Writing: A New Activity Introduced to a Traditional Curriculum

ERIC Educational Resources Information Center

Kommalage, Mahinda

2012-01-01

Medical students following a traditional curriculum get few opportunities to engage in activities such as a literature search, scientific writing, and active and collaborative learning. An analytical essay writing activity (AEWA) in physiology was introduced to first-year students. Each student prepared an essay incorporating new research findings…

SOMFlow: Guided Exploratory Cluster Analysis with Self-Organizing Maps and Analytic Provenance.

PubMed

Sacha, Dominik; Kraus, Matthias; Bernard, Jurgen; Behrisch, Michael; Schreck, Tobias; Asano, Yuki; Keim, Daniel A

2018-01-01

Clustering is a core building block for data analysis, aiming to extract otherwise hidden structures and relations from raw datasets, such as particular groups that can be effectively related, compared, and interpreted. A plethora of visual-interactive cluster analysis techniques has been proposed to date, however, arriving at useful clusterings often requires several rounds of user interactions to fine-tune the data preprocessing and algorithms. We present a multi-stage Visual Analytics (VA) approach for iterative cluster refinement together with an implementation (SOMFlow) that uses Self-Organizing Maps (SOM) to analyze time series data. It supports exploration by offering the analyst a visual platform to analyze intermediate results, adapt the underlying computations, iteratively partition the data, and to reflect previous analytical activities. The history of previous decisions is explicitly visualized within a flow graph, allowing to compare earlier cluster refinements and to explore relations. We further leverage quality and interestingness measures to guide the analyst in the discovery of useful patterns, relations, and data partitions. We conducted two pair analytics experiments together with a subject matter expert in speech intonation research to demonstrate that the approach is effective for interactive data analysis, supporting enhanced understanding of clustering results as well as the interactive process itself.

Fast 3D Net Expeditions: Tools for Effective Scientific Collaboration on the World Wide Web

NASA Technical Reports Server (NTRS)

Watson, Val; Chancellor, Marisa K. (Technical Monitor)

1996-01-01

Two new technologies, the FASTexpedition and Remote FAST, have been developed that provide remote, 3D (three dimensional), high resolution, dynamic, interactive viewing of scientific data. The FASTexpedition permits one to access scientific data from the World Wide Web, take guided expeditions through the data, and continue with self controlled expeditions through the data. Remote FAST permits collaborators at remote sites to simultaneously view an analysis of scientific data being controlled by one of the collaborators. Control can be transferred between sites. These technologies are now being used for remote collaboration in joint university, industry, and NASA projects. Also, NASA Ames Research Center has initiated a project to make scientific data and guided expeditions through the data available as FASTexpeditions on the World Wide Web for educational purposes. Previously, remote visualization of dynamic data was done using video format (transmitting pixel information) such as video conferencing or MPEG (Motion Picture Expert Group) movies on the Internet. The concept for this new technology is to send the raw data (e.g., grids, vectors, and scalars) along with viewing scripts over the Internet and have the pixels generated by a visualization tool running on the viewers local workstation. The visualization tool that is currently used is FAST (Flow Analysis Software Toolkit). The advantages of this new technology over using video format are: (1) The visual is much higher in resolution (1280x1024 pixels with 24 bits of color) than typical video format transmitted over the network. (2) The form of the visualization can be controlled interactively (because the viewer is interactively controlling the visualization tool running on his workstation). (3) A rich variety of guided expeditions through the data can be included easily. (4) A capability is provided for other sites to see a visual analysis of one site as the analysis is interactively performed. Control of the analysis can be passed from site to site. (5) The scenes can be viewed in 3D using stereo vision. (6) The network bandwidth for the visualization using this new technology is much smaller than when using video format. (The measured peak bandwidth used was 1 Kbit/sec whereas the measured bandwidth for a small video picture was 500 Kbits/sec.) This talk will illustrate the use of these new technologies and present a proposal for using these technologies to improve science education.

Desktop Cloud Visualization: the new technology to remote access 3D interactive applications in the Cloud.

PubMed

Torterolo, Livia; Ruffino, Francesco

2012-01-01

In the proposed demonstration we will present DCV (Desktop Cloud Visualization): a unique technology that allows users to remote access 2D and 3D interactive applications over a standard network. This allows geographically dispersed doctors work collaboratively and to acquire anatomical or pathological images and visualize them for further investigations.

Visual Thinking Routines: A Mixed Methods Approach Applied to Student Teachers at the American University in Dubai

ERIC Educational Resources Information Center

Gholam, Alain

2017-01-01

Visual thinking routines are principles based on several theories, approaches, and strategies. Such routines promote thinking skills, call for collaboration and sharing of ideas, and above all, make thinking and learning visible. Visual thinking routines were implemented in the teaching methodology graduate course at the American University in…

Collaboration in Visual Culture Learning Communities: Towards a Synergy of Individual and Collective Creative Practice

ERIC Educational Resources Information Center

Karpati, Andrea; Freedman, Kerry; Castro, Juan Carlos; Kallio-Tavin, Mira; Heijnen, Emiel

2017-01-01

A visual culture learning community (VCLC) is an adolescent or young adult group engaged in expression and creation outside of formal institutions and without adult supervision. In the framework of an international, comparative research project executed between 2010 and 2014, members of a variety of eight self-initiated visual culture groups…

Ingredients to Successful Students Presentations: It's More Than Just a Sum of Raw Materials.

ERIC Educational Resources Information Center

Kerns, H. Dan; Johnson, Nial

Recognizing the decline in student visual communication skills, faculty from different disciplines collaborated in the design of a visual literacy course. The visual literacy skills developed in the course are that students learn in the following ways: (1) through faculty presentation and demonstration of the various tools available; (2) with…

Risky Business or Sharing the Load?--Social Flow in Collaborative Mobile Learning

ERIC Educational Resources Information Center

Ryu, Hokyoung; Parsons, David

2012-01-01

Mobile learning has been built upon the premise that we can transform traditional classroom or computer-based learning activities into a more ubiquitous and connected form of learning. Tentative outcomes from this assertion have been witnessed in many collaborative learning activities, but few analytic observations on what triggers this…

OVERVIEW OF AN INTERLABORATORY COLLABORATION ON EVALUATING THE EFFECTS OF MODEL HEPATOTOXICANTS ON HEPATIC GENE EXPRESSION

EPA Science Inventory

Evaluating the Effects of Methapyrilene and Clofibrate on Hepatic Gene Expression: A Collaboration Between Laboratories and a Comparison of Platform and Analytical Approaches

Roger G. Ulrich1, John C. Rockett2, G. Gordon Gibson3 and Syril Pettit4

1 Rosetta Inpharmat...

Reusable Client-Side JavaScript Modules for Immersive Web-Based Real-Time Collaborative Neuroimage Visualization

PubMed Central

Bernal-Rusiel, Jorge L.; Rannou, Nicolas; Gollub, Randy L.; Pieper, Steve; Murphy, Shawn; Robertson, Richard; Grant, Patricia E.; Pienaar, Rudolph

2017-01-01

In this paper we present a web-based software solution to the problem of implementing real-time collaborative neuroimage visualization. In both clinical and research settings, simple and powerful access to imaging technologies across multiple devices is becoming increasingly useful. Prior technical solutions have used a server-side rendering and push-to-client model wherein only the server has the full image dataset. We propose a rich client solution in which each client has all the data and uses the Google Drive Realtime API for state synchronization. We have developed a small set of reusable client-side object-oriented JavaScript modules that make use of the XTK toolkit, a popular open-source JavaScript library also developed by our team, for the in-browser rendering and visualization of brain image volumes. Efficient realtime communication among the remote instances is achieved by using just a small JSON object, comprising a representation of the XTK image renderers' state, as the Google Drive Realtime collaborative data model. The developed open-source JavaScript modules have already been instantiated in a web-app called MedView, a distributed collaborative neuroimage visualization application that is delivered to the users over the web without requiring the installation of any extra software or browser plugin. This responsive application allows multiple physically distant physicians or researchers to cooperate in real time to reach a diagnosis or scientific conclusion. It also serves as a proof of concept for the capabilities of the presented technological solution. PMID:28507515

Learning Visualization Strategies: A qualitative investigation

NASA Astrophysics Data System (ADS)

Halpern, Daniel; Oh, Kyong Eun; Tremaine, Marilyn; Chiang, James; Bemis, Karen; Silver, Deborah

2015-12-01

The following study investigates the range of strategies individuals develop to infer and interpret cross-sections of three-dimensional objects. We focus on the identification of mental representations and problem-solving processes made by 11 individuals with the goal of building training applications that integrate the strategies developed by the participants in our study. Our results suggest that although spatial transformation and perspective-taking techniques are useful for visualizing cross-section problems, these visual processes are augmented by analytical thinking. Further, our study shows that participants employ general analytic strategies for extended periods which evolve through practice into a set of progressively more expert strategies. Theoretical implications are discussed and five main findings are recommended for integration into the design of education software that facilitates visual learning and comprehension.

Toward a Shared Vocabulary for Visual Analysis: An Analytic Toolkit for Deconstructing the Visual Design of Graphic Novels

ERIC Educational Resources Information Center

Connors, Sean P.

2012-01-01

Literacy educators might advocate using graphic novels to develop students' visual literacy skills, but teachers who lack a vocabulary for engaging in close analysis of visual texts may be reluctant to teach them. Recognizing this, teacher educators should equip preservice teachers with a vocabulary for analyzing visual texts. This article…

Sciologer: Visualizing and Exploring Scientific Communities

ERIC Educational Resources Information Center

Bales, Michael Eliot

2009-01-01

Despite the recognized need to increase interdisciplinary collaboration, there are few information resources available to provide researchers with an overview of scientific communities--topics under investigation by various groups, and patterns of collaboration among groups. The tools that are available are designed for expert social network…

Application of Andrew's Plots to Visualization of Multidimensional Data

ERIC Educational Resources Information Center

Grinshpun, Vadim

2016-01-01

Importance: The article raises a point of visual representation of big data, recently considered to be demanded for many scientific and real-life applications, and analyzes particulars for visualization of multi-dimensional data, giving examples of the visual analytics-related problems. Objectives: The purpose of this paper is to study application…

Employing socially driven techniques for framing, contextualization, and collaboration in complex analytical threads

NASA Astrophysics Data System (ADS)

Wollocko, Arthur; Danczyk, Jennifer; Farry, Michael; Jenkins, Michael; Voshell, Martin

2015-05-01

The proliferation of sensor technologies continues to impact Intelligence Analysis (IA) work domains. Historical procurement focus on sensor platform development and acquisition has resulted in increasingly advanced collection systems; however, such systems often demonstrate classic data overload conditions by placing increased burdens on already overtaxed human operators and analysts. Support technologies and improved interfaces have begun to emerge to ease that burden, but these often focus on single modalities or sensor platforms rather than underlying operator and analyst support needs, resulting in systems that do not adequately leverage their natural human attentional competencies, unique skills, and training. One particular reason why emerging support tools often fail is due to the gap between military applications and their functions, and the functions and capabilities afforded by cutting edge technology employed daily by modern knowledge workers who are increasingly "digitally native." With the entry of Generation Y into these workplaces, "net generation" analysts, who are familiar with socially driven platforms that excel at giving users insight into large data sets while keeping cognitive burdens at a minimum, are creating opportunities for enhanced workflows. By using these ubiquitous platforms, net generation analysts have trained skills in discovering new information socially, tracking trends among affinity groups, and disseminating information. However, these functions are currently under-supported by existing tools. In this paper, we describe how socially driven techniques can be contextualized to frame complex analytical threads throughout the IA process. This paper focuses specifically on collaborative support technology development efforts for a team of operators and analysts. Our work focuses on under-supported functions in current working environments, and identifies opportunities to improve a team's ability to discover new information and disseminate insightful analytic findings. We describe our Cognitive Systems Engineering approach to developing a novel collaborative enterprise IA system that combines modern collaboration tools with familiar contemporary social technologies. Our current findings detail specific cognitive and collaborative work support functions that defined the design requirements for a prototype analyst collaborative support environment.

Collaborative WorkBench (cwb): Enabling Experiment Execution, Analysis and Visualization with Increased Scientific Productivity

NASA Astrophysics Data System (ADS)

Maskey, Manil; Ramachandran, Rahul; Kuo, Kwo-Sen

2015-04-01

The Collaborative WorkBench (CWB) has been successfully developed to support collaborative science algorithm development. It incorporates many features that enable and enhance science collaboration, including the support for both asynchronous and synchronous modes of interactions in collaborations. With the former, members in a team can share a full range of research artifacts, e.g. data, code, visualizations, and even virtual machine images. With the latter, they can engage in dynamic interactions such as notification, instant messaging, file exchange, and, most notably, collaborative programming. CWB also implements behind-the-scene provenance capture as well as version control to relieve scientists of these chores. Furthermore, it has achieved a seamless integration between researchers' local compute environments and those of the Cloud. CWB has also been successfully extended to support instrument verification and validation. Adopted by almost every researcher, the current practice of downloading data to local compute resources for analysis results in much duplication and inefficiency. CWB leverages Cloud infrastructure to provide a central location for data used by an entire science team, thereby eliminating much of this duplication and waste. Furthermore, use of CWB in concert with this same Cloud infrastructure enables co-located analysis with data where opportunities of data-parallelism can be better exploited, thereby further improving efficiency. With its collaboration-enabling features apposite to steps throughout the scientific process, we expect CWB to fundamentally transform research collaboration and realize maximum science productivity.

[application of the analytical transmission electron microscopy techniques for detection, identification and visualization of localization of nanoparticles of titanium and cerium oxides in mammalian cells].

PubMed

Shebanova, A S; Bogdanov, A G; Ismagulova, T T; Feofanov, A V; Semenyuk, P I; Muronets, V I; Erokhina, M V; Onishchenko, G E; Kirpichnikov, M P; Shaitan, K V

2014-01-01

This work represents the results of the study on applicability of the modern methods of analytical transmission electron microscopy for detection, identification and visualization of localization of nanoparticles of titanium and cerium oxides in A549 cell, human lung adenocarcinoma cell line. A comparative analysis of images of the nanoparticles in the cells obtained in the bright field mode of transmission electron microscopy, under dark-field scanning transmission electron microscopy and high-angle annular dark field scanning transmission electron was performed. For identification of nanoparticles in the cells the analytical techniques, energy-dispersive X-ray spectroscopy and electron energy loss spectroscopy, were compared when used in the mode of obtaining energy spectrum from different particles and element mapping. It was shown that the method for electron tomography is applicable to confirm that nanoparticles are localized in the sample but not coated by contamination. The possibilities and fields of utilizing different techniques for analytical transmission electron microscopy for detection, visualization and identification of nanoparticles in the biological samples are discussed.

VAP/VAT: video analytics platform and test bed for testing and deploying video analytics

NASA Astrophysics Data System (ADS)

Gorodnichy, Dmitry O.; Dubrofsky, Elan

2010-04-01

Deploying Video Analytics in operational environments is extremely challenging. This paper presents a methodological approach developed by the Video Surveillance and Biometrics Section (VSB) of the Science and Engineering Directorate (S&E) of the Canada Border Services Agency (CBSA) to resolve these problems. A three-phase approach to enable VA deployment within an operational agency is presented and the Video Analytics Platform and Testbed (VAP/VAT) developed by the VSB section is introduced. In addition to allowing the integration of third party and in-house built VA codes into an existing video surveillance infrastructure, VAP/VAT also allows the agency to conduct an unbiased performance evaluation of the cameras and VA software available on the market. VAP/VAT consists of two components: EventCapture, which serves to Automatically detect a "Visual Event", and EventBrowser, which serves to Display & Peruse of "Visual Details" captured at the "Visual Event". To deal with Open architecture as well as with Closed architecture cameras, two video-feed capture mechanisms have been developed within the EventCapture component: IPCamCapture and ScreenCapture.

A Strategy for Uncertainty Visualization Design

DTIC Science & Technology

2009-10-01

143–156, Magdeburg , Germany . [11] Thomson, J., Hetzler, E., MacEachren, A., Gahegan, M. and Pavel, M. (2005), A Typology for Visualizing Uncertainty...and Stasko [20] to bridge analytic gaps in visualization design, when tasks in the strategy overlap (and therefore complement) design frameworks

A Grammar-based Approach for Modeling User Interactions and Generating Suggestions During the Data Exploration Process.

PubMed

Dabek, Filip; Caban, Jesus J

2017-01-01

Despite the recent popularity of visual analytics focusing on big data, little is known about how to support users that use visualization techniques to explore multi-dimensional datasets and accomplish specific tasks. Our lack of models that can assist end-users during the data exploration process has made it challenging to learn from the user's interactive and analytical process. The ability to model how a user interacts with a specific visualization technique and what difficulties they face are paramount in supporting individuals with discovering new patterns within their complex datasets. This paper introduces the notion of visualization systems understanding and modeling user interactions with the intent of guiding a user through a task thereby enhancing visual data exploration. The challenges faced and the necessary future steps to take are discussed; and to provide a working example, a grammar-based model is presented that can learn from user interactions, determine the common patterns among a number of subjects using a K-Reversible algorithm, build a set of rules, and apply those rules in the form of suggestions to new users with the goal of guiding them along their visual analytic process. A formal evaluation study with 300 subjects was performed showing that our grammar-based model is effective at capturing the interactive process followed by users and that further research in this area has the potential to positively impact how users interact with a visualization system.

Urban Space Explorer: A Visual Analytics System for Urban Planning.

PubMed

Karduni, Alireza; Cho, Isaac; Wessel, Ginette; Ribarsky, William; Sauda, Eric; Dou, Wenwen

2017-01-01

Understanding people's behavior is fundamental to many planning professions (including transportation, community development, economic development, and urban design) that rely on data about frequently traveled routes, places, and social and cultural practices. Based on the results of a practitioner survey, the authors designed Urban Space Explorer, a visual analytics system that utilizes mobile social media to enable interactive exploration of public-space-related activity along spatial, temporal, and semantic dimensions.

2D-Visualization of metabolic activity with planar optical chemical sensors (optodes)

NASA Astrophysics Data System (ADS)

Meier, R. J.; Liebsch, G.

2015-12-01

Microbia plays an outstandingly important role in many hydrologic compartments, such as e.g. the benthic community in sediments, or biologically active microorganisms in the capillary fringe, in ground water, or soil. Oxygen, pH, and CO2 are key factors and indicators for microbial activity. They can be measured using optical chemical sensors. These sensors record changing fluorescence properties of specific indicator dyes. The signals can be measured in a non-contact mode, even through transparent walls, which is important for many lab-experiments. They can measure in closed (transparent) systems, without sampling or intruding into the sample. They do not consume the analytes while measuring, are fully reversible and able to measure in non-stirred solutions. These sensors can be applied as high precision fiberoptic sensors (for profiling), robust sensor spots, or as planar sensors for 2D visualization (imaging). Imaging enables to detect thousands of measurement spots at the same time and generate 2D analyte maps over a region of interest. It allows for comparing different regions within one recorded image, visualizing spatial analyte gradients, or more important to identify hot spots of metabolic activity. We present ready-to-use portable imaging systems for the analytes oxygen, pH, and CO2. They consist of a detector unit, planar sensor foils and a software for easy data recording and evaluation. Sensors foils for various analytes and measurement ranges enable visualizing metabolic activity or analyte changes in the desired range. Dynamics of metabolic activity can be detected in one shot or over long time periods. We demonstrate the potential of this analytical technique by presenting experiments on benthic disturbance-recovery dynamics in sediments and microbial degradation of organic material in the capillary fringe. We think this technique is a new tool to further understand how microbial and geochemical processes are linked in (not solely) hydrologic systems.

Text Stream Trend Analysis using Multiscale Visual Analytics with Applications to Social Media Systems

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

Steed, Chad A; Beaver, Justin M; BogenII, Paul L.

In this paper, we introduce a new visual analytics system, called Matisse, that allows exploration of global trends in textual information streams with specific application to social media platforms. Despite the potential for real-time situational awareness using these services, interactive analysis of such semi-structured textual information is a challenge due to the high-throughput and high-velocity properties. Matisse addresses these challenges through the following contributions: (1) robust stream data management, (2) automated sen- timent/emotion analytics, (3) inferential temporal, geospatial, and term-frequency visualizations, and (4) a flexible drill-down interaction scheme that progresses from macroscale to microscale views. In addition to describing thesemore » contributions, our work-in-progress paper concludes with a practical case study focused on the analysis of Twitter 1% sample stream information captured during the week of the Boston Marathon bombings.« less

Visual analytics as a translational cognitive science.

PubMed

Fisher, Brian; Green, Tera Marie; Arias-Hernández, Richard

2011-07-01

Visual analytics is a new interdisciplinary field of study that calls for a more structured scientific approach to understanding the effects of interaction with complex graphical displays on human cognitive processes. Its primary goal is to support the design and evaluation of graphical information systems that better support cognitive processes in areas as diverse as scientific research and emergency management. The methodologies that make up this new field are as yet ill defined. This paper proposes a pathway for development of visual analytics as a translational cognitive science that bridges fundamental research in human/computer cognitive systems and design and evaluation of information systems in situ. Achieving this goal will require the development of enhanced field methods for conceptual decomposition of human/computer cognitive systems that maps onto laboratory studies, and improved methods for conducting laboratory investigations that might better map onto real-world cognitive processes in technology-rich environments. Copyright © 2011 Cognitive Science Society, Inc.

Exploring Interhemispheric Collaboration in Older Compared to Younger Adults

ERIC Educational Resources Information Center

Cherry, Barbara J.; Yamashiro, Mariana; Anderson, Erin; Barrett, Christopher; Adamson, Maheen M.; Hellige, Joseph B.

2010-01-01

Physical and Name Identity letter-matching tasks were used to explore differences in interhemispheric collaboration in younger and older adults. To determine whether other factors might also be related to across/within-hemisphere processing or visual field asymmetries, neuropsychological tests measuring frontal/executive functioning were…

BiSet: Semantic Edge Bundling with Biclusters for Sensemaking.

PubMed

Sun, Maoyuan; Mi, Peng; North, Chris; Ramakrishnan, Naren

2016-01-01

Identifying coordinated relationships is an important task in data analytics. For example, an intelligence analyst might want to discover three suspicious people who all visited the same four cities. Existing techniques that display individual relationships, such as between lists of entities, require repetitious manual selection and significant mental aggregation in cluttered visualizations to find coordinated relationships. In this paper, we present BiSet, a visual analytics technique to support interactive exploration of coordinated relationships. In BiSet, we model coordinated relationships as biclusters and algorithmically mine them from a dataset. Then, we visualize the biclusters in context as bundled edges between sets of related entities. Thus, bundles enable analysts to infer task-oriented semantic insights about potentially coordinated activities. We make bundles as first class objects and add a new layer, "in-between", to contain these bundle objects. Based on this, bundles serve to organize entities represented in lists and visually reveal their membership. Users can interact with edge bundles to organize related entities, and vice versa, for sensemaking purposes. With a usage scenario, we demonstrate how BiSet supports the exploration of coordinated relationships in text analytics.

Iontophoresis and Flame Photometry: A Hybrid Interdisciplinary Experiment

ERIC Educational Resources Information Center

Sharp, Duncan; Cottam, Linzi; Bradley, Sarah; Brannigan, Jeanie; Davis, James

2010-01-01

The combination of reverse iontophoresis and flame photometry provides an engaging analytical experiment that gives first-year undergraduate students a flavor of modern drug delivery and analyte extraction techniques while reinforcing core analytical concepts. The experiment provides a highly visual demonstration of the iontophoresis technique and…

TrajGraph: A Graph-Based Visual Analytics Approach to Studying Urban Network Centralities Using Taxi Trajectory Data.

PubMed

Huang, Xiaoke; Zhao, Ye; Yang, Jing; Zhang, Chong; Ma, Chao; Ye, Xinyue

2016-01-01

We propose TrajGraph, a new visual analytics method, for studying urban mobility patterns by integrating graph modeling and visual analysis with taxi trajectory data. A special graph is created to store and manifest real traffic information recorded by taxi trajectories over city streets. It conveys urban transportation dynamics which can be discovered by applying graph analysis algorithms. To support interactive, multiscale visual analytics, a graph partitioning algorithm is applied to create region-level graphs which have smaller size than the original street-level graph. Graph centralities, including Pagerank and betweenness, are computed to characterize the time-varying importance of different urban regions. The centralities are visualized by three coordinated views including a node-link graph view, a map view and a temporal information view. Users can interactively examine the importance of streets to discover and assess city traffic patterns. We have implemented a fully working prototype of this approach and evaluated it using massive taxi trajectories of Shenzhen, China. TrajGraph's capability in revealing the importance of city streets was evaluated by comparing the calculated centralities with the subjective evaluations from a group of drivers in Shenzhen. Feedback from a domain expert was collected. The effectiveness of the visual interface was evaluated through a formal user study. We also present several examples and a case study to demonstrate the usefulness of TrajGraph in urban transportation analysis.

XCluSim: a visual analytics tool for interactively comparing multiple clustering results of bioinformatics data

PubMed Central

2015-01-01

Background Though cluster analysis has become a routine analytic task for bioinformatics research, it is still arduous for researchers to assess the quality of a clustering result. To select the best clustering method and its parameters for a dataset, researchers have to run multiple clustering algorithms and compare them. However, such a comparison task with multiple clustering results is cognitively demanding and laborious. Results In this paper, we present XCluSim, a visual analytics tool that enables users to interactively compare multiple clustering results based on the Visual Information Seeking Mantra. We build a taxonomy for categorizing existing techniques of clustering results visualization in terms of the Gestalt principles of grouping. Using the taxonomy, we choose the most appropriate interactive visualizations for presenting individual clustering results from different types of clustering algorithms. The efficacy of XCluSim is shown through case studies with a bioinformatician. Conclusions Compared to other relevant tools, XCluSim enables users to compare multiple clustering results in a more scalable manner. Moreover, XCluSim supports diverse clustering algorithms and dedicated visualizations and interactions for different types of clustering results, allowing more effective exploration of details on demand. Through case studies with a bioinformatics researcher, we received positive feedback on the functionalities of XCluSim, including its ability to help identify stably clustered items across multiple clustering results. PMID:26328893

Fusion Analytics: A Data Integration System for Public Health and Medical Disaster Response Decision Support

PubMed Central

Passman, Dina B.

2013-01-01

Objective The objective of this demonstration is to show conference attendees how they can integrate, analyze, and visualize diverse data type data from across a variety of systems by leveraging an off-the-shelf enterprise business intelligence (EBI) solution to support decision-making in disasters. Introduction Fusion Analytics is the data integration system developed by the Fusion Cell at the U.S. Department of Health and Human Services (HHS), Office of the Assistant Secretary for Preparedness and Response (ASPR). Fusion Analytics meaningfully augments traditional public and population health surveillance reporting by providing web-based data analysis and visualization tools. Methods Fusion Analytics serves as a one-stop-shop for the web-based data visualizations of multiple real-time data sources within ASPR. The 24-7 web availability makes it an ideal analytic tool for situational awareness and response allowing stakeholders to access the portal from any internet-enabled device without installing any software. The Fusion Analytics data integration system was built using off-the-shelf EBI software. Fusion Analytics leverages the full power of statistical analysis software and delivers reports to users in a secure web-based environment. Fusion Analytics provides an example of how public health staff can develop and deploy a robust public health informatics solution using an off-the shelf product and with limited development funding. It also provides the unique example of a public health information system that combines patient data for traditional disease surveillance with manpower and resource data to provide overall decision support for federal public health and medical disaster response operations. Conclusions We are currently in a unique position within public health. One the one hand, we have been gaining greater and greater access to electronic data of all kinds over the last few years. On the other, we are working in a time of reduced government spending to support leveraging this data for decision support with robust analytics and visualizations. Fusion Analytics provides an opportunity for attendees to see how various types of data are integrated into a single application for population health decision support. It also can provide them with ideas of how they can use their own staff to create analyses and reports that support their public health activities.

Understanding How to Build Long-Lived Learning Collaborators

DTIC Science & Technology

2016-03-16

discrimination in learning, and dynamic encoding strategies to improve visual encoding for learning via analogical generalization. We showed that spatial concepts...a 20,000 sketch corpus to examine the tradeoffs involved in visual representation and analogical generalization. 15. SUBJECT TERMS...strategies to improve visual encoding for learning via analogical generalization. We showed that spatial concepts can be learned via analogical

Visual Communication in Transition: Designing for New Media Literacies and Visual Culture Art Education across Activities and Settings

ERIC Educational Resources Information Center

Zuiker, Steven J.

2014-01-01

As an example of design-based research, this case study describes and analyses the enactment of a collaborative drawing and animation studio in a Singapore secondary school art classroom. The design embodies principles of visual culture art education and new media literacies in order to organize transitions in the settings of participation and…

"This Is the Best Lesson Ever, Miss...": Disrupting Linear Logics of Visual Arts Teaching Practice

ERIC Educational Resources Information Center

Mitchell, Donna Mathewson

2016-01-01

Research in visual arts education is often focused on philosophical issues or broad concerns related to approaches to curriculum. In focusing on the everyday work of teaching, this article addresses a gap in the literature to report on collaborative research exploring the experiences of secondary visual arts teachers in regional New South Wales,…

Connecting Art and the Brain: An Artist's Perspective on Visual Indeterminacy

PubMed Central

Pepperell, Robert

2011-01-01

In this article I will discuss the intersection between art and neuroscience from the perspective of a practicing artist. I have collaborated on several scientific studies into the effects of art on the brain and behavior, looking in particular at the phenomenon of “visual indeterminacy.” This is a perceptual state in which subjects fail to recognize objects from visual cues. I will look at the background to this phenomenon, and show how various artists have exploited its effect through the history of art. My own attempts to create indeterminate images will be discussed, including some of the technical problems I faced in trying to manipulate the viewer's perceptual state through paintings. Visual indeterminacy is not widely studied in neuroscience, although references to it can be found in the literature on visual agnosia and object recognition. I will briefly review some of this work and show how my attempts to understand the science behind visual indeterminacy led me to collaborate with psychophysicists and neuroscientists. After reviewing this work, I will discuss the conclusions I have drawn from its findings and consider the problem of how best to integrate neuroscientific methods with artistic knowledge to create truly interdisciplinary approach. PMID:21887141

Visualization of the Mode Shapes of Pressure Oscillation in a Cylindrical Cavity

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

He, Xin; Qi, Yunliang; Wang, Zhi

Our work describes a novel experimental method to visualize the mode shapes of pressure oscillation in a cylindrical cavity. Acoustic resonance in a cavity is a grand old problem that has been under investigation (using both analytical and numerical methods) for more than a century. In this article, a novel method based on high speed imaging of combustion chemiluminescence was presented to visualize the mode shapes of pressure oscillation in a cylindrical cavity. By generating high-temperature combustion gases and strong pressure waves simultaneously in a cylindrical cavity, the pressure oscillation can be inferred due to the chemiluminescence emissions of themore » combustion products. We can then visualized the mode shapes by reconstructing the images based on the amplitudes of the luminosity spectrum at the corresponding resonant frequencies. Up to 11 resonant mode shapes were clearly visualized, each matching very well with the analytical solutions.« less

Combining computational analyses and interactive visualization for document exploration and sensemaking in jigsaw.

PubMed

Görg, Carsten; Liu, Zhicheng; Kihm, Jaeyeon; Choo, Jaegul; Park, Haesun; Stasko, John

2013-10-01

Investigators across many disciplines and organizations must sift through large collections of text documents to understand and piece together information. Whether they are fighting crime, curing diseases, deciding what car to buy, or researching a new field, inevitably investigators will encounter text documents. Taking a visual analytics approach, we integrate multiple text analysis algorithms with a suite of interactive visualizations to provide a flexible and powerful environment that allows analysts to explore collections of documents while sensemaking. Our particular focus is on the process of integrating automated analyses with interactive visualizations in a smooth and fluid manner. We illustrate this integration through two example scenarios: an academic researcher examining InfoVis and VAST conference papers and a consumer exploring car reviews while pondering a purchase decision. Finally, we provide lessons learned toward the design and implementation of visual analytics systems for document exploration and understanding.

Realistic terrain visualization based on 3D virtual world technology

NASA Astrophysics Data System (ADS)

Huang, Fengru; Lin, Hui; Chen, Bin; Xiao, Cai

2009-09-01

The rapid advances in information technologies, e.g., network, graphics processing, and virtual world, have provided challenges and opportunities for new capabilities in information systems, Internet applications, and virtual geographic environments, especially geographic visualization and collaboration. In order to achieve meaningful geographic capabilities, we need to explore and understand how these technologies can be used to construct virtual geographic environments to help to engage geographic research. The generation of three-dimensional (3D) terrain plays an important part in geographical visualization, computer simulation, and virtual geographic environment applications. The paper introduces concepts and technologies of virtual worlds and virtual geographic environments, explores integration of realistic terrain and other geographic objects and phenomena of natural geographic environment based on SL/OpenSim virtual world technologies. Realistic 3D terrain visualization is a foundation of construction of a mirror world or a sand box model of the earth landscape and geographic environment. The capabilities of interaction and collaboration on geographic information are discussed as well. Further virtual geographic applications can be developed based on the foundation work of realistic terrain visualization in virtual environments.

Realistic terrain visualization based on 3D virtual world technology

NASA Astrophysics Data System (ADS)

Huang, Fengru; Lin, Hui; Chen, Bin; Xiao, Cai

2010-11-01

The rapid advances in information technologies, e.g., network, graphics processing, and virtual world, have provided challenges and opportunities for new capabilities in information systems, Internet applications, and virtual geographic environments, especially geographic visualization and collaboration. In order to achieve meaningful geographic capabilities, we need to explore and understand how these technologies can be used to construct virtual geographic environments to help to engage geographic research. The generation of three-dimensional (3D) terrain plays an important part in geographical visualization, computer simulation, and virtual geographic environment applications. The paper introduces concepts and technologies of virtual worlds and virtual geographic environments, explores integration of realistic terrain and other geographic objects and phenomena of natural geographic environment based on SL/OpenSim virtual world technologies. Realistic 3D terrain visualization is a foundation of construction of a mirror world or a sand box model of the earth landscape and geographic environment. The capabilities of interaction and collaboration on geographic information are discussed as well. Further virtual geographic applications can be developed based on the foundation work of realistic terrain visualization in virtual environments.

Integration and Visualization of Translational Medicine Data for Better Understanding of Human Diseases

PubMed Central

Satagopam, Venkata; Gu, Wei; Eifes, Serge; Gawron, Piotr; Ostaszewski, Marek; Gebel, Stephan; Barbosa-Silva, Adriano; Balling, Rudi; Schneider, Reinhard

2016-01-01

Abstract Translational medicine is a domain turning results of basic life science research into new tools and methods in a clinical environment, for example, as new diagnostics or therapies. Nowadays, the process of translation is supported by large amounts of heterogeneous data ranging from medical data to a whole range of -omics data. It is not only a great opportunity but also a great challenge, as translational medicine big data is difficult to integrate and analyze, and requires the involvement of biomedical experts for the data processing. We show here that visualization and interoperable workflows, combining multiple complex steps, can address at least parts of the challenge. In this article, we present an integrated workflow for exploring, analysis, and interpretation of translational medicine data in the context of human health. Three Web services—tranSMART, a Galaxy Server, and a MINERVA platform—are combined into one big data pipeline. Native visualization capabilities enable the biomedical experts to get a comprehensive overview and control over separate steps of the workflow. The capabilities of tranSMART enable a flexible filtering of multidimensional integrated data sets to create subsets suitable for downstream processing. A Galaxy Server offers visually aided construction of analytical pipelines, with the use of existing or custom components. A MINERVA platform supports the exploration of health and disease-related mechanisms in a contextualized analytical visualization system. We demonstrate the utility of our workflow by illustrating its subsequent steps using an existing data set, for which we propose a filtering scheme, an analytical pipeline, and a corresponding visualization of analytical results. The workflow is available as a sandbox environment, where readers can work with the described setup themselves. Overall, our work shows how visualization and interfacing of big data processing services facilitate exploration, analysis, and interpretation of translational medicine data. PMID:27441714

Modeling and evaluating user behavior in exploratory visual analysis

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

Reda, Khairi; Johnson, Andrew E.; Papka, Michael E.

Empirical evaluation methods for visualizations have traditionally focused on assessing the outcome of the visual analytic process as opposed to characterizing how that process unfolds. There are only a handful of methods that can be used to systematically study how people use visualizations, making it difficult for researchers to capture and characterize the subtlety of cognitive and interaction behaviors users exhibit during visual analysis. To validate and improve visualization design, however, it is important for researchers to be able to assess and understand how users interact with visualization systems under realistic scenarios. This paper presents a methodology for modeling andmore » evaluating the behavior of users in exploratory visual analysis. We model visual exploration using a Markov chain process comprising transitions between mental, interaction, and computational states. These states and the transitions between them can be deduced from a variety of sources, including verbal transcripts, videos and audio recordings, and log files. This model enables the evaluator to characterize the cognitive and computational processes that are essential to insight acquisition in exploratory visual analysis, and reconstruct the dynamics of interaction between the user and the visualization system. We illustrate this model with two exemplar user studies, and demonstrate the qualitative and quantitative analytical tools it affords.« less

Visualizing Qualitative Information

ERIC Educational Resources Information Center

Slone, Debra J.

2009-01-01

The abundance of qualitative data in today's society and the need to easily scrutinize, digest, and share this information calls for effective visualization and analysis tools. Yet, no existing qualitative tools have the analytic power, visual effectiveness, and universality of familiar quantitative instruments like bar charts, scatter-plots, and…

Group Projects as a Method of Promoting Student Scientific Communication and Collaboration in a Public Health Microbiology Course

ERIC Educational Resources Information Center

Walton, Kristen L. W.; Baker, Jason C.

2009-01-01

Communication of scientific and medical information and collaborative work are important skills for students pursuing careers in health professions and other biomedical sciences. In addition, group work and active learning can increase student engagement and analytical skills. Students in our public health microbiology class were required to work…

Empirical Analysis of the Subjective Impressions and Objective Measures of Domain Scientists’ Analytical Judgment Using Visualizations

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

Dasgupta, Aritra; Burrows, Susannah M.; Han, Kyungsik

Scientists working in a particular domain often adhere to conventional data analysis and presentation methods and this leads to familiarity with these methods over time. But does high familiarity always lead to better analytical judgment? This question is especially relevant when visualizations are used in scientific tasks, as there can be discrepancies between visualization best practices and domain conventions. However, there is little empirical evidence of the relationships between scientists’ subjective impressions about familiar and unfamiliar visualizations and objective measures of their effect on scientific judgment. To address this gap and to study these factors, we focus on the climatemore » science domain, specifically on visualizations used for comparison of model performance. We present a comprehensive user study with 47 climate scientists where we explored the following factors: i) relationships between scientists’ familiarity, their perceived levels of com- fort, confidence, accuracy, and objective measures of accuracy, and ii) relationships among domain experience, visualization familiarity, and post-study preference.« less

Thinking graphically: Connecting vision and cognition during graph comprehension.

PubMed

Ratwani, Raj M; Trafton, J Gregory; Boehm-Davis, Deborah A

2008-03-01

Task analytic theories of graph comprehension account for the perceptual and conceptual processes required to extract specific information from graphs. Comparatively, the processes underlying information integration have received less attention. We propose a new framework for information integration that highlights visual integration and cognitive integration. During visual integration, pattern recognition processes are used to form visual clusters of information; these visual clusters are then used to reason about the graph during cognitive integration. In 3 experiments, the processes required to extract specific information and to integrate information were examined by collecting verbal protocol and eye movement data. Results supported the task analytic theories for specific information extraction and the processes of visual and cognitive integration for integrative questions. Further, the integrative processes scaled up as graph complexity increased, highlighting the importance of these processes for integration in more complex graphs. Finally, based on this framework, design principles to improve both visual and cognitive integration are described. PsycINFO Database Record (c) 2008 APA, all rights reserved

How I Learned to Swim: The Visual Journal as a Companion to Creative Inquiry

ERIC Educational Resources Information Center

Scott Shields, Sara

2016-01-01

In this paper, I discuss my engagement with a visual journal as a companion to creative research practice during my dissertation research. Grounded in arts based research methodologies; I explore visual journals in relationship to research, reflection and analytic processes. I begin with a discussion of the visual journal as an artifact of…

The Importance of Data Visualization: Incorporating Storytelling into the Scientific Presentation

NASA Technical Reports Server (NTRS)

Babiak-Vazquez, A.; Cornett, A. N.; Wear, M. L.; Sams, C.

2014-01-01

From its inception in 2000, one of the primary tasks of the Biomedical Data Reduction Analysis (BDRA) group has been translation of large amounts of data into information that is relevant to the audience receiving it. BDRA helps translate data into an integrated model that supports both operational and research activities. This data integrated model and subsequent visual data presentations have contributed to BDRA's success in delivering the message (i.e., the story) that its customers have needed to communicate. This success has led to additional collaborations among groups that had previously not felt they had much in common until they worked together to develop solutions in an integrated fashion. As more emphasis is placed on working with "big data" and on showing how NASA's efforts contribute to the greater good of the American people and of the world, it becomes imperative to visualize the story of our data to communicate the greater message we need to share. METHODS To create and expand its data integrated model, BDRA has incorporated data from many different collaborating partner labs and other sources. Data are compiled from the repositories of the Lifetime Surveillance of Astronaut Health and the Life Sciences Data Archive, and from the individual laboratories at Johnson Space Center that support collection of data from medical testing, environmental monitoring, and countermeasures, as designated in the Medical Requirements Integration Documents. Ongoing communication with the participating collaborators is maintained to ensure that the message and story of the data are retained as data are translated into information and visual data presentations are delivered in different venues and to different audiences. RESULTS We will describe the importance of storytelling through an integrated model and of subsequent data visualizations in today's scientific presentations and discuss the collaborative methods used. We will illustrate the discussion with examples of graphs from BDRA's past work supporting operations and/or research efforts.

Seamless online science workflow development and collaboration using IDL and the ENVI Services Engine

NASA Astrophysics Data System (ADS)

Harris, A. T.; Ramachandran, R.; Maskey, M.

2013-12-01

The Exelis-developed IDL and ENVI software are ubiquitous tools in Earth science research environments. The IDL Workbench is used by the Earth science community for programming custom data analysis and visualization modules. ENVI is a software solution for processing and analyzing geospatial imagery that combines support for multiple Earth observation scientific data types (optical, thermal, multi-spectral, hyperspectral, SAR, LiDAR) with advanced image processing and analysis algorithms. The ENVI & IDL Services Engine (ESE) is an Earth science data processing engine that allows researchers to use open standards to rapidly create, publish and deploy advanced Earth science data analytics within any existing enterprise infrastructure. Although powerful in many ways, the tools lack collaborative features out-of-box. Thus, as part of the NASA funded project, Collaborative Workbench to Accelerate Science Algorithm Development, researchers at the University of Alabama in Huntsville and Exelis have developed plugins that allow seamless research collaboration from within IDL workbench. Such additional features within IDL workbench are possible because IDL workbench is built using the Eclipse Rich Client Platform (RCP). RCP applications allow custom plugins to be dropped in for extended functionalities. Specific functionalities of the plugins include creating complex workflows based on IDL application source code, submitting workflows to be executed by ESE in the cloud, and sharing and cloning of workflows among collaborators. All these functionalities are available to scientists without leaving their IDL workbench. Because ESE can interoperate with any middleware, scientific programmers can readily string together IDL processing tasks (or tasks written in other languages like C++, Java or Python) to create complex workflows for deployment within their current enterprise architecture (e.g. ArcGIS Server, GeoServer, Apache ODE or SciFlo from JPL). Using the collaborative IDL Workbench, coupled with ESE for execution in the cloud, asynchronous workflows could be executed in batch mode on large data in the cloud. We envision that a scientist will initially develop a scientific workflow locally on a small set of data. Once tested, the scientist will deploy the workflow to the cloud for execution. Depending on the results, the scientist may share the workflow and results, allowing them to be stored in a community catalog and instantly loaded into the IDL Workbench of other scientists. Thereupon, scientists can clone and modify or execute the workflow with different input parameters. The Collaborative Workbench will provide a platform for collaboration in the cloud, helping Earth scientists solve big-data problems in the Earth and planetary sciences.

Incidence of Group Awareness Information on Students' Collaborative Learning Processes

ERIC Educational Resources Information Center

Pifarré, M.; Cobos, R.; Argelagós, E.

2014-01-01

This paper studies how the integration of group awareness tools in the knowledge management system called KnowCat (Knowledge Catalyser), which promotes collaborative knowledge construction, may both foster the students' perception about the meaningfulness of visualization of group awareness information and promote better collaborative…

The Brussels Metro: Accessibility through Collaboration

ERIC Educational Resources Information Center

Strickfaden, Megan; Devlieger, Patrick

2011-01-01

This article describes and analyzes the development of a navigation and orientation system for people with visual impairments as it evolved over three decades. It includes reflections on how users have been involved in the redesign process and illustrates how people with and without disabilities have collaborated to create a more suitable and…

Collaborative Outcome Measurement: Development of the Nationally Standardized Minimum Data Set

ERIC Educational Resources Information Center

Stephens, Barry C.; Kirchner, Corinne; Orr, Alberta L.; Suvino, Dawn; Rogers, Priscilla

2009-01-01

This article discusses the challenging process of developing a common data set for independent living programs serving older adults who are visually impaired. The three-year project, which included collaborative efforts among many stakeholders that encompass diverse program models, resulted in the development of the Internet-based Nationally…

Collaborative Processes in Species Identification Using an Internet-Based Taxonomic Resource

ERIC Educational Resources Information Center

Kontkanen, Jani; Kärkkäinen, Sirpa; Dillon, Patrick; Hartikainen-Ahia, Anu; Åhlberg, Mauri

2016-01-01

Visual databases are increasingly important resources through which individuals and groups can undertake species identification. This paper reports research on the collaborative processes undertaken by pre-service teacher students when working in small groups to identify birds using an Internet-based taxonomic resource. The student groups are…

Measuring and Visualizing Group Knowledge Elaboration in Online Collaborative Discussions

ERIC Educational Resources Information Center

Zheng, Yafeng; Xu, Chang; Li, Yanyan; Su, You

2018-01-01

Knowledge elaboration plays a critical role in promoting knowledge acquisition and facilitating the retention of target knowledge in online collaborative discussions. Adopting a key-term-based automated analysis approach, we proposed an indicator framework to measure the level of knowledge elaboration in terms of coverage, activation, and…

Penetrating the Fog: Analytics in Learning and Education

ERIC Educational Resources Information Center

Siemens, George; Long, Phil

2011-01-01

Attempts to imagine the future of education often emphasize new technologies--ubiquitous computing devices, flexible classroom designs, and innovative visual displays. But the most dramatic factor shaping the future of higher education is something that people cannot actually touch or see: "big data and analytics." Learning analytics is still in…

Be the Data: Embodied Visual Analytics

ERIC Educational Resources Information Center

Chen, Xin; Self, Jessica Zeitz; House, Leanna; Wenskovitch, John; Sun, Maoyuan; Wycoff, Nathan; Evia, Jane Robertson; Leman, Scotland; North, Chris

2018-01-01

With the rise of big data, it is becoming increasingly important to educate groups of students at many educational levels about data analytics. In particular, students without a strong mathematical background may have an unenthusiastic attitude towards high-dimensional data and find it challenging to understand relevant complex analytical methods,…

Conversion of National Health Insurance Service-National Sample Cohort (NHIS-NSC) Database into Observational Medical Outcomes Partnership-Common Data Model (OMOP-CDM).

PubMed

You, Seng Chan; Lee, Seongwon; Cho, Soo-Yeon; Park, Hojun; Jung, Sungjae; Cho, Jaehyeong; Yoon, Dukyong; Park, Rae Woong

2017-01-01

It is increasingly necessary to generate medical evidence applicable to Asian people compared to those in Western countries. Observational Health Data Sciences a Informatics (OHDSI) is an international collaborative which aims to facilitate generating high-quality evidence via creating and applying open-source data analytic solutions to a large network of health databases across countries. We aimed to incorporate Korean nationwide cohort data into the OHDSI network by converting the national sample cohort into Observational Medical Outcomes Partnership-Common Data Model (OMOP-CDM). The data of 1.13 million subjects was converted to OMOP-CDM, resulting in average 99.1% conversion rate. The ACHILLES, open-source OMOP-CDM-based data profiling tool, was conducted on the converted database to visualize data-driven characterization and access the quality of data. The OMOP-CDM version of National Health Insurance Service-National Sample Cohort (NHIS-NSC) can be a valuable tool for multiple aspects of medical research by incorporation into the OHDSI research network.

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

Cook, Kris A.; Scholtz, Jean; Whiting, Mark A.

The VAST Challenge has been a popular venue for academic and industry participants for over ten years. Many participants comment that the majority of their time in preparing VAST Challenge entries is discovering elements in their software environments that need to be redesigned in order to solve the given task. Fortunately, there is no need to wait until the VAST Challenge is announced to test out software systems. The Visual Analytics Benchmark Repository contains all past VAST Challenge tasks, data, solutions and submissions. This paper details the various types of evaluations that may be conducted using the Repository information. Inmore » this paper we describe how developers can do informal evaluations of various aspects of their visual analytics environments using VAST Challenge information. Aspects that can be evaluated include the appropriateness of the software for various tasks, the various data types and formats that can be accommodated, the effectiveness and efficiency of the process supported by the software, and the intuitiveness of the visualizations and interactions. Researchers can compare their visualizations and interactions to those submitted to determine novelty. In addition, the paper provides pointers to various guidelines that software teams can use to evaluate the usability of their software. While these evaluations are not a replacement for formal evaluation methods, this information can be extremely useful during the development of visual analytics environments.« less

The Top 10 Challenges in Extreme-Scale Visual Analytics

PubMed Central

Wong, Pak Chung; Shen, Han-Wei; Johnson, Christopher R.; Chen, Chaomei; Ross, Robert B.

2013-01-01

In this issue of CG&A, researchers share their R&D findings and results on applying visual analytics (VA) to extreme-scale data. Having surveyed these articles and other R&D in this field, we’ve identified what we consider the top challenges of extreme-scale VA. To cater to the magazine’s diverse readership, our discussion evaluates challenges in all areas of the field, including algorithms, hardware, software, engineering, and social issues. PMID:24489426

Real-time analysis for intensive care: development and deployment of the artemis analytic system.

PubMed

Blount, Marion; Ebling, Maria R; Eklund, J Mikael; James, Andrew G; McGregor, Carolyn; Percival, Nathan; Smith, Kathleen P; Sow, Daby

2010-01-01

The lives of many thousands of children born premature or ill at term around the world have been saved by those who work within neonatal intensive care units (NICUs). Modern-day neonatologists, together with nursing staff and other specialists within this domain, enjoy modern technologies for activities such as financial transactions, online purchasing, music, and video on demand. Yet, when they move into their workspace, in many cases, they are supported by nearly the same technology they used 20 years ago. Medical devices provide visual displays of vital signs through physiological streams such as electrocardiogram (ECG), heart rate, blood oxygen saturation (SpO(2)), and respiratory rate. Electronic health record initiatives around the world provide an environment for the electronic management of medical records, but they fail to support the high-frequency interpretation of streaming physiological data. We have taken a collaborative research approach to address this need to provide a flexible platform for the real-time online analysis of patients' data streams to detect medically significant conditions that precede the onset of medical complications. The platform supports automated or clinician-driven knowledge discovery to discover new relationships between physiological data stream events and latent medical conditions as well as to refine existing analytics. Patients benefit from the system because earlier detection of signs of the medical conditions may lead to earlier intervention that may potentially lead to improved patient outcomes and reduced length of stays. The clinician benefits from a decision support tool that provides insight into multiple streams of data that are too voluminous to assess with traditional methods. The remainder of this article summarizes the strengths of our research collaboration and the resulting environment known as Artemis, which is currently being piloted within the NICU of The Hospital for Sick Children (SickKids) in Toronto, Ontario, Canada. Although the discussion in this article focuses on a NICU, the technologies can be applied to any intensive care environment.

Reports of the AAAI 2009 Spring Symposia: Technosocial Predictive Analytics.

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

Sanfilippo, Antonio P.

2009-10-01

The Technosocial Predictive Analytics AAAI symposium was held at Stanford University, Stanford, CA, March 23-25, 2009. The goal of this symposium was to explore new methods for anticipatory analytical thinking that provide decision advantage through the integration of human and physical models. Special attention was also placed on how to leverage supporting disciplines to (a) facilitate the achievement of knowledge inputs, (b) improve the user experience, and (c) foster social intelligence through collaborative/competitive work.

What makes 'big data' different from 'regular data' within radiology? The easiest answer: when it no longer fits into Excel!

NASA Astrophysics Data System (ADS)

Lindsköld, L.; Alvfeldt, G.; Wintell, M.

2015-03-01

One of the challenges of today's healthcare is that data from radiology is heterogeneous, stored and managed in silos created by PACS vendors. Also seen is a lack of coordinated use of harmonized reference information models and established healthcare standards. Radiology in Region Västra Götaland has been entering the world of "Big Data" since 2006, 34 departments split into 4 private image center, 2 small-size hospital, 4 middle-sized hospital groups and one University hospital. Using the same information infrastructure as a means of collaborating and sharing information between. As an organization building for the future we must meet the values and requirements of the stakeholders and count the patient as the major actor. Can "Big Data" analytics be a valuable asset from a regional management perspective? Our initial findings indicates that this is the case, based on three different perspectives - work practice changes, understanding data quality when sharing information and introducing new services in work practice. Going from local to enterprise workflow utilizing the power of "Big Data", not only by volume but also by combining diverse sources and aggregate the information domains, visualize new trends as well as dependencies more effectively. Building trust by the use of Big Data in healthcare involves a long and winding journey, but the persevering infrastructure-oriented organization will give new ways of collaboration for the enterprise it serves. It also involves continuous negotiation with people concerning how and why they should collaborate with new actors within the region to achieve patient centric care. This will nurture a more open-minded, hopeful and life-affirming holistic approach involving all stakeholders, newcomers' specialists and patients.

Enhancing radiological volumes with symbolic anatomy using image fusion and collaborative virtual reality.

PubMed

Silverstein, Jonathan C; Dech, Fred; Kouchoukos, Philip L

2004-01-01

Radiological volumes are typically reviewed by surgeons using cross-sections and iso-surface reconstructions. Applications that combine collaborative stereo volume visualization with symbolic anatomic information and data fusions would expand surgeons' capabilities in interpretation of data and in planning treatment. Such an application has not been seen clinically. We are developing methods to systematically combine symbolic anatomy (term hierarchies and iso-surface atlases) with patient data using data fusion. We describe our progress toward integrating these methods into our collaborative virtual reality application. The fully combined application will be a feature-rich stereo collaborative volume visualization environment for use by surgeons in which DICOM datasets will self-report underlying anatomy with visual feedback. Using hierarchical navigation of SNOMED-CT anatomic terms integrated with our existing Tele-immersive DICOM-based volumetric rendering application, we will display polygonal representations of anatomic systems on the fly from menus that query a database. The methods and tools involved in this application development are SNOMED-CT, DICOM, VISIBLE HUMAN, volumetric fusion and C++ on a Tele-immersive platform. This application will allow us to identify structures and display polygonal representations from atlas data overlaid with the volume rendering. First, atlas data is automatically translated, rotated, and scaled to the patient data during loading using a public domain volumetric fusion algorithm. This generates a modified symbolic representation of the underlying canonical anatomy. Then, through the use of collision detection or intersection testing of various transparent polygonal representations, the polygonal structures are highlighted into the volumetric representation while the SNOMED names are displayed. Thus, structural names and polygonal models are associated with the visualized DICOM data. This novel juxtaposition of information promises to expand surgeons' abilities to interpret images and plan treatment.

A Collaborative Education Network for Advancing Climate Literacy using Data Visualization Technology

NASA Astrophysics Data System (ADS)

McDougall, C.; Russell, E. L.; Murray, M.; Bendel, W. B.

2013-12-01

One of the more difficult issues in engaging broad audiences with scientific research is to present it in a way that is intuitive, captivating and up-to-date. Over the past ten years, the National Oceanic and Atmospheric Administration (NOAA) has made significant progress in this area through Science On a Sphere(R) (SOS). SOS is a room-sized, global display system that uses computers and video projectors to display Earth systems data onto a six-foot diameter sphere, analogous to a giant animated globe. This well-crafted data visualization system serves as a way to integrate and display global change phenomena; including polar ice melt, projected sea level rise, ocean acidification and global climate models. Beyond a display for individual data sets, SOS provides a holistic global perspective that highlights the interconnectedness of Earth systems, nations and communities. SOS is now a featured exhibit at more than 100 science centers, museums, universities, aquariums and other institutions around the world reaching more than 33 million visitors every year. To facilitate the development of how this data visualization technology and these visualizations could be used with public audiences, we recognized the need for the exchange of information among the users. To accomplish this, we established the SOS Users Collaborative Network. This network consists of the institutions that have an SOS system or partners who are creating content and educational programming for SOS. When we began the Network in 2005, many museums had limited capacity to both incorporate real-time, authentic scientific data about the Earth system and interpret global change visualizations. They needed not only the visualization platform and the scientific content, but also assistance with methods of approach. We needed feedback from these users on how to craft understandable visualizations and how to further develop the SOS platform to support learning. Through this Network and the collaboration among members, we have, collectively, been able to advance all of our efforts. The member institutions, through regular face-to-face workshops and an online community, share practices in creation and cataloging of datasets, new methods for delivering content via SOS, and updates on the SOS system and software. One hallmark of the SOS Users Collaborative Network is that it exemplifies an ideal partnership between federal science agencies and informal science education institutions. The science agencies (including NOAA, NASA, and the Department of Energy) provide continuously updated global datasets, scientific expertise, funding, and support. In turn, museums act as trusted public providers of scientific information, provide audience-appropriate presentations, localized relevance to global phenomena and a forum for discussing the complex science and repercussions of global change. We will discuss the characteristics of this Network that maximize collaboration and what we're learning as a community to improve climate literacy.

Visual Narrative: A Technique to Enhance Secondary Students' Contribution to the Development of Inclusive, Socially Just School Environments--Lessons from a Box of Crayons

ERIC Educational Resources Information Center

Carrington, Suzanne; Allen, Kate; Osmolowski, Daniel

2007-01-01

This paper reports on a project that involved Australian secondary school students working as participatory researchers in collaboration with a researcher and two teachers. Research methodology using visual narrative techniques provided the students with a conceptual lens to view their school community. The examples of visual narrative shared in…

A Social Media Practicum: An Action-Learning Approach to Social Media Marketing and Analytics

ERIC Educational Resources Information Center

Atwong, Catherine T.

2015-01-01

To prepare students for the rapidly evolving field of digital marketing, which requires more and more technical skills every year, a social media practicum creates a learning environment in which students can apply marketing principles and become ready for collaborative work in social media marketing and analytics. Using student newspapers as…

PISA 2015 Assessment and Analytical Framework: Science, Reading, Mathematic, Financial Literacy and Collaborative Problem Solving

ERIC Educational Resources Information Center

OECD Publishing, 2017

2017-01-01

What is important for citizens to know and be able to do? The OECD Programme for International Student Assessment (PISA) seeks to answer that question through the most comprehensive and rigorous international assessment of student knowledge and skills. The PISA 2015 Assessment and Analytical Framework presents the conceptual foundations of the…

Prototyping Visual Learning Analytics Guided by an Educational Theory Informed Goal

ERIC Educational Resources Information Center

Hillaire, Garron; Rappolt-Schlichtmann, Gabrielle; Ducharme, Kim

2016-01-01

Prototype work can support the creation of data visualizations throughout the research and development process through paper prototypes with sketching, designed prototypes with graphic design tools, and functional prototypes to explore how the implementation will work. One challenging aspect of data visualization work is coordinating the expertise…

The Kaleidoscope of Visual Poetry: New Approaches to Visual Literacy

ERIC Educational Resources Information Center

Bennett, Tamryn

2011-01-01

What are the possibilities for poetry? This paper introduces approaches to creating and teaching poetry through a critical survey of contemporary practitioners within the field. Analysis of ekphrastic traditions, comics and concrete poetry, artists books, graffiti poems, film, performance and interdisciplinary collaborations reveal new…

The biodigital human: a web-based 3D platform for medical visualization and education.

PubMed

Qualter, John; Sculli, Frank; Oliker, Aaron; Napier, Zachary; Lee, Sabrina; Garcia, Julio; Frenkel, Sally; Harnik, Victoria; Triola, Marc

2012-01-01

NYU School of Medicine's Division of Educational Informatics in collaboration with BioDigital Systems LLC (New York, NY) has created a virtual human body dataset that is being used for visualization, education and training and is accessible over modern web browsers.

"Let's Set Up Some Subgoals": Understanding Human-Pedagogical Agent Collaborations and Their Implications for Learning and Prompt and Feedback Compliance

ERIC Educational Resources Information Center

Harley, Jason M.; Taub, Michelle; Azevedo, Roger; Bouchet, Francois

2018-01-01

Research on collaborative learning between humans and virtual pedagogical agents represents a necessary extension to recent research on the conceptual, theoretical, methodological, analytical, and educational issues behind co- and socially-shared regulated learning between humans. This study presents a novel coding framework that was developed and…

A Collaborative Approach to Designing Graduate Admission Studies: A Model for Influencing Program Planning and Policy. AIR 1999 Annual Forum Paper.

ERIC Educational Resources Information Center

Delaney, Anne Marie

This paper presents the rationale, research design, analytical approaches, and results of a graduate admission study which examined the motivation and enrollment decision processes of students accepted to a newly redesigned Master of Business Administration (MBA) Program. The study was developed collaboratively by the institution's Office of…

An Analysis of a Subject Department in an English Secondary School Using the Collaborative Practice Analytical Framework

ERIC Educational Resources Information Center

James, Christopher; Goodhew, Carolyn

2011-01-01

This article reports the outcomes of research into the nature of and influences on collective working in an English secondary school. A design and technology department was studied over a 13-month period. Data collection was by interviews, observations and document scrutiny. The findings were analysed using collaborative practice (CP) analytical…

A Web Portal-Based Time-Aware KML Animation Tool for Exploring Spatiotemporal Dynamics of Hydrological Events

NASA Astrophysics Data System (ADS)

Bao, X.; Cai, X.; Liu, Y.

2009-12-01

Understanding spatiotemporal dynamics of hydrological events such as storms and droughts is highly valuable for decision making on disaster mitigation and recovery. Virtual Globe-based technologies such as Google Earth and Open Geospatial Consortium KML standards show great promises for collaborative exploration of such events using visual analytical approaches. However, currently there are two barriers for wider usage of such approaches. First, there lacks an easy way to use open source tools to convert legacy or existing data formats such as shapefiles, geotiff, or web services-based data sources to KML and to produce time-aware KML files. Second, an integrated web portal-based time-aware animation tool is currently not available. Thus users usually share their files in the portal but have no means to visually explore them without leaving the portal environment which the users are familiar with. We develop a web portal-based time-aware KML animation tool for viewing extreme hydrologic events. The tool is based on Google Earth JavaScript API and Java Portlet standard 2.0 JSR-286, and it is currently deployable in one of the most popular open source portal frameworks, namely Liferay. We have also developed an open source toolkit kml-soc-ncsa (http://code.google.com/p/kml-soc-ncsa/) to facilitate the conversion of multiple formats into KML and the creation of time-aware KML files. We illustrate our tool using some example cases, in which drought and storm events with both time and space dimension can be explored in this web-based KML animation portlet. The tool provides an easy-to-use web browser-based portal environment for multiple users to collaboratively share and explore their time-aware KML files as well as improving the understanding of the spatiotemporal dynamics of the hydrological events.

Encounter Detection Using Visual Analytics to Improve Maritime Domain Awareness

DTIC Science & Technology

2015-06-01

assigned to be processed in a record set consisting of all the records within a one degree of latitude by one degree of longitude square box. For the case...0.002 3 30 185 0.001 4 30 370 0.002 37 a degree of latitude by a tenth of a degree of longitude . This prototype further reduces the processing ...STATEMENT Approved for public release; distribution is unlimited 12b. DISTRIBUTION CODE 13. ABSTRACT (maximum 200 words) A visual analytics process

Integrating visualization and interaction research to improve scientific workflows.

PubMed

Keefe, Daniel F

2010-01-01

Scientific-visualization research is, nearly by necessity, interdisciplinary. In addition to their collaborators in application domains (for example, cell biology), researchers regularly build on close ties with disciplines related to visualization, such as graphics, human-computer interaction, and cognitive science. One of these ties is the connection between visualization and interaction research. This isn't a new direction for scientific visualization (see the "Early Connections" sidebar). However, momentum recently seems to be increasing toward integrating visualization research (for example, effective visual presentation of data) with interaction research (for example, innovative interactive techniques that facilitate manipulating and exploring data). We see evidence of this trend in several places, including the visualization literature and conferences.

Applications of image processing and visualization in the evaluation of murder and assault

NASA Astrophysics Data System (ADS)

Oliver, William R.; Rosenman, Julian G.; Boxwala, Aziz; Stotts, David; Smith, John; Soltys, Mitchell; Symon, James; Cullip, Tim; Wagner, Glenn

1994-09-01

Recent advances in image processing and visualization are of increasing use in the investigation of violent crime. The Digital Image Processing Laboratory at the Armed Forces Institute of Pathology in collaboration with groups at the University of North Carolina at Chapel Hill are actively exploring visualization applications including image processing of trauma images, 3D visualization, forensic database management and telemedicine. Examples of recent applications are presented. Future directions of effort include interactive consultation and image manipulation tools for forensic data exploration.

Author in the Arts: Composing and Collaborating in Text, Music, and the Visual Arts

ERIC Educational Resources Information Center

Gerben, Chris

2015-01-01

Many disciplines share similar terminology for making: creating, composing, writing, and authoring. The last term authoring, however, is problematic in how it privileges an end goal of individual authority and reward. To interrogate this term, and argue for its importance in future collaborative, interdisciplinary work, this article examines a…

Aligning Web-Based Tools to the Research Process Cycle: A Resource for Collaborative Research Projects

ERIC Educational Resources Information Center

Price, Geoffrey P.; Wright, Vivian H.

2012-01-01

Using John Creswell's Research Process Cycle as a framework, this article describes various web-based collaborative technologies useful for enhancing the organization and efficiency of educational research. Visualization tools (Cacoo) assist researchers in identifying a research problem. Resource storage tools (Delicious, Mendeley, EasyBib)…

DIVE: A Graph-based Visual Analytics Framework for Big Data

PubMed Central

Rysavy, Steven J.; Bromley, Dennis; Daggett, Valerie

2014-01-01

The need for data-centric scientific tools is growing; domains like biology, chemistry, and physics are increasingly adopting computational approaches. As a result, scientists must now deal with the challenges of big data. To address these challenges, we built a visual analytics platform named DIVE: Data Intensive Visualization Engine. DIVE is a data-agnostic, ontologically-expressive software framework capable of streaming large datasets at interactive speeds. Here we present the technical details of the DIVE platform, multiple usage examples, and a case study from the Dynameomics molecular dynamics project. We specifically highlight our novel contributions to structured data model manipulation and high-throughput streaming of large, structured datasets. PMID:24808197

Advanced engineering environment collaboration project.

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

Lamph, Jane Ann; Pomplun, Alan R.; Kiba, Grant W.

2008-12-01

The Advanced Engineering Environment (AEE) is a model for an engineering design and communications system that will enhance project collaboration throughout the nuclear weapons complex (NWC). Sandia National Laboratories and Parametric Technology Corporation (PTC) worked together on a prototype project to evaluate the suitability of a portion of PTC's Windchill 9.0 suite of data management, design and collaboration tools as the basis for an AEE. The AEE project team implemented Windchill 9.0 development servers in both classified and unclassified domains and used them to test and evaluate the Windchill tool suite relative to the needs of the NWC using weaponsmore » project use cases. A primary deliverable was the development of a new real time collaborative desktop design and engineering process using PDMLink (data management tool), Pro/Engineer (mechanical computer aided design tool) and ProductView Lite (visualization tool). Additional project activities included evaluations of PTC's electrical computer aided design, visualization, and engineering calculations applications. This report documents the AEE project work to share information and lessons learned with other NWC sites. It also provides PTC with recommendations for improving their products for NWC applications.« less

Collaborative Visualization Project: shared-technology learning environments for science learning

NASA Astrophysics Data System (ADS)

Pea, Roy D.; Gomez, Louis M.

1993-01-01

Project-enhanced science learning (PESL) provides students with opportunities for `cognitive apprenticeships' in authentic scientific inquiry using computers for data-collection and analysis. Student teams work on projects with teacher guidance to develop and apply their understanding of science concepts and skills. We are applying advanced computing and communications technologies to augment and transform PESL at-a-distance (beyond the boundaries of the individual school), which is limited today to asynchronous, text-only networking and unsuitable for collaborative science learning involving shared access to multimedia resources such as data, graphs, tables, pictures, and audio-video communication. Our work creates user technology (a Collaborative Science Workbench providing PESL design support and shared synchronous document views, program, and data access; a Science Learning Resource Directory for easy access to resources including two-way video links to collaborators, mentors, museum exhibits, media-rich resources such as scientific visualization graphics), and refine enabling technologies (audiovisual and shared-data telephony, networking) for this PESL niche. We characterize participation scenarios for using these resources and we discuss national networked access to science education expertise.

Planetary Surface Visualization and Analytics

NASA Astrophysics Data System (ADS)

Law, E. S.; Solar System Treks Team

2018-04-01

An introduction and update of the Solar System Treks Project which provides a suite of interactive visualization and analysis tools to enable users (engineers, scientists, public) to access large amounts of mapped planetary data products.

Concept of Operations Visualization for Ares I Production

NASA Technical Reports Server (NTRS)

Chilton, Jim; Smith, David Alan

2008-01-01

Establishing Computer Aided Design models of the Ares I production facility, tooling and vehicle components and integrating them into manufacturing visualizations/simulations allows Boeing and NASA to collaborate real time early in the design/development cycle. This collaboration identifies cost effective and lean solutions that can be easily shared with Ares stakeholders (e.g., other NASA Centers and potential science users). These Ares I production visualizations and analyses by their nature serve as early manufacturing improvement precursors for other Constellation elements to be built at the Michoud Assembly Facility such as Ares V and the Altair Lander. Key to this Boeing and Marshall Space Flight Center collaboration has been the use of advanced virtual manufacturing tools to understand the existing Shuttle era infrastructure and trade potential modifications to support Ares I production. These approaches are then used to determine an optimal manufacturing configuration in terms of labor efficiency, safety and facility enhancements. These same models and tools can be used in an interactive simulation of Ares I and V flight to the Space Station or moon to educate the human space constituency (e.g., government, academia, media and the public) in order to increase national and international understanding of Constellation goals and benefits.

Analytic information processing style in epilepsy patients.

PubMed

Buonfiglio, Marzia; Di Sabato, Francesco; Mandillo, Silvia; Albini, Mariarita; Di Bonaventura, Carlo; Giallonardo, Annateresa; Avanzini, Giuliano

2017-08-01

Relevant to the study of epileptogenesis is learning processing, given the pivotal role that neuroplasticity assumes in both mechanisms. Recently, evoked potential analyses showed a link between analytic cognitive style and altered neural excitability in both migraine and healthy subjects, regardless of cognitive impairment or psychological disorders. In this study we evaluated analytic/global and visual/auditory perceptual dimensions of cognitive style in patients with epilepsy. Twenty-five cryptogenic temporal lobe epilepsy (TLE) patients matched with 25 idiopathic generalized epilepsy (IGE) sufferers and 25 healthy volunteers were recruited and participated in three cognitive style tests: "Sternberg-Wagner Self-Assessment Inventory", the C. Cornoldi test series called AMOS, and the Mariani Learning style Questionnaire. Our results demonstrate a significant association between analytic cognitive style and both IGE and TLE and respectively a predominant auditory and visual analytic style (ANOVA: p values <0,0001). These findings should encourage further research to investigate information processing style and its neurophysiological correlates in epilepsy. Copyright © 2017 Elsevier Inc. All rights reserved.

Oak Ridge Bio-surveillance Toolkit (ORBiT): Integrating Big-Data Analytics with Visual Analysis for Public Health Dynamics

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

Ramanathan, Arvind; Pullum, Laura L; Steed, Chad A

In this position paper, we describe the design and implementation of the Oak Ridge Bio-surveillance Toolkit (ORBiT): a collection of novel statistical and machine learning tools implemented for (1) integrating heterogeneous traditional (e.g. emergency room visits, prescription sales data, etc.) and non-traditional (social media such as Twitter and Instagram) data sources, (2) analyzing large-scale datasets and (3) presenting the results from the analytics as a visual interface for the end-user to interact and provide feedback. We present examples of how ORBiT can be used to summarize ex- tremely large-scale datasets effectively and how user interactions can translate into the datamore » analytics process for bio-surveillance. We also present a strategy to estimate parameters relevant to dis- ease spread models from near real time data feeds and show how these estimates can be integrated with disease spread models for large-scale populations. We conclude with a perspective on how integrating data and visual analytics could lead to better forecasting and prediction of disease spread as well as improved awareness of disease susceptible regions.« less

Other Resources Related to SAM

EPA Pesticide Factsheets

Learn more about websites and information related to EPA's Selected Analytical Methods for Environmental Remediation and Recovery (SAM), including key EPA collaborators, laboratories, and research centers.

Vroom: designing an augmented environment for remote collaboration in digital cinema production

NASA Astrophysics Data System (ADS)

Margolis, Todd; Cornish, Tracy

2013-03-01

As media technologies become increasingly affordable, compact and inherently networked, new generations of telecollaborative platforms continue to arise which integrate these new affordances. Virtual reality has been primarily concerned with creating simulations of environments that can transport participants to real or imagined spaces that replace the "real world". Meanwhile Augmented Reality systems have evolved to interleave objects from Virtual Reality environments into the physical landscape. Perhaps now there is a new class of systems that reverse this precept to enhance dynamic media landscapes and immersive physical display environments to enable intuitive data exploration through collaboration. Vroom (Virtual Room) is a next-generation reconfigurable tiled display environment in development at the California Institute for Telecommunications and Information Technology (Calit2) at the University of California, San Diego. Vroom enables freely scalable digital collaboratories, connecting distributed, high-resolution visualization resources for collaborative work in the sciences, engineering and the arts. Vroom transforms a physical space into an immersive media environment with large format interactive display surfaces, video teleconferencing and spatialized audio built on a highspeed optical network backbone. Vroom enables group collaboration for local and remote participants to share knowledge and experiences. Possible applications include: remote learning, command and control, storyboarding, post-production editorial review, high resolution video playback, 3D visualization, screencasting and image, video and multimedia file sharing. To support these various scenarios, Vroom features support for multiple user interfaces (optical tracking, touch UI, gesture interface, etc.), support for directional and spatialized audio, giga-pixel image interactivity, 4K video streaming, 3D visualization and telematic production. This paper explains the design process that has been utilized to make Vroom an accessible and intuitive immersive environment for remote collaboration specifically for digital cinema production.

Equilibrium relations and bipolar cognitive mapping for online analytical processing with applications in international relations and strategic decision support.

PubMed

Zhang, Wen-Ran

2003-01-01

Bipolar logic, bipolar sets, and equilibrium relations are proposed for bipolar cognitive mapping and visualization in online analytical processing (OLAP) and online analytical mining (OLAM). As cognitive models, cognitive maps (CMs) hold great potential for clustering and visualization. Due to the lack of a formal mathematical basis, however, CM-based OLAP and OLAM have not gained popularity. Compared with existing approaches, bipolar cognitive mapping has a number of advantages. First, bipolar CMs are formal logical models as well as cognitive models. Second, equilibrium relations (with polarized reflexivity, symmetry, and transitivity), as bipolar generalizations and fusions of equivalence relations, provide a theoretical basis for bipolar visualization and coordination. Third, an equilibrium relation or CM induces bipolar partitions that distinguish disjoint coalition subsets not involved in any conflict, disjoint coalition subsets involved in a conflict, disjoint conflict subsets, and disjoint harmony subsets. Finally, equilibrium energy analysis leads to harmony and stability measures for strategic decision and multiagent coordination. Thus, this work bridges a gap for CM-based clustering and visualization in OLAP and OLAM. Basic ideas are illustrated with example CMs in international relations.

The VAST Challenge: History, Scope, and Outcomes: An introduction to the Special Issue

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

Cook, Kristin A.; Grinstein, Georges; Whiting, Mark A.

2014-10-01

Visual analytics aims to facilitate human insight from complex data via a combination of visual representations, interaction techniques, and supporting algorithms. To create new tools and techniques that achieve this goal requires that researchers have an understanding of analytical questions to be addressed, data that illustrates the complexities and ambiguities found in realistic analytic settings, and methods for evaluating whether the plausible insights are gained through use of the new methods. However, researchers do not, generally speaking, have access to analysts who can articulate their problems or operational data that is used for analysis. To fill this gap, the Visualmore » Analytics Science and Technology (VAST) Challenge has been held annually since 2006. The VAST Challenge provides an opportunity for researchers to experiment with realistic but not real problems, using realistic synthetic data with known events embedded. Since its inception, the VAST Challenge has evolved along with the visual analytics research community to pose more complex challenges, ranging from text analysis to video analysis to large scale network log analysis. The seven years of the VAST Challenge have seen advancements in research and development, education, evaluation, and in the challenge process itself. This special issue of Information Visualization highlights some of the noteworthy advancements in each of these areas. Some of these papers focus on important research questions related to the challenge itself, and other papers focus on innovative research that has been shaped by participation in the challenge. This paper describes the VAST Challenge process and benefits in detail. It also provides an introduction to and context for the remaining papers in the issue.« less

Telearch - Integrated visual simulation environment for collaborative virtual archaeology.

NASA Astrophysics Data System (ADS)

Kurillo, Gregorij; Forte, Maurizio

Archaeologists collect vast amounts of digital data around the world; however, they lack tools for integration and collaborative interaction to support reconstruction and interpretation process. TeleArch software is aimed to integrate different data sources and provide real-time interaction tools for remote collaboration of geographically distributed scholars inside a shared virtual environment. The framework also includes audio, 2D and 3D video streaming technology to facilitate remote presence of users. In this paper, we present several experimental case studies to demonstrate the integration and interaction with 3D models and geographical information system (GIS) data in this collaborative environment.

Visual Arts in the Schools: A Joint Venture.

ERIC Educational Resources Information Center

Sproll, Paul A. C.

1998-01-01

In 1994, the Rhode Island School of Design (RISD) launched a customized professional development program for art teachers, funded through a coalition of hospitals, colleges, and universities. It fostered a collaboration between RISD and city art teachers, which resulted in development of an overall strategic reform plan for visual arts education…

Students from Non-Dominant Linguistic Backgrounds Making Sense of Cosmology Visualizations

ERIC Educational Resources Information Center

Buck Bracey, Zoë E.

2017-01-01

This article presents the results of exploratory research with community college students from non-dominant linguistic backgrounds (NDLB) in an introductory astronomy class as they collaborated to reconstruct dynamic cosmology visualizations through drawing. Data included student discourse during the drawing activity, post-activity interviews, and…

Breeder survey, tools, and resources to visualize diversity and pedigree relationships at MaizeGDB

USDA-ARS?s Scientific Manuscript database

In collaboration with maize researchers, the MaizeGDB Team prepared a survey to identify breeder needs for visualizing pedigrees, diversity data, and haplotypes, and distributed it to the maize community on behalf of the Maize Genetics Executive Committee (Summer 2015). We received 48 responses from...

Interprofessional collaboration - a matter of differentiation and integration? Theoretical reflections based in the context of Norwegian childcare.

PubMed

Willumsen, Elisabeth

2008-08-01

This paper presents a selection of theoretical approaches illuminating some aspects of interprofessional collaboration, which will be related to theory of contingency as well as to the concepts of differentiation and integration. Theories that describe collaboration on an interpersonal as well as inter-organizational level are outlined and related to dynamic and contextual factors. Implications for the organization of welfare services are elucidated and a categorization of internal and external collaborative forms is proposed. A reflection model is presented in order to analyse the degree of integration in collaborative work and may serve as an analytical tool for addressing the linkage between different levels of collaboration and identifying opportunities and limitations. Some implications related to the legal mandate(s) given to childcare agencies are discussed in relation to the context of childcare in Norway.

Acts of Discovery: Using Collaborative Research to Mobilize and Generate Knowledge about Visual Arts Teaching Practice

ERIC Educational Resources Information Center

Mitchell, Donna Mathewson

2014-01-01

Visual arts teachers engage in complex work on a daily basis. This work is informed by practical knowledge that is rarely examined or drawn on in research or in the development of policy. Focusing on the work of secondary visual arts teachers, this article reports on a research program conducted in a regional area of New South Wales, Australia.…

Decision exploration lab: a visual analytics solution for decision management.

PubMed

Broeksema, Bertjan; Baudel, Thomas; Telea, Arthur G; Crisafulli, Paolo

2013-12-01

We present a visual analytics solution designed to address prevalent issues in the area of Operational Decision Management (ODM). In ODM, which has its roots in Artificial Intelligence (Expert Systems) and Management Science, it is increasingly important to align business decisions with business goals. In our work, we consider decision models (executable models of the business domain) as ontologies that describe the business domain, and production rules that describe the business logic of decisions to be made over this ontology. Executing a decision model produces an accumulation of decisions made over time for individual cases. We are interested, first, to get insight in the decision logic and the accumulated facts by themselves. Secondly and more importantly, we want to see how the accumulated facts reveal potential divergences between the reality as captured by the decision model, and the reality as captured by the executed decisions. We illustrate the motivation, added value for visual analytics, and our proposed solution and tooling through a business case from the car insurance industry.

High performance visual display for HENP detectors

NASA Astrophysics Data System (ADS)

McGuigan, Michael; Smith, Gordon; Spiletic, John; Fine, Valeri; Nevski, Pavel

2001-08-01

A high end visual display for High Energy Nuclear Physics (HENP) detectors is necessary because of the sheer size and complexity of the detector. For BNL this display will be of special interest because of STAR and ATLAS. To load, rotate, query, and debug simulation code with a modern detector simply takes too long even on a powerful work station. To visualize the HENP detectors with maximal performance we have developed software with the following characteristics. We develop a visual display of HENP detectors on BNL multiprocessor visualization server at multiple level of detail. We work with general and generic detector framework consistent with ROOT, GAUDI etc, to avoid conflicting with the many graphic development groups associated with specific detectors like STAR and ATLAS. We develop advanced OpenGL features such as transparency and polarized stereoscopy. We enable collaborative viewing of detector and events by directly running the analysis in BNL stereoscopic theatre. We construct enhanced interactive control, including the ability to slice, search and mark areas of the detector. We incorporate the ability to make a high quality still image of a view of the detector and the ability to generate animations and a fly through of the detector and output these to MPEG or VRML models. We develop data compression hardware and software so that remote interactive visualization will be possible among dispersed collaborators. We obtain real time visual display for events accumulated during simulations.

Geovisual analytics to enhance spatial scan statistic interpretation: an analysis of U.S. cervical cancer mortality

PubMed Central

Chen, Jin; Roth, Robert E; Naito, Adam T; Lengerich, Eugene J; MacEachren, Alan M

2008-01-01

Background Kulldorff's spatial scan statistic and its software implementation – SaTScan – are widely used for detecting and evaluating geographic clusters. However, two issues make using the method and interpreting its results non-trivial: (1) the method lacks cartographic support for understanding the clusters in geographic context and (2) results from the method are sensitive to parameter choices related to cluster scaling (abbreviated as scaling parameters), but the system provides no direct support for making these choices. We employ both established and novel geovisual analytics methods to address these issues and to enhance the interpretation of SaTScan results. We demonstrate our geovisual analytics approach in a case study analysis of cervical cancer mortality in the U.S. Results We address the first issue by providing an interactive visual interface to support the interpretation of SaTScan results. Our research to address the second issue prompted a broader discussion about the sensitivity of SaTScan results to parameter choices. Sensitivity has two components: (1) the method can identify clusters that, while being statistically significant, have heterogeneous contents comprised of both high-risk and low-risk locations and (2) the method can identify clusters that are unstable in location and size as the spatial scan scaling parameter is varied. To investigate cluster result stability, we conducted multiple SaTScan runs with systematically selected parameters. The results, when scanning a large spatial dataset (e.g., U.S. data aggregated by county), demonstrate that no single spatial scan scaling value is known to be optimal to identify clusters that exist at different scales; instead, multiple scans that vary the parameters are necessary. We introduce a novel method of measuring and visualizing reliability that facilitates identification of homogeneous clusters that are stable across analysis scales. Finally, we propose a logical approach to proceed through the analysis of SaTScan results. Conclusion The geovisual analytics approach described in this manuscript facilitates the interpretation of spatial cluster detection methods by providing cartographic representation of SaTScan results and by providing visualization methods and tools that support selection of SaTScan parameters. Our methods distinguish between heterogeneous and homogeneous clusters and assess the stability of clusters across analytic scales. Method We analyzed the cervical cancer mortality data for the United States aggregated by county between 2000 and 2004. We ran SaTScan on the dataset fifty times with different parameter choices. Our geovisual analytics approach couples SaTScan with our visual analytic platform, allowing users to interactively explore and compare SaTScan results produced by different parameter choices. The Standardized Mortality Ratio and reliability scores are visualized for all the counties to identify stable, homogeneous clusters. We evaluated our analysis result by comparing it to that produced by other independent techniques including the Empirical Bayes Smoothing and Kafadar spatial smoother methods. The geovisual analytics approach introduced here is developed and implemented in our Java-based Visual Inquiry Toolkit. PMID:18992163

Geovisual analytics to enhance spatial scan statistic interpretation: an analysis of U.S. cervical cancer mortality.

PubMed

Chen, Jin; Roth, Robert E; Naito, Adam T; Lengerich, Eugene J; Maceachren, Alan M

2008-11-07

Kulldorff's spatial scan statistic and its software implementation - SaTScan - are widely used for detecting and evaluating geographic clusters. However, two issues make using the method and interpreting its results non-trivial: (1) the method lacks cartographic support for understanding the clusters in geographic context and (2) results from the method are sensitive to parameter choices related to cluster scaling (abbreviated as scaling parameters), but the system provides no direct support for making these choices. We employ both established and novel geovisual analytics methods to address these issues and to enhance the interpretation of SaTScan results. We demonstrate our geovisual analytics approach in a case study analysis of cervical cancer mortality in the U.S. We address the first issue by providing an interactive visual interface to support the interpretation of SaTScan results. Our research to address the second issue prompted a broader discussion about the sensitivity of SaTScan results to parameter choices. Sensitivity has two components: (1) the method can identify clusters that, while being statistically significant, have heterogeneous contents comprised of both high-risk and low-risk locations and (2) the method can identify clusters that are unstable in location and size as the spatial scan scaling parameter is varied. To investigate cluster result stability, we conducted multiple SaTScan runs with systematically selected parameters. The results, when scanning a large spatial dataset (e.g., U.S. data aggregated by county), demonstrate that no single spatial scan scaling value is known to be optimal to identify clusters that exist at different scales; instead, multiple scans that vary the parameters are necessary. We introduce a novel method of measuring and visualizing reliability that facilitates identification of homogeneous clusters that are stable across analysis scales. Finally, we propose a logical approach to proceed through the analysis of SaTScan results. The geovisual analytics approach described in this manuscript facilitates the interpretation of spatial cluster detection methods by providing cartographic representation of SaTScan results and by providing visualization methods and tools that support selection of SaTScan parameters. Our methods distinguish between heterogeneous and homogeneous clusters and assess the stability of clusters across analytic scales. We analyzed the cervical cancer mortality data for the United States aggregated by county between 2000 and 2004. We ran SaTScan on the dataset fifty times with different parameter choices. Our geovisual analytics approach couples SaTScan with our visual analytic platform, allowing users to interactively explore and compare SaTScan results produced by different parameter choices. The Standardized Mortality Ratio and reliability scores are visualized for all the counties to identify stable, homogeneous clusters. We evaluated our analysis result by comparing it to that produced by other independent techniques including the Empirical Bayes Smoothing and Kafadar spatial smoother methods. The geovisual analytics approach introduced here is developed and implemented in our Java-based Visual Inquiry Toolkit.

State of practice and emerging application of analytical techniques of nuclear forensic analysis: highlights from the 4th Collaborative Materials Exercise of the Nuclear Forensics International Technical Working Group (ITWG)

DOE PAGES

Schwantes, Jon M.; Marsden, Oliva; Pellegrini, Kristi L.

2016-09-16

The Nuclear Forensics International Technical Working Group (ITWG) recently completed its fourth Collaborative Materials Exercise (CMX-4) in the 21 year history of the Group. This was also the largest materials exercise to date, with participating laboratories from 16 countries or international organizations. Moreover, exercise samples (including three separate samples of low enriched uranium oxide) were shipped as part of an illicit trafficking scenario, for which each laboratory was asked to conduct nuclear forensic analyses in support of a fictitious criminal investigation. In all, over 30 analytical techniques were applied to characterize exercise materials, for which ten of those techniques weremore » applied to ITWG exercises for the first time. We performed an objective review of the state of practice and emerging application of analytical techniques of nuclear forensic analysis based upon the outcome of this most recent exercise is provided.« less

State of practice and emerging application of analytical techniques of nuclear forensic analysis: highlights from the 4th Collaborative Materials Exercise of the Nuclear Forensics International Technical Working Group (ITWG)

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

Schwantes, Jon M.; Marsden, Oliva; Pellegrini, Kristi L.

The Nuclear Forensics International Technical Working Group (ITWG) recently completed its fourth Collaborative Materials Exercise (CMX-4) in the 21 year history of the Group. This was also the largest materials exercise to date, with participating laboratories from 16 countries or international organizations. Moreover, exercise samples (including three separate samples of low enriched uranium oxide) were shipped as part of an illicit trafficking scenario, for which each laboratory was asked to conduct nuclear forensic analyses in support of a fictitious criminal investigation. In all, over 30 analytical techniques were applied to characterize exercise materials, for which ten of those techniques weremore » applied to ITWG exercises for the first time. We performed an objective review of the state of practice and emerging application of analytical techniques of nuclear forensic analysis based upon the outcome of this most recent exercise is provided.« less

The Collaborative Coordination of Special Interest Groups on the Telemedicine University Network (RUTE) in Brazil.

PubMed

de Lima Verde Brito, Thiago Delevidove; Baptista, Roberto Silva; de Lima Lopes, Paulo Roberto; Haddad, Ana Estela; Messina, Luiz Ary; Torres Pisa, Ivan

2015-01-01

In Brazil the Telemedicine University Network (Rede Universitária de Telemedicina RUTE) is an initiative that among others promotes collaboration between university hospitals, universities, and health professionals through information technology infrastructure and special interest groups (SIGs) support. This paper presents results of analyses on collaboration during implementation and coordination activities of RUTE SIGs. This study is based on descriptive statistics and data visualization previously collected by RUTE national coordination relative to the status in July 2014. The analysis through collaboration graph identified the strongest collaboration RUTE units. The graph also highlights the collaborative relationship of RUTE units in form of communities, the most collaborative with each other in a communion in the same SIGs, and the less the collaborative units in the network. It should be stated that the most active units are also the oldest in the community.

The Preference of Visualization in Teaching and Learning Absolute Value

ERIC Educational Resources Information Center

Konyalioglu, Alper Cihan; Aksu, Zeki; Senel, Esma Ozge

2012-01-01

Visualization is mostly despised although it complements and--sometimes--guides the analytical process. This study mainly investigates teachers' preferences concerning the use of the visualization method and determines the extent to which they encourage their students to make use of it within the problem-solving process. This study was conducted…

DIA2: Web-based Cyberinfrastructure for Visual Analysis of Funding Portfolios.

PubMed

Madhavan, Krishna; Elmqvist, Niklas; Vorvoreanu, Mihaela; Chen, Xin; Wong, Yuetling; Xian, Hanjun; Dong, Zhihua; Johri, Aditya

2014-12-01

We present a design study of the Deep Insights Anywhere, Anytime (DIA2) platform, a web-based visual analytics system that allows program managers and academic staff at the U.S. National Science Foundation to search, view, and analyze their research funding portfolio. The goal of this system is to facilitate users' understanding of both past and currently active research awards in order to make more informed decisions of their future funding. This user group is characterized by high domain expertise yet not necessarily high literacy in visualization and visual analytics-they are essentially casual experts-and thus require careful visual and information design, including adhering to user experience standards, providing a self-instructive interface, and progressively refining visualizations to minimize complexity. We discuss the challenges of designing a system for casual experts and highlight how we addressed this issue by modeling the organizational structure and workflows of the NSF within our system. We discuss each stage of the design process, starting with formative interviews, prototypes, and finally live deployments and evaluation with stakeholders.

Interactive visual exploration and analysis of origin-destination data

NASA Astrophysics Data System (ADS)

Ding, Linfang; Meng, Liqiu; Yang, Jian; Krisp, Jukka M.

2018-05-01

In this paper, we propose a visual analytics approach for the exploration of spatiotemporal interaction patterns of massive origin-destination data. Firstly, we visually query the movement database for data at certain time windows. Secondly, we conduct interactive clustering to allow the users to select input variables/features (e.g., origins, destinations, distance, and duration) and to adjust clustering parameters (e.g. distance threshold). The agglomerative hierarchical clustering method is applied for the multivariate clustering of the origin-destination data. Thirdly, we design a parallel coordinates plot for visualizing the precomputed clusters and for further exploration of interesting clusters. Finally, we propose a gradient line rendering technique to show the spatial and directional distribution of origin-destination clusters on a map view. We implement the visual analytics approach in a web-based interactive environment and apply it to real-world floating car data from Shanghai. The experiment results show the origin/destination hotspots and their spatial interaction patterns. They also demonstrate the effectiveness of our proposed approach.

Real-Time Visualization of Network Behaviors for Situational Awareness

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

Best, Daniel M.; Bohn, Shawn J.; Love, Douglas V.

Plentiful, complex, and dynamic data make understanding the state of an enterprise network difficult. Although visualization can help analysts understand baseline behaviors in network traffic and identify off-normal events, visual analysis systems often do not scale well to operational data volumes (in the hundreds of millions to billions of transactions per day) nor to analysis of emergent trends in real-time data. We present a system that combines multiple, complementary visualization techniques coupled with in-stream analytics, behavioral modeling of network actors, and a high-throughput processing platform called MeDICi. This system provides situational understanding of real-time network activity to help analysts takemore » proactive response steps. We have developed these techniques using requirements gathered from the government users for which the tools are being developed. By linking multiple visualization tools to a streaming analytic pipeline, and designing each tool to support a particular kind of analysis (from high-level awareness to detailed investigation), analysts can understand the behavior of a network across multiple levels of abstraction.« less

ProteoLens: a visual analytic tool for multi-scale database-driven biological network data mining.

PubMed

Huan, Tianxiao; Sivachenko, Andrey Y; Harrison, Scott H; Chen, Jake Y

2008-08-12

New systems biology studies require researchers to understand how interplay among myriads of biomolecular entities is orchestrated in order to achieve high-level cellular and physiological functions. Many software tools have been developed in the past decade to help researchers visually navigate large networks of biomolecular interactions with built-in template-based query capabilities. To further advance researchers' ability to interrogate global physiological states of cells through multi-scale visual network explorations, new visualization software tools still need to be developed to empower the analysis. A robust visual data analysis platform driven by database management systems to perform bi-directional data processing-to-visualizations with declarative querying capabilities is needed. We developed ProteoLens as a JAVA-based visual analytic software tool for creating, annotating and exploring multi-scale biological networks. It supports direct database connectivity to either Oracle or PostgreSQL database tables/views, on which SQL statements using both Data Definition Languages (DDL) and Data Manipulation languages (DML) may be specified. The robust query languages embedded directly within the visualization software help users to bring their network data into a visualization context for annotation and exploration. ProteoLens supports graph/network represented data in standard Graph Modeling Language (GML) formats, and this enables interoperation with a wide range of other visual layout tools. The architectural design of ProteoLens enables the de-coupling of complex network data visualization tasks into two distinct phases: 1) creating network data association rules, which are mapping rules between network node IDs or edge IDs and data attributes such as functional annotations, expression levels, scores, synonyms, descriptions etc; 2) applying network data association rules to build the network and perform the visual annotation of graph nodes and edges according to associated data values. We demonstrated the advantages of these new capabilities through three biological network visualization case studies: human disease association network, drug-target interaction network and protein-peptide mapping network. The architectural design of ProteoLens makes it suitable for bioinformatics expert data analysts who are experienced with relational database management to perform large-scale integrated network visual explorations. ProteoLens is a promising visual analytic platform that will facilitate knowledge discoveries in future network and systems biology studies.

Using a Practical Instructional Development Process to Show That Integrating Lab and Active Learning Benefits Undergraduate Analytical Chemistry

ERIC Educational Resources Information Center

Goacher, Robyn E.; Kline, Cynthia M.; Targus, Alexis; Vermette, Paul J.

2017-01-01

We describe how a practical instructional development process helped a first-year assistant professor rapidly develop, implement, and assess the impact on her Analytical Chemistry course caused by three changes: (a) moving the lab into the same semester as the lecture, (b) developing a more collaborative classroom environment, and (c) increasing…

7 CFR 90.103 - [Reserved

Code of Federal Regulations, 2010 CFR

2010-01-01

... most recent years: (a) Prepared solution standardizations; (b) Recovery studies by known analyte... check sample testing or collaborative studies; (g) Daily critical parameter checks of equipment, such as...

7 CFR 90.103 - [Reserved

Code of Federal Regulations, 2011 CFR

2011-01-01

... most recent years: (a) Prepared solution standardizations; (b) Recovery studies by known analyte... check sample testing or collaborative studies; (g) Daily critical parameter checks of equipment, such as...

Using Maps in Web Analytics to Evaluate the Impact of Web-Based Extension Programs

ERIC Educational Resources Information Center

Veregin, Howard

2015-01-01

Maps can be a valuable addition to the Web analytics toolbox for Extension programs that use the Web to disseminate information. Extension professionals use Web analytics tools to evaluate program impacts. Maps add a unique perspective through visualization and analysis of geographic patterns and their relationships to other variables. Maps can…

An Agent Based Collaborative Simplification of 3D Mesh Model

NASA Astrophysics Data System (ADS)

Wang, Li-Rong; Yu, Bo; Hagiwara, Ichiro

Large-volume mesh model faces the challenge in fast rendering and transmission by Internet. The current mesh models obtained by using three-dimensional (3D) scanning technology are usually very large in data volume. This paper develops a mobile agent based collaborative environment on the development platform of mobile-C. Communication among distributed agents includes grasping image of visualized mesh model, annotation to grasped image and instant message. Remote and collaborative simplification can be efficiently conducted by Internet.

Forging a link between mentoring and collaboration: a new training model for implementation science.

PubMed

Luke, Douglas A; Baumann, Ana A; Carothers, Bobbi J; Landsverk, John; Proctor, Enola K

2016-10-13

Training investigators for the rapidly developing field of implementation science requires both mentoring and scientific collaboration. Using social network descriptive analyses, visualization, and modeling, this paper presents results of an evaluation of the mentoring and collaborations fostered over time through the National Institute of Mental Health (NIMH) supported by Implementation Research Institute (IRI). Data were comprised of IRI participant self-reported collaborations and mentoring relationships, measured in three annual surveys from 2012 to 2014. Network descriptive statistics, visualizations, and network statistical modeling were conducted to examine patterns of mentoring and collaboration among IRI participants and to model the relationship between mentoring and subsequent collaboration. Findings suggest that IRI is successful in forming mentoring relationships among its participants, and that these mentoring relationships are related to future scientific collaborations. Exponential random graph network models demonstrated that mentoring received in 2012 was positively and significantly related to the likelihood of having a scientific collaboration 2 years later in 2014 (p = 0.001). More specifically, mentoring was significantly related to future collaborations focusing on new research (p = 0.009), grant submissions (p = 0.003), and publications (p = 0.017). Predictions based on the network model suggest that for every additional mentoring relationships established in 2012, the likelihood of a scientific collaboration 2 years later is increased by almost 7 %. These results support the importance of mentoring in implementation science specifically and team science more generally. Mentoring relationships were established quickly and early by the IRI core faculty. IRI fellows reported increasing scientific collaboration of all types over time, including starting new research, submitting new grants, presenting research results, and publishing peer-reviewed papers. Statistical network models demonstrated that mentoring was strongly and significantly related to subsequent scientific collaboration, which supported a core design principle of the IRI. Future work should establish the link between mentoring and scientific productivity. These results may be of interest to team science, as they suggest the importance of mentoring for future team collaborations, as well as illustrate the utility of network analysis for studying team characteristics and activities.

Visualization and Analytics Tools for Infectious Disease Epidemiology: A Systematic Review

PubMed Central

Carroll, Lauren N.; Au, Alan P.; Detwiler, Landon Todd; Fu, Tsung-chieh; Painter, Ian S.; Abernethy, Neil F.

2014-01-01

Background A myriad of new tools and algorithms have been developed to help public health professionals analyze and visualize the complex data used in infectious disease control. To better understand approaches to meet these users' information needs, we conducted a systematic literature review focused on the landscape of infectious disease visualization tools for public health professionals, with a special emphasis on geographic information systems (GIS), molecular epidemiology, and social network analysis. The objectives of this review are to: (1) Identify public health user needs and preferences for infectious disease information visualization tools; (2) Identify existing infectious disease information visualization tools and characterize their architecture and features; (3) Identify commonalities among approaches applied to different data types; and (4) Describe tool usability evaluation efforts and barriers to the adoption of such tools. Methods We identified articles published in English from January 1, 1980 to June 30, 2013 from five bibliographic databases. Articles with a primary focus on infectious disease visualization tools, needs of public health users, or usability of information visualizations were included in the review. Results A total of 88 articles met our inclusion criteria. Users were found to have diverse needs, preferences and uses for infectious disease visualization tools, and the existing tools are correspondingly diverse. The architecture of the tools was inconsistently described, and few tools in the review discussed the incorporation of usability studies or plans for dissemination. Many studies identified concerns regarding data sharing, confidentiality and quality. Existing tools offer a range of features and functions that allow users to explore, analyze, and visualize their data, but the tools are often for siloed applications. Commonly cited barriers to widespread adoption included lack of organizational support, access issues, and misconceptions about tool use. Discussion and Conclusion As the volume and complexity of infectious disease data increases, public health professionals must synthesize highly disparate data to facilitate communication with the public and inform decisions regarding measures to protect the public's health. Our review identified several themes: consideration of users' needs, preferences, and computer literacy; integration of tools into routine workflow; complications associated with understanding and use of visualizations; and the role of user trust and organizational support in the adoption of these tools. Interoperability also emerged as a prominent theme, highlighting challenges associated with the increasingly collaborative and interdisciplinary nature of infectious disease control and prevention. Future work should address methods for representing uncertainty and missing data to avoid misleading users as well as strategies to minimize cognitive overload. PMID:24747356

Visualization and analytics tools for infectious disease epidemiology: a systematic review.

PubMed

Carroll, Lauren N; Au, Alan P; Detwiler, Landon Todd; Fu, Tsung-Chieh; Painter, Ian S; Abernethy, Neil F

2014-10-01

A myriad of new tools and algorithms have been developed to help public health professionals analyze and visualize the complex data used in infectious disease control. To better understand approaches to meet these users' information needs, we conducted a systematic literature review focused on the landscape of infectious disease visualization tools for public health professionals, with a special emphasis on geographic information systems (GIS), molecular epidemiology, and social network analysis. The objectives of this review are to: (1) identify public health user needs and preferences for infectious disease information visualization tools; (2) identify existing infectious disease information visualization tools and characterize their architecture and features; (3) identify commonalities among approaches applied to different data types; and (4) describe tool usability evaluation efforts and barriers to the adoption of such tools. We identified articles published in English from January 1, 1980 to June 30, 2013 from five bibliographic databases. Articles with a primary focus on infectious disease visualization tools, needs of public health users, or usability of information visualizations were included in the review. A total of 88 articles met our inclusion criteria. Users were found to have diverse needs, preferences and uses for infectious disease visualization tools, and the existing tools are correspondingly diverse. The architecture of the tools was inconsistently described, and few tools in the review discussed the incorporation of usability studies or plans for dissemination. Many studies identified concerns regarding data sharing, confidentiality and quality. Existing tools offer a range of features and functions that allow users to explore, analyze, and visualize their data, but the tools are often for siloed applications. Commonly cited barriers to widespread adoption included lack of organizational support, access issues, and misconceptions about tool use. As the volume and complexity of infectious disease data increases, public health professionals must synthesize highly disparate data to facilitate communication with the public and inform decisions regarding measures to protect the public's health. Our review identified several themes: consideration of users' needs, preferences, and computer literacy; integration of tools into routine workflow; complications associated with understanding and use of visualizations; and the role of user trust and organizational support in the adoption of these tools. Interoperability also emerged as a prominent theme, highlighting challenges associated with the increasingly collaborative and interdisciplinary nature of infectious disease control and prevention. Future work should address methods for representing uncertainty and missing data to avoid misleading users as well as strategies to minimize cognitive overload. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

From Streaming Data to Streaming Insights: The Impact of Data Velocities on Mental Models

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

Endert, Alexander; Pike, William A.; Cook, Kristin A.

The rise of Big Data has influenced the design and technical implementation of visual analytic tools required to handle the increased volumes, velocities, and varieties of data. This has required a set of data management and computational advancements to allow us to store and compute on such datasets. However, as the ultimate goal of visual analytic technology is to enable the discovery and creation of insights from the users, an under-explored area is understanding how these datasets impact their mental models. That is, how have the analytic processes and strategies of users changed? How have users changed their perception ofmore » how to leverage, and ask questions of, these datasets?« less

The Use of Visual Approach in Teaching and Learning the Epsilon-Delta Definition of Continuity

ERIC Educational Resources Information Center

Pešic, Duška; Pešic, Aleksandar

2015-01-01

In this paper we introduce a new collaborative technique in teaching and learning the epsilon-delta definition of a continuous function at the point from its domain, which connects mathematical logic, combinatorics and calculus. This collaborative approach provides an opportunity for mathematical high school students to engage in mathematical…

A Methodological Approach to Support Collaborative Media Creation in an E-Learning Higher Education Context

ERIC Educational Resources Information Center

Ornellas, Adriana; Muñoz Carril, Pablo César

2014-01-01

This article outlines a methodological approach to the creation, production and dissemination of online collaborative audio-visual projects, using new social learning technologies and open-source video tools, which can be applied to any e-learning environment in higher education. The methodology was developed and used to design a course in the…

Making It All Count: A Cross-Disciplinary Collaboration Model Incorporating Scholarship, Creative Activity, and Student Engagement

ERIC Educational Resources Information Center

Dailey, Rocky; Hauschild-Mork, Melissa

2017-01-01

This study takes a grounded theory approach as a basis for a case study examining a cross-disciplinary artistic and academic collaborative project involving faculty from the areas of English, music, dance, theatre, design, and visual journalism resulting in the creation of research, scholarly, and creative activity that fosters student engagement…

Educational Visualizations in 3D Collaborative Virtual Environments: A Methodology

ERIC Educational Resources Information Center

Fominykh, Mikhail; Prasolova-Forland, Ekaterina

2012-01-01

Purpose: Collaborative virtual environments (CVEs) have become increasingly popular in educational settings and the role of 3D content is becoming more and more important. Still, there are many challenges in this area, such as lack of empirical studies that provide design for educational activities in 3D CVEs and lack of norms of how to support…

Slushy weightings for the optimal pilot model. [considering visual tracking task

NASA Technical Reports Server (NTRS)

Dillow, J. D.; Picha, D. G.; Anderson, R. O.

1975-01-01

A pilot model is described which accounts for the effect of motion cues in a well defined visual tracking task. The effect of visual and motion cues are accounted for in the model in two ways. First, the observation matrix in the pilot model is structured to account for the visual and motion inputs presented to the pilot. Secondly, the weightings in the quadratic cost function associated with the pilot model are modified to account for the pilot's perception of the variables he considers important in the task. Analytic results obtained using the pilot model are compared to experimental results and in general good agreement is demonstrated. The analytic model yields small improvements in tracking performance with the addition of motion cues for easily controlled task dynamics and large improvements in tracking performance with the addition of motion cues for difficult task dynamics.

Visual analytics techniques for large multi-attribute time series data

NASA Astrophysics Data System (ADS)

Hao, Ming C.; Dayal, Umeshwar; Keim, Daniel A.

2008-01-01

Time series data commonly occur when variables are monitored over time. Many real-world applications involve the comparison of long time series across multiple variables (multi-attributes). Often business people want to compare this year's monthly sales with last year's sales to make decisions. Data warehouse administrators (DBAs) want to know their daily data loading job performance. DBAs need to detect the outliers early enough to act upon them. In this paper, two new visual analytic techniques are introduced: The color cell-based Visual Time Series Line Charts and Maps highlight significant changes over time in a long time series data and the new Visual Content Query facilitates finding the contents and histories of interesting patterns and anomalies, which leads to root cause identification. We have applied both methods to two real-world applications to mine enterprise data warehouse and customer credit card fraud data to illustrate the wide applicability and usefulness of these techniques.

Effective Collaboration between Physical Therapists and Teachers of Students with Visual Impairments Who Are Working with Students with Multiple Disabilities and Visual Impairments

ERIC Educational Resources Information Center

Stearns, Erica

2017-01-01

In this article, Erica Stearns writes that she has worked as a physical therapist assistant in various settings for nearly 20 years. Her experiences have been in long-term and acute care settings, short-term rehabilitation and the school system. For the past three years she has also worked as a teacher of students with visual impairments.…

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

King, A.G.

The Pacific Northwest Laboratory (PNL)/Analytical Chemistry Laboratory (ACL) and the Westinghouse Hanford Company (WHC)/Process Analytical Laboratory (PAL) provide analytical support services to various environmental restoration and waste management projects/programs at Hanford. In response to a US Department of Energy -- Richland Field Office (DOE-RL) audit, which questioned the comparability of analytical methods employed at each laboratory, the Sample Exchange/Exchange (SEE) program was initiated. The SEE Program is a selfassessment program designed to compare analytical methods of the PAL and ACL laboratories using sitespecific waste material. The SEE program is managed by a collaborative, the Quality Assurance Triad (Triad). Triad membershipmore » is made up of representatives from the WHC/PAL, PNL/ACL, and WHC Hanford Analytical Services Management (HASM) organizations. The Triad works together to design/evaluate/implement each phase of the SEE Program.« less

A Grass-Roots Endeavor To Develop a Permanent University Program for Vision Professionals: The North Carolina Model.

ERIC Educational Resources Information Center

Walker, Brad R.; Bozeman, Laura A.

2002-01-01

This article describes a collaborative process that parents, teachers, consumers, and advocacy groups in North Carolina used to successfully establish a permanently funded university training program specializing in visual impairments, the Visual Impairment Training Program. Within this process several factors were identified that contributed to…

Seventh Grade Students and the Visual Messages They Love

ERIC Educational Resources Information Center

De Abreu, Belinha

2008-01-01

Most seventh grade students partially define themselves through everyday media messages. As a part of understanding how these images and the media impacts their lives, the author collaborated with her colleagues to develop a unit to help teens learn how visual messages such as those in pictures, media icons, logos, slogans, clothing, toys, and…

The DaVinci Project: Multimedia in Art and Chemistry.

ERIC Educational Resources Information Center

Simonson, Michael; Schlosser, Charles

1998-01-01

Provides an overview of the DaVinci Project, a collaboration of students, teachers, and researchers in chemistry and art to develop multimedia materials for grades 3-12 visualizing basic concepts in chemistry and visual art. Topics addressed include standards in art and science; the conceptual framework for the project; and project goals,…

Consultation and Collaboration on Health Self-Management for People Who Are Visually Impaired from Diabetes.

ERIC Educational Resources Information Center

Cleary, Margaret E.

1993-01-01

The expertise of rehabilitation teachers and diabetes nurse educators can complement each other in components of diabetes management for people who have become visually impaired. The role of each professional involves education; integration of diabetes self-management into a comprehensive rehabilitation program; nutrition; exercise; medication,…

Becoming Theatrical: Performing Narrative Research, Staging Visual Representation

ERIC Educational Resources Information Center

Valle, Jan W.; Connor, David J.

2012-01-01

This article describes a collaborative project among the author of a book about mothers and special education (based on a collection of oral narratives of mothers who represent diverse generations, races, and social classes), a playwright, and an artist. Together, they created a theatrical and visual staging of the author's narrative research. The…

SensorDB: a virtual laboratory for the integration, visualization and analysis of varied biological sensor data.

PubMed

Salehi, Ali; Jimenez-Berni, Jose; Deery, David M; Palmer, Doug; Holland, Edward; Rozas-Larraondo, Pablo; Chapman, Scott C; Georgakopoulos, Dimitrios; Furbank, Robert T

2015-01-01

To our knowledge, there is no software or database solution that supports large volumes of biological time series sensor data efficiently and enables data visualization and analysis in real time. Existing solutions for managing data typically use unstructured file systems or relational databases. These systems are not designed to provide instantaneous response to user queries. Furthermore, they do not support rapid data analysis and visualization to enable interactive experiments. In large scale experiments, this behaviour slows research discovery, discourages the widespread sharing and reuse of data that could otherwise inform critical decisions in a timely manner and encourage effective collaboration between groups. In this paper we present SensorDB, a web based virtual laboratory that can manage large volumes of biological time series sensor data while supporting rapid data queries and real-time user interaction. SensorDB is sensor agnostic and uses web-based, state-of-the-art cloud and storage technologies to efficiently gather, analyse and visualize data. Collaboration and data sharing between different agencies and groups is thereby facilitated. SensorDB is available online at http://sensordb.csiro.au.

Integrating Heterogeneous Healthcare Datasets and Visual Analytics for Disease Bio-surveillance and Dynamics

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

Ramanathan, Arvind; Pullum, Laura L; Steed, Chad A

2013-01-01

n this paper, we present an overview of the big data chal- lenges in disease bio-surveillance and then discuss the use of visual analytics for integrating data and turning it into knowl- edge. We will explore two integration scenarios: (1) combining text and multimedia sources to improve situational awareness and (2) enhancing disease spread model data with real-time bio-surveillance data. Together, the proposed integration methodologies can improve awareness about when, where and how emerging diseases can affect wide geographic regions.

Semantic Interaction for Visual Analytics: Toward Coupling Cognition and Computation

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

Endert, Alexander

2014-07-01

The dissertation discussed in this article [1] was written in the midst of an era of digitization. The world is becoming increasingly instrumented with sensors, monitoring, and other methods for generating data describing social, physical, and natural phenomena. Thus, data exist with the potential of being analyzed to uncover, or discover, the phenomena from which it was created. However, as the analytic models leveraged to analyze these data continue to increase in complexity and computational capability, how can visualizations and user interaction methodologies adapt and evolve to continue to foster discovery and sensemaking?

A Graph Based Interface for Representing Volume Visualization Results

NASA Technical Reports Server (NTRS)

Patten, James M.; Ma, Kwan-Liu

1998-01-01

This paper discusses a graph based user interface for representing the results of the volume visualization process. As images are rendered, they are connected to other images in a graph based on their rendering parameters. The user can take advantage of the information in this graph to understand how certain rendering parameter changes affect a dataset, making the visualization process more efficient. Because the graph contains more information than is contained in an unstructured history of images, the image graph is also helpful for collaborative visualization and animation.

Visual business ecosystem intelligence: lessons from the field.

PubMed

Basole, Rahul C

2014-01-01

Macroscopic insight into business ecosystems is becoming increasingly important. With the emergence of new digital business data, opportunities exist to develop rich, interactive visual-analytics tools. Georgia Institute of Technology researchers have been developing and implementing visual business ecosystem intelligence tools in corporate settings. This article discusses the challenges they faced, the lessons learned, and opportunities for future research.

A Virtual World of Visualization

NASA Technical Reports Server (NTRS)

1998-01-01

In 1990, Sterling Software, Inc., developed the Flow Analysis Software Toolkit (FAST) for NASA Ames on contract. FAST is a workstation based modular analysis and visualization tool. It is used to visualize and animate grids and grid oriented data, typically generated by finite difference, finite element and other analytical methods. FAST is now available through COSMIC, NASA's software storehouse.

Meta-analysis of individual registry results enhances international registry collaboration.

PubMed

Paxton, Elizabeth W; Mohaddes, Maziar; Laaksonen, Inari; Lorimer, Michelle; Graves, Stephen E; Malchau, Henrik; Namba, Robert S; Kärrholm, John; Rolfson, Ola; Cafri, Guy

2018-03-28

Background and purpose - Although common in medical research, meta-analysis has not been widely adopted in registry collaborations. A meta-analytic approach in which each registry conducts a standardized analysis on its own data followed by a meta-analysis to calculate a weighted average of the estimates allows collaboration without sharing patient-level data. The value of meta-analysis as an alternative to individual patient data analysis is illustrated in this study by comparing the risk of revision of porous tantalum cups versus other uncemented cups in primary total hip arthroplasties from Sweden, Australia, and a US registry (2003-2015). Patients and methods - For both individual patient data analysis and meta-analysis approaches a Cox proportional hazard model was fit for time to revision, comparing porous tantalum (n = 23,201) with other uncemented cups (n = 128,321). Covariates included age, sex, diagnosis, head size, and stem fixation. In the meta-analysis approach, treatment effect size (i.e., Cox model hazard ratio) was calculated within each registry and a weighted average for the individual registries' estimates was calculated. Results - Patient-level data analysis and meta-analytic approaches yielded the same results with the porous tantalum cups having a higher risk of revision than other uncemented cups (HR (95% CI) 1.6 (1.4-1.7) and HR (95% CI) 1.5 (1.4-1.7), respectively). Adding the US cohort to the meta-analysis led to greater generalizability, increased precision of the treatment effect, and similar findings (HR (95% CI) 1.6 (1.4-1.7)) with increased risk of porous tantalum cups. Interpretation - The meta-analytic technique is a viable option to address privacy, security, and data ownership concerns allowing more expansive registry collaboration, greater generalizability, and increased precision of treatment effects.

Storyline Visualizations of Eye Tracking of Movie Viewing

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

Balint, John T.; Arendt, Dustin L.; Blaha, Leslie M.

Storyline visualizations offer an approach that promises to capture the spatio-temporal characteristics of individual observers and simultaneously illustrate emerging group behaviors. We develop a visual analytics approach to parsing, aligning, and clustering fixation sequences from eye tracking data. Visualization of the results captures the similarities and differences across a group of observers performing a common task. We apply our storyline approach to visualize gaze patterns of people watching dynamic movie clips. Storylines mitigate some of the shortcomings of existent spatio-temporal visualization techniques and, importantly, continue to highlight individual observer behavioral dynamics.

Improving collaboration between Primary Care Research Networks using Access Grid technology.

PubMed

Nagykaldi, Zsolt; Fox, Chester; Gallo, Steve; Stone, Joseph; Fontaine, Patricia; Peterson, Kevin; Arvanitis, Theodoros

2008-01-01

Access Grid (AG) is an Internet2-driven, high performance audio-visual conferencing technology used worldwide by academic and government organisations to enhance communication, human interaction and group collaboration. AG technology is particularly promising for improving academic multi-centre research collaborations. This manuscript describes how the AG technology was utilised by the electronic Primary Care Research Network (ePCRN) that is part of the National Institutes of Health (NIH) Roadmap initiative to improve primary care research and collaboration among practice-based research networks (PBRNs) in the USA. It discusses the design, installation and use of AG implementations, potential future applications, barriers to adoption, and suggested solutions.

Learner Dashboards a Double-Edged Sword? Students' Sense-Making of a Collaborative Critical Reading and Learning Analytics Environment for Fostering 21st-Century Literacies

ERIC Educational Resources Information Center

Pei-Ling Tan, Jennifer; Koh, Elizabeth; Jonathan, Christin; Yang, Simon

2017-01-01

The affordances of learning analytics (LA) tools and solutions are being increasingly harnessed for enhancing 21st century pedagogical and learning strategies and outcomes. However, use cases and empirical understandings of students' experiences with LA tools and environments aimed at fostering 21st century literacies, especially in the K-12…

Commentary on "Theory-Led Design of Instruments and Representations in Learning Analytics: Developing a Novel Tool for Orchestration of Online Collaborative Learning"

ERIC Educational Resources Information Center

Teplovs, Chris

2015-01-01

This commentary reflects on the contributions to learning analytics and theory by a paper that describes how multiple theoretical frameworks were woven together to inform the creation of a new, automated discourse analysis tool. The commentary highlights the contributions of the original paper, provides some alternative approaches, and touches on…

Incorporating temporal variation in seabird telemetry data: time variant kernel density models

USGS Publications Warehouse

Gilbert, Andrew; Adams, Evan M.; Anderson, Carl; Berlin, Alicia; Bowman, Timothy D.; Connelly, Emily; Gilliland, Scott; Gray, Carrie E.; Lepage, Christine; Meattey, Dustin; Montevecchi, William; Osenkowski, Jason; Savoy, Lucas; Stenhouse, Iain; Williams, Kathryn

2015-01-01

A key component of the Mid-Atlantic Baseline Studies project was tracking the individual movements of focal marine bird species (Red-throated Loon [Gavia stellata], Northern Gannet [Morus bassanus], and Surf Scoter [Melanitta perspicillata]) through the use of satellite telemetry. This element of the project was a collaborative effort with the Department of Energy (DOE), Bureau of Ocean Energy Management (BOEM), the U.S. Fish and Wildlife Service (USFWS), and Sea Duck Joint Venture (SDJV), among other organizations. Satellite telemetry is an effective and informative tool for understanding individual animal movement patterns, allowing researchers to mark an individual once, and thereafter follow the movements of the animal in space and time. Aggregating telemetry data from multiple individuals can provide information about the spatial use and temporal movements of populations. Tracking data is three dimensional, with the first two dimensions, X and Y, ordered along the third dimension, time. GIS software has many capabilities to store, analyze and visualize the location information, but little or no support for visualizing the temporal data, and tools for processing temporal data are lacking. We explored several ways of analyzing the movement patterns using the spatiotemporal data provided by satellite tags. Here, we present the results of one promising method: time-variant kernel density analysis (Keating and Cherry, 2009). The goal of this chapter is to demonstrate new methods in spatial analysis to visualize and interpret tracking data for a large number of individual birds across time in the mid-Atlantic study area and beyond. In this chapter, we placed greater emphasis on analytical methods than on the behavior and ecology of the animals tracked. For more detailed examinations of the ecology and wintering habitat use of the focal species in the midAtlantic, see Chapters 20-22.

WC WAVE - Integrating Diverse Hydrological-Modeling Data and Services Into an Interoperable Geospatial Infrastructure

NASA Astrophysics Data System (ADS)

Hudspeth, W. B.; Baros, S.; Barrett, H.; Savickas, J.; Erickson, J.

2015-12-01

WC WAVE (Western Consortium for Watershed Analysis, Visualization and Exploration) is a collaborative research project between the states of Idaho, Nevada, and New Mexico that is funded under the National Science Foundation's Experimental Program to Stimulate Competitive Research (EPSCoR). The goal of the project is to understand and document the effects of climate change on interactions between precipitation, vegetation growth, soil moisture and other landscape properties. These interactions are modeled within a framework we refer to as a virtual watershed (VW), a computer infrastructure that simulates watershed dynamics by linking scientific modeling, visualization, and data management components into a coherent whole. Developed and hosted at the Earth Data Analysis Center, University of New Mexico, the virtual watershed has a number of core functions which include: a) streamlined access to data required for model initialization and boundary conditions; b) the development of analytic scenarios through interactive visualization of available data and the storage of model configuration options; c) coupling of hydrological models through the rapid assimilation of model outputs into the data management system for access and use by sequent models. The WC-WAVE virtual watershed accomplishes these functions by provision of large-scale vector and raster data discovery, subsetting, and delivery via Open Geospatial Consortium (OGC) and REST web service standards. Central to the virtual watershed is the design and use of an innovative array of metadata elements that permits the stepwise coupling of diverse hydrological models (e.g. ISNOBAL, PRMS, CASiMiR) and input data to rapidly assess variation in outcomes under different climatic conditions. We present details on the architecture and functionality of the virtual watershed, results from three western U.S. watersheds, and discuss the realized benefits to watershed science of employing this integrated solution.

Analysis, Mining and Visualization Service at NCSA

NASA Astrophysics Data System (ADS)

Wilhelmson, R.; Cox, D.; Welge, M.

2004-12-01

NCSA's goal is to create a balanced system that fully supports high-end computing as well as: 1) high-end data management and analysis; 2) visualization of massive, highly complex data collections; 3) large databases; 4) geographically distributed Grid computing; and 5) collaboratories, all based on a secure computational environment and driven with workflow-based services. To this end NCSA has defined a new technology path that includes the integration and provision of cyberservices in support of data analysis, mining, and visualization. NCSA has begun to develop and apply a data mining system-NCSA Data-to-Knowledge (D2K)-in conjunction with both the application and research communities. NCSA D2K will enable the formation of model-based application workflows and visual programming interfaces for rapid data analysis. The Java-based D2K framework, which integrates analytical data mining methods with data management, data transformation, and information visualization tools, will be configurable from the cyberservices (web and grid services, tools, ..) viewpoint to solve a wide range of important data mining problems. This effort will use modules, such as a new classification methods for the detection of high-risk geoscience events, and existing D2K data management, machine learning, and information visualization modules. A D2K cyberservices interface will be developed to seamlessly connect client applications with remote back-end D2K servers, providing computational resources for data mining and integration with local or remote data stores. This work is being coordinated with SDSC's data and services efforts. The new NCSA Visualization embedded workflow environment (NVIEW) will be integrated with D2K functionality to tightly couple informatics and scientific visualization with the data analysis and management services. Visualization services will access and filter disparate data sources, simplifying tasks such as fusing related data from distinct sources into a coherent visual representation. This approach enables collaboration among geographically dispersed researchers via portals and front-end clients, and the coupling with data management services enables recording associations among datasets and building annotation systems into visualization tools and portals, giving scientists a persistent, shareable, virtual lab notebook. To facilitate provision of these cyberservices to the national community, NCSA will be providing a computational environment for large-scale data assimilation, analysis, mining, and visualization. This will be initially implemented on the new 512 processor shared memory SGI's recently purchased by NCSA. In addition to standard batch capabilities, NCSA will provide on-demand capabilities for those projects requiring rapid response (e.g., development of severe weather, earthquake events) for decision makers. It will also be used for non-sequential interactive analysis of data sets where it is important have access to large data volumes over space and time.

Coping with Volume and Variety in Temporal Event Sequences: Strategies for Sharpening Analytic Focus.

PubMed

Fan Du; Shneiderman, Ben; Plaisant, Catherine; Malik, Sana; Perer, Adam

2017-06-01

The growing volume and variety of data presents both opportunities and challenges for visual analytics. Addressing these challenges is needed for big data to provide valuable insights and novel solutions for business, security, social media, and healthcare. In the case of temporal event sequence analytics it is the number of events in the data and variety of temporal sequence patterns that challenges users of visual analytic tools. This paper describes 15 strategies for sharpening analytic focus that analysts can use to reduce the data volume and pattern variety. Four groups of strategies are proposed: (1) extraction strategies, (2) temporal folding, (3) pattern simplification strategies, and (4) iterative strategies. For each strategy, we provide examples of the use and impact of this strategy on volume and/or variety. Examples are selected from 20 case studies gathered from either our own work, the literature, or based on email interviews with individuals who conducted the analyses and developers who observed analysts using the tools. Finally, we discuss how these strategies might be combined and report on the feedback from 10 senior event sequence analysts.

Data Wrangling Within Different Astronomy Career Trajectories

NASA Astrophysics Data System (ADS)

Guillen, Reynal; Gu, D.; Holbrook, J.; Murillo, L.; Traweek, S.

2012-01-01

Five kinds of astronomers work with large data sets: cosmologists, data analysts, instrumentation people, observers, and numerical theorists. Each of these career trajectories can diverge and converge in and out of collaborations with each other and perform different kinds of work. Nonetheless, each group defines and wrangles data differently. This poster characterizes their different meanings of data, analytic skills, techniques, and technologies. It also identifies some sites and patterns of convergence. We plot these collaborative relationships in bi-partite graphs. These emergent characteristics of the astronomy workforce have implications for curricula, pedagogies, and the division of labor in research collaborations.

3rd Annual Earth System Grid Federation and 3rd Annual Earth System Grid Federation and Ultrascale Visualization Climate Data Analysis Tools Face-to-Face Meeting Report December 2013

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

Williams, Dean N.

The climate and weather data science community gathered December 3–5, 2013, at Lawrence Livermore National Laboratory, in Livermore, California, for the third annual Earth System Grid Federation (ESGF) and Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT) Face-to-Face (F2F) Meeting, which was hosted by the Department of Energy, National Aeronautics and Space Administration, National Oceanic and Atmospheric Administration, the European Infrastructure for the European Network of Earth System Modelling, and the Australian Department of Education. Both ESGF and UV-CDAT are global collaborations designed to develop a new generation of open-source software infrastructure that provides distributed access and analysis to observed andmore » simulated data from the climate and weather communities. The tools and infrastructure developed under these international multi-agency collaborations are critical to understanding extreme weather conditions and long-term climate change, while the F2F meetings help to build a stronger climate and weather data science community and stronger federated software infrastructure. The 2013 F2F meeting determined requirements for existing and impending national and international community projects; enhancements needed for data distribution, analysis, and visualization infrastructure; and standards and resources needed for better collaborations.« less

Supporting Trust in Globally Distributed Software Teams: The Impact of Visualized Collaborative Traces on Perceived Trustworthiness

ERIC Educational Resources Information Center

Trainer, Erik Harrison

2012-01-01

Trust plays an important role in collaborations because it creates an environment in which people can openly exchange ideas and information with one another and engineer innovative solutions together with less perceived risk. The rise in globally distributed software development has created an environment in which workers are likely to have less…

SERVIR Regional Visualization and Monitoring System: A Brief Overview

NASA Technical Reports Server (NTRS)

Limaye, Ashutosh

2011-01-01

SERVIR is a joint USAID NASA effort, which uses remotely sensed data and products for societal benefit. SERVIR currently has three hubs, in Central America, East Africa and Himalaya. Science Applications, IT infrastructure and capacity building is central to SERVIR efforts. Collaborations are key. SERVIR is continuing to develop strong, working collaborations with government entities in the region, such as KMD.

Research Infrastructure for Collaborative Team Science: Challenges in Technology-Supported Workflows in and Across Laboratories, Institutions, and Geographies.

PubMed

Mirel, Barbara; Luo, Airong; Harris, Marcelline

2015-05-01

Collaborative research has many challenges. One under-researched challenge is how to align collaborators' research practices and evolving analytical reasoning with technologies and configurations of technologies that best support them. The goal of such alignment is to enhance collaborative problem solving capabilities in research. Toward this end, we draw on our own research and a synthesis of the literature to characterize the workflow of collaborating scientists in systems-level renal disease research. We describe the various phases of a hypothetical workflow among diverse collaborators within and across laboratories, extending from their primary analysis through secondary analysis. For each phase, we highlight required technology supports, and. At time, complementary organizational supports. This survey of supports matching collaborators' analysis practices and needs in research projects to technological support is preliminary, aimed ultimately at developing a research capability framework that can help scientists and technologists mutually understand workflows and technologies that can help enable and enhance them. Copyright © 2015 Elsevier Inc. All rights reserved.

Using Text Analytics of AJPE Article Titles to Reveal Trends In Pharmacy Education Over the Past Two Decades.

PubMed

Pedrami, Farnoush; Asenso, Pamela; Devi, Sachin

2016-08-25

Objective. To identify trends in pharmacy education during last two decades using text mining. Methods. Articles published in the American Journal of Pharmaceutical Education (AJPE) in the past two decades were compiled in a database. Custom text analytics software was written using Visual Basic programming language in the Visual Basic for Applications (VBA) editor of Excel 2007. Frequency of words appearing in article titles was calculated using the custom VBA software. Data were analyzed to identify the emerging trends in pharmacy education. Results. Three educational trends emerged: active learning, interprofessional, and cultural competency. Conclusion. The text analytics program successfully identified trends in article topics and may be a useful compass to predict the future course of pharmacy education.

Review of experience with a collaborative eye care clinic in inpatient stroke rehabilitation.

PubMed

Herron, Sarah

2016-02-01

Visual deficits following stroke are frequently subtle and are often overlooked. Even though these visual deficits may be less overt in nature, they are still debilitating to survivors. Visual deficits have been shown to negatively impact cognition, mobility, and activities of daily living (ADL). There is little consistency across healthcare facilities regarding protocol for assessing vision following stroke. This research was designed to describe a profile for patients exhibiting visual deficits following stroke, examine the role of occupational therapists in vision assessment, and discuss a potential model to provide a protocol for collaboration with an eye care professional as part of the rehabilitation team. The sample consisted of 131 patients in an inpatient rehabilitation (IPR) unit who were identified as having potential visual deficits. Occupational therapists on an IPR unit administered initial vision screenings and these patients were subsequently evaluated by the consulting optometrist. Frequencies were calculated for the appearance of functional symptoms, diagnoses, and recommendations. Correlations were also computed relating diagnoses and recommendations made. All patients referred by the occupational therapist for optometrist evaluation had at least one visual diagnosis. The most frequent visual diagnoses included: saccades (77.7%), pursuits (61.8%), and convergence (63.4%). There was also a positive correlation between number of functional symptoms seen by occupational therapists and visual diagnoses made by the optometrist (r  =  0.209, P  =  0.016). Results of this study support the need for vision assessment following stroke in IPR, confirm the role of occupational therapists in vision assessment, and support the need for an optometrist as a member of the rehabilitation team.

Distributed Observer Network

NASA Technical Reports Server (NTRS)

2008-01-01

NASA s advanced visual simulations are essential for analyses associated with life cycle planning, design, training, testing, operations, and evaluation. Kennedy Space Center, in particular, uses simulations for ground services and space exploration planning in an effort to reduce risk and costs while improving safety and performance. However, it has been difficult to circulate and share the results of simulation tools among the field centers, and distance and travel expenses have made timely collaboration even harder. In response, NASA joined with Valador Inc. to develop the Distributed Observer Network (DON), a collaborative environment that leverages game technology to bring 3-D simulations to conventional desktop and laptop computers. DON enables teams of engineers working on design and operations to view and collaborate on 3-D representations of data generated by authoritative tools. DON takes models and telemetry from these sources and, using commercial game engine technology, displays the simulation results in a 3-D visual environment. Multiple widely dispersed users, working individually or in groups, can view and analyze simulation results on desktop and laptop computers in real time.

Drawing from Freirian empowerment methods to develop and use innovative learning maps: increasing enrollment of uninsured children on Detroit's eastside.

PubMed

Lopez, Ellen D S; Lichtenstein, Richard; Lewis, Alonzo; Banaszak-Holl, Jane; Lewis, Cheryl; Johnson, Penni; Riley, Scherry; Baum, Nancy M

2007-04-01

In 2001, virtually every child on Detroit's eastside was eligible for health coverage, yet approximately 3,000 children remained uninsured. The primary aim of the Eastside Access Partnership (EAP), a community-based participatory research collaboration, was to increase enrollment of uninsured children in state programs. To achieve this aim, one of the approaches that EAP is using is the innovative Learning Map titled Choosing the Healthy Path, which was developed in collaboration with Root Learning, Inc. Although Learning Maps were originally developed to assist corporations in implementing strategic change, their integration of visualization and interactive dialogue incorporates Freirian principles of empowerment education, making them a viable option for providing meaningful learning opportunities for community residents. This article presents the collaborative process involving the University of Michigan, local community-based organizations, community members, and Root Learning consultants to develop a visual map that enables community residents to understand and overcome the barriers that prevent them from obtaining health insurance for their children.

Modern analytical chemistry in the contemporary world

NASA Astrophysics Data System (ADS)

Šíma, Jan

2016-12-01

Students not familiar with chemistry tend to misinterpret analytical chemistry as some kind of the sorcery where analytical chemists working as modern wizards handle magical black boxes able to provide fascinating results. However, this approach is evidently improper and misleading. Therefore, the position of modern analytical chemistry among sciences and in the contemporary world is discussed. Its interdisciplinary character and the necessity of the collaboration between analytical chemists and other experts in order to effectively solve the actual problems of the human society and the environment are emphasized. The importance of the analytical method validation in order to obtain the accurate and precise results is highlighted. The invalid results are not only useless; they can often be even fatal (e.g., in clinical laboratories). The curriculum of analytical chemistry at schools and universities is discussed. It is referred to be much broader than traditional equilibrium chemistry coupled with a simple description of individual analytical methods. Actually, the schooling of analytical chemistry should closely connect theory and practice.

Survey of Network Visualization Tools

DTIC Science & Technology

2007-12-01

Dimensionality • 2D Comments: Deployment Type: • Components for tool building • Standalone Tool OS: • Windows Extensibility • ActiveX ...Visual Basic Comments: Interoperability Daisy is fully compliant with Microsoft’s ActiveX , therefore, other Windows based programs can...other functions that improve analytic decision making. Available in ActiveX , C++, Java, and .NET editions. • Tom Sawyer Visualization: Enables you to

Situated Knowledge and Visual Education: Patrick Geddes and Reclus's Geography (1886-1932)

ERIC Educational Resources Information Center

Ferretti, Federico

2017-01-01

This article addresses Patrick Geddes's relationship with geography and visual education by focusing on his collaboration with the network of the anarchist geographers Élie, Élisée, and Paul Reclus. Drawing on empirical archival research, it contributes to the current debates on geographies of anarchist education and on geographic teaching. The…

Collaborative Action Research Approach Promoting Professional Development for Teachers of Students with Visual Impairment in Assistive Technology

ERIC Educational Resources Information Center

Argyropoulos, Vassilios; Nikolaraizi, Magda; Tsiakali, Thomai; Kountrias, Polychronis; Koutsogiorgou, Sofia-Marina; Martos, Aineias

2014-01-01

This paper highlights the framework and discusses the results of an action research project which aimed to facilitate the adoption of assistive technology devices and specialized software by teachers of students with visual impairment via a digital educational game, developed specifically for this project. The persons involved in this…

How Can Visual Arts Help Doctors Develop Medical Insight?

ERIC Educational Resources Information Center

Edmonds, Kathleen; Hammond, Margaret F.

2012-01-01

This research project examines how using the visual arts can develop medical insight, as part of a pilot programme for two groups of medical students. It was a UK study; a collaboration between Liverpool and Glyndw University's and Tate Liverpool's learning team. Tate Liverpool is the home of the National Collection of Modern Arts in the North of…

"Whoa! We're Going Deep in the Trees!": Patterns of Collaboration around an Interactive Information Visualization Exhibit

ERIC Educational Resources Information Center

Davis, Pryce; Horn, Michael; Block, Florian; Phillips, Brenda; Evans, E. Margaret; Diamond, Judy; Shen, Chia

2015-01-01

In this paper we present a qualitative analysis of natural history museum visitor interaction around a multi-touch tabletop exhibit called "DeepTree" that we designed around concepts of evolution and common descent. DeepTree combines several large scientific datasets and an innovative visualization technique to display a phylogenetic…

Deconstructing Immigrant Girls' Identities through the Production of Visual Narratives in a Catalan Urban Primary School

ERIC Educational Resources Information Center

Rifa-Valls, Montserrat

2009-01-01

In this article, the research findings of a deconstructive visual ethnography focused on the production of immigrant girls' identities will be analysed. This collaborative research project involved experimentation with a dialogic curriculum aimed at creating diverse identity narratives with immigrant girls at an urban primary school in Barcelona.…

Visual Arts as a Lever for Social Justice Education: Labor Studies in the High School Art Curriculum

ERIC Educational Resources Information Center

Sosin, Adrienne Andi; Bekkala, Elsa; Pepper-Sanello, Miriam

2010-01-01

This collaborative action research study of pedagogy examines an introductory high school visual arts curriculum that includes artworks pertinent to labor studies, and their impact on students' understanding of the power of art for social commentary. Urban students with multicultural backgrounds study social realism as an historical artistic…

The Integration of Visual Expression in Music Education for Children

ERIC Educational Resources Information Center

Roels, Johanna Maria; Van Petegem, Peter

2014-01-01

This study is the result of a two-year experimental collaboration with children from my piano class. Together, the children and I designed a method that uses visual expression as a starting point for composing and visualising music-theoretical concepts. In this method various dimensions of musicality such as listening, creating, noting down and…

Visualization of Expert Chat Development in a World of Warcraft Player Group

ERIC Educational Resources Information Center

Chen, Mark

2009-01-01

This article describes expertise development in a player group in the massively multiplayer online game World of Warcraft using visualization of chat log data. Charts were created to get a general sense of chat trends in a specific player group engaged in "high-end raiding", a 40-person collaborative activity. These charts helped identify patterns…

Constructing a Streaming Video-Based Learning Forum for Collaborative Learning

ERIC Educational Resources Information Center

Chang, Chih-Kai

2004-01-01

As web-based courses using videos have become popular in recent years, the issue of managing audio-visual aids has become pertinent. Generally, the contents of audio-visual aids may include a lecture, an interview, a report, or an experiment, which may be transformed into a streaming format capable of making the quality of Internet-based videos…

The Effect of Color Choice on Learner Interpretation of a Cosmology Visualization

ERIC Educational Resources Information Center

Buck, Zoe

2013-01-01

As we turn more and more to high-end computing to understand the Universe at cosmological scales, dynamic visualizations of simulations will take on a vital role as perceptual and cognitive tools. In collaboration with the Adler Planetarium and University of California High-Performance AstroComputing Center (UC-HiPACC), I am interested in better…

Giving raw data a chance to talk: a demonstration of exploratory visual analytics with a pediatric research database using Microsoft Live Labs Pivot to promote cohort discovery, research, and quality assessment.

PubMed

Viangteeravat, Teeradache; Nagisetty, Naga Satya V Rao

2014-01-01

Secondary use of large and open data sets provides researchers with an opportunity to address high-impact questions that would otherwise be prohibitively expensive and time consuming to study. Despite the availability of data, generating hypotheses from huge data sets is often challenging, and the lack of complex analysis of data might lead to weak hypotheses. To overcome these issues and to assist researchers in building hypotheses from raw data, we are working on a visual and analytical platform called PRD Pivot. PRD Pivot is a de-identified pediatric research database designed to make secondary use of rich data sources, such as the electronic health record (EHR). The development of visual analytics using Microsoft Live Labs Pivot makes the process of data elaboration, information gathering, knowledge generation, and complex information exploration transparent to tool users and provides researchers with the ability to sort and filter by various criteria, which can lead to strong, novel hypotheses.

Giving Raw Data a Chance to Talk: A Demonstration of Exploratory Visual Analytics with a Pediatric Research Database Using Microsoft Live Labs Pivot to Promote Cohort Discovery, Research, and Quality Assessment

PubMed Central

Viangteeravat, Teeradache; Nagisetty, Naga Satya V. Rao

2014-01-01

Secondary use of large and open data sets provides researchers with an opportunity to address high-impact questions that would otherwise be prohibitively expensive and time consuming to study. Despite the availability of data, generating hypotheses from huge data sets is often challenging, and the lack of complex analysis of data might lead to weak hypotheses. To overcome these issues and to assist researchers in building hypotheses from raw data, we are working on a visual and analytical platform called PRD Pivot. PRD Pivot is a de-identified pediatric research database designed to make secondary use of rich data sources, such as the electronic health record (EHR). The development of visual analytics using Microsoft Live Labs Pivot makes the process of data elaboration, information gathering, knowledge generation, and complex information exploration transparent to tool users and provides researchers with the ability to sort and filter by various criteria, which can lead to strong, novel hypotheses. PMID:24808811

Integrated genome browser: visual analytics platform for genomics.

PubMed

Freese, Nowlan H; Norris, David C; Loraine, Ann E

2016-07-15

Genome browsers that support fast navigation through vast datasets and provide interactive visual analytics functions can help scientists achieve deeper insight into biological systems. Toward this end, we developed Integrated Genome Browser (IGB), a highly configurable, interactive and fast open source desktop genome browser. Here we describe multiple updates to IGB, including all-new capabilities to display and interact with data from high-throughput sequencing experiments. To demonstrate, we describe example visualizations and analyses of datasets from RNA-Seq, ChIP-Seq and bisulfite sequencing experiments. Understanding results from genome-scale experiments requires viewing the data in the context of reference genome annotations and other related datasets. To facilitate this, we enhanced IGB's ability to consume data from diverse sources, including Galaxy, Distributed Annotation and IGB-specific Quickload servers. To support future visualization needs as new genome-scale assays enter wide use, we transformed the IGB codebase into a modular, extensible platform for developers to create and deploy all-new visualizations of genomic data. IGB is open source and is freely available from http://bioviz.org/igb aloraine@uncc.edu. © The Author 2016. Published by Oxford University Press.

Theory-Led Design of Instruments and Representations in Learning Analytics: Developing a Novel Tool for Orchestration of Online Collaborative Learning

ERIC Educational Resources Information Center

Kelly, Nick; Thompson, Kate; Yeoman, Pippa

2015-01-01

This paper describes theory-led design as a way of developing novel tools for learning analytics (LA). It focuses upon the domain of automated discourse analysis (ADA) of group learning activities to help an instructor to orchestrate online groups in real-time. The paper outlines the literature on the development of LA tools within the domain of…

Experimental and Analytic Evaluation of the Effects of Visual and Motion Simulation in SH-3 Helicopter Training. Technical Report 85-002.

ERIC Educational Resources Information Center

Pfeiffer, Mark G.; Scott, Paul G.

A fly-only group (N=16) of Navy replacement pilots undergoing fleet readiness training in the SH-3 helicopter was compared with groups pre-trained on Device 2F64C with: (1) visual only (N=13); (2) no visual/no motion (N=14); and (3) one visual plus motion group (N=19). Groups were compared for their SH-3 helicopter performance in the transition…

Liquid-to-gel transition for visual and tactile detection of biological analytes.

PubMed

Fedotova, Tatiana A; Kolpashchikov, Dmitry M

2017-11-23

So far all visual and instrument-free methods have been based on a color change. However, colorimetric assays cannot be used by blind or color-blind people. Here we introduce a liquid-to-gel transition as a general output platform. The signal output (a piece of gel) can be unambiguously distinguished from liquid both visually and by touch. This approach promises to contribute to the development of an accessible environment for visually impaired persons.

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

Nakafuji, Dora; Gouveia, Lauren

This project supports development of the next generation, integrated energy management infrastructure (EMS) able to incorporate advance visualization of behind-the-meter distributed resource information and probabilistic renewable energy generation forecasts to inform real-time operational decisions. The project involves end-users and active feedback from an Utility Advisory Team (UAT) to help inform how information can be used to enhance operational functions (e.g. unit commitment, load forecasting, Automatic Generation Control (AGC) reserve monitoring, ramp alerts) within two major EMS platforms. Objectives include: Engaging utility operations personnel to develop user input on displays, set expectations, test and review; Developing ease of use and timelinessmore » metrics for measuring enhancements; Developing prototype integrated capabilities within two operational EMS environments; Demonstrating an integrated decision analysis platform with real-time wind and solar forecasting information and timely distributed resource information; Seamlessly integrating new 4-dimensional information into operations without increasing workload and complexities; Developing sufficient analytics to inform and confidently transform and adopt new operating practices and procedures; Disseminating project lessons learned through industry sponsored workshops and conferences;Building on collaborative utility-vendor partnership and industry capabilities« less

Qualitative evaluation of water displacement in simulated analytical breaststroke movements.

PubMed

Martens, Jonas; Daly, Daniel

2012-05-01

One purpose of evaluating a swimmer is to establish the individualized optimal technique. A swimmer's particular body structure and the resulting movement pattern will cause the surrounding water to react in differing ways. Consequently, an assessment method based on flow visualization was developed complimentary to movement analysis and body structure quantification. A fluorescent dye was used to make the water displaced by the body visible on video. To examine the hypothesis on the propulsive mechanisms applied in breaststroke swimming, we analyzed the movements of the surrounding water during 4 analytical breaststroke movements using the flow visualization technique.

ID-Viewer: a visual analytics architecture for infectious diseases surveillance and response management in Pakistan.

PubMed

Ali, M A; Ahsan, Z; Amin, M; Latif, S; Ayyaz, A; Ayyaz, M N

2016-05-01

Globally, disease surveillance systems are playing a significant role in outbreak detection and response management of Infectious Diseases (IDs). However, in developing countries like Pakistan, epidemic outbreaks are difficult to detect due to scarcity of public health data and absence of automated surveillance systems. Our research is intended to formulate an integrated service-oriented visual analytics architecture for ID surveillance, identify key constituents and set up a baseline for easy reproducibility of such systems in the future. This research focuses on development of ID-Viewer, which is a visual analytics decision support system for ID surveillance. It is a blend of intelligent approaches to make use of real-time streaming data from Emergency Departments (EDs) for early outbreak detection, health care resource allocation and epidemic response management. We have developed a robust service-oriented visual analytics architecture for ID surveillance, which provides automated mechanisms for ID data acquisition, outbreak detection and epidemic response management. Classification of chief-complaints is accomplished using dynamic classification module, which employs neural networks and fuzzy-logic to categorize syndromes. Standard routines by Center for Disease Control (CDC), i.e. c1-c3 (c1-mild, c2-medium and c3-ultra), and spatial scan statistics are employed for detection of temporal and spatio-temporal disease outbreaks respectively. Prediction of imminent disease threats is accomplished using support vector regression for early warnings and response planning. Geographical visual analytics displays are developed that allow interactive visualization of syndromic clusters, monitoring disease spread patterns, and identification of spatio-temporal risk zones. We analysed performance of surveillance framework using ID data for year 2011-2015. Dynamic syndromic classifier is able to classify chief-complaints to appropriate syndromes with high classification accuracy. Outbreak detection methods are able to detect the ID outbreaks in start of epidemic time zones. Prediction model is able to forecast dengue trend for 20 weeks ahead with nominal normalized root mean square error of 0.29. Interactive geo-spatiotemporal displays, i.e. heat-maps, and choropleth are shown in respective sections. The proposed framework will set a standard and provide necessary details for future implementation of such a system for resource-constrained regions. It will improve early outbreak detection attributable to natural and man-made biological threats, monitor spatio-temporal epidemic trends and provide assurance that an outbreak has, or has not occurred. Advanced analytics features will be beneficial in timely organization/formulation of health management policies, disease control activities and efficient health care resource allocation. Copyright © 2016 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

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

Marrinan, Thomas; Leigh, Jason; Renambot, Luc

Mixed presence collaboration involves remote collaboration between multiple collocated groups. This paper presents the design and results of a user study that focused on mixed presence collaboration using large-scale tiled display walls. The research was conducted in order to compare data synchronization schemes for multi-user visualization applications. Our study compared three techniques for sharing data between display spaces with varying constraints and affordances. The results provide empirical evidence that using data sharing techniques with continuous synchronization between the sites lead to improved collaboration for a search and analysis task between remotely located groups. We have also identified aspects of synchronizedmore » sessions that result in increased remote collaborator awareness and parallel task coordination. It is believed that this research will lead to better utilization of large-scale tiled display walls for distributed group work.« less

Regional Visualization and Monitoring System SERVIR: A Brief Overview, Water Resources Challenges and Approaches

NASA Technical Reports Server (NTRS)

Limaye, Ashutosh

2011-01-01

SERVIR is a joint USAID -- NASA effort, which uses remotely sensed data and products for societal benefit. SERVIR currently has three hubs, in Mesoamerica, East Africa and Himalaya. Collaborations are key. SE RVIR is continuing to develop strong, working collaborations with government entities, such as KMD. Science Applications, IT infrastructure and capacity building is central to SERVIR efforts.

An annotation system for 3D fluid flow visualization

NASA Technical Reports Server (NTRS)

Loughlin, Maria M.; Hughes, John F.

1995-01-01

Annotation is a key activity of data analysis. However, current systems for data analysis focus almost exclusively on visualization. We propose a system which integrates annotations into a visualization system. Annotations are embedded in 3D data space, using the Post-it metaphor. This embedding allows contextual-based information storage and retrieval, and facilitates information sharing in collaborative environments. We provide a traditional database filter and a Magic Lens filter to create specialized views of the data. The system has been customized for fluid flow applications, with features which allow users to store parameters of visualization tools and sketch 3D volumes.

The D3 Middleware Architecture

NASA Technical Reports Server (NTRS)

Walton, Joan; Filman, Robert E.; Korsmeyer, David J.; Lee, Diana D.; Mak, Ron; Patel, Tarang

2002-01-01

DARWIN is a NASA developed, Internet-based system for enabling aerospace researchers to securely and remotely access and collaborate on the analysis of aerospace vehicle design data, primarily the results of wind-tunnel testing and numeric (e.g., computational fluid-dynamics) model executions. DARWIN captures, stores and indexes data; manages derived knowledge (such as visualizations across multiple datasets); and provides an environment for designers to collaborate in the analysis of test results. DARWIN is an interesting application because it supports high-volumes of data. integrates multiple modalities of data display (e.g., images and data visualizations), and provides non-trivial access control mechanisms. DARWIN enables collaboration by allowing not only sharing visualizations of data, but also commentary about and views of data. Here we provide an overview of the architecture of D3, the third generation of DARWIN. Earlier versions of DARWIN were characterized by browser-based interfaces and a hodge-podge of server technologies: CGI scripts, applets, PERL, and so forth. But browsers proved difficult to control, and a proliferation of computational mechanisms proved inefficient and difficult to maintain. D3 substitutes a pure-Java approach for that medley: A Java client communicates (though RMI over HTTPS) with a Java-based application server. Code on the server accesses information from JDBC databases, distributed LDAP security services, and a collaborative information system. D3 is a three tier-architecture, but unlike 'E-commerce' applications, the data usage pattern suggests different strategies than traditional Enterprise Java Beans - we need to move volumes of related data together, considerable processing happens on the client, and the 'business logic' on the server-side is primarily data integration and collaboration. With D3, we are extending DARWIN to handle other data domains and to be a distributed system, where a single login allows a user transparent access to test results from multiple servers and authority domains.

Visual Thinking and Gender Differences in High School Calculus

ERIC Educational Resources Information Center

Haciomeroglu, Erhan Selcuk; Chicken, Eric

2012-01-01

This study sought to examine calculus students' mathematical performances and preferences for visual or analytic thinking regarding derivative and antiderivative tasks presented graphically. It extends previous studies by investigating factors mediating calculus students' mathematical performances and their preferred modes of thinking. Data were…

Visual Basic programs for spreadsheet analysis.

PubMed

Hunt, Bruce

2005-01-01

A collection of Visual Basic programs, entitled Function.xls, has been written for ground water spreadsheet calculations. This collection includes programs for calculating mathematical functions and for evaluating analytical solutions in ground water hydraulics and contaminant transport. Several spreadsheet examples are given to illustrate their use.

Bringing "Scientific Expeditions" Into the Schools

NASA Technical Reports Server (NTRS)

Watson, Val; Lasinski, T. A. (Technical Monitor)

1995-01-01

Two new technologies, the FASTexpedition and Remote FAST, have been developed that provide remote, 3D, high resolution, dynamic, interactive viewing of scientific data (such as simulations or measurements of fluid dynamics). The FASTexpedition permits one to access scientific data from the World Wide Web, take guided expeditions through the data, and continue with self controlled expeditions through the data. Remote FAST permits collaborators at remote sites to simultaneously view an analysis of scientific data being controlled by one of the collaborators. Control can be transferred between sites. These technologies are now being used for remote collaboration in joint university, industry, and NASA projects in computational fluid dynamics (CFD) and wind tunnel testing. Also, NASA Ames Research Center has initiated a project to make scientific data and guided expeditions through the data available as FASTexpeditions on the World Wide Web for educational purposes. Previously, remote visualiZation of dynamic data was done using video format (transmitting pixel information) such as video conferencing or MPEG movies on the Internet. The concept for this new technology is to send the raw data (e.g., grids, vectors, and scalars) along with viewing scripts over the Internet and have the pixels generated by a visualization tool running on the viewer's local workstation. The visualization tool that is currently used is FAST (Flow Analysis Software Toolkit). The advantages of this new technology over using video format are: 1. The visual is much higher in resolution (1280xl024 pixels with 24 bits of color) than typical video format transmitted over the network. 2. The form of the visualization can be controlled interactively (because the viewer is interactively controlling the visualization tool running on his workstation). 3. A rich variety of guided expeditions through the data can be included easily. 4. A capability is provided for other sites to see a visual analysis of one site as the analysis is interactively performed. Control of the analysis can be passed from site to site. 5. The scenes can be viewed in 3D using stereo vision. 6. The network bandwidth used for the visualization using this new technology is much smaller than when using video format. (The measured peak bandwidth used was 1 Kbit/sec whereas the measured bandwidth for a small video picture was 500 Kbits/sec.)

Report: New analytical and statistical approaches for interpreting the relationships among environmental stressors and biomarkers

EPA Science Inventory

The broad topic of biomarker research has an often-overlooked component: the documentation and interpretation of the surrounding chemical environment and other meta-data, especially from visualization, analytical, and statistical perspectives (Pleil et al. 2014; Sobus et al. 2011...

Visualizing Progress

NASA Technical Reports Server (NTRS)

2000-01-01

Reality Capture Technologies, Inc. is a spinoff company from Ames Research Center. Offering e-business solutions for optimizing management, design and production processes, RCT uses visual collaboration environments (VCEs) such as those used to prepare the Mars Pathfinder mission.The product, 4-D Reality Framework, allows multiple users from different locations to manage and share data. The insurance industry is one targeted commercial application for this technology.

Visualizing Biological Data in Museums: Visitor Learning with an Interactive Tree of Life Exhibit

ERIC Educational Resources Information Center

Horn, Michael S.; Phillips, Brenda C.; Evans, Evelyn Margaret; Block, Florian; Diamond, Judy; Shen, Chia

2016-01-01

In this study, we investigate museum visitor learning and engagement at an interactive visualization of an evolutionary tree of life consisting of over 70,000 species. The study was conducted at two natural history museums where visitors collaboratively explored the tree of life using direct touch gestures on a multi-touch tabletop display. In the…

The Avian Knowledge Network : A partnership to organize, analyze, and visualize bird observation data for education, conservation, research, and land management

Treesearch

Marshall Iliff; Leo Salas; Ernesto Ruelas Inzunza; Grant Ballard; Denis Lepage; Steve Kelling

2009-01-01

The Avian Knowledge Network (AKN) is an international collaboration of academic, nongovernment, and government institutions with the goal of organizing observations of birds into an interoperable format to enhance access, data visualization and exploration, and scientifi c analyses. The AKN uses proven cyberinfrastructure and informatics techniques as the foundation of...

The Creation of the "Hong Kong Visual Arts Education Web" and the Use of the Inquiry-Based Teaching Approach

ERIC Educational Resources Information Center

Sang, Anita Ng Heung

2009-01-01

This article describes a collaborative action research conducted by a lecturer and several primary school art teachers, who between 2001 and 2006 created the Visual Arts Education Web ("iii web") in Hong Kong. The creation of the "iii web" was accomplished through research that employed questionnaires, focus group discussions…

Using Virtual Microscopy to Scaffold Learning of Pathology: A Naturalistic Experiment on the Role of Visual and Conceptual Cues

ERIC Educational Resources Information Center

Nivala, Markus; Saljo, Roger; Rystedt, Hans; Kronqvist, Pauliina; Lehtinen, Erno

2012-01-01

New representational technologies, such as virtual microscopy, create new affordances for medical education. In the article, a study on the following two issues is reported: (a) How does collaborative use of virtual microscopy shape students' engagement with and learning from virtual slides of tissue specimen? (b) How do visual and conceptual cues…

Using visual art and collaborative reflection to explore medical attitudes toward vulnerable persons

PubMed Central

Kidd, Monica; Nixon, Lara; Rosenal, Tom; Jackson, Roberta; Pereles, Laurie; Mitchell, Ian; Bendiak, Glenda; Hughes, Lisa

2016-01-01

Background Vulnerable persons often face stigma-related barriers while seeking health care. Innovative education and professional development methods are needed to help change this. Method We describe an interdisciplinary group workshop designed around a discomfiting oil portrait, intended to trigger provocative conversations among health care students and practitioners, and we present our mixed methods analysis of participant reflections. Results After the workshop, participants were significantly more likely to endorse the statements that the observation and interpretive skills involved in viewing visual art are relevant to patient care and that visual art should be used in medical education to improve students’ observational skills, narrative skills, and empathy with their patients. Subsequent to the workshop, significantly more participants agreed that art interpretation should be required curriculum for health care students. Qualitative comments from two groups from two different education and professional contexts were examined for themes; conversations focused on issues of power, body image/self-esteem, and lessons for clinical practice. Conclusions We argue that difficult conversations about affective responses to vulnerable persons are possible in a collaborative context using well-chosen works of visual art that can stand in for a patient. PMID:27103949

Using visual art and collaborative reflection to explore medical attitudes toward vulnerable persons.

PubMed

Kidd, Monica; Nixon, Lara; Rosenal, Tom; Jackson, Roberta; Pereles, Laurie; Mitchell, Ian; Bendiak, Glenda; Hughes, Lisa

2016-01-01

Vulnerable persons often face stigma-related barriers while seeking health care. Innovative education and professional development methods are needed to help change this. We describe an interdisciplinary group workshop designed around a discomfiting oil portrait, intended to trigger provocative conversations among health care students and practitioners, and we present our mixed methods analysis of participant reflections. After the workshop, participants were significantly more likely to endorse the statements that the observation and interpretive skills involved in viewing visual art are relevant to patient care and that visual art should be used in medical education to improve students' observational skills, narrative skills, and empathy with their patients. Subsequent to the workshop, significantly more participants agreed that art interpretation should be required curriculum for health care students. Qualitative comments from two groups from two different education and professional contexts were examined for themes; conversations focused on issues of power, body image/self-esteem, and lessons for clinical practice. We argue that difficult conversations about affective responses to vulnerable persons are possible in a collaborative context using well-chosen works of visual art that can stand in for a patient.

Stakeholder perspectives on decision-analytic modeling frameworks to assess genetic services policy.

PubMed

Guzauskas, Gregory F; Garrison, Louis P; Stock, Jacquie; Au, Sylvia; Doyle, Debra Lochner; Veenstra, David L

2013-01-01

Genetic services policymakers and insurers often make coverage decisions in the absence of complete evidence of clinical utility and under budget constraints. We evaluated genetic services stakeholder opinions on the potential usefulness of decision-analytic modeling to inform coverage decisions, and asked them to identify genetic tests for decision-analytic modeling studies. We presented an overview of decision-analytic modeling to members of the Western States Genetic Services Collaborative Reimbursement Work Group and state Medicaid representatives and conducted directed content analysis and an anonymous survey to gauge their attitudes toward decision-analytic modeling. Participants also identified and prioritized genetic services for prospective decision-analytic evaluation. Participants expressed dissatisfaction with current processes for evaluating insurance coverage of genetic services. Some participants expressed uncertainty about their comprehension of decision-analytic modeling techniques. All stakeholders reported openness to using decision-analytic modeling for genetic services assessments. Participants were most interested in application of decision-analytic concepts to multiple-disorder testing platforms, such as next-generation sequencing and chromosomal microarray. Decision-analytic modeling approaches may provide a useful decision tool to genetic services stakeholders and Medicaid decision-makers.

The challenge of big data in public health: an opportunity for visual analytics.

PubMed

Ola, Oluwakemi; Sedig, Kamran

2014-01-01

Public health (PH) data can generally be characterized as big data. The efficient and effective use of this data determines the extent to which PH stakeholders can sufficiently address societal health concerns as they engage in a variety of work activities. As stakeholders interact with data, they engage in various cognitive activities such as analytical reasoning, decision-making, interpreting, and problem solving. Performing these activities with big data is a challenge for the unaided mind as stakeholders encounter obstacles relating to the data's volume, variety, velocity, and veracity. Such being the case, computer-based information tools are needed to support PH stakeholders. Unfortunately, while existing computational tools are beneficial in addressing certain work activities, they fall short in supporting cognitive activities that involve working with large, heterogeneous, and complex bodies of data. This paper presents visual analytics (VA) tools, a nascent category of computational tools that integrate data analytics with interactive visualizations, to facilitate the performance of cognitive activities involving big data. Historically, PH has lagged behind other sectors in embracing new computational technology. In this paper, we discuss the role that VA tools can play in addressing the challenges presented by big data. In doing so, we demonstrate the potential benefit of incorporating VA tools into PH practice, in addition to highlighting the need for further systematic and focused research.

Process monitoring and visualization solutions for hot-melt extrusion: a review.

PubMed

Saerens, Lien; Vervaet, Chris; Remon, Jean Paul; De Beer, Thomas

2014-02-01

Hot-melt extrusion (HME) is applied as a continuous pharmaceutical manufacturing process for the production of a variety of dosage forms and formulations. To ensure the continuity of this process, the quality of the extrudates must be assessed continuously during manufacturing. The objective of this review is to provide an overview and evaluation of the available process analytical techniques which can be applied in hot-melt extrusion. Pharmaceutical extruders are equipped with traditional (univariate) process monitoring tools, observing barrel and die temperatures, throughput, screw speed, torque, drive amperage, melt pressure and melt temperature. The relevance of several spectroscopic process analytical techniques for monitoring and control of pharmaceutical HME has been explored recently. Nevertheless, many other sensors visualizing HME and measuring diverse critical product and process parameters with potential use in pharmaceutical extrusion are available, and were thoroughly studied in polymer extrusion. The implementation of process analytical tools in HME serves two purposes: (1) improving process understanding by monitoring and visualizing the material behaviour and (2) monitoring and analysing critical product and process parameters for process control, allowing to maintain a desired process state and guaranteeing the quality of the end product. This review is the first to provide an evaluation of the process analytical tools applied for pharmaceutical HME monitoring and control, and discusses techniques that have been used in polymer extrusion having potential for monitoring and control of pharmaceutical HME. © 2013 Royal Pharmaceutical Society.

The Challenge of Big Data in Public Health: An Opportunity for Visual Analytics

PubMed Central

Ola, Oluwakemi; Sedig, Kamran

2014-01-01

Public health (PH) data can generally be characterized as big data. The efficient and effective use of this data determines the extent to which PH stakeholders can sufficiently address societal health concerns as they engage in a variety of work activities. As stakeholders interact with data, they engage in various cognitive activities such as analytical reasoning, decision-making, interpreting, and problem solving. Performing these activities with big data is a challenge for the unaided mind as stakeholders encounter obstacles relating to the data’s volume, variety, velocity, and veracity. Such being the case, computer-based information tools are needed to support PH stakeholders. Unfortunately, while existing computational tools are beneficial in addressing certain work activities, they fall short in supporting cognitive activities that involve working with large, heterogeneous, and complex bodies of data. This paper presents visual analytics (VA) tools, a nascent category of computational tools that integrate data analytics with interactive visualizations, to facilitate the performance of cognitive activities involving big data. Historically, PH has lagged behind other sectors in embracing new computational technology. In this paper, we discuss the role that VA tools can play in addressing the challenges presented by big data. In doing so, we demonstrate the potential benefit of incorporating VA tools into PH practice, in addition to highlighting the need for further systematic and focused research. PMID:24678376

Opportunities and challenges for real-world studies on chronic inflammatory joint diseases through data enrichment and collaboration between national registers: the Nordic example

PubMed Central

Chatzidionysiou, Katerina; Hetland, Merete Lund; Frisell, Thomas; Di Giuseppe, Daniela; Hellgren, Karin; Glintborg, Bente; Nordström, Dan; Aaltonen, Kalle; Törmänen, Minna RK; Klami Kristianslund, Eirik; Kvien, Tore K; Provan, Sella A; Guðbjörnsson, Bjorn; Dreyer, Lene; Kristensen, Lars Erik; Jørgensen, Tanja Schjødt; Jacobsson, Lennart; Askling, Johan

2018-01-01

There are increasing needs for detailed real-world data on rheumatic diseases and their treatments. Clinical register data are essential sources of information that can be enriched through linkage to additional data sources such as national health data registers. Detailed analyses call for international collaborative observational research to increase the number of patients and the statistical power. Such linkages and collaborations come with legal, logistic and methodological challenges. In collaboration between registers of inflammatory arthritides in Sweden, Denmark, Norway, Finland and Iceland, we plan to enrich, harmonise and standardise individual data repositories to investigate analytical approaches to multisource data, to assess the viability of different logistical approaches to data protection and sharing and to perform collaborative studies on treatment effectiveness, safety and health-economic outcomes. This narrative review summarises the needs and potentials and the challenges that remain to be overcome in order to enable large-scale international collaborative research based on clinical and other types of data. PMID:29682328

Clinical laboratory analytics: Challenges and promise for an emerging discipline.

PubMed

Shirts, Brian H; Jackson, Brian R; Baird, Geoffrey S; Baron, Jason M; Clements, Bryan; Grisson, Ricky; Hauser, Ronald George; Taylor, Julie R; Terrazas, Enrique; Brimhall, Brad

2015-01-01

The clinical laboratory is a major source of health care data. Increasingly these data are being integrated with other data to inform health system-wide actions meant to improve diagnostic test utilization, service efficiency, and "meaningful use." The Academy of Clinical Laboratory Physicians and Scientists hosted a satellite meeting on clinical laboratory analytics in conjunction with their annual meeting on May 29, 2014 in San Francisco. There were 80 registrants for the clinical laboratory analytics meeting. The meeting featured short presentations on current trends in clinical laboratory analytics and several panel discussions on data science in laboratory medicine, laboratory data and its role in the larger healthcare system, integrating laboratory analytics, and data sharing for collaborative analytics. One main goal of meeting was to have an open forum of leaders that work with the "big data" clinical laboratories produce. This article summarizes the proceedings of the meeting and content discussed.

Clinical laboratory analytics: Challenges and promise for an emerging discipline

PubMed Central

Shirts, Brian H.; Jackson, Brian R.; Baird, Geoffrey S.; Baron, Jason M.; Clements, Bryan; Grisson, Ricky; Hauser, Ronald George; Taylor, Julie R.; Terrazas, Enrique; Brimhall, Brad

2015-01-01

The clinical laboratory is a major source of health care data. Increasingly these data are being integrated with other data to inform health system-wide actions meant to improve diagnostic test utilization, service efficiency, and “meaningful use.” The Academy of Clinical Laboratory Physicians and Scientists hosted a satellite meeting on clinical laboratory analytics in conjunction with their annual meeting on May 29, 2014 in San Francisco. There were 80 registrants for the clinical laboratory analytics meeting. The meeting featured short presentations on current trends in clinical laboratory analytics and several panel discussions on data science in laboratory medicine, laboratory data and its role in the larger healthcare system, integrating laboratory analytics, and data sharing for collaborative analytics. One main goal of meeting was to have an open forum of leaders that work with the “big data” clinical laboratories produce. This article summarizes the proceedings of the meeting and content discussed. PMID:25774320

a Web-Based Framework for Visualizing Industrial Spatiotemporal Distribution Using Standard Deviational Ellipse and Shifting Routes of Gravity Centers

NASA Astrophysics Data System (ADS)

Song, Y.; Gui, Z.; Wu, H.; Wei, Y.

2017-09-01

Analysing spatiotemporal distribution patterns and its dynamics of different industries can help us learn the macro-level developing trends of those industries, and in turn provides references for industrial spatial planning. However, the analysis process is challenging task which requires an easy-to-understand information presentation mechanism and a powerful computational technology to support the visual analytics of big data on the fly. Due to this reason, this research proposes a web-based framework to enable such a visual analytics requirement. The framework uses standard deviational ellipse (SDE) and shifting route of gravity centers to show the spatial distribution and yearly developing trends of different enterprise types according to their industry categories. The calculation of gravity centers and ellipses is paralleled using Apache Spark to accelerate the processing. In the experiments, we use the enterprise registration dataset in Mainland China from year 1960 to 2015 that contains fine-grain location information (i.e., coordinates of each individual enterprise) to demonstrate the feasibility of this framework. The experiment result shows that the developed visual analytics method is helpful to understand the multi-level patterns and developing trends of different industries in China. Moreover, the proposed framework can be used to analyse any nature and social spatiotemporal point process with large data volume, such as crime and disease.

Toward a Visualization-Supported Workflow for Cyber Alert Management using Threat Models and Human-Centered Design

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

Franklin, Lyndsey; Pirrung, Megan A.; Blaha, Leslie M.

Cyber network analysts follow complex processes in their investigations of potential threats to their network. Much research is dedicated to providing automated tool support in the effort to make their tasks more efficient, accurate, and timely. This tool support comes in a variety of implementations from machine learning algorithms that monitor streams of data to visual analytic environments for exploring rich and noisy data sets. Cyber analysts, however, often speak of a need for tools which help them merge the data they already have and help them establish appropriate baselines against which to compare potential anomalies. Furthermore, existing threat modelsmore » that cyber analysts regularly use to structure their investigation are not often leveraged in support tools. We report on our work with cyber analysts to understand they analytic process and how one such model, the MITRE ATT&CK Matrix [32], is used to structure their analytic thinking. We present our efforts to map specific data needed by analysts into the threat model to inform our eventual visualization designs. We examine data mapping for gaps where the threat model is under-supported by either data or tools. We discuss these gaps as potential design spaces for future research efforts. We also discuss the design of a prototype tool that combines machine-learning and visualization components to support cyber analysts working with this threat model.« less

Eyes of the Storm: Can Fusion Centers Play a Crucial Role During the Response Phase of Natural Disasters Through Collaborative Relationships With Emergency Operations Centers?

DTIC Science & Technology

2014-09-01

Hispanic, street, and outlaw motorcycle gang activity in the Commonwealth. The VFC manages the suspicious activity reporting (SAR) initiative...Davis Highway, Suite 1204, Arlington, VA 22202-4302, and to the Office of Management and Budget, Paperwork Reduction Project (0704-0188) Washington... management . This thesis examined three case studies of fusion center disaster responses through a collaborative-based analytical framework. The resulting

Proactive human-computer collaboration for information discovery

NASA Astrophysics Data System (ADS)

DiBona, Phil; Shilliday, Andrew; Barry, Kevin

2016-05-01

Lockheed Martin Advanced Technology Laboratories (LM ATL) is researching methods, representations, and processes for human/autonomy collaboration to scale analysis and hypotheses substantiation for intelligence analysts. This research establishes a machinereadable hypothesis representation that is commonsensical to the human analyst. The representation unifies context between the human and computer, enabling autonomy in the form of analytic software, to support the analyst through proactively acquiring, assessing, and organizing high-value information that is needed to inform and substantiate hypotheses.

Determination of isoflavones in soy and selected foods containing soy by extraction, saponification, and liquid chromatography: collaborative study.

PubMed

Klump, S P; Allred, M C; MacDonald, J L; Ballam, J M

2001-01-01

Isoflavones are biologically active compounds occurring naturally in a variety of plants, with relatively high levels found in soybeans. Twelve laboratories participated in a collaborative study to determine the aglycon isoflavone content of 8 test samples of soy and foods containing soy. The analytical method for the determination of isoflavones incorporates a mild saponification step that reduces the number of analytes measured and permits quantitation versus commercially available, stable reference standards. Test samples were extracted at 65 degrees C with methanol-water (80 + 20), saponified with dilute sodium hydroxide solution, and analyzed by reversed-phase liquid chromatography with UV detection at 260 nm. Isoflavone results were reported as microg/aglycon/g or microg aglycon equivalents/g. The 8 test samples included 2 blind duplicates and 4 single test samples with total isoflavone concentrations ranging from approximately 50 to 3000 microg/g. Test samples of soy ingredients and products made with soy were distributed to collaborators with appropriate reference standards. Collaborators were asked to analyze test samples in duplicate on 2 separate days. The data were analyzed for individual isoflavone components, subtotals of daidzin-daidzein, glycitin-glycitein, and genistin-genistein, and total isoflavones. The relative standard deviation (RSD) for repeatability was 1.8-7.1%, and the RSD for reproducibility was 3.2-16.1% for total isoflavone values of 47-3099 microg/g.

BrainBrowser: distributed, web-based neurological data visualization.

PubMed

Sherif, Tarek; Kassis, Nicolas; Rousseau, Marc-Étienne; Adalat, Reza; Evans, Alan C

2014-01-01

Recent years have seen massive, distributed datasets become the norm in neuroimaging research, and the methodologies used to analyze them have, in response, become more collaborative and exploratory. Tools and infrastructure are continuously being developed and deployed to facilitate research in this context: grid computation platforms to process the data, distributed data stores to house and share them, high-speed networks to move them around and collaborative, often web-based, platforms to provide access to and sometimes manage the entire system. BrainBrowser is a lightweight, high-performance JavaScript visualization library built to provide easy-to-use, powerful, on-demand visualization of remote datasets in this new research environment. BrainBrowser leverages modern web technologies, such as WebGL, HTML5 and Web Workers, to visualize 3D surface and volumetric neuroimaging data in any modern web browser without requiring any browser plugins. It is thus trivial to integrate BrainBrowser into any web-based platform. BrainBrowser is simple enough to produce a basic web-based visualization in a few lines of code, while at the same time being robust enough to create full-featured visualization applications. BrainBrowser can dynamically load the data required for a given visualization, so no network bandwidth needs to be waisted on data that will not be used. BrainBrowser's integration into the standardized web platform also allows users to consider using 3D data visualization in novel ways, such as for data distribution, data sharing and dynamic online publications. BrainBrowser is already being used in two major online platforms, CBRAIN and LORIS, and has been used to make the 1TB MACACC dataset openly accessible.

Integrating Visualizations into Modeling NEST Simulations

PubMed Central

Nowke, Christian; Zielasko, Daniel; Weyers, Benjamin; Peyser, Alexander; Hentschel, Bernd; Kuhlen, Torsten W.

2015-01-01

Modeling large-scale spiking neural networks showing realistic biological behavior in their dynamics is a complex and tedious task. Since these networks consist of millions of interconnected neurons, their simulation produces an immense amount of data. In recent years it has become possible to simulate even larger networks. However, solutions to assist researchers in understanding the simulation's complex emergent behavior by means of visualization are still lacking. While developing tools to partially fill this gap, we encountered the challenge to integrate these tools easily into the neuroscientists' daily workflow. To understand what makes this so challenging, we looked into the workflows of our collaborators and analyzed how they use the visualizations to solve their daily problems. We identified two major issues: first, the analysis process can rapidly change focus which requires to switch the visualization tool that assists in the current problem domain. Second, because of the heterogeneous data that results from simulations, researchers want to relate data to investigate these effectively. Since a monolithic application model, processing and visualizing all data modalities and reflecting all combinations of possible workflows in a holistic way, is most likely impossible to develop and to maintain, a software architecture that offers specialized visualization tools that run simultaneously and can be linked together to reflect the current workflow, is a more feasible approach. To this end, we have developed a software architecture that allows neuroscientists to integrate visualization tools more closely into the modeling tasks. In addition, it forms the basis for semantic linking of different visualizations to reflect the current workflow. In this paper, we present this architecture and substantiate the usefulness of our approach by common use cases we encountered in our collaborative work. PMID:26733860

BrainBrowser: distributed, web-based neurological data visualization

PubMed Central

Sherif, Tarek; Kassis, Nicolas; Rousseau, Marc-Étienne; Adalat, Reza; Evans, Alan C.

2015-01-01

Recent years have seen massive, distributed datasets become the norm in neuroimaging research, and the methodologies used to analyze them have, in response, become more collaborative and exploratory. Tools and infrastructure are continuously being developed and deployed to facilitate research in this context: grid computation platforms to process the data, distributed data stores to house and share them, high-speed networks to move them around and collaborative, often web-based, platforms to provide access to and sometimes manage the entire system. BrainBrowser is a lightweight, high-performance JavaScript visualization library built to provide easy-to-use, powerful, on-demand visualization of remote datasets in this new research environment. BrainBrowser leverages modern web technologies, such as WebGL, HTML5 and Web Workers, to visualize 3D surface and volumetric neuroimaging data in any modern web browser without requiring any browser plugins. It is thus trivial to integrate BrainBrowser into any web-based platform. BrainBrowser is simple enough to produce a basic web-based visualization in a few lines of code, while at the same time being robust enough to create full-featured visualization applications. BrainBrowser can dynamically load the data required for a given visualization, so no network bandwidth needs to be waisted on data that will not be used. BrainBrowser's integration into the standardized web platform also allows users to consider using 3D data visualization in novel ways, such as for data distribution, data sharing and dynamic online publications. BrainBrowser is already being used in two major online platforms, CBRAIN and LORIS, and has been used to make the 1TB MACACC dataset openly accessible. PMID:25628562

Teaching Science through Pictorial Models during Read-Alouds

ERIC Educational Resources Information Center

Oliveira, Alandeom W.; Rivera, Seema; Glass, Rory; Mastroianni, Michael; Wizner, Francine; Amodeo, Vincent

2013-01-01

This study examines how three elementary teachers refer to pictorial models (photographs, drawings, and cartoons) during science read-alouds. While one teacher used realistic photographs for the purpose of visually verifying facts about crystals, another employed analytical diagrams as heuristic tools to help students visualize complex target…

75 FR 53262 - Privacy Act of 1974; System of Records

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-31

... a new Privacy Act system of records, JUSTICE/FBI- 021, the Data Integration and Visualization System... Act system of records, the Data Integration and Visualization System (DIVS), Justice/FBI-021. The... investigative mission by enabling access, search, integration, and analytics across multiple existing databases...

The Diesel Combustion Collaboratory: Combustion Researchers Collaborating over the Internet

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

C. M. Pancerella; L. A. Rahn; C. Yang

2000-02-01

The Diesel Combustion Collaborator (DCC) is a pilot project to develop and deploy collaborative technologies to combustion researchers distributed throughout the DOE national laboratories, academia, and industry. The result is a problem-solving environment for combustion research. Researchers collaborate over the Internet using DCC tools, which include: a distributed execution management system for running combustion models on widely distributed computers, including supercomputers; web-accessible data archiving capabilities for sharing graphical experimental or modeling data; electronic notebooks and shared workspaces for facilitating collaboration; visualization of combustion data; and video-conferencing and data-conferencing among researchers at remote sites. Security is a key aspect of themore » collaborative tools. In many cases, the authors have integrated these tools to allow data, including large combustion data sets, to flow seamlessly, for example, from modeling tools to data archives. In this paper the authors describe the work of a larger collaborative effort to design, implement and deploy the DCC.« less

Combining data visualization and statistical approaches for interpreting measurements and meta-data: Integrating heatmaps, variable clustering, and mixed regression models

EPA Science Inventory

The advent of new higher throughput analytical instrumentation has put a strain on interpreting and explaining the results from complex studies. Contemporary human, environmental, and biomonitoring data sets are comprised of tens or hundreds of analytes, multiple repeat measures...

Reimagining Khan Analytics for Student Coaches

ERIC Educational Resources Information Center

Cunningham, Jim

2015-01-01

In this paper, I describe preliminary work on a new research project in learning analytics at Arizona State University. In conjunction with an innovative remedial mathematics course using Khan Academy and student coaches, this study seeks to measure the effectiveness of visualized data in assisting student coaches as they help remedial math…

LATUX: An Iterative Workflow for Designing, Validating, and Deploying Learning Analytics Visualizations

ERIC Educational Resources Information Center

Martinez-Maldonado, Roberto; Pardo, Abelardo; Mirriahi, Negin; Yacef, Kalina; Kay, Judy; Clayphan, Andrew

2015-01-01

Designing, validating, and deploying learning analytics tools for instructors or students is a challenge that requires techniques and methods from different disciplines, such as software engineering, human-computer interaction, computer graphics, educational design, and psychology. Whilst each has established its own design methodologies, we now…

Instrumentation: Photodiode Array Detectors in UV-VIS Spectroscopy. Part II.

ERIC Educational Resources Information Center

Jones, Dianna G.

1985-01-01

A previous part (Analytical Chemistry; v57 n9 p1057A) discussed the theoretical aspects of diode ultraviolet-visual (UV-VIS) spectroscopy. This part describes the applications of diode arrays in analytical chemistry, also considering spectroelectrochemistry, high performance liquid chromatography (HPLC), HPLC data processing, stopped flow, and…

Resource Exchange: Making Art to Make a Difference--A Review of a Collaborative Project between an Arts and a Social Service Organization

ERIC Educational Resources Information Center

Barniskis, Becca; Oxton, Jane

2013-01-01

The Resource Exchange design team met in May 2013 to learn about and respond to a multifaceted collaboration between the Paramount Theatre & Visual Arts Center and Hands Across the World (HAW), a social service agency that serves the needs of new refugees and immigrants in St. Cloud, Minnesota. In recent years a significant immigrant…

hackseq: Catalyzing collaboration between biological and computational scientists via hackathon.

PubMed

2017-01-01

hackseq ( http://www.hackseq.com) was a genomics hackathon with the aim of bringing together a diverse set of biological and computational scientists to work on collaborative bioinformatics projects. In October 2016, 66 participants from nine nations came together for three days for hackseq and collaborated on nine projects ranging from data visualization to algorithm development. The response from participants was overwhelmingly positive with 100% (n = 54) of survey respondents saying they would like to participate in future hackathons. We detail key steps for others interested in organizing a successful hackathon and report excerpts from each project.

hackseq: Catalyzing collaboration between biological and computational scientists via hackathon

PubMed Central

2017-01-01

hackseq ( http://www.hackseq.com) was a genomics hackathon with the aim of bringing together a diverse set of biological and computational scientists to work on collaborative bioinformatics projects. In October 2016, 66 participants from nine nations came together for three days for hackseq and collaborated on nine projects ranging from data visualization to algorithm development. The response from participants was overwhelmingly positive with 100% (n = 54) of survey respondents saying they would like to participate in future hackathons. We detail key steps for others interested in organizing a successful hackathon and report excerpts from each project. PMID:28417000

New insight into California’s drought through open data

USGS Publications Warehouse

Read, Emily K.; Bucknell, Mary; Hines, Megan K.; Kreft, James M.; Lucido, Jessica M.; Read, Jordan S.; Schroedl, Carl; Sibley, David M.; Stephan, Shirley; Suftin, Ivan; Thongsavanh, Phethala; Van Den Hoek, Jamon; Walker, Jordan I.; Wernimont, Martin R; Winslow, Luke A.; Yan, Andrew N.

2015-01-01

Historically unprecedented drought in California has brought water issues to the forefront of the nation’s attention. Crucial investigations that concern water policy, management, and research, in turn, require extensive information about the quality and quantity of California’s water. Unfortunately, key sources of pertinent data are unevenly distributed and frequently hard to find. Thankfully, the vital importance of integrating water data across federal, state, and tribal, academic, and private entities, has recently been recognized and addressed through federal initiatives such as the Climate Data Initiative of President Obama’s Climate Action Plan and the Advisory Committee on Water Information’sOpen Water Data Initiative. Here, we demonstrate an application of integrated open water data, visualized and made available online using open source software, for the purpose of exploring the impact of the current California drought. Our collaborative approach and technical tools enabled a rapid, distributed development process. Many positive outcomes have resulted: the application received recognition within and outside of the Federal Government, inspired others to visualize open water data, spurred new collaborations for our group, and strengthened the collaborative relationships within the team of developers. In this article, we describe the technical tools and collaborative process that enabled the success of the application. 

Bring It to the Pitch: Combining Video and Movement Data to Enhance Team Sport Analysis.

PubMed

Stein, Manuel; Janetzko, Halldor; Lamprecht, Andreas; Breitkreutz, Thorsten; Zimmermann, Philipp; Goldlucke, Bastian; Schreck, Tobias; Andrienko, Gennady; Grossniklaus, Michael; Keim, Daniel A

2018-01-01

Analysts in professional team sport regularly perform analysis to gain strategic and tactical insights into player and team behavior. Goals of team sport analysis regularly include identification of weaknesses of opposing teams, or assessing performance and improvement potential of a coached team. Current analysis workflows are typically based on the analysis of team videos. Also, analysts can rely on techniques from Information Visualization, to depict e.g., player or ball trajectories. However, video analysis is typically a time-consuming process, where the analyst needs to memorize and annotate scenes. In contrast, visualization typically relies on an abstract data model, often using abstract visual mappings, and is not directly linked to the observed movement context anymore. We propose a visual analytics system that tightly integrates team sport video recordings with abstract visualization of underlying trajectory data. We apply appropriate computer vision techniques to extract trajectory data from video input. Furthermore, we apply advanced trajectory and movement analysis techniques to derive relevant team sport analytic measures for region, event and player analysis in the case of soccer analysis. Our system seamlessly integrates video and visualization modalities, enabling analysts to draw on the advantages of both analysis forms. Several expert studies conducted with team sport analysts indicate the effectiveness of our integrated approach.

Analytic modeling of aerosol size distributions

NASA Technical Reports Server (NTRS)

Deepack, A.; Box, G. P.

1979-01-01

Mathematical functions commonly used for representing aerosol size distributions are studied parametrically. Methods for obtaining best fit estimates of the parameters are described. A catalog of graphical plots depicting the parametric behavior of the functions is presented along with procedures for obtaining analytical representations of size distribution data by visual matching of the data with one of the plots. Examples of fitting the same data with equal accuracy by more than one analytic model are also given.

The Earth Data Analytic Services (EDAS) Framework

NASA Astrophysics Data System (ADS)

Maxwell, T. P.; Duffy, D.

2017-12-01

Faced with unprecedented growth in earth data volume and demand, NASA has developed the Earth Data Analytic Services (EDAS) framework, a high performance big data analytics framework built on Apache Spark. This framework enables scientists to execute data processing workflows combining common analysis operations close to the massive data stores at NASA. The data is accessed in standard (NetCDF, HDF, etc.) formats in a POSIX file system and processed using vetted earth data analysis tools (ESMF, CDAT, NCO, etc.). EDAS utilizes a dynamic caching architecture, a custom distributed array framework, and a streaming parallel in-memory workflow for efficiently processing huge datasets within limited memory spaces with interactive response times. EDAS services are accessed via a WPS API being developed in collaboration with the ESGF Compute Working Team to support server-side analytics for ESGF. The API can be accessed using direct web service calls, a Python script, a Unix-like shell client, or a JavaScript-based web application. New analytic operations can be developed in Python, Java, or Scala (with support for other languages planned). Client packages in Python, Java/Scala, or JavaScript contain everything needed to build and submit EDAS requests. The EDAS architecture brings together the tools, data storage, and high-performance computing required for timely analysis of large-scale data sets, where the data resides, to ultimately produce societal benefits. It is is currently deployed at NASA in support of the Collaborative REAnalysis Technical Environment (CREATE) project, which centralizes numerous global reanalysis datasets onto a single advanced data analytics platform. This service enables decision makers to compare multiple reanalysis datasets and investigate trends, variability, and anomalies in earth system dynamics around the globe.

Seeking Information with an Information Visualization System: A Study of Cognitive Styles

ERIC Educational Resources Information Center

Yuan, Xiaojun; Zhang, Xiangman; Chen, Chaomei; Avery, Joshua M.

2011-01-01

Introduction: This study investigated the effect of cognitive styles on users' information-seeking task performance using a knowledge domain information visualization system called CiteSpace. Method: Sixteen graduate students participated in a user experiment. Each completed an extended cognitive style analysis wholistic-analytic test (the…

Improving Student Performance Using Nudge Analytics

ERIC Educational Resources Information Center

Feild, Jacqueline

2015-01-01

Providing students with continuous and personalized feedback on their performance is an important part of encouraging self regulated learning. As part of our higher education platform, we built a set of data visualizations to provide feedback to students on their assignment performance. These visualizations give students information about how they…

Visualizing the Solute Vaporization Interference in Flame Atomic Absorption Spectroscopy

ERIC Educational Resources Information Center

Dockery, Christopher R.; Blew, Michael J.; Goode, Scott R.

2008-01-01

Every day, tens of thousands of chemists use analytical atomic spectroscopy in their work, often without knowledge of possible interferences. We present a unique approach to study these interferences by using modern response surface methods to visualize an interference in which aluminum depresses the calcium atomic absorption signal. Calcium…

Innovative Didactic Designs: Visual Analytics and Visual Literacy in School

ERIC Educational Resources Information Center

Stenliden, Linnéa; Nissen, Jörgen; Bodén, Ulrika

2017-01-01

In a world of massively mediated information and communication, students must learn to handle rapidly growing information volumes inside and outside school. Pedagogy attuned to processing this growing production and communication of information is needed. However, ordinary educational models often fail to support students, trialing neither…

The identification of van Hiele level students on the topic of space analytic geometry

NASA Astrophysics Data System (ADS)

Yudianto, E.; Sunardi; Sugiarti, T.; Susanto; Suharto; Trapsilasiwi, D.

2018-03-01

Geometry topics are still considered difficult by most students. Therefore, this study focused on the identification of students related to van Hiele levels. The task used from result of the development of questions related to analytical geometry of space. The results of the work involving 78 students who worked on these questions covered 11.54% (nine students) classified on a visual level; 5.13% (four students) on analysis level; 1.28% (one student) on informal deduction level; 2.56% (two students) on deduction and 2.56% (two students) on rigor level, and 76.93% (sixty students) classified on the pre-visualization level.

T.Rex Visual Analytics for Transactional Exploration

ScienceCinema

None

2018-01-16

T.Rex is PNNL's visual analytics tool that specializes in tabular structured data, like you might open with Excel. It's a client-server application, allowing the server to do a lot of the heavy lifting and the client to open spreadsheets with millions of rows. With datasets of that size, especially if you're unfamiliar with the contents, it's very hard to get a good grasp of what's in it using traditional tools. With T.Rex, the multiple views allow you to see categorical, temporal, numerical, relational, and summary data. The interactivity lets you look across your data and see how things relate to each other.

T.Rex Visual Analytics for Transactional Exploration

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

None

2014-07-01

T.Rex is PNNL's visual analytics tool that specializes in tabular structured data, like you might open with Excel. It's a client-server application, allowing the server to do a lot of the heavy lifting and the client to open spreadsheets with millions of rows. With datasets of that size, especially if you're unfamiliar with the contents, it's very hard to get a good grasp of what's in it using traditional tools. With T.Rex, the multiple views allow you to see categorical, temporal, numerical, relational, and summary data. The interactivity lets you look across your data and see how things relate tomore » each other.« less

AUVA - Augmented Reality Empowers Visual Analytics to explore Medical Curriculum Data.

PubMed

Nifakos, Sokratis; Vaitsis, Christos; Zary, Nabil

2015-01-01

Medical curriculum data play a key role in the structure and the organization of medical programs in Universities around the world. The effective processing and usage of these data may improve the educational environment of medical students. As a consequence, the new generation of health professionals would have improved skills from the previous ones. This study introduces the process of enhancing curriculum data by the use of augmented reality technology as a management and presentation tool. The final goal is to enrich the information presented from a visual analytics approach applied on medical curriculum data and to sustain low levels of complexity of understanding these data.