Meteor Observations as Big Data Citizen Science

NASA Astrophysics Data System (ADS)

Gritsevich, M.; Vinkovic, D.; Schwarz, G.; Nina, A.; Koschny, D.; Lyytinen, E.

2016-12-01

Meteor science represents an excellent example of the citizen science project, where progress in the field has been largely determined by amateur observations. Over the last couple of decades technological advancements in observational techniques have yielded drastic improvements in the quality, quantity and diversity of meteor data, while even more ambitious instruments are about to become operational. This empowers meteor science to boost its experimental and theoretical horizons and seek more advanced scientific goals. We review some of the developments that push meteor science into the Big Data era that requires more complex methodological approaches through interdisciplinary collaborations with other branches of physics and computer science. We argue that meteor science should become an integral part of large surveys in astronomy, aeronomy and space physics, and tackle the complexity of micro-physics of meteor plasma and its interaction with the atmosphere. The recent increased interest in meteor science triggered by the Chelyabinsk fireball helps in building the case for technologically and logistically more ambitious meteor projects. This requires developing new methodological approaches in meteor research, with Big Data science and close collaboration between citizen science, geoscience and astronomy as critical elements. We discuss possibilities for improvements and promote an opportunity for collaboration in meteor science within the currently established BigSkyEarth http://bigskyearth.eu/ network.

Why Do Bees Sting? Reflecting on Talk in Science Lessons

ERIC Educational Resources Information Center

Boctor, Sonia; Rowell, Patricia M.

2004-01-01

Learning science in a meaningful way involves more than doing a series of activities directed towards anticipated outcomes. Learning science entails teacher and children talking together as "co-constructors" of knowledge (Barnes, 1976). Karen Gallas (1995) has described her long-term observations of the kinds of talk which contribute to…

Big data - a 21st century science Maginot Line? No-boundary thinking: shifting from the big data paradigm.

PubMed

Huang, Xiuzhen; Jennings, Steven F; Bruce, Barry; Buchan, Alison; Cai, Liming; Chen, Pengyin; Cramer, Carole L; Guan, Weihua; Hilgert, Uwe Kk; Jiang, Hongmei; Li, Zenglu; McClure, Gail; McMullen, Donald F; Nanduri, Bindu; Perkins, Andy; Rekepalli, Bhanu; Salem, Saeed; Specker, Jennifer; Walker, Karl; Wunsch, Donald; Xiong, Donghai; Zhang, Shuzhong; Zhang, Yu; Zhao, Zhongming; Moore, Jason H

2015-01-01

Whether your interests lie in scientific arenas, the corporate world, or in government, you have certainly heard the praises of big data: Big data will give you new insights, allow you to become more efficient, and/or will solve your problems. While big data has had some outstanding successes, many are now beginning to see that it is not the Silver Bullet that it has been touted to be. Here our main concern is the overall impact of big data; the current manifestation of big data is constructing a Maginot Line in science in the 21st century. Big data is not "lots of data" as a phenomena anymore; The big data paradigm is putting the spirit of the Maginot Line into lots of data. Big data overall is disconnecting researchers and science challenges. We propose No-Boundary Thinking (NBT), applying no-boundary thinking in problem defining to address science challenges.

Hot Talk, Cold Science

NASA Astrophysics Data System (ADS)

Oglesby, Robert J.

One of the hottest topics in climate science is understanding and evaluating the impacts of possible global warming caused by anthropogenic emissions of greenhouse gases. In Hot Talk, Cold Science, S. Fred Singer does not accept global warming. Singer says in his preface, “The purpose of this book is to demonstrate that the evidence [for global warming] is neither settled, nor compelling, nor even convincing. On the contrary, scientists continue to discover new mechanisms for climate change and to put forth new theories to try to account for the fact that global temperature is not rising, even though greenhouse theory says it should”.

From big data to deep insight in developmental science.

PubMed

Gilmore, Rick O

2016-01-01

The use of the term 'big data' has grown substantially over the past several decades and is now widespread. In this review, I ask what makes data 'big' and what implications the size, density, or complexity of datasets have for the science of human development. A survey of existing datasets illustrates how existing large, complex, multilevel, and multimeasure data can reveal the complexities of developmental processes. At the same time, significant technical, policy, ethics, transparency, cultural, and conceptual issues associated with the use of big data must be addressed. Most big developmental science data are currently hard to find and cumbersome to access, the field lacks a culture of data sharing, and there is no consensus about who owns or should control research data. But, these barriers are dissolving. Developmental researchers are finding new ways to collect, manage, store, share, and enable others to reuse data. This promises a future in which big data can lead to deeper insights about some of the most profound questions in behavioral science. © 2016 The Authors. WIREs Cognitive Science published by Wiley Periodicals, Inc.

Presenting the 'Big Ideas' of Science: Earth Science Examples.

ERIC Educational Resources Information Center

King, Chris

2001-01-01

Details an 'explanatory Earth story' on plate tectonics to show how such a 'story' can be developed in an earth science context. Presents five other stories in outline form. Explains the use of these stories as vehicles to present the big ideas of science. (DDR)

Talking Science: Developing a Discourse of Inquiry

ERIC Educational Resources Information Center

Hackling, Mark; Smith, Pru; Murcia, Karen

2010-01-01

A key principle of inquiry-based science education is that the process of inquiry must include opportunities for the exploration of questions and ideas, as well as reasoning with ideas and evidence. Teaching and learning Science therefore involves teachers managing a discourse that supports inquiry and students engaging in talk that facilitates…

The Level and Quality of Accountability Talk in the Science Lessons

ERIC Educational Resources Information Center

Motlhabane, Abraham

2016-01-01

Teachers are actively encouraged to plan their lessons such that there is maximum classroom talk, namely accountability talk. However, many lessons do not display sufficient accountability talk. This study attempted to better understand the level and quality of accountability talk in six science lessons. The study aimed to provide teachers with…

Big Biology: Supersizing Science During the Emergence of the 21st Century

PubMed Central

Vermeulen, Niki

2017-01-01

Ist Biologie das jüngste Mitglied in der Familie von Big Science? Die vermehrte Zusammenarbeit in der biologischen Forschung wurde in der Folge des Human Genome Project zwar zum Gegenstand hitziger Diskussionen, aber Debatten und Reflexionen blieben meist im Polemischen verhaftet und zeigten eine begrenzte Wertschätzung für die Vielfalt und Erklärungskraft des Konzepts von Big Science. Zur gleichen Zeit haben Wissenschafts- und Technikforscher/innen in ihren Beschreibungen des Wandels der Forschungslandschaft die Verwendung des Begriffs Big Science gemieden. Dieser interdisziplinäre Artikel kombiniert eine begriffliche Analyse des Konzepts von Big Science mit unterschiedlichen Daten und Ideen aus einer Multimethodenuntersuchung mehrerer großer Forschungsprojekte in der Biologie. Ziel ist es, ein empirisch fundiertes, nuanciertes und analytisch nützliches Verständnis von Big Biology zu entwickeln und die normativen Debatten mit ihren einfachen Dichotomien und rhetorischen Positionen hinter sich zu lassen. Zwar kann das Konzept von Big Science als eine Mode in der Wissenschaftspolitik gesehen werden – inzwischen vielleicht sogar als ein altmodisches Konzept –, doch lautet meine innovative Argumentation, dass dessen analytische Verwendung unsere Aufmerksamkeit auf die Ausweitung der Zusammenarbeit in den Biowissenschaften lenkt. Die Analyse von Big Biology zeigt Unterschiede zu Big Physics und anderen Formen von Big Science, namentlich in den Mustern der Forschungsorganisation, der verwendeten Technologien und der gesellschaftlichen Zusammenhänge, in denen sie tätig ist. So können Reflexionen über Big Science, Big Biology und ihre Beziehungen zur Wissensproduktion die jüngsten Behauptungen über grundlegende Veränderungen in der Life Science-Forschung in einen historischen Kontext stellen. PMID:27215209

From Big Data to Knowledge in the Social Sciences.

PubMed

Hesse, Bradford W; Moser, Richard P; Riley, William T

2015-05-01

One of the challenges associated with high-volume, diverse datasets is whether synthesis of open data streams can translate into actionable knowledge. Recognizing that challenge and other issues related to these types of data, the National Institutes of Health developed the Big Data to Knowledge or BD2K initiative. The concept of translating "big data to knowledge" is important to the social and behavioral sciences in several respects. First, a general shift to data-intensive science will exert an influence on all scientific disciplines, but particularly on the behavioral and social sciences given the wealth of behavior and related constructs captured by big data sources. Second, science is itself a social enterprise; by applying principles from the social sciences to the conduct of research, it should be possible to ameliorate some of the systemic problems that plague the scientific enterprise in the age of big data. We explore the feasibility of recalibrating the basic mechanisms of the scientific enterprise so that they are more transparent and cumulative; more integrative and cohesive; and more rapid, relevant, and responsive.

From Big Data to Knowledge in the Social Sciences

PubMed Central

Hesse, Bradford W.; Moser, Richard P.; Riley, William T.

2015-01-01

One of the challenges associated with high-volume, diverse datasets is whether synthesis of open data streams can translate into actionable knowledge. Recognizing that challenge and other issues related to these types of data, the National Institutes of Health developed the Big Data to Knowledge or BD2K initiative. The concept of translating “big data to knowledge” is important to the social and behavioral sciences in several respects. First, a general shift to data-intensive science will exert an influence on all scientific disciplines, but particularly on the behavioral and social sciences given the wealth of behavior and related constructs captured by big data sources. Second, science is itself a social enterprise; by applying principles from the social sciences to the conduct of research, it should be possible to ameliorate some of the systemic problems that plague the scientific enterprise in the age of big data. We explore the feasibility of recalibrating the basic mechanisms of the scientific enterprise so that they are more transparent and cumulative; more integrative and cohesive; and more rapid, relevant, and responsive. PMID:26294799

Family Science Talk in Museums: Predicting Children's Engagement From Variations in Talk and Activity.

PubMed

Callanan, Maureen A; Castañeda, Claudia L; Luce, Megan R; Martin, Jennifer L

2017-09-01

Children's developing reasoning skills are better understood within the context of their social and cultural lives. As part of a research-museum partnership, this article reports a study exploring science-relevant conversations of 82 families, with children between 3 and 11 years, while visiting a children's museum exhibit about mammoth bones, and in a focused one-on-one exploration of a "mystery object." Parents' use of a variety of types of science talk predicted children's conceptual engagement in the exhibit, but interestingly, different types of parent talk predicted children's engagement depending on the order of the two activities. The findings illustrate the importance of studying children's thinking in real-world contexts and inform creation of effective real-world science experiences for children and families. © 2017 The Authors. Child Development © 2017 Society for Research in Child Development, Inc.

Big data in forensic science and medicine.

PubMed

Lefèvre, Thomas

2018-07-01

In less than a decade, big data in medicine has become quite a phenomenon and many biomedical disciplines got their own tribune on the topic. Perspectives and debates are flourishing while there is a lack for a consensual definition for big data. The 3Vs paradigm is frequently evoked to define the big data principles and stands for Volume, Variety and Velocity. Even according to this paradigm, genuine big data studies are still scarce in medicine and may not meet all expectations. On one hand, techniques usually presented as specific to the big data such as machine learning techniques are supposed to support the ambition of personalized, predictive and preventive medicines. These techniques are mostly far from been new and are more than 50 years old for the most ancient. On the other hand, several issues closely related to the properties of big data and inherited from other scientific fields such as artificial intelligence are often underestimated if not ignored. Besides, a few papers temper the almost unanimous big data enthusiasm and are worth attention since they delineate what is at stakes. In this context, forensic science is still awaiting for its position papers as well as for a comprehensive outline of what kind of contribution big data could bring to the field. The present situation calls for definitions and actions to rationally guide research and practice in big data. It is an opportunity for grounding a true interdisciplinary approach in forensic science and medicine that is mainly based on evidence. Copyright © 2017 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Big Data and Data Science in Critical Care.

PubMed

Sanchez-Pinto, L Nelson; Luo, Yuan; Churpek, Matthew M

2018-05-09

The digitalization of the health-care system has resulted in a deluge of clinical Big Data and has prompted the rapid growth of data science in medicine. Data science, which is the field of study dedicated to the principled extraction of knowledge from complex data, is particularly relevant in the critical care setting. The availability of large amounts of data in the ICU, the need for better evidence-based care, and the complexity of critical illness makes the use of data science techniques and data-driven research particularly appealing to intensivists. Despite the increasing number of studies and publications in the field, thus far there have been few examples of data science projects that have resulted in successful implementations of data-driven systems in the ICU. However, given the expected growth in the field, intensivists should be familiar with the opportunities and challenges of Big Data and data science. The present article reviews the definitions, types of algorithms, applications, challenges, and future of Big Data and data science in critical care. Copyright © 2018 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

Nursing Knowledge: Big Data Science-Implications for Nurse Leaders.

PubMed

Westra, Bonnie L; Clancy, Thomas R; Sensmeier, Joyce; Warren, Judith J; Weaver, Charlotte; Delaney, Connie W

2015-01-01

The integration of Big Data from electronic health records and other information systems within and across health care enterprises provides an opportunity to develop actionable predictive models that can increase the confidence of nursing leaders' decisions to improve patient outcomes and safety and control costs. As health care shifts to the community, mobile health applications add to the Big Data available. There is an evolving national action plan that includes nursing data in Big Data science, spearheaded by the University of Minnesota School of Nursing. For the past 3 years, diverse stakeholders from practice, industry, education, research, and professional organizations have collaborated through the "Nursing Knowledge: Big Data Science" conferences to create and act on recommendations for inclusion of nursing data, integrated with patient-generated, interprofessional, and contextual data. It is critical for nursing leaders to understand the value of Big Data science and the ways to standardize data and workflow processes to take advantage of newer cutting edge analytics to support analytic methods to control costs and improve patient quality and safety.

Big data science: A literature review of nursing research exemplars.

PubMed

Westra, Bonnie L; Sylvia, Martha; Weinfurter, Elizabeth F; Pruinelli, Lisiane; Park, Jung In; Dodd, Dianna; Keenan, Gail M; Senk, Patricia; Richesson, Rachel L; Baukner, Vicki; Cruz, Christopher; Gao, Grace; Whittenburg, Luann; Delaney, Connie W

Big data and cutting-edge analytic methods in nursing research challenge nurse scientists to extend the data sources and analytic methods used for discovering and translating knowledge. The purpose of this study was to identify, analyze, and synthesize exemplars of big data nursing research applied to practice and disseminated in key nursing informatics, general biomedical informatics, and nursing research journals. A literature review of studies published between 2009 and 2015. There were 650 journal articles identified in 17 key nursing informatics, general biomedical informatics, and nursing research journals in the Web of Science database. After screening for inclusion and exclusion criteria, 17 studies published in 18 articles were identified as big data nursing research applied to practice. Nurses clearly are beginning to conduct big data research applied to practice. These studies represent multiple data sources and settings. Although numerous analytic methods were used, the fundamental issue remains to define the types of analyses consistent with big data analytic methods. There are needs to increase the visibility of big data and data science research conducted by nurse scientists, further examine the use of state of the science in data analytics, and continue to expand the availability and use of a variety of scientific, governmental, and industry data resources. A major implication of this literature review is whether nursing faculty and preparation of future scientists (PhD programs) are prepared for big data and data science. Copyright © 2016 Elsevier Inc. All rights reserved.

'Big data' in pharmaceutical science: challenges and opportunities.

PubMed

Dossetter, Al G; Ecker, Gerhard; Laverty, Hugh; Overington, John

2014-05-01

Future Medicinal Chemistry invited a selection of experts to express their views on the current impact of big data in drug discovery and design, as well as speculate on future developments in the field. The topics discussed include the challenges of implementing big data technologies, maintaining the quality and privacy of data sets, and how the industry will need to adapt to welcome the big data era. Their enlightening responses provide a snapshot of the many and varied contributions being made by big data to the advancement of pharmaceutical science.

Facilitymetrics for Big Ocean Science: Towards Improved Measurement of Scientific Impact

NASA Astrophysics Data System (ADS)

Juniper, K.; Owens, D.; Moran, K.; Pirenne, B.; Hallonsten, O.; Matthews, K.

2016-12-01

Cabled ocean observatories are examples of "Big Science" facilities requiring significant public investments for installation and ongoing maintenance. Large observatory networks in Canada and the United States, for example, have been established after extensive up-front planning and hundreds of millions of dollars in start-up costs. As such, they are analogous to particle accelerators and astronomical observatories, which may often be required to compete for public funding in an environment of ever-tightening national science budget allocations. Additionally, the globalization of Big Science compels these facilities to respond to increasing demands for demonstrable productivity, excellence and competitiveness. How should public expenditures on "Big Science" facilities be evaluated and justified in terms of benefits to the countries that invest in them? Published literature counts are one quantitative measure often highlighted in the annual reports of large science facilities. But, as recent research has demonstrated, publication counts can lead to distorted characterizations of scientific impact, inviting evaluators to calculate scientific outputs in terms of costs per publication—a ratio that can be simplistically misconstrued to conclude Big Science is wildly expensive. Other commonly promoted measurements of Big Science facilities include technical reliability (a.k.a. uptime), provision of training opportunities for Highly Qualified Personnel, generation of commercialization opportunities, and so forth. "Facilitymetrics" is a new empirical focus for scientometrical studies, which has been applied to the evaluation and comparison of synchrotron facilities. This paper extends that quantitative and qualitative examination to a broader inter-disciplinary comparison of Big Science facilities in the ocean science realm to established facilities in the fields of astronomy and particle physics.

Facilitymetrics for Big Ocean Science: Towards Improved Measurement of Scientific Impact

NASA Astrophysics Data System (ADS)

Juniper, K.; Owens, D.; Moran, K.; Pirenne, B.; Hallonsten, O.; Matthews, K.

2016-02-01

Cabled ocean observatories are examples of "Big Science" facilities requiring significant public investments for installation and ongoing maintenance. Large observatory networks in Canada and the United States, for example, have been established after extensive up-front planning and hundreds of millions of dollars in start-up costs. As such, they are analogous to particle accelerators and astronomical observatories, which may often be required to compete for public funding in an environment of ever-tightening national science budget allocations. Additionally, the globalization of Big Science compels these facilities to respond to increasing demands for demonstrable productivity, excellence and competitiveness. How should public expenditures on "Big Science" facilities be evaluated and justified in terms of benefits to the countries that invest in them? Published literature counts are one quantitative measure often highlighted in the annual reports of large science facilities. But, as recent research has demonstrated, publication counts can lead to distorted characterizations of scientific impact, inviting evaluators to calculate scientific outputs in terms of costs per publication—a ratio that can be simplistically misconstrued to conclude Big Science is wildly expensive. Other commonly promoted measurements of Big Science facilities include technical reliability (a.k.a. uptime), provision of training opportunities for Highly Qualified Personnel, generation of commercialization opportunities, and so forth. "Facilitymetrics" is a new empirical focus for scientometrical studies, which has been applied to the evaluation and comparison of synchrotron facilities. This paper extends that quantitative and qualitative examination to a broader inter-disciplinary comparison of Big Science facilities in the ocean science realm to established facilities in the fields of astronomy and particle physics.

Development of a Computer-Based Measure of Listening Comprehension of Science Talk

ERIC Educational Resources Information Center

Lin, Sheau-Wen; Liu, Yu; Chen, Shin-Feng; Wang, Jing-Ru; Kao, Huey-Lien

2015-01-01

The purpose of this study was to develop a computer-based assessment for elementary school students' listening comprehension of science talk within an inquiry-oriented environment. The development procedure had 3 steps: a literature review to define the framework of the test, collecting and identifying key constructs of science talk, and…

The faces of Big Science.

PubMed

Schatz, Gottfried

2014-06-01

Fifty years ago, academic science was a calling with few regulations or financial rewards. Today, it is a huge enterprise confronted by a plethora of bureaucratic and political controls. This change was not triggered by specific events or decisions but reflects the explosive 'knee' in the exponential growth that science has sustained during the past three-and-a-half centuries. Coming to terms with the demands and benefits of 'Big Science' is a major challenge for today's scientific generation. Since its foundation 50 years ago, the European Molecular Biology Organization (EMBO) has been of invaluable help in meeting this challenge.

The Ethics of Big Data and Nursing Science.

PubMed

Milton, Constance L

2017-10-01

Big data is a scientific, social, and technological trend referring to the process and size of datasets available for analysis. Ethical implications arise as healthcare disciplines, including nursing, struggle over questions of informed consent, privacy, ownership of data, and its possible use in epistemology. The author offers straight-thinking possibilities for the use of big data in nursing science.

From big data to deep insight in developmental science

PubMed Central

2016-01-01

The use of the term ‘big data’ has grown substantially over the past several decades and is now widespread. In this review, I ask what makes data ‘big’ and what implications the size, density, or complexity of datasets have for the science of human development. A survey of existing datasets illustrates how existing large, complex, multilevel, and multimeasure data can reveal the complexities of developmental processes. At the same time, significant technical, policy, ethics, transparency, cultural, and conceptual issues associated with the use of big data must be addressed. Most big developmental science data are currently hard to find and cumbersome to access, the field lacks a culture of data sharing, and there is no consensus about who owns or should control research data. But, these barriers are dissolving. Developmental researchers are finding new ways to collect, manage, store, share, and enable others to reuse data. This promises a future in which big data can lead to deeper insights about some of the most profound questions in behavioral science. WIREs Cogn Sci 2016, 7:112–126. doi: 10.1002/wcs.1379 For further resources related to this article, please visit the WIREs website. PMID:26805777

Rethinking Big Science. Modest, mezzo, grand science and the development of the Bevalac, 1971-1993.

PubMed

Westfall, Catherine

2003-03-01

Historians of science have tended to focus exclusively on scale in investigations of largescale research, perhaps because it has been easy to assume that comprehending a phenomenon dubbed "Big Science" hinges on an understanding of bigness. A close look at Lawrence Berkeley Laboratory's Bevalac, a medium-scale "mezzo science" project formed by uniting two preexisting machines--the modest SuperHILAC and the grand Bevatron--shows what can be gained by overcoming this preoccupation with bigness. The Bevalac story reveals how interconnections, connections, and disconnections ultimately led to the development of a new kind of science that transformed the landscape of large-scale research in the United States. Important lessons in historiography also emerge: the value of framing discussions in terms of networks, the necessity of constantly expanding and refining methodology, and the importance of avoiding the rhetoric of participants and instead finding words to tell our own stories.

Entering the Conversation: Exploratory Talk in Middle School Science

ERIC Educational Resources Information Center

Cervetti, Gina N.; DiPardo, Anne L.; Staley, Sara J.

2014-01-01

Much has been written recently about the role of talk in content-area learning, including science learning. However, there is still much to be learned about how teachers begin to engage students in the kinds of peer-to-peer conversations that help them make sense of their investigations in science and that advance their conceptual understandings.…

Enabling a new Paradigm to Address Big Data and Open Science Challenges

NASA Astrophysics Data System (ADS)

Ramamurthy, Mohan; Fisher, Ward

2017-04-01

also need to give scientists an ecosystem that includes data, tools, workflows and other services needed to perform analytics, integration, interpretation, and synthesis - all in the same environment or platform. Instead of moving data to processing systems near users, as is the tradition, the cloud permits one to bring processing, computing, analysis and visualization to data - so called data proximate workbench capabilities, also known as server-side processing. In this talk, I will present the ongoing work at Unidata to facilitate a new paradigm for doing science by offering a suite of tools, resources, and platforms to leverage cloud technologies for addressing both big data and Open Science/reproducibility challenges. That work includes the development and deployment of new protocols for data access and server-side operations and Docker container images of key applications, JupyterHub Python notebook tools, and cloud-based analysis and visualization capability via the CloudIDV tool to enable reproducible workflows and effectively use the accessed data.

The nature of parent-child talk during the sharing of science trade books at home

NASA Astrophysics Data System (ADS)

Groothuis, Becky Anne

This study examined the interactions between parents and their typically developing fourth grade children as they shared science trade books together at home. The aim of this research was to understand how parents and children make meaning together in this context and how parent-child talk related to children's developing scientific views. Four parent-child dyads ranging in information book sharing experiences were videotaped once a week for three weeks in their home during the reading of three science trade books. Both parents and children were interviewed about their interactive experiences following each reading. Parent-child talk was captured and characterized using an analytic framework for discourse, along with a typology of intertextuality and interview data. The results of this research provide preliminary evidence of the capacity of parent-child talk in the context of science books at home to support both children's inquiry skills and their active participation in their sense making behaviors, both of which are integral to their scientific literacy development. The present investigation provides tentative evidence of how parent-child talk about science books can support children's developing social language of science, as well as encourage the practice of science process skills. The results of this study shed light on the importance of older readers' continued access and experiences with science books, and the potential of parent-child talk about science books at home to positively influence children's developing scientific literacy. Keywords: parent-child tally sharing science books, inquiry, scientific literacy.

Students talk about energy in project-based inquiry science

NASA Astrophysics Data System (ADS)

Harrer, Benedikt W.; Flood, Virginia J.; Wittmann, Michael C.

2013-01-01

We examine the types of emergent language eighth grade students in rural Maine middle schools use when they discuss energy in their first experiences with Project-Based Inquiry Science: Energy, a research-based curriculum that uses a specific language for talking about energy. By comparative analysis of the language used by the curriculum materials to students' language, we find that students' talk is at times more aligned with a Stores and Transfer model of energy than the Forms model supported by the curriculum.

Emerging Thoughts on an Approach to Engaging Pupils in Effective Group Talk in Science

ERIC Educational Resources Information Center

Hewitt, Elizabeth

2014-01-01

Group talk opportunities in science can be a rich site for conceptual change. The role of the teacher is vital in scaffolding the exploratory talk which can lead children to talk their way to new understandings and clarify their ideas with peers. This study aims to uncover teacher strategies which lead to effective talk for developing scientific…

On Establishing Big Data Wave Breakwaters with Analytics (Invited)

NASA Astrophysics Data System (ADS)

Riedel, M.

2013-12-01

The Research Data Alliance Big Data Analytics (RDA-BDA) Interest Group seeks to develop community based recommendations on feasible data analytics approaches to address scientific community needs of utilizing large quantities of data. RDA-BDA seeks to analyze different scientific domain applications and their potential use of various big data analytics techniques. A systematic classification of feasible combinations of analysis algorithms, analytical tools, data and resource characteristics and scientific queries will be covered in these recommendations. These combinations are complex since a wide variety of different data analysis algorithms exist (e.g. specific algorithms using GPUs of analyzing brain images) that need to work together with multiple analytical tools reaching from simple (iterative) map-reduce methods (e.g. with Apache Hadoop or Twister) to sophisticated higher level frameworks that leverage machine learning algorithms (e.g. Apache Mahout). These computational analysis techniques are often augmented with visual analytics techniques (e.g. computational steering on large-scale high performance computing platforms) to put the human judgement into the analysis loop or new approaches with databases that are designed to support new forms of unstructured or semi-structured data as opposed to the rather tradtional structural databases (e.g. relational databases). More recently, data analysis and underpinned analytics frameworks also have to consider energy footprints of underlying resources. To sum up, the aim of this talk is to provide pieces of information to understand big data analytics in the context of science and engineering using the aforementioned classification as the lighthouse and as the frame of reference for a systematic approach. This talk will provide insights about big data analytics methods in context of science within varios communities and offers different views of how approaches of correlation and causality offer complementary methods

Leo Szilard Lectureship Award Talk: From Reductionism to Complexity; A Theoretical Physicist's Journey into Biology and the Social Sciences

NASA Astrophysics Data System (ADS)

West, Geoffrey

2013-04-01

In this talk I review how a high energy physicist serendipitously migrated from quarks and gluons, dark matter and string theory to thinking about equally big topics like why we live for 100 years (and not a thousand or 2-3 like a mouse), how is this generated from molecular time scales, why do we sleep and where does 8 hours come from, and how is this related to the rate at which we evolve, can there be a quantitative, mathematisable science of cities and companies, and can our exponentially expanding socio-economic universe be sustained, etc, etc? I consider these as integral parts of physics, related to the interface between Reductionism and Complexity, Thermodynamics and Information Theory. The saga will be a personal one ranging from issues connected with the demise of the SSC and attacks on science to the future role of physics and transdisciplinary thinking.

Elementary School Students' Science Talk Ability in Inquiry-Oriented Settings in Taiwan: Test Development, Verification, and Performance Benchmarks

ERIC Educational Resources Information Center

Lin, Sheau-Wen; Liu, Yu; Chen, Shin-Feng; Wang, Jing-Ru; Kao, Huey-Lien

2016-01-01

The purpose of this study was to develop a computer-based measure of elementary students' science talk and to report students' benchmarks. The development procedure had three steps: defining the framework of the test, collecting and identifying key reference sets of science talk, and developing and verifying the science talk instrument. The…

A Talk Focus for Promoting Enjoyment and Developing Understanding in Science

ERIC Educational Resources Information Center

Dawes, Lyn; Dore, Babs; Loxley, Peter; Nicholls, Linda

2010-01-01

In this paper we suggest a practical, talk-based model for the successful pursuit of teaching science in primary classrooms (Loxley et al., 2010). This model is not only based on our own experience of teaching in primary schools, and of training teachers to do so, but is also based substantially on research on classroom talk, which has built upon…

Earth Science Data Analysis in the Era of Big Data

NASA Technical Reports Server (NTRS)

Kuo, K.-S.; Clune, T. L.; Ramachandran, R.

2014-01-01

Anyone with even a cursory interest in information technology cannot help but recognize that "Big Data" is one of the most fashionable catchphrases of late. From accurate voice and facial recognition, language translation, and airfare prediction and comparison, to monitoring the real-time spread of flu, Big Data techniques have been applied to many seemingly intractable problems with spectacular successes. They appear to be a rewarding way to approach many currently unsolved problems. Few fields of research can claim a longer history with problems involving voluminous data than Earth science. The problems we are facing today with our Earth's future are more complex and carry potentially graver consequences than the examples given above. How has our climate changed? Beside natural variations, what is causing these changes? What are the processes involved and through what mechanisms are these connected? How will they impact life as we know it? In attempts to answer these questions, we have resorted to observations and numerical simulations with ever-finer resolutions, which continue to feed the "data deluge." Plausibly, many Earth scientists are wondering: How will Big Data technologies benefit Earth science research? As an example from the global water cycle, one subdomain among many in Earth science, how would these technologies accelerate the analysis of decades of global precipitation to ascertain the changes in its characteristics, to validate these changes in predictive climate models, and to infer the implications of these changes to ecosystems, economies, and public health? Earth science researchers need a viable way to harness the power of Big Data technologies to analyze large volumes and varieties of data with velocity and veracity. Beyond providing speedy data analysis capabilities, Big Data technologies can also play a crucial, albeit indirect, role in boosting scientific productivity by facilitating effective collaboration within an analysis environment

Small Talk: A Big Communicative Function in the Organization?

ERIC Educational Resources Information Center

Levine, Deborah Clark

Defining small talk as "superficial talk about matters of little concern," a study examined the role of small talk in the work place. Subjects, 51 white collar workers and clerical employees at three corporations, an Eastern state university, and two small businesses completed a questionnaire concerning the following questions: (1) What…

Big Science for Growing Minds: Constructivist Classrooms for Young Thinkers. Early Childhood Education Series

ERIC Educational Resources Information Center

Brooks, Jacqueline Grennon

2011-01-01

Strong evidence from recent brain research shows that the intentional teaching of science is crucial in early childhood. "Big Science for Growing Minds" describes a groundbreaking curriculum that invites readers to rethink science education through a set of unifying concepts or "big ideas." Using an integrated learning approach, the author shows…

Filling a gap: Public talks about earthquake preparation and the 'Big One'

NASA Astrophysics Data System (ADS)

Reinen, L. A.

2013-12-01

Residents of southern California are aware they live in a seismically active area and earthquake drills have trained us to Duck-Cover-Hold On. While many of my acquaintance are familiar with what to do during an earthquake, few have made preparations for living with the aftermath of a large earthquake. The ShakeOut Scenario (Jones et al., USGS Open File Report 2008-1150) describes the physical, social, and economic consequences of a plausible M7.8 earthquake on the southernmost San Andreas Fault. While not detailing an actual event, the ShakeOut Scenario illustrates how individual and community preparation may improve the potential after-affects of a major earthquake in the region. To address the gap between earthquake drills and preparation in my community, for the past several years I have been giving public talks to promote understanding of: the science behind the earthquake predictions; why individual, as well as community, preparation is important; and, ways in which individuals can prepare their home and work environments. The public presentations occur in an array of venues, including elementary school and college classes, a community forum linked with the annual ShakeOut Drill, and local businesses including the local microbrewery. While based on the same fundamental information, each presentation is modified for audience and setting. Assessment of the impact of these talks is primarily anecdotal and includes an increase in the number of venues requesting these talks, repeat invitations, and comments from audience members (sometimes months or years after a talk). I will present elements of these talks, the background information used, and examples of how they have affected change in the earthquake preparedness of audience members. Discussion and suggestions (particularly about effective means of conducting rigorous long-term assessment) are strongly encouraged.

Student use of narrative and paradigmatic forms of talk in elementary science conversations

NASA Astrophysics Data System (ADS)

Kurth, Lori A.; Kidd, Raymond; Gardner, Roberta; Smith, Edward L.

2002-11-01

The purpose of this work was to examine and characterize student use of narrative and paradigmatic expression in elementary science discourse. This interpretive study occurred over a 2-year period in a professional development school with a largely international population. This analysis focused on the narrative and paradigmatic modes of expression used by combined first-second- and second-grade students in a semistructured, fairly autonomous, whole-class conversational format. Students demonstrated competence with both modes of talk at the beginning of the year. Over time, students moved toward more paradigmatic talk, but narrative examples continued to be key components of the science conversations. Topically, students used narrative more often for life sciences and paradigmatic talk for physical sciences. For gender there were no qualitative differences in narrative or paradigmatic expression. However, boys obtained more opportunities to practice their use of both discourse forms by either receiving more speaking turns or expressing more language features per turn. These conversations show that narrative and paradigmatic modes in science need not be in opposition but can, in fact, be used together in complementary ways that are mutually enhancing.

Teachers' Ways of Talking about Nature of Science and Its Teaching

ERIC Educational Resources Information Center

Leden, Lotta; Hansson, Lena; Redfors, Andreas; Ideland, Malin

2015-01-01

Nature of science (NOS) has for a long time been regarded as a key component in science teaching. Much research has focused on students' and teachers' views of NOS, while less attention has been paid to teachers' perspectives on NOS teaching. This article focuses on in-service science teachers' ways of talking about NOS and NOS teaching, e.g. what…

Toward a Big Data Science: A challenge of "Science Cloud"

NASA Astrophysics Data System (ADS)

Murata, Ken T.; Watanabe, Hidenobu

2013-04-01

During these 50 years, along with appearance and development of high-performance computers (and super-computers), numerical simulation is considered to be a third methodology for science, following theoretical (first) and experimental and/or observational (second) approaches. The variety of data yielded by the second approaches has been getting more and more. It is due to the progress of technologies of experiments and observations. The amount of the data generated by the third methodologies has been getting larger and larger. It is because of tremendous development and programming techniques of super computers. Most of the data files created by both experiments/observations and numerical simulations are saved in digital formats and analyzed on computers. The researchers (domain experts) are interested in not only how to make experiments and/or observations or perform numerical simulations, but what information (new findings) to extract from the data. However, data does not usually tell anything about the science; sciences are implicitly hidden in the data. Researchers have to extract information to find new sciences from the data files. This is a basic concept of data intensive (data oriented) science for Big Data. As the scales of experiments and/or observations and numerical simulations get larger, new techniques and facilities are required to extract information from a large amount of data files. The technique is called as informatics as a fourth methodology for new sciences. Any methodologies must work on their facilities: for example, space environment are observed via spacecraft and numerical simulations are performed on super-computers, respectively in space science. The facility of the informatics, which deals with large-scale data, is a computational cloud system for science. This paper is to propose a cloud system for informatics, which has been developed at NICT (National Institute of Information and Communications Technology), Japan. The NICT science

White House Science Fair

NASA Image and Video Library

2013-04-22

Director of Strategic Communications and Senior Science and Technology Policy Analyst, Office of Science and Technology Policy, Executive Office of the President, Rick Weiss, left, “Big Bang Theory” co-creator Bill Prady, center, and NASA Mars Curiosity Landing mission controller, Bobak "Mohawk Guy" Ferdowsi talk during the White House Science Fair held at the White House, April 22, 2013. The science fair celebrated student winners of a broad range of science, technology, engineering and math (STEM) competitions from across the country. Photo Credit: (NASA/Bill Ingalls)

Big Data in Science and Healthcare: A Review of Recent Literature and Perspectives

PubMed Central

Miron-Shatz, T.; Lau, A. Y. S.; Paton, C.

2014-01-01

Summary Objectives As technology continues to evolve and rise in various industries, such as healthcare, science, education, and gaming, a sophisticated concept known as Big Data is surfacing. The concept of analytics aims to understand data. We set out to portray and discuss perspectives of the evolving use of Big Data in science and healthcare and, to examine some of the opportunities and challenges. Methods A literature review was conducted to highlight the implications associated with the use of Big Data in scientific research and healthcare innovations, both on a large and small scale. Results Scientists and health-care providers may learn from one another when it comes to understanding the value of Big Data and analytics. Small data, derived by patients and consumers, also requires analytics to become actionable. Connectivism provides a framework for the use of Big Data and analytics in the areas of science and healthcare. This theory assists individuals to recognize and synthesize how human connections are driving the increase in data. Despite the volume and velocity of Big Data, it is truly about technology connecting humans and assisting them to construct knowledge in new ways. Concluding Thoughts The concept of Big Data and associated analytics are to be taken seriously when approaching the use of vast volumes of both structured and unstructured data in science and health-care. Future exploration of issues surrounding data privacy, confidentiality, and education are needed. A greater focus on data from social media, the quantified self-movement, and the application of analytics to “small data” would also be useful. PMID:25123717

Detection and Characterisation of Meteors as a Big Data Citizen Science project

NASA Astrophysics Data System (ADS)

Gritsevich, M.

2017-12-01

Out of a total around 50,000 meteorites currently known to science, the atmospheric passage was recorded instrumentally in only 30 cases with the potential to derive their atmospheric trajectories and pre-impact heliocentric orbits. Similarly, while the observations of meteors, add thousands of new entries per month to existing databases, it is extremely rare they lead to meteorite recovery. Meteor studies thus represent an excellent example of the Big Data citizen science project, where progress in the field largely depends on the prompt identification and characterisation of meteor events as well as on extensive and valuable contributions by amateur observers. Over the last couple of decades technological advancements in observational techniques have yielded drastic improvements in the quality, quantity and diversity of meteor data, while even more ambitious instruments are about to become operational. This empowers meteor science to boost its experimental and theoretical horizons and seek more advanced scientific goals. We review some of the developments that push meteor science into the Big Data era that requires more complex methodological approaches through interdisciplinary collaborations with other branches of physics and computer science. We argue that meteor science should become an integral part of large surveys in astronomy, aeronomy and space physics, and tackle the complexity of micro-physics of meteor plasma and its interaction with the atmosphere. The recent increased interest in meteor science triggered by the Chelyabinsk fireball helps in building the case for technologically and logistically more ambitious meteor projects. This requires developing new methodological approaches in meteor research, with Big Data science and close collaboration between citizen science, geoscience and astronomy as critical elements. We discuss possibilities for improvements and promote an opportunity for collaboration in meteor science within the currently

Complexity Science Framework for Big Data: Data-enabled Science

NASA Astrophysics Data System (ADS)

Surjalal Sharma, A.

2016-07-01

such new analytics can yield improved risk estimates. The challenges of scientific inference from complex and massive data are addressed by data-enabled science, also referred as the Fourth paradigm, after experiment, theory and simulation. An example of this approach is the modelling of dynamical and statistical features of natural systems, without assumptions of specific processes. An effective use of the techniques of complexity science to yield the inherent features of a system from extensive data from observations and large scale numerical simulations is evident in the case of Earth's magnetosphere. The multiscale nature of the magnetosphere makes the numerical simulations a challenge, requiring very large computing resources. The reconstruction of dynamics from observational data can however yield the inherent characteristics using typical desktop computers. Such studies for other systems are in progress. Data-enabled approach using the framework of complexity science provides new techniques for modelling and prediction using Big Data. The studies of Earth's magnetosphere, provide an example of the potential for a new approach to the development of quantitative analytic tools.

Examining Teacher Talk in an Engineering Design-Based Science Curricular Unit

NASA Astrophysics Data System (ADS)

Aranda, Maurina L.; Lie, Richard; Selcen Guzey, S.; Makarsu, Murat; Johnston, Amanda; Moore, Tamara J.

2018-03-01

Recent science education reforms highlight the importance for teachers to implement effective instructional practices that promote student learning of science and engineering content and their practices. Effective classroom discussion has been shown to support the learning of science, but work is needed to examine teachers' enactment of engineering design-based science curricula by focusing on the content, complexity, structure, and orchestration of classroom discussions. In the present study, we explored teacher-student talk with respect to science in a middle school curriculum focused on genetics and genetic engineering. Our study was guided by the following major research question: What are the similarities and differences in teacher talk moves that occurred within an engineering design-based science unit enacted by two teachers? Through qualitative and quantitative approaches, we found that there were clear differences in two teachers' use of questioning strategies and presentation of new knowledge that affected the level of student involvement in classroom discourse and the richness and details of student contributions to the conversations. We also found that the verbal explanations of science content differed between two teachers. Collectively, the findings in this study demonstrate that although the teachers worked together to design an engineering designed-based science curriculum unit, their use of different discussion strategies and patterns, and interactions with students differed to affect classroom discourse.

Nursing Needs Big Data and Big Data Needs Nursing.

PubMed

Brennan, Patricia Flatley; Bakken, Suzanne

2015-09-01

Contemporary big data initiatives in health care will benefit from greater integration with nursing science and nursing practice; in turn, nursing science and nursing practice has much to gain from the data science initiatives. Big data arises secondary to scholarly inquiry (e.g., -omics) and everyday observations like cardiac flow sensors or Twitter feeds. Data science methods that are emerging ensure that these data be leveraged to improve patient care. Big data encompasses data that exceed human comprehension, that exist at a volume unmanageable by standard computer systems, that arrive at a velocity not under the control of the investigator and possess a level of imprecision not found in traditional inquiry. Data science methods are emerging to manage and gain insights from big data. The primary methods included investigation of emerging federal big data initiatives, and exploration of exemplars from nursing informatics research to benchmark where nursing is already poised to participate in the big data revolution. We provide observations and reflections on experiences in the emerging big data initiatives. Existing approaches to large data set analysis provide a necessary but not sufficient foundation for nursing to participate in the big data revolution. Nursing's Social Policy Statement guides a principled, ethical perspective on big data and data science. There are implications for basic and advanced practice clinical nurses in practice, for the nurse scientist who collaborates with data scientists, and for the nurse data scientist. Big data and data science has the potential to provide greater richness in understanding patient phenomena and in tailoring interventional strategies that are personalized to the patient. © 2015 Sigma Theta Tau International.

A Big Data Guide to Understanding Climate Change: The Case for Theory-Guided Data Science.

PubMed

Faghmous, James H; Kumar, Vipin

2014-09-01

Global climate change and its impact on human life has become one of our era's greatest challenges. Despite the urgency, data science has had little impact on furthering our understanding of our planet in spite of the abundance of climate data. This is a stark contrast from other fields such as advertising or electronic commerce where big data has been a great success story. This discrepancy stems from the complex nature of climate data as well as the scientific questions climate science brings forth. This article introduces a data science audience to the challenges and opportunities to mine large climate datasets, with an emphasis on the nuanced difference between mining climate data and traditional big data approaches. We focus on data, methods, and application challenges that must be addressed in order for big data to fulfill their promise with regard to climate science applications. More importantly, we highlight research showing that solely relying on traditional big data techniques results in dubious findings, and we instead propose a theory-guided data science paradigm that uses scientific theory to constrain both the big data techniques as well as the results-interpretation process to extract accurate insight from large climate data .

Teaching About the Epistemology of Science in Upper Secondary Schools: An Analysis of Teachers' Classroom Talk

NASA Astrophysics Data System (ADS)

Ryder, Jim; Leach, John

2008-02-01

We begin by drawing upon the available literature to identify four characteristics of teacher talk likely to support student learning about the epistemology of science: making appropriate statements about the epistemology of science in the classroom, linking the epistemology of science with specific science concepts, stating and justifying learning aims, and working with students’ ideas. These characteristics are then used in an analysis of the classroom talk of seven teachers as they use published resources for teaching about the epistemology of science for the first time. By focusing on teachers’ initial classroom experiences of using these published resources we identify feasible starting points for professional development activities likely to support these teachers in developing their expertise in this challenging area of teaching. Lessons focused on a specific aspect of the epistemology of science (the development of theoretical models) contextualised within two content areas: electromagnetism and cell membrane structure. Our analysis shows that none of these teachers made clearly inappropriate statements about the epistemology of science in the classroom. However, expertise related to the remaining three characteristics of teacher talk varied between teachers. For example, some teachers used a range of approaches to working with students’ ideas during whole class talk (e.g. asking students to justify their ideas and challenging students’ views) whereas for other teachers students’ ideas were not a strong feature of classroom discourse.

Perspectives on Policy and the Value of Nursing Science in a Big Data Era.

PubMed

Gephart, Sheila M; Davis, Mary; Shea, Kimberly

2018-01-01

As data volume explodes, nurse scientists grapple with ways to adapt to the big data movement without jeopardizing its epistemic values and theoretical focus that celebrate while acknowledging the authority and unity of its body of knowledge. In this article, the authors describe big data and emphasize ways that nursing science brings value to its study. Collective nursing voices that call for more nursing engagement in the big data era are answered with ways to adapt and integrate theoretical and domain expertise from nursing into data science.

Conducting Talk in Secondary Science Classrooms: Investigating Instructional Moves and Teachers' Beliefs

ERIC Educational Resources Information Center

Pimentel, Diane Silva; McNeill, Katherine L.

2013-01-01

Whole-class discussion is a common instructional approach used by secondary science teachers. When orchestrated well, such an approach can provide students with opportunities to engage in extensive science talk with the benefit of teacher guidance and feedback. Our study investigated teachers' approaches to discussion during the piloting of an…

A Big Data Guide to Understanding Climate Change: The Case for Theory-Guided Data Science

PubMed Central

Kumar, Vipin

2014-01-01

Abstract Global climate change and its impact on human life has become one of our era's greatest challenges. Despite the urgency, data science has had little impact on furthering our understanding of our planet in spite of the abundance of climate data. This is a stark contrast from other fields such as advertising or electronic commerce where big data has been a great success story. This discrepancy stems from the complex nature of climate data as well as the scientific questions climate science brings forth. This article introduces a data science audience to the challenges and opportunities to mine large climate datasets, with an emphasis on the nuanced difference between mining climate data and traditional big data approaches. We focus on data, methods, and application challenges that must be addressed in order for big data to fulfill their promise with regard to climate science applications. More importantly, we highlight research showing that solely relying on traditional big data techniques results in dubious findings, and we instead propose a theory-guided data science paradigm that uses scientific theory to constrain both the big data techniques as well as the results-interpretation process to extract accurate insight from large climate data. PMID:25276499

Learning science through talk: A case study of middle school students engaged in collaborative group investigation

NASA Astrophysics Data System (ADS)

Zinicola, Debra Ann

Reformers call for change in how science is taught in schools by shifting the focus towards conceptual understanding for all students. Constructivist learning is being promoted through the dissemination of National and State Science Standards that recommend group learning practices in science classrooms. This study examined the science learning and interactions, using case study methodology, of one collaborative group of 4 students in an urban middle school. Data on science talk and social interaction were collected over 9 weeks through 12 science problem solving sessions. To determine student learning through peer interaction, varied group structures were implemented, and students reflected on the group learning experience. Data included: field notes, cognitive and reflective journals, audiotapes and videotapes of student talk, and audiotapes of group interviews. Journal data were analyzed quantitatively and all other data was transcribed into The Ethnograph database for qualitative analysis. The data record was organized into social and cognitive domains and coded with respect to interaction patterns to show how group members experienced the social construction of science concepts. The most significant finding was that all students learned as a result of 12 talk sessions as evidenced by pre- and post-conceptual change scores. Interactions that promoted learning involved students connecting their thoughts, rephrasing, and challenging ideas. The role structure was only used by students about 15% of the time, but it started the talk with a science focus, created awareness of scientific methods, and created an awareness of equitable member participation. Students offered more spontaneous, explanatory talk when the role structure was relaxed, but did not engage in as much scientific writing. They said the role structure was important for helping them know what to do in the talk but they no longer needed it after a time. Gender bias, status, and early adolescent

Big Data in Plant Science: Resources and Data Mining Tools for Plant Genomics and Proteomics.

PubMed

Popescu, George V; Noutsos, Christos; Popescu, Sorina C

2016-01-01

In modern plant biology, progress is increasingly defined by the scientists' ability to gather and analyze data sets of high volume and complexity, otherwise known as "big data". Arguably, the largest increase in the volume of plant data sets over the last decade is a consequence of the application of the next-generation sequencing and mass-spectrometry technologies to the study of experimental model and crop plants. The increase in quantity and complexity of biological data brings challenges, mostly associated with data acquisition, processing, and sharing within the scientific community. Nonetheless, big data in plant science create unique opportunities in advancing our understanding of complex biological processes at a level of accuracy without precedence, and establish a base for the plant systems biology. In this chapter, we summarize the major drivers of big data in plant science and big data initiatives in life sciences with a focus on the scope and impact of iPlant, a representative cyberinfrastructure platform for plant science.

Big data in medical science--a biostatistical view.

PubMed

Binder, Harald; Blettner, Maria

2015-02-27

Inexpensive techniques for measurement and data storage now enable medical researchers to acquire far more data than can conveniently be analyzed by traditional methods. The expression "big data" refers to quantities on the order of magnitude of a terabyte (1012 bytes); special techniques must be used to evaluate such huge quantities of data in a scientifically meaningful way. Whether data sets of this size are useful and important is an open question that currently confronts medical science. In this article, we give illustrative examples of the use of analytical techniques for big data and discuss them in the light of a selective literature review. We point out some critical aspects that should be considered to avoid errors when large amounts of data are analyzed. Machine learning techniques enable the recognition of potentially relevant patterns. When such techniques are used, certain additional steps should be taken that are unnecessary in more traditional analyses; for example, patient characteristics should be differentially weighted. If this is not done as a preliminary step before similarity detection, which is a component of many data analysis operations, characteristics such as age or sex will be weighted no higher than any one out of 10 000 gene expression values. Experience from the analysis of conventional observational data sets can be called upon to draw conclusions about potential causal effects from big data sets. Big data techniques can be used, for example, to evaluate observational data derived from the routine care of entire populations, with clustering methods used to analyze therapeutically relevant patient subgroups. Such analyses can provide complementary information to clinical trials of the classic type. As big data analyses become more popular, various statistical techniques for causality analysis in observational data are becoming more widely available. This is likely to be of benefit to medical science, but specific adaptations will

Examining Scientific and Technical Writing Strategies in the 11th Century Chinese Science Book "Brush Talks from Dream Brook"

ERIC Educational Resources Information Center

Zhang, Yuejiao

2013-01-01

This article examines the influential Chinese science book "Brush Talks from Dream Brook," written by Shen Kuo in the 11th century. I suggest that "Brush Talks" reveals a tension between institutionalized science and science in the public, and a gap between the making of scientific knowledge and the communication of such…

Teacher talk about science: An examination of the constructed understanding of science held by four elementary school teachers

NASA Astrophysics Data System (ADS)

Price, Robert John

The elementary school teacher's personal understanding of science has not been a primary focus of consideration in educational reform discussions. This study examines how four elementary school teachers have constructed their personal understanding of science. The purpose of this study is to explore core understandings about science held by these teachers, and to examine the origins of these ideas. This study assumes that a teacher's understanding of science is unique and constructed on personal experiences affected by influences. This study further explores the relationship of the teachers understanding to the school's stated curriculum. The theoretical framework of this research recognizes three guiding assumptions: science exists as a set of ideas that have developed over time through competing discourses; the teacher plays an important role in the implementation of the science curriculum; and the guiding influences of a teacher's understanding of science are associated with power that emerges from discourse. The methodology in this qualitative study is closely associated with narrative inquiry. Data collection methods include a questionnaire, focus group sessions, and individual interviews. Teachers' stories were collected through collaborative interview opportunities between the researcher and the participants. The findings are presented through the narratives of the four teachers, and are organized through the guiding influences, and talk related to the stated science curriculum. The teachers' talk can be categorized by three broad guiding influences: family, education, and an image of science. The talk related to the stated curriculum illustrates both conflicts, and a relationship between the teachers' understanding of science and the curriculum. The finding of this study provides evidence that each teacher's understanding of science is unique and developed over time. Additionally, this understanding plays a role in how the stated curriculum is discussed and

From darwin to the census of marine life: marine biology as big science.

PubMed

Vermeulen, Niki

2013-01-01

With the development of the Human Genome Project, a heated debate emerged on biology becoming 'big science'. However, biology already has a long tradition of collaboration, as natural historians were part of the first collective scientific efforts: exploring the variety of life on earth. Such mappings of life still continue today, and if field biology is gradually becoming an important subject of studies into big science, research into life in the world's oceans is not taken into account yet. This paper therefore explores marine biology as big science, presenting the historical development of marine research towards the international 'Census of Marine Life' (CoML) making an inventory of life in the world's oceans. Discussing various aspects of collaboration--including size, internationalisation, research practice, technological developments, application, and public communication--I will ask if CoML still resembles traditional collaborations to collect life. While showing both continuity and change, I will argue that marine biology is a form of natural history: a specific way of working together in biology that has transformed substantially in interaction with recent developments in the life sciences and society. As a result, the paper does not only give an overview of transformations towards large scale research in marine biology, but also shines a new light on big biology, suggesting new ways to deepen the understanding of collaboration in the life sciences by distinguishing between different 'collective ways of knowing'.

Big Data: Philosophy, Emergence, Crowdledge, and Science Education

ERIC Educational Resources Information Center

dos Santos, Renato P.

2015-01-01

Big Data already passed out of hype, is now a field that deserves serious academic investigation, and natural scientists should also become familiar with Analytics. On the other hand, there is little empirical evidence that any science taught in school is helping people to lead happier, more prosperous, or more politically well-informed lives. In…

Big Science and Big Big Science

ERIC Educational Resources Information Center

Marshall, Steve

2012-01-01

In his introduction to the science shows feature in "Primary Science" 115, Ian B. Dunne asks the question "Why have science shows?" He lists a host of very sound reasons, starting with because "science is fun" so why not engage and entertain, inspire, grab attention and encourage them to learn? He goes onto to state that: "Even in today's…

The role of administrative data in the big data revolution in social science research.

PubMed

Connelly, Roxanne; Playford, Christopher J; Gayle, Vernon; Dibben, Chris

2016-09-01

The term big data is currently a buzzword in social science, however its precise meaning is ambiguous. In this paper we focus on administrative data which is a distinctive form of big data. Exciting new opportunities for social science research will be afforded by new administrative data resources, but these are currently under appreciated by the research community. The central aim of this paper is to discuss the challenges associated with administrative data. We emphasise that it is critical for researchers to carefully consider how administrative data has been produced. We conclude that administrative datasets have the potential to contribute to the development of high-quality and impactful social science research, and should not be overlooked in the emerging field of big data. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

A Demonstration of Big Data Technology for Data Intensive Earth Science (Invited)

NASA Astrophysics Data System (ADS)

Kuo, K.; Clune, T.; Ramachandran, R.; Rushing, J.; Fekete, G.; Lin, A.; Doan, K.; Oloso, A. O.; Duffy, D.

2013-12-01

Big Data technologies exhibit great potential to change the way we conduct scientific investigations, especially analysis of voluminous and diverse data sets. Obviously, not all Big Data technologies are applicable to all aspects of scientific data analysis. Our NASA Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST) project, Automated Event Service (AES), pioneers the exploration of Big Data technologies for data intensive Earth science. Since Earth science data are largely stored and manipulated in the form of multidimensional arrays, the project first evaluates array performance of several candidate Big Data technologies, including MapReduce (Hadoop), SciDB, and a custom-built Polaris system, which have one important feature in common: shared nothing architecture. The evaluation finds SicDB to be the most promising. In this presentation, we demonstrate SciDB using a couple of use cases, each operating on a distinct data set in the regular latitude-longitude grid. The first use case is the discovery and identification of blizzards using NASA's Modern Era Retrospective-analysis for Research and Application (MERRA) data sets. The other finds diurnal signals in the same 8-year period using SSMI data from three different instruments with different equator crossing times by correlating their retrieved parameters. In addition, the AES project is also developing a collaborative component to enable the sharing of event queries and results. Preliminary capabilities will be presented as well.

From Darwin to the Census of Marine Life: Marine Biology as Big Science

PubMed Central

Vermeulen, Niki

2013-01-01

With the development of the Human Genome Project, a heated debate emerged on biology becoming ‘big science’. However, biology already has a long tradition of collaboration, as natural historians were part of the first collective scientific efforts: exploring the variety of life on earth. Such mappings of life still continue today, and if field biology is gradually becoming an important subject of studies into big science, research into life in the world's oceans is not taken into account yet. This paper therefore explores marine biology as big science, presenting the historical development of marine research towards the international ‘Census of Marine Life’ (CoML) making an inventory of life in the world's oceans. Discussing various aspects of collaboration – including size, internationalisation, research practice, technological developments, application, and public communication – I will ask if CoML still resembles traditional collaborations to collect life. While showing both continuity and change, I will argue that marine biology is a form of natural history: a specific way of working together in biology that has transformed substantially in interaction with recent developments in the life sciences and society. As a result, the paper does not only give an overview of transformations towards large scale research in marine biology, but also shines a new light on big biology, suggesting new ways to deepen the understanding of collaboration in the life sciences by distinguishing between different ‘collective ways of knowing’. PMID:23342119

Technology and science in classroom and interview talk with Swiss lower secondary school students: a Marxist sociological approach

NASA Astrophysics Data System (ADS)

Roth, Wolff-Michael

2013-06-01

In much of science education research, the content of talk tends to be attributed to the persons who produce the sound-words in a speech situation. A radically different, sociological perspective on language-in-use grounded in Marxism derives from the work of L. S. Vygotsky and the members of the circle around M. M. Bakhtin. Accordingly, each word belongs to speaker and recipient simultaneously. It represents collective consciousness and, therefore, shared ideology, which can no longer be attributed to the individual. The purpose of this study is to develop a sociological perspective on language in science education, a perspective in which language continuously changes. I articulate this position in the context of classroom and interview talk with 14-year-old Swiss non-academically streamed lower secondary students about technology and science. In this context, science classrooms and interviews are shown to be microcosms of Swiss (German) culture and society reproduced in and through the situated talk about science and technology.

Big Outcrops and Big Ideas in Earth Science K-8 Professional Development

NASA Astrophysics Data System (ADS)

Baldwin, K. A.; Cooper, C. M.; Cavagnetto, A.; Morrison, J.; Adesope, O.

2014-12-01

Washington State has recently adopted the Next Generation Science Standards (NGSS) and state leaders are now working toward supporting teachers' implementation of the new standards and the pedagogical practices that support them. This poster encompasses one of one such professional development (PD) effort. The Enhancing Understanding of Concepts and Processes of Science (EUCAPS) project serves 31 K-8 in-service teachers in two southeast Washington school districts. In year two of this three year PD project, in-service teachers explored the Earth sciences and pedagogical approaches such as the Science Writing Heuristic, concept mapping, and activities which emphasized the epistemic nature of science. The goals of the EUCAPS PD project are to increase in-service teachers' big ideas in science and to provide support to in-service teachers as they transition to the NGSS. Teachers used concepts maps to document their knowledge of Earth science processes before and after visiting a local field site in Lewiston, Idaho. In the context of immersive inquiries, teachers collected field-based evidence to support their claims about the geological history of the field site. Teachers presented their claims and evidence to their peers in the form a story about the local geologic history. This poster will present an overview of the PD as well as provide examples of teacher's work and alignment with the NGSS.

Teaching about the Epistemology of Science in Upper Secondary Schools: An Analysis of Teachers' Classroom Talk

ERIC Educational Resources Information Center

Ryder, Jim; Leach, John

2008-01-01

We begin by drawing upon the available literature to identify four characteristics of teacher talk likely to support student learning about the epistemology of science: making appropriate statements about the epistemology of science in the classroom, linking the epistemology of science with specific science concepts, stating and justifying…

Big questions, big science: meeting the challenges of global ecology.

PubMed

Schimel, David; Keller, Michael

2015-04-01

Ecologists are increasingly tackling questions that require significant infrastucture, large experiments, networks of observations, and complex data and computation. Key hypotheses in ecology increasingly require more investment, and larger data sets to be tested than can be collected by a single investigator's or s group of investigator's labs, sustained for longer than a typical grant. Large-scale projects are expensive, so their scientific return on the investment has to justify the opportunity cost-the science foregone because resources were expended on a large project rather than supporting a number of individual projects. In addition, their management must be accountable and efficient in the use of significant resources, requiring the use of formal systems engineering and project management to mitigate risk of failure. Mapping the scientific method into formal project management requires both scientists able to work in the context, and a project implementation team sensitive to the unique requirements of ecology. Sponsoring agencies, under pressure from external and internal forces, experience many pressures that push them towards counterproductive project management but a scientific community aware and experienced in large project science can mitigate these tendencies. For big ecology to result in great science, ecologists must become informed, aware and engaged in the advocacy and governance of large ecological projects.

The Human Genome Project: big science transforms biology and medicine.

PubMed

Hood, Leroy; Rowen, Lee

2013-01-01

The Human Genome Project has transformed biology through its integrated big science approach to deciphering a reference human genome sequence along with the complete sequences of key model organisms. The project exemplifies the power, necessity and success of large, integrated, cross-disciplinary efforts - so-called 'big science' - directed towards complex major objectives. In this article, we discuss the ways in which this ambitious endeavor led to the development of novel technologies and analytical tools, and how it brought the expertise of engineers, computer scientists and mathematicians together with biologists. It established an open approach to data sharing and open-source software, thereby making the data resulting from the project accessible to all. The genome sequences of microbes, plants and animals have revolutionized many fields of science, including microbiology, virology, infectious disease and plant biology. Moreover, deeper knowledge of human sequence variation has begun to alter the practice of medicine. The Human Genome Project has inspired subsequent large-scale data acquisition initiatives such as the International HapMap Project, 1000 Genomes, and The Cancer Genome Atlas, as well as the recently announced Human Brain Project and the emerging Human Proteome Project.

Methods and Strategies: Talk Strategies

ERIC Educational Resources Information Center

Shea, Lauren M.; Shanahan, Therese B.

2011-01-01

This article discusses how to promote oral language development through science. The authors describe how they incorporate academic "talk strategies" into science lessons in a nonintrusive and meaningful manner. These talk strategies are adapted from the "Avenues" (2007) curriculum for English learners (ELs), which gives examples of cooperative…

"small problems, Big Trouble": An Art and Science Collaborative Exhibition Reflecting Seemingly small problems Leading to Big Threats

NASA Astrophysics Data System (ADS)

Waller, J. L.; Brey, J. A.

2014-12-01

"small problems, Big Trouble" (spBT) is an exhibition of artist Judith Waller's paintings accompanied by text panels written by Earth scientist Dr. James A. Brey and several science researchers and educators. The text panels' message is as much the focus of the show as the art--true interdisciplinarity! Waller and Brey's history of art and earth science collaborations include the successful exhibition "Layers: Places in Peril". New in spBT is extended collaboration with other scientists in order to create awareness of geoscience and other subjects (i.e. soil, parasites, dust, pollutants, invasive species, carbon, ground water contaminants, solar wind) small in scale which pose significant threats. The paintings are the size of a mirror, a symbol suggesting the problems depicted are those we increasingly need to face, noting our collective reflections of shared current and future reality. Naturalistic rendering and abstract form in the art helps reach a broad audience including those familiar with art and those familiar with science. The goal is that gallery visitors gain greater appreciation and understanding of both—and of the sober content of the show as a whole. "small problems, Big Trouble" premiers in Wisconsin April, 2015. As in previous collaborations, Waller and Brey actively utilize art and science (specifically geoscience) as an educational vehicle for active student learning. Planned are interdisciplinary university and area high school activities linked through spBT. The exhibition in a public gallery offers a means to enhance community awareness of and action on scientific issues through art's power to engage people on an emotional level. This AGU presentation includes a description of past Waller and Brey activities: incorporating art and earth science in lab and studio classrooms, producing gallery and museum exhibitions and delivering workshops and other presentations. They also describe how walking the paths of several past earth science

Science for Diplomacy, Diplomacy for Science

NASA Astrophysics Data System (ADS)

Colglazier, E. Wiliam

2015-04-01

I was a strong proponent of ``science diplomacy'' when I became Science and Technology Adviser to the Secretary of State in 2011. I thought I knew a lot about the subject after being engaged for four decades on international S&T policy issues and having had distinguished scientists as mentors who spent much of their time using science as a tool for building better relations between countries and working to make the world more peaceful, prosperous, and secure. I learned a lot from my three years inside the State Department, including great appreciation and respect for the real diplomats who work to defuse conflicts and avoid wars. But I also learned a lot about science diplomacy, both using science to advance diplomacy and diplomacy to advance science. My talk will focus on the five big things that I learned, and from that the one thing where I am focusing my energies to try to make a difference now that I am a private citizen again.

Big data and clinicians: a review on the state of the science.

PubMed

Wang, Weiqi; Krishnan, Eswar

2014-01-17

In the past few decades, medically related data collection saw a huge increase, referred to as big data. These huge datasets bring challenges in storage, processing, and analysis. In clinical medicine, big data is expected to play an important role in identifying causality of patient symptoms, in predicting hazards of disease incidence or reoccurrence, and in improving primary-care quality. The objective of this review was to provide an overview of the features of clinical big data, describe a few commonly employed computational algorithms, statistical methods, and software toolkits for data manipulation and analysis, and discuss the challenges and limitations in this realm. We conducted a literature review to identify studies on big data in medicine, especially clinical medicine. We used different combinations of keywords to search PubMed, Science Direct, Web of Knowledge, and Google Scholar for literature of interest from the past 10 years. This paper reviewed studies that analyzed clinical big data and discussed issues related to storage and analysis of this type of data. Big data is becoming a common feature of biological and clinical studies. Researchers who use clinical big data face multiple challenges, and the data itself has limitations. It is imperative that methodologies for data analysis keep pace with our ability to collect and store data.

The natural science underlying big history.

PubMed

Chaisson, Eric J

2014-01-01

Nature's many varied complex systems-including galaxies, stars, planets, life, and society-are islands of order within the increasingly disordered Universe. All organized systems are subject to physical, biological, or cultural evolution, which together comprise the grander interdisciplinary subject of cosmic evolution. A wealth of observational data supports the hypothesis that increasingly complex systems evolve unceasingly, uncaringly, and unpredictably from big bang to humankind. These are global history greatly extended, big history with a scientific basis, and natural history broadly portrayed across ∼14 billion years of time. Human beings and our cultural inventions are not special, unique, or apart from Nature; rather, we are an integral part of a universal evolutionary process connecting all such complex systems throughout space and time. Such evolution writ large has significant potential to unify the natural sciences into a holistic understanding of who we are and whence we came. No new science (beyond frontier, nonequilibrium thermodynamics) is needed to describe cosmic evolution's major milestones at a deep and empirical level. Quantitative models and experimental tests imply that a remarkable simplicity underlies the emergence and growth of complexity for a wide spectrum of known and diverse systems. Energy is a principal facilitator of the rising complexity of ordered systems within the expanding Universe; energy flows are as central to life and society as they are to stars and galaxies. In particular, energy rate density-contrasting with information content or entropy production-is an objective metric suitable to gauge relative degrees of complexity among a hierarchy of widely assorted systems observed throughout the material Universe. Operationally, those systems capable of utilizing optimum amounts of energy tend to survive, and those that cannot are nonrandomly eliminated.

The Natural Science Underlying Big History

PubMed Central

Chaisson, Eric J.

2014-01-01

Nature's many varied complex systems—including galaxies, stars, planets, life, and society—are islands of order within the increasingly disordered Universe. All organized systems are subject to physical, biological, or cultural evolution, which together comprise the grander interdisciplinary subject of cosmic evolution. A wealth of observational data supports the hypothesis that increasingly complex systems evolve unceasingly, uncaringly, and unpredictably from big bang to humankind. These are global history greatly extended, big history with a scientific basis, and natural history broadly portrayed across ∼14 billion years of time. Human beings and our cultural inventions are not special, unique, or apart from Nature; rather, we are an integral part of a universal evolutionary process connecting all such complex systems throughout space and time. Such evolution writ large has significant potential to unify the natural sciences into a holistic understanding of who we are and whence we came. No new science (beyond frontier, nonequilibrium thermodynamics) is needed to describe cosmic evolution's major milestones at a deep and empirical level. Quantitative models and experimental tests imply that a remarkable simplicity underlies the emergence and growth of complexity for a wide spectrum of known and diverse systems. Energy is a principal facilitator of the rising complexity of ordered systems within the expanding Universe; energy flows are as central to life and society as they are to stars and galaxies. In particular, energy rate density—contrasting with information content or entropy production—is an objective metric suitable to gauge relative degrees of complexity among a hierarchy of widely assorted systems observed throughout the material Universe. Operationally, those systems capable of utilizing optimum amounts of energy tend to survive, and those that cannot are nonrandomly eliminated. PMID:25032228

How the "I Can Explain!" Project Helps Children Learn Science through Talk

ERIC Educational Resources Information Center

Eley, Alison

2016-01-01

The role of talk in developing understanding in science has been well documented and the recognition of this in the new National Curriculum for England is very positive. The curriculum outlines the need for quality and variety of language in order for children to develop their scientific vocabulary and to articulate scientific concepts clearly and…

Highlighting hybridity: A critical discourse analysis of teacher talk in science classrooms

NASA Astrophysics Data System (ADS)

Hanrahan, Mary U.

2006-01-01

There is evidence that alienation from science is linked to the dominant discourse practices of science classrooms (cf. Lemke, J. L. (1990). Talking Science: Language, Learning, and Values. Norwood, NJ: Ablex). Yet, in secondary science education it is particularly hard to find evidence of curriculum reform that includes explicit changes in pedagogic discourses to accommodate the needs of students from a wide range of backgrounds. However, such evidence does exist and needs to be highlighted wherever it is found to help address social justice concerns in science education. In this article, I show how critical discourse analysis can be used to explore a way of challenging the dominant discourse in teacher - student interactions in science classrooms. My findings suggest a new way of moving toward more socially just science curricula in middle years and secondary classrooms by using hybrid discourses that can serve emancipatory purposes.

Big Data and Clinicians: A Review on the State of the Science

PubMed Central

Wang, Weiqi

2014-01-01

Background In the past few decades, medically related data collection saw a huge increase, referred to as big data. These huge datasets bring challenges in storage, processing, and analysis. In clinical medicine, big data is expected to play an important role in identifying causality of patient symptoms, in predicting hazards of disease incidence or reoccurrence, and in improving primary-care quality. Objective The objective of this review was to provide an overview of the features of clinical big data, describe a few commonly employed computational algorithms, statistical methods, and software toolkits for data manipulation and analysis, and discuss the challenges and limitations in this realm. Methods We conducted a literature review to identify studies on big data in medicine, especially clinical medicine. We used different combinations of keywords to search PubMed, Science Direct, Web of Knowledge, and Google Scholar for literature of interest from the past 10 years. Results This paper reviewed studies that analyzed clinical big data and discussed issues related to storage and analysis of this type of data. Conclusions Big data is becoming a common feature of biological and clinical studies. Researchers who use clinical big data face multiple challenges, and the data itself has limitations. It is imperative that methodologies for data analysis keep pace with our ability to collect and store data. PMID:25600256

samiDB: A Prototype Data Archive for Big Science Exploration

NASA Astrophysics Data System (ADS)

Konstantopoulos, I. S.; Green, A. W.; Cortese, L.; Foster, C.; Scott, N.

2015-04-01

samiDB is an archive, database, and query engine to serve the spectra, spectral hypercubes, and high-level science products that make up the SAMI Galaxy Survey. Based on the versatile Hierarchical Data Format (HDF5), samiDB does not depend on relational database structures and hence lightens the setup and maintenance load imposed on science teams by metadata tables. The code, written in Python, covers the ingestion, querying, and exporting of data as well as the automatic setup of an HTML schema browser. samiDB serves as a maintenance-light data archive for Big Science and can be adopted and adapted by science teams that lack the means to hire professional archivists to set up the data back end for their projects.

Perspective: Materials informatics and big data: Realization of the "fourth paradigm" of science in materials science

NASA Astrophysics Data System (ADS)

Agrawal, Ankit; Choudhary, Alok

2016-05-01

Our ability to collect "big data" has greatly surpassed our capability to analyze it, underscoring the emergence of the fourth paradigm of science, which is data-driven discovery. The need for data informatics is also emphasized by the Materials Genome Initiative (MGI), further boosting the emerging field of materials informatics. In this article, we look at how data-driven techniques are playing a big role in deciphering processing-structure-property-performance relationships in materials, with illustrative examples of both forward models (property prediction) and inverse models (materials discovery). Such analytics can significantly reduce time-to-insight and accelerate cost-effective materials discovery, which is the goal of MGI.

Teaching long-term science investigations: A matter of talk, text, and time

NASA Astrophysics Data System (ADS)

Bills, Patricia Susan

Science educators regard long-term investigations as one impactful form of teaching science through inquiry in K-12 classrooms. While we have idealized notions of what this work looks like, we have few, if any, descriptive studies about investigations that engage students in sustained, focused work over a period of time longer than a few days or even weeks. In a policy context that calls for teachers to develop strategies for engaging students in authentic science practices, such as those that can come from long-term science investigations, we would do well to learn from experienced teachers. This study followed three middle school science teachers in a large U. S. urban school district as they conducted long-term investigations. Using discourse analysis and taking a sociocultural perspective, this study documented the classroom talk and interaction of teachers and their students. The study's goals were to describe how teachers engage students in long-term investigations and the ways that classroom interaction involved specific reform-based science practices. Data include field notes and transcripts of audio recordings from 15 observations of three experienced middle school science teachers, three semi-structured interviews with each teacher, curriculum materials, student work, and classroom demographic data. Teachers engaged students in whole group, small group, and one-on-one conversations about several stages of the long-term investigations. Teachers most often discussed two of the eight science practices: 1) planning and carrying out investigations; and 2) obtaining, evaluating, and communicating information. The planning discussions involved conversations about identifying and describing variables, measuring and recording data, and concerns about data collection procedures. Conversations about using and communicating scientific information included talk about formal science writing conventions, and using background information to support all other parts of the

Integrated Science and Logistical Planning to Support Big Questions in Antarctic Science

NASA Astrophysics Data System (ADS)

Vaughan, D. G.; Stockings, T. M.

2015-12-01

Each year, British Antarctic Survey (BAS) supports an extensive programme of science at five Antarctic and sub-Antarctic stations, ranging from the tiny Bird Island Research Station at 54°S in the South Atlantic, to the massive, and fully re-locatable, Halley Research Station on Brunt Ice Shelf at 75°S. The BAS logistics hub, Rothera Research Station on the Antarctic Peninsula supports deployment of deep-field and airborne field campaigns through much of the Antarctic continent, and an innovative new UK polar research vessel is under design, and planned to enter service in the Southern Ocean in 2019. BAS's core science programme covering all aspects of physical, biological and geological science is delivered by our own science teams, but every year many other UK scientists and overseas collaborators also access BAS's Antarctic logistics to support their own programmes. As an integrated science and logistics provider, BAS is continuously reviewing its capabilities and operational procedures to ensure that the future long-term requirements of science are optimally supported. Current trends are towards providing the capacity for heavier remote operations and larger-scale field camps, increasing use of autonomous ocean and airborne platforms, and increasing opportunities to provide turnkey solutions for low-cost experimental deployments. This talk will review of expected trends in Antarctic science and the opportunities to conduct science in Antarctica. It will outline the anticipated logistic developments required to support future stakeholder-led and strategically-directed science programmes, and the long-term ambitions of our science communities indentified in several recent horizon-scanning activities.

The Human Genome Project: big science transforms biology and medicine

PubMed Central

2013-01-01

The Human Genome Project has transformed biology through its integrated big science approach to deciphering a reference human genome sequence along with the complete sequences of key model organisms. The project exemplifies the power, necessity and success of large, integrated, cross-disciplinary efforts - so-called ‘big science’ - directed towards complex major objectives. In this article, we discuss the ways in which this ambitious endeavor led to the development of novel technologies and analytical tools, and how it brought the expertise of engineers, computer scientists and mathematicians together with biologists. It established an open approach to data sharing and open-source software, thereby making the data resulting from the project accessible to all. The genome sequences of microbes, plants and animals have revolutionized many fields of science, including microbiology, virology, infectious disease and plant biology. Moreover, deeper knowledge of human sequence variation has begun to alter the practice of medicine. The Human Genome Project has inspired subsequent large-scale data acquisition initiatives such as the International HapMap Project, 1000 Genomes, and The Cancer Genome Atlas, as well as the recently announced Human Brain Project and the emerging Human Proteome Project. PMID:24040834

Big-Data-Driven Stem Cell Science and Tissue Engineering: Vision and Unique Opportunities.

PubMed

Del Sol, Antonio; Thiesen, Hans J; Imitola, Jaime; Carazo Salas, Rafael E

2017-02-02

Achieving the promises of stem cell science to generate precise disease models and designer cell samples for personalized therapeutics will require harnessing pheno-genotypic cell-level data quantitatively and predictively in the lab and clinic. Those requirements could be met by developing a Big-Data-driven stem cell science strategy and community. Copyright © 2017 Elsevier Inc. All rights reserved.

From big data analysis in the cloud to robotic pot drumming: tales from the Met Office Informatics Lab

NASA Astrophysics Data System (ADS)

Robinson, Niall; Tomlinson, Jacob; Prudden, Rachel; Hilson, Alex; Arribas, Alberto

2017-04-01

The Met Office Informatics Lab is a small multidisciplinary team which sits between science, technology and design. Our mission is simply "to make Met Office data useful" - a deliberately broad objective. Our prototypes often trial cutting edge technologies, and so far have included projects such as virtual reality data visualisation in the web browser, bots and natural language interfaces, and artificially intelligent weather warnings. In this talk we focus on our latest project, Jade, a big data analysis platform in the cloud. It is a powerful, flexible and simple to use implementation which makes extensive use of technologies such as Jupyter, Dask, containerisation, Infrastructure as Code, and auto-scaling. Crucially, Jade is flexible enough to be used for a diverse set of applications: it can present weather forecast information to meteorologists and allow climate scientists to analyse big data sets, but it is also effective for analysing non-geospatial data. As well as making data useful, the Informatics Lab also trials new working practises. In this presentation, we will talk about our experience of making a group like the Lab successful.

Big Data Science: Opportunities and Challenges to Address Minority Health and Health Disparities in the 21st Century

PubMed Central

Zhang, Xinzhi; Pérez-Stable, Eliseo J.; Bourne, Philip E.; Peprah, Emmanuel; Duru, O. Kenrik; Breen, Nancy; Berrigan, David; Wood, Fred; Jackson, James S.; Wong, David W.S.; Denny, Joshua

2017-01-01

Addressing minority health and health disparities has been a missing piece of the puzzle in Big Data science. This article focuses on three priority opportunities that Big Data science may offer to the reduction of health and health care disparities. One opportunity is to incorporate standardized information on demographic and social determinants in electronic health records in order to target ways to improve quality of care for the most disadvantaged populations over time. A second opportunity is to enhance public health surveillance by linking geographical variables and social determinants of health for geographically defined populations to clinical data and health outcomes. Third and most importantly, Big Data science may lead to a better understanding of the etiology of health disparities and understanding of minority health in order to guide intervention development. However, the promise of Big Data needs to be considered in light of significant challenges that threaten to widen health disparities. Care must be taken to incorporate diverse populations to realize the potential benefits. Specific recommendations include investing in data collection on small sample populations, building a diverse workforce pipeline for data science, actively seeking to reduce digital divides, developing novel ways to assure digital data privacy for small populations, and promoting widespread data sharing to benefit under-resourced minority-serving institutions and minority researchers. With deliberate efforts, Big Data presents a dramatic opportunity for reducing health disparities but without active engagement, it risks further widening them. PMID:28439179

Big Data Science: Opportunities and Challenges to Address Minority Health and Health Disparities in the 21st Century.

PubMed

Zhang, Xinzhi; Pérez-Stable, Eliseo J; Bourne, Philip E; Peprah, Emmanuel; Duru, O Kenrik; Breen, Nancy; Berrigan, David; Wood, Fred; Jackson, James S; Wong, David W S; Denny, Joshua

2017-01-01

Addressing minority health and health disparities has been a missing piece of the puzzle in Big Data science. This article focuses on three priority opportunities that Big Data science may offer to the reduction of health and health care disparities. One opportunity is to incorporate standardized information on demographic and social determinants in electronic health records in order to target ways to improve quality of care for the most disadvantaged populations over time. A second opportunity is to enhance public health surveillance by linking geographical variables and social determinants of health for geographically defined populations to clinical data and health outcomes. Third and most importantly, Big Data science may lead to a better understanding of the etiology of health disparities and understanding of minority health in order to guide intervention development. However, the promise of Big Data needs to be considered in light of significant challenges that threaten to widen health disparities. Care must be taken to incorporate diverse populations to realize the potential benefits. Specific recommendations include investing in data collection on small sample populations, building a diverse workforce pipeline for data science, actively seeking to reduce digital divides, developing novel ways to assure digital data privacy for small populations, and promoting widespread data sharing to benefit under-resourced minority-serving institutions and minority researchers. With deliberate efforts, Big Data presents a dramatic opportunity for reducing health disparities but without active engagement, it risks further widening them.

Talk in Primary Science: A Method to Promote Productive and Contextualised Group Discourse

ERIC Educational Resources Information Center

Braund, Martin

2009-01-01

Modelled Discussions About Science (MoDAS), where adults talk together about scientific ideas, procedures and applications, were devised to model and improve the quality of pupils' discussions. Two examples from one of the project schools are examined to see if these aims were fulfilled and to comment on examples of cognitive and social aspects of…

Research Data Alliance: Understanding Big Data Analytics Applications in Earth Science

NASA Astrophysics Data System (ADS)

Riedel, Morris; Ramachandran, Rahul; Baumann, Peter

2014-05-01

The Research Data Alliance (RDA) enables data to be shared across barriers through focused working groups and interest groups, formed of experts from around the world - from academia, industry and government. Its Big Data Analytics (BDA) interest groups seeks to develop community based recommendations on feasible data analytics approaches to address scientific community needs of utilizing large quantities of data. BDA seeks to analyze different scientific domain applications (e.g. earth science use cases) and their potential use of various big data analytics techniques. These techniques reach from hardware deployment models up to various different algorithms (e.g. machine learning algorithms such as support vector machines for classification). A systematic classification of feasible combinations of analysis algorithms, analytical tools, data and resource characteristics and scientific queries will be covered in these recommendations. This contribution will outline initial parts of such a classification and recommendations in the specific context of the field of Earth Sciences. Given lessons learned and experiences are based on a survey of use cases and also providing insights in a few use cases in detail.

Research Data Alliance: Understanding Big Data Analytics Applications in Earth Science

NASA Technical Reports Server (NTRS)

Riedel, Morris; Ramachandran, Rahul; Baumann, Peter

2014-01-01

The Research Data Alliance (RDA) enables data to be shared across barriers through focused working groups and interest groups, formed of experts from around the world - from academia, industry and government. Its Big Data Analytics (BDA) interest groups seeks to develop community based recommendations on feasible data analytics approaches to address scientific community needs of utilizing large quantities of data. BDA seeks to analyze different scientific domain applications (e.g. earth science use cases) and their potential use of various big data analytics techniques. These techniques reach from hardware deployment models up to various different algorithms (e.g. machine learning algorithms such as support vector machines for classification). A systematic classification of feasible combinations of analysis algorithms, analytical tools, data and resource characteristics and scientific queries will be covered in these recommendations. This contribution will outline initial parts of such a classification and recommendations in the specific context of the field of Earth Sciences. Given lessons learned and experiences are based on a survey of use cases and also providing insights in a few use cases in detail.

Game, cloud architecture and outreach for The BIG Bell Test

NASA Astrophysics Data System (ADS)

Abellan, Carlos; Tura, Jordi; Garcia, Marta; Beduini, Federica; Hirschmann, Alina; Pruneri, Valerio; Acin, Antonio; Marti, Maria; Mitchell, Morgan

The BIG Bell test uses the input from the Bellsters, self-selected human participants introducing zeros and ones through an online videogame, to perform a suite of quantum physics experiments. In this talk, we will explore the videogame, the data infrastructure and the outreach efforts of the BIG Bell test collaboration. First, we will discuss how the game was designed so as to eliminate possible feedback mechanisms that could influence people's behavior. Second, we will discuss the cloud architecture design for scalability as well as explain how we sent each individual bit from the users to the labs. Also, and using all the bits collected via the BIG Bell test interface, we will show a data analysis on human randomness, e.g. are younger Bellsters more random than older Bellsters? Finally, we will talk about the outreach and communication efforts of the BIG Bell test collaboration, exploring both the social media campaigns as well as the close interaction with teachers and educators to bring the project into classrooms.

Neuroblastoma, a Paradigm for Big Data Science in Pediatric Oncology.

PubMed

Salazar, Brittany M; Balczewski, Emily A; Ung, Choong Yong; Zhu, Shizhen

2016-12-27

Pediatric cancers rarely exhibit recurrent mutational events when compared to most adult cancers. This poses a challenge in understanding how cancers initiate, progress, and metastasize in early childhood. Also, due to limited detected driver mutations, it is difficult to benchmark key genes for drug development. In this review, we use neuroblastoma, a pediatric solid tumor of neural crest origin, as a paradigm for exploring "big data" applications in pediatric oncology. Computational strategies derived from big data science-network- and machine learning-based modeling and drug repositioning-hold the promise of shedding new light on the molecular mechanisms driving neuroblastoma pathogenesis and identifying potential therapeutics to combat this devastating disease. These strategies integrate robust data input, from genomic and transcriptomic studies, clinical data, and in vivo and in vitro experimental models specific to neuroblastoma and other types of cancers that closely mimic its biological characteristics. We discuss contexts in which "big data" and computational approaches, especially network-based modeling, may advance neuroblastoma research, describe currently available data and resources, and propose future models of strategic data collection and analyses for neuroblastoma and other related diseases.

NASA's Big Data Task Force

NASA Astrophysics Data System (ADS)

Holmes, C. P.; Kinter, J. L.; Beebe, R. F.; Feigelson, E.; Hurlburt, N. E.; Mentzel, C.; Smith, G.; Tino, C.; Walker, R. J.

2017-12-01

Two years ago NASA established the Ad Hoc Big Data Task Force (BDTF - https://science.nasa.gov/science-committee/subcommittees/big-data-task-force), an advisory working group with the NASA Advisory Council system. The scope of the Task Force included all NASA Big Data programs, projects, missions, and activities. The Task Force focused on such topics as exploring the existing and planned evolution of NASA's science data cyber-infrastructure that supports broad access to data repositories for NASA Science Mission Directorate missions; best practices within NASA, other Federal agencies, private industry and research institutions; and Federal initiatives related to big data and data access. The BDTF has completed its two-year term and produced several recommendations plus four white papers for NASA's Science Mission Directorate. This presentation will discuss the activities and results of the TF including summaries of key points from its focused study topics. The paper serves as an introduction to the papers following in this ESSI session.

Urgent Call for Nursing Big Data.

PubMed

Delaney, Connie W

2016-01-01

The purpose of this panel is to expand internationally a National Action Plan for sharable and comparable nursing data for quality improvement and big data science. There is an urgent need to assure that nursing has sharable and comparable data for quality improvement and big data science. A national collaborative - Nursing Knowledge and Big Data Science includes multi-stakeholder groups focused on a National Action Plan toward implementing and using sharable and comparable nursing big data. Panelists will share accomplishments and future plans with an eye toward international collaboration. This presentation is suitable for any audience attending the NI2016 conference.

Doing, talking and writing science: A discourse analysis of the process of resemiotization in a middle school lab-based science class

NASA Astrophysics Data System (ADS)

Wright, Laura J.

This study examines students' sense making practices in a middle school science class from a discourse analytic perspective. Using Mediated Discourse Analysis (MDA) (Scollon 1998, 2001) and interactional sociolinguistics (Gumperz 1999, 2001, Schiffrin 1994), my research seeks to enrich findings from recent sociocultural studies of science classrooms that focus on doing, talking and writing science (Roth 2005, Kress, et al. 2002, Halliday & Martin 1993, Lemke 1990). Within a middle school science classroom, these fundamental activities form a nexus of practice (Scollon 1998, 2001) basic to science literacy (AAAS 1989) and reflective of the work of practicing scientists. Moreover, students' engagement in these practices provides insight into the cultural production and reproduction of science and scientist. I first examine how the students' curriculum text encourages these three scientific practices and then trace students' uptake; that is, how they subsequently do, talk, and write science throughout the course of the unit. I argue that learning science with this curriculum unit requires students to resemiotize (Iedema 2001, 2003) first hand experience so they can represent their knowledge cohesively and coherently in evaluable forms. Ultimately, students must transform language from the curriculum text and their teacher into action in their laboratory activities and action in their laboratory activities into language. In addition, I show how students are apprenticed to the conventionalized practices and voices (Bakhtin 1986) of science (i.e. the scientific register), and how their figures of personhood (Agha 2005) reflect the development of their scientific identities. Overall, I argue that the microanalytic methods I use illuminate how students draw upon curricular resources to become scientifically literate and develop scientific identities.

Big Data in Science and Healthcare: A Review of Recent Literature and Perspectives. Contribution of the IMIA Social Media Working Group.

PubMed

Hansen, M M; Miron-Shatz, T; Lau, A Y S; Paton, C

2014-08-15

As technology continues to evolve and rise in various industries, such as healthcare, science, education, and gaming, a sophisticated concept known as Big Data is surfacing. The concept of analytics aims to understand data. We set out to portray and discuss perspectives of the evolving use of Big Data in science and healthcare and, to examine some of the opportunities and challenges. A literature review was conducted to highlight the implications associated with the use of Big Data in scientific research and healthcare innovations, both on a large and small scale. Scientists and health-care providers may learn from one another when it comes to understanding the value of Big Data and analytics. Small data, derived by patients and consumers, also requires analytics to become actionable. Connectivism provides a framework for the use of Big Data and analytics in the areas of science and healthcare. This theory assists individuals to recognize and synthesize how human connections are driving the increase in data. Despite the volume and velocity of Big Data, it is truly about technology connecting humans and assisting them to construct knowledge in new ways. Concluding Thoughts: The concept of Big Data and associated analytics are to be taken seriously when approaching the use of vast volumes of both structured and unstructured data in science and health-care. Future exploration of issues surrounding data privacy, confidentiality, and education are needed. A greater focus on data from social media, the quantified self-movement, and the application of analytics to "small data" would also be useful.

Talking after school: Parents' conversational styles and children's memory for a science lesson.

PubMed

Leichtman, Michelle D; Camilleri, Kaitlin A; Pillemer, David B; Amato-Wierda, Carmela C; Hogan, Jennifer E; Dongo, Melissa D

2017-04-01

A scientist taught 40 4- to 6-year-old children an interactive science lesson at school. The same day, children talked about the lesson at home with a parent who was naive to the details of what had transpired at school. Six days later, a researcher interviewed children about objects, activities, and concepts that were part of the lesson. Aspects of parents' conversational style (e.g., open-ended memory questions, descriptive language) predicted how much information children provided in talking with them, which in turn predicted children's memory performance 6days later. The findings suggest that elaborative parent-child conversations at home could boost children's retention of academic information acquired at school even when parents have no specific knowledge of what children have experienced there. Copyright © 2016 Elsevier Inc. All rights reserved.

Frontiers in Laser Cooling, Single-Molecule Biophysics, and Energy Science: A Talk from Eric Cornell

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

Cornell, Eric

2008-08-30

Eric Cornell presents a talk at Frontiers in Laser Cooling, Single-Molecule Biophysics and Energy Science, a scientific symposium honoring Steve Chu, director of Lawrence Berkeley National Laboratory and recipient of the 1997 Nobel Prize in Physics. The symposium was held August 30, 2008 in Berkeley.

Frontiers in Laser Cooling, Single-Molecule Biophysics, and Energy Science: A Talk from Kurt Gibble

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

Gibble, Kurt

2008-08-30

Kurt Gibble presents a talk at Frontiers in Laser Cooling, Single-Molecule Biophysics and Energy Science, a scientific symposium honoring Steve Chu, director of Lawrence Berkeley National Laboratory and recipient of the 1997 Nobel Prize in Physics. The symposium was held August 30, 2008 in Berkeley.

Frontiers in Laser Cooling, Single-Molecule Biophysics, and Energy Science: A Talk from Jay Keasling

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

Keasling, Jay

2008-08-30

Jay Keasling presents a talk at Frontiers in Laser Cooling, Single-Molecule Biophysics and Energy Science, a scientific symposium honoring Steve Chu, director of Lawrence Berkeley National Laboratory and recipient of the 1997 Nobel Prize in Physics. The symposium was held August 30, 2008 in Berkeley.

Frontiers in Laser Cooling, Single-Molecule Biophysics, and Enrgy Science: A Talk by Carl Wieman

ScienceCinema

Wieman, Carl

2017-12-09

Carl Wieman presents a talk at Frontiers in Laser Cooling, Single-Molecule Biophysics and Energy Science, a scientific symposium honoring Steve Chu, director of Lawrence Berkeley National Laboratory and recipient of the 1997 Nobel Prize in Physics. The symposium was held August 30, 2008 in Berkeley.

Frontiers in Laser Cooling, Single-Molecule Biophysics, and Energy Science: A Talk from Eric Cornell

ScienceCinema

Cornell, Eric

2018-02-05

Eric Cornell presents a talk at Frontiers in Laser Cooling, Single-Molecule Biophysics and Energy Science, a scientific symposium honoring Steve Chu, director of Lawrence Berkeley National Laboratory and recipient of the 1997 Nobel Prize in Physics. The symposium was held August 30, 2008 in Berkeley.

Frontiers in Laser Cooling, Single-Molecule Biophysics, and Enrgy Science: A Talk by Carl Wieman

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

Wieman, Carl

Carl Wieman presents a talk at Frontiers in Laser Cooling, Single-Molecule Biophysics and Energy Science, a scientific symposium honoring Steve Chu, director of Lawrence Berkeley National Laboratory and recipient of the 1997 Nobel Prize in Physics. The symposium was held August 30, 2008 in Berkeley.

Frontiers in Laser Cooling, Single-Molecule Biophysics, and Energy Science: A Talk from Jay Keasling

ScienceCinema

Keasling, Jay

2018-02-14

Jay Keasling presents a talk at Frontiers in Laser Cooling, Single-Molecule Biophysics and Energy Science, a scientific symposium honoring Steve Chu, director of Lawrence Berkeley National Laboratory and recipient of the 1997 Nobel Prize in Physics. The symposium was held August 30, 2008 in Berkeley.

Frontiers in Laser Cooling, Single-Molecule Biophysics, and Energy Science: A Talk from Kurt Gibble

ScienceCinema

Gibble, Kurt

2018-02-05

Kurt Gibble presents a talk at Frontiers in Laser Cooling, Single-Molecule Biophysics and Energy Science, a scientific symposium honoring Steve Chu, director of Lawrence Berkeley National Laboratory and recipient of the 1997 Nobel Prize in Physics. The symposium was held August 30, 2008 in Berkeley.

A big data approach for climate change indicators processing in the CLIP-C project

NASA Astrophysics Data System (ADS)

D'Anca, Alessandro; Conte, Laura; Palazzo, Cosimo; Fiore, Sandro; Aloisio, Giovanni

2016-04-01

Defining and implementing processing chains with multiple (e.g. tens or hundreds of) data analytics operators can be a real challenge in many practical scientific use cases such as climate change indicators. This is usually done via scripts (e.g. bash) on the client side and requires climate scientists to take care of, implement and replicate workflow-like control logic aspects (which may be error-prone too) in their scripts, along with the expected application-level part. Moreover, the big amount of data and the strong I/O demand pose additional challenges related to the performance. In this regard, production-level tools for climate data analysis are mostly sequential and there is a lack of big data analytics solutions implementing fine-grain data parallelism or adopting stronger parallel I/O strategies, data locality, workflow optimization, etc. High-level solutions leveraging on workflow-enabled big data analytics frameworks for eScience could help scientists in defining and implementing the workflows related to their experiments by exploiting a more declarative, efficient and powerful approach. This talk will start introducing the main needs and challenges regarding big data analytics workflow management for eScience and will then provide some insights about the implementation of some real use cases related to some climate change indicators on large datasets produced in the context of the CLIP-C project - a EU FP7 project aiming at providing access to climate information of direct relevance to a wide variety of users, from scientists to policy makers and private sector decision makers. All the proposed use cases have been implemented exploiting the Ophidia big data analytics framework. The software stack includes an internal workflow management system, which coordinates, orchestrates, and optimises the execution of multiple scientific data analytics and visualization tasks. Real-time workflow monitoring execution is also supported through a graphical user

Dawn: A Simulation Model for Evaluating Costs and Tradeoffs of Big Data Science Architectures

NASA Astrophysics Data System (ADS)

Cinquini, L.; Crichton, D. J.; Braverman, A. J.; Kyo, L.; Fuchs, T.; Turmon, M.

2014-12-01

In many scientific disciplines, scientists and data managers are bracing for an upcoming deluge of big data volumes, which will increase the size of current data archives by a factor of 10-100 times. For example, the next Climate Model Inter-comparison Project (CMIP6) will generate a global archive of model output of approximately 10-20 Peta-bytes, while the upcoming next generation of NASA decadal Earth Observing instruments are expected to collect tens of Giga-bytes/day. In radio-astronomy, the Square Kilometre Array (SKA) will collect data in the Exa-bytes/day range, of which (after reduction and processing) around 1.5 Exa-bytes/year will be stored. The effective and timely processing of these enormous data streams will require the design of new data reduction and processing algorithms, new system architectures, and new techniques for evaluating computation uncertainty. Yet at present no general software tool or framework exists that will allow system architects to model their expected data processing workflow, and determine the network, computational and storage resources needed to prepare their data for scientific analysis. In order to fill this gap, at NASA/JPL we have been developing a preliminary model named DAWN (Distributed Analytics, Workflows and Numerics) for simulating arbitrary complex workflows composed of any number of data processing and movement tasks. The model can be configured with a representation of the problem at hand (the data volumes, the processing algorithms, the available computing and network resources), and is able to evaluate tradeoffs between different possible workflows based on several estimators: overall elapsed time, separate computation and transfer times, resulting uncertainty, and others. So far, we have been applying DAWN to analyze architectural solutions for 4 different use cases from distinct science disciplines: climate science, astronomy, hydrology and a generic cloud computing use case. This talk will present

Big Data, Big Problems: A Healthcare Perspective.

PubMed

Househ, Mowafa S; Aldosari, Bakheet; Alanazi, Abdullah; Kushniruk, Andre W; Borycki, Elizabeth M

2017-01-01

Much has been written on the benefits of big data for healthcare such as improving patient outcomes, public health surveillance, and healthcare policy decisions. Over the past five years, Big Data, and the data sciences field in general, has been hyped as the "Holy Grail" for the healthcare industry promising a more efficient healthcare system with the promise of improved healthcare outcomes. However, more recently, healthcare researchers are exposing the potential and harmful effects Big Data can have on patient care associating it with increased medical costs, patient mortality, and misguided decision making by clinicians and healthcare policy makers. In this paper, we review the current Big Data trends with a specific focus on the inadvertent negative impacts that Big Data could have on healthcare, in general, and specifically, as it relates to patient and clinical care. Our study results show that although Big Data is built up to be as a the "Holy Grail" for healthcare, small data techniques using traditional statistical methods are, in many cases, more accurate and can lead to more improved healthcare outcomes than Big Data methods. In sum, Big Data for healthcare may cause more problems for the healthcare industry than solutions, and in short, when it comes to the use of data in healthcare, "size isn't everything."

Rigor in Elementary Science Students' Discourse: The Role of Responsiveness and Supportive Conditions for Talk

ERIC Educational Resources Information Center

Colley, Carolyn; Windschitl, Mark

2016-01-01

Teaching that is responsive to students' ideas can create opportunities for rigorous sense-making talk by young learners. Yet we have few accounts of how thoughtful attempts at responsive teaching unfold across units of instruction in elementary science classrooms and have only begun to understand how responsiveness encourages rigor in…

Applying science and mathematics to big data for smarter buildings.

PubMed

Lee, Young M; An, Lianjun; Liu, Fei; Horesh, Raya; Chae, Young Tae; Zhang, Rui

2013-08-01

Many buildings are now collecting a large amount of data on operations, energy consumption, and activities through systems such as a building management system (BMS), sensors, and meters (e.g., submeters and smart meters). However, the majority of data are not utilized and are thrown away. Science and mathematics can play an important role in utilizing these big data and accurately assessing how energy is consumed in buildings and what can be done to save energy, make buildings energy efficient, and reduce greenhouse gas (GHG) emissions. This paper discusses an analytical tool that has been developed to assist building owners, facility managers, operators, and tenants of buildings in assessing, benchmarking, diagnosing, tracking, forecasting, and simulating energy consumption in building portfolios. © 2013 New York Academy of Sciences.

How to Talk About Science: Lessons from a Middle School Science Classroom

NASA Astrophysics Data System (ADS)

Cushman-Patz, B. J.

2010-12-01

Middle school students are curious, energetic, and impatient. A middle school science teacher is always challenged to find ways to relate the content she’d like to convey to the students’ everyday lives, working to both satiate and foster their natural curiosity. She must communicate science in language appropriate for her audience, teaching new vocabulary words the first time she uses them, and reviewing them often. A thriving middle school science classroom is noisy, messy, and fun. Understanding what makes this classroom dynamic work can lead to better communication about science to any audience. 1) Know your bottom-line message, and keep it simple. Research science is complicated and nuanced. Your audience may be interested in some of these details, but start with the big picture first, and fill in the details as appropriate. 2) Avoid jargon. Use language that you would use to explain science to your 13-year-old neighbor or your 85-year old grandmother. They know what a volcano is, but they may not know the difference between a crater and a caldera. They definitely don’t know what a phreatomagmatic eruption is. As you introduce necessary jargon into your discussion, define it clearly in terms of something you are sure they do know and understand. 3) Engage the audience. Use pictures; use your hands; use common-reference points. Whenever possible, get the audience members to use their hands to mimic your motion. Encourage them to try to reframe what you say in terms that they’re comfortable with. Make it a two-way conversation 4) Pause. New concepts take time to absorb. Take a breath; give your audience a moment to absorb what you just explained and to formulate questions they may have. 5) Pay attention to cues. Middle school students make it obvious when they’re bored; adults tend to be more subtle. When eyes wander or eyelids droop, ask a question that engages your audience, even if it’s just, “do you follow?” or, “where did I lose you

Big data analytics workflow management for eScience

NASA Astrophysics Data System (ADS)

Fiore, Sandro; D'Anca, Alessandro; Palazzo, Cosimo; Elia, Donatello; Mariello, Andrea; Nassisi, Paola; Aloisio, Giovanni

2015-04-01

In many domains such as climate and astrophysics, scientific data is often n-dimensional and requires tools that support specialized data types and primitives if it is to be properly stored, accessed, analysed and visualized. Currently, scientific data analytics relies on domain-specific software and libraries providing a huge set of operators and functionalities. However, most of these software fail at large scale since they: (i) are desktop based, rely on local computing capabilities and need the data locally; (ii) cannot benefit from available multicore/parallel machines since they are based on sequential codes; (iii) do not provide declarative languages to express scientific data analysis tasks, and (iv) do not provide newer or more scalable storage models to better support the data multidimensionality. Additionally, most of them: (v) are domain-specific, which also means they support a limited set of data formats, and (vi) do not provide a workflow support, to enable the construction, execution and monitoring of more complex "experiments". The Ophidia project aims at facing most of the challenges highlighted above by providing a big data analytics framework for eScience. Ophidia provides several parallel operators to manipulate large datasets. Some relevant examples include: (i) data sub-setting (slicing and dicing), (ii) data aggregation, (iii) array-based primitives (the same operator applies to all the implemented UDF extensions), (iv) data cube duplication, (v) data cube pivoting, (vi) NetCDF-import and export. Metadata operators are available too. Additionally, the Ophidia framework provides array-based primitives to perform data sub-setting, data aggregation (i.e. max, min, avg), array concatenation, algebraic expressions and predicate evaluation on large arrays of scientific data. Bit-oriented plugins have also been implemented to manage binary data cubes. Defining processing chains and workflows with tens, hundreds of data analytics operators is the

Using Exploratory Talk to Enhance Problem-Solving and Reasoning Skills in Grade-7 Science Classrooms

ERIC Educational Resources Information Center

Webb, Paul; Treagust, David F.

2006-01-01

This study investigates whether the generation of exploratory talk in grade seven, second-language science classrooms in the Eastern Cape Province, South Africa, has a positive effect on learners in terms of their problem-solving and reasoning skills and whether socio-cultural "milieus" (urban, peri-urban and rural settings of schools)…

The Nature of Parent-Child Talk during the Sharing of Science Trade Books at Home

ERIC Educational Resources Information Center

Groothuis, Becky Anne

2015-01-01

This study examined the interactions between parents and their typically developing fourth grade children as they shared science trade books together at home. The aim of this research was to understand how parents and children make meaning together in this context and how parent-child talk related to children's developing scientific views. Four…

The History of Science and Technology at Bell Labs

NASA Astrophysics Data System (ADS)

Bishop, David

2008-03-01

Over the last 80 years, Bell Labs has been one of the most scientifically and technologically productive research labs in the world. Inventions such as the transistor, laser, cell phone, solar cell, negative feedback amplifier, communications satellite and many others were made there. Scientific breakthroughs such as discovery of the Big Bang, the wave nature of the electron, electron localization and the fractional quantum hall effect were also made there making Bell Labs almost unique in terms of large impacts in both science and technology. In my talk, I will discuss the history of the lab, talk about the present and give some suggestions for how I see it evolving into the future.

Scientists Popularizing Science: Characteristics and Impact of TED Talk Presenters

PubMed Central

Sugimoto, Cassidy R.; Thelwall, Mike; Larivière, Vincent; Tsou, Andrew; Mongeon, Philippe; Macaluso, Benoit

2013-01-01

The TED (Technology, Entertainment, Design) conference and associated website of recorded conference presentations (TED Talks) is a highly successful disseminator of science-related videos, claiming over a billion online views. Although hundreds of scientists have presented at TED, little information is available regarding the presenters, their academic credentials, and the impact of TED Talks on the general population. This article uses bibliometric and webometric techniques to gather data on the characteristics of TED presenters and videos and analyze the relationship between these characteristics and the subsequent impact of the videos. The results show that the presenters were predominately male and non-academics. Male-authored videos were more popular and more liked when viewed on YouTube. Videos by academic presenters were more commented on than videos by others and were more liked on YouTube, although there was little difference in how frequently they were viewed. The majority of academic presenters were senior faculty, males, from United States-based institutions, were visible online, and were cited more frequently than average for their field. However, giving a TED presentation appeared to have no impact on the number of citations subsequently received by an academic, suggesting that although TED popularizes research, it may not promote the work of scientists within the academic community. PMID:23638069

Scientists popularizing science: characteristics and impact of TED talk presenters.

PubMed

Sugimoto, Cassidy R; Thelwall, Mike; Larivière, Vincent; Tsou, Andrew; Mongeon, Philippe; Macaluso, Benoit

2013-01-01

The TED (Technology, Entertainment, Design) conference and associated website of recorded conference presentations (TED Talks) is a highly successful disseminator of science-related videos, claiming over a billion online views. Although hundreds of scientists have presented at TED, little information is available regarding the presenters, their academic credentials, and the impact of TED Talks on the general population. This article uses bibliometric and webometric techniques to gather data on the characteristics of TED presenters and videos and analyze the relationship between these characteristics and the subsequent impact of the videos. The results show that the presenters were predominately male and non-academics. Male-authored videos were more popular and more liked when viewed on YouTube. Videos by academic presenters were more commented on than videos by others and were more liked on YouTube, although there was little difference in how frequently they were viewed. The majority of academic presenters were senior faculty, males, from United States-based institutions, were visible online, and were cited more frequently than average for their field. However, giving a TED presentation appeared to have no impact on the number of citations subsequently received by an academic, suggesting that although TED popularizes research, it may not promote the work of scientists within the academic community.

Opportunity and Challenges for Migrating Big Data Analytics in Cloud

NASA Astrophysics Data System (ADS)

Amitkumar Manekar, S.; Pradeepini, G., Dr.

2017-08-01

Big Data Analytics is a big word now days. As per demanding and more scalable process data generation capabilities, data acquisition and storage become a crucial issue. Cloud storage is a majorly usable platform; the technology will become crucial to executives handling data powered by analytics. Now a day’s trend towards “big data-as-a-service” is talked everywhere. On one hand, cloud-based big data analytics exactly tackle in progress issues of scale, speed, and cost. But researchers working to solve security and other real-time problem of big data migration on cloud based platform. This article specially focused on finding possible ways to migrate big data to cloud. Technology which support coherent data migration and possibility of doing big data analytics on cloud platform is demanding in natute for new era of growth. This article also gives information about available technology and techniques for migration of big data in cloud.

The roles of teachers' science talk in revealing language demands within diverse elementary school classrooms: a study of teaching heat and temperature in Singapore

NASA Astrophysics Data System (ADS)

Seah, Lay Hoon; Yore, Larry D.

2017-01-01

This study of three science teachers' lessons on heat and temperature seeks to characterise classroom talk that highlighted the ways language is used and to examine the nature of the language demands revealed in constructing, negotiating, arguing and communicating science ideas. The transcripts from the entire instructional units for these teachers' four culturally and linguistically diverse Grade 4 classes (10 years old) with English as the language of instruction constitute the data for this investigation. Analysis of these transcripts focused on teachers' talk that made explicit reference to the form or function of the language of science and led to the inductive development of the 'Attending to Language Demands in Science' analytical framework. This framework in turn revealed that the major foregrounding purposes of teachers' talk include labelling, explaining, differentiating, selecting and constructing. Further classification of the instances within these categories revealed the extensive and contextualised nature of the language demands. The results challenge the conventional assumption that basic literacy skills dominate over disciplinary literacy skills in primary school science. Potential uses of the analytical framework that could further expand our understanding of the forms, functions and demands of language used in elementary school science are also discussed.

Crowd-funded micro-grants for genomics and "big data": an actionable idea connecting small (artisan) science, infrastructure science, and citizen philanthropy.

PubMed

Özdemir, Vural; Badr, Kamal F; Dove, Edward S; Endrenyi, Laszlo; Geraci, Christy Jo; Hotez, Peter J; Milius, Djims; Neves-Pereira, Maria; Pang, Tikki; Rotimi, Charles N; Sabra, Ramzi; Sarkissian, Christineh N; Srivastava, Sanjeeva; Tims, Hesther; Zgheib, Nathalie K; Kickbusch, Ilona

2013-04-01

Biomedical science in the 21(st) century is embedded in, and draws from, a digital commons and "Big Data" created by high-throughput Omics technologies such as genomics. Classic Edisonian metaphors of science and scientists (i.e., "the lone genius" or other narrow definitions of expertise) are ill equipped to harness the vast promises of the 21(st) century digital commons. Moreover, in medicine and life sciences, experts often under-appreciate the important contributions made by citizen scholars and lead users of innovations to design innovative products and co-create new knowledge. We believe there are a large number of users waiting to be mobilized so as to engage with Big Data as citizen scientists-only if some funding were available. Yet many of these scholars may not meet the meta-criteria used to judge expertise, such as a track record in obtaining large research grants or a traditional academic curriculum vitae. This innovation research article describes a novel idea and action framework: micro-grants, each worth $1000, for genomics and Big Data. Though a relatively small amount at first glance, this far exceeds the annual income of the "bottom one billion"-the 1.4 billion people living below the extreme poverty level defined by the World Bank ($1.25/day). We describe two types of micro-grants. Type 1 micro-grants can be awarded through established funding agencies and philanthropies that create micro-granting programs to fund a broad and highly diverse array of small artisan labs and citizen scholars to connect genomics and Big Data with new models of discovery such as open user innovation. Type 2 micro-grants can be funded by existing or new science observatories and citizen think tanks through crowd-funding mechanisms described herein. Type 2 micro-grants would also facilitate global health diplomacy by co-creating crowd-funded micro-granting programs across nation-states in regions facing political and financial instability, while sharing similar disease

Talk Like a Scientist

ERIC Educational Resources Information Center

Marcum-Dietrich, Nanette

2010-01-01

In the scientific community, the symposium is one formal structure of conversation. Scientists routinely hold symposiums to gather and talk about a common topic. To model this method of communication in the classroom, the author designed an activity in which students conduct their own science symposiums. This article presents the science symposium…

Between the State and the Individual: "Big Society" Communitarianism and English Conservative Rhetoric

ERIC Educational Resources Information Center

Gibson, Howard

2015-01-01

During his quest for leadership of the English Conservative Party, David Cameron declared his intention to turn Britain into a Big Society. In May 2010, having gained office as Prime Minister, he unveiled a string of policies to bring his vision to fruition. After five years, however, talk of the Big Society has withered in public debate such that…

Big Data Science Education: A Case Study of a Project-Focused Introductory Course

ERIC Educational Resources Information Center

Saltz, Jeffrey; Heckman, Robert

2015-01-01

This paper reports on a case study of a project-focused introduction to big data science course. The pedagogy of the course leveraged boundary theory, where students were positioned to be at the boundary between a client's desire to understand their data and the academic class. The results of the case study demonstrate that using live clients…

Supporting Disciplinary Talk from the Start of School: Teaching Students to Think and Talk Like Scientists

ERIC Educational Resources Information Center

Wright, Tanya S.; Gotwals, Amelia Wenk

2017-01-01

In this article, the authors first review the research literature to show why supporting talk from the start of school is important for students' long-term literacy development. The authors then define and describe disciplinary talk and argue that it is an important entry point into science and disciplinary literacy learning for young students.…

Optimizing the orchestration of resemiotization with teacher "talk moves": A model of guided-inquiry instruction in middle school science

NASA Astrophysics Data System (ADS)

Millstone, Rachel Diana

The current conceptualization of science set forth by the National Research Council (2008) is one of science as a social activity, rather than a view of science as a fixed body of knowledge. This requires teachers to consider how communication, processing, and meaning-making contribute to science learning. It also requires teachers to think deeply about what constitutes knowledge and understanding in science, and what types of instruction are most conducive to preparing students to participate meaningfully in the society of tomorrow. Because argumentation is the prominent form of productive talk leading to the building of new scientific knowledge, one indicator of successful inquiry lies in students' abilities to communicate their scientific understandings in scientific argumentation structures. The overarching goal of this study is to identify factors that promote effective inquiry-based instruction in middle school science classrooms, as evidenced in students' abilities to engage in quality argumentation with their peers. Three specific research questions were investigated: (1) What factors do teachers identify in their practice as significant to the teaching and learning of science? (2) What factors do students identify as significant to their learning of science? and (3) What factors affect students' opportunities and abilities to achieve sophisticated levels of argumentation in the classroom? Two teachers and forty students participated in this study. Four principle sources of data were collected over a three-month period of time. These included individual teacher interviews, student focus group interviews, fieldnotes, and approximately 85 hours of classroom videotape. From this sample, four pathways for guided-inquiry instruction are identified. Opportunities for student talk were influenced by a combination of factors located in the domains of "teacher practice," "classroom systems," and "physical structures." Combinations of elements from these three

Toward a manifesto for the 'public understanding of big data'.

PubMed

Michael, Mike; Lupton, Deborah

2016-01-01

In this article, we sketch a 'manifesto' for the 'public understanding of big data'. On the one hand, this entails such public understanding of science and public engagement with science and technology-tinged questions as follows: How, when and where are people exposed to, or do they engage with, big data? Who are regarded as big data's trustworthy sources, or credible commentators and critics? What are the mechanisms by which big data systems are opened to public scrutiny? On the other hand, big data generate many challenges for public understanding of science and public engagement with science and technology: How do we address publics that are simultaneously the informant, the informed and the information of big data? What counts as understanding of, or engagement with, big data, when big data themselves are multiplying, fluid and recursive? As part of our manifesto, we propose a range of empirical, conceptual and methodological exhortations. We also provide Appendix 1 that outlines three novel methods for addressing some of the issues raised in the article. © The Author(s) 2015.

Crowd-Funded Micro-Grants for Genomics and “Big Data”: An Actionable Idea Connecting Small (Artisan) Science, Infrastructure Science, and Citizen Philanthropy

PubMed Central

Badr, Kamal F.; Dove, Edward S.; Endrenyi, Laszlo; Geraci, Christy Jo; Hotez, Peter J.; Milius, Djims; Neves-Pereira, Maria; Pang, Tikki; Rotimi, Charles N.; Sabra, Ramzi; Sarkissian, Christineh N.; Srivastava, Sanjeeva; Tims, Hesther; Zgheib, Nathalie K.; Kickbusch, Ilona

2013-01-01

Abstract Biomedical science in the 21st century is embedded in, and draws from, a digital commons and “Big Data” created by high-throughput Omics technologies such as genomics. Classic Edisonian metaphors of science and scientists (i.e., “the lone genius” or other narrow definitions of expertise) are ill equipped to harness the vast promises of the 21st century digital commons. Moreover, in medicine and life sciences, experts often under-appreciate the important contributions made by citizen scholars and lead users of innovations to design innovative products and co-create new knowledge. We believe there are a large number of users waiting to be mobilized so as to engage with Big Data as citizen scientists—only if some funding were available. Yet many of these scholars may not meet the meta-criteria used to judge expertise, such as a track record in obtaining large research grants or a traditional academic curriculum vitae. This innovation research article describes a novel idea and action framework: micro-grants, each worth $1000, for genomics and Big Data. Though a relatively small amount at first glance, this far exceeds the annual income of the “bottom one billion”—the 1.4 billion people living below the extreme poverty level defined by the World Bank ($1.25/day). We describe two types of micro-grants. Type 1 micro-grants can be awarded through established funding agencies and philanthropies that create micro-granting programs to fund a broad and highly diverse array of small artisan labs and citizen scholars to connect genomics and Big Data with new models of discovery such as open user innovation. Type 2 micro-grants can be funded by existing or new science observatories and citizen think tanks through crowd-funding mechanisms described herein. Type 2 micro-grants would also facilitate global health diplomacy by co-creating crowd-funded micro-granting programs across nation-states in regions facing political and financial instability, while

Nursing Management Minimum Data Set: Cost-Effective Tool To Demonstrate the Value of Nurse Staffing in the Big Data Science Era.

PubMed

Pruinelli, Lisiane; Delaney, Connie W; Garciannie, Amy; Caspers, Barbara; Westra, Bonnie L

2016-01-01

There is a growing body of evidence of the relationship of nurse staffing to patient, nurse, and financial outcomes. With the advent of big data science and developing big data analytics in nursing, data science with the reuse of big data is emerging as a timely and cost-effective approach to demonstrate nursing value. The Nursing Management Minimum Date Set (NMMDS) provides standard administrative data elements, definitions, and codes to measure the context where care is delivered and, consequently, the value of nursing. The integration of the NMMDS elements in the current health system provides evidence for nursing leaders to measure and manage decisions, leading to better patient, staffing, and financial outcomes. It also enables the reuse of data for clinical scholarship and research.

Who Owns Educational Theory? Big Data, Algorithms and the Expert Power of Education Data Science

ERIC Educational Resources Information Center

Williamson, Ben

2017-01-01

"Education data science" is an emerging methodological field which possesses the algorithm-driven technologies required to generate insights and knowledge from educational big data. This article consists of an analysis of the Lytics Lab, Stanford University's laboratory for research and development in learning analytics, and the Center…

Describing students' talk about physical science phenomena outside and inside the classroom: A case of secondary school students from Maragoli, western region of Kenya

NASA Astrophysics Data System (ADS)

Oberrecht, Stephen Patrick

Because of cultural and linguistic influences on science learning involving students from diverse cultural and linguistic backgrounds, calls have been made for teachers to enact teaching that is sensitive to these students' backgrounds. However, most of the research involving such students has tended to focus on students at elementary grade levels from predominantly two linguistic backgrounds, Hispanic and Haitian Creole, learning science concepts mainly in the life sciences. Also, most of the studies examined classroom interactions between teachers and the students and among students. Not much attention had been paid to how students talk about ideas inherent in scientific phenomena in an outside-the-classroom context and much less on how that talk relates to that of the classroom. Thus, this research extends knowledge in the area of science learning involving students learning science in a language other than their first language to include students from a language background other than Hispanic and Haitian Creole at not only the high school level but also their learning of ideas in a content area other than the life science (i.e., the physical sciences). More importantly, this research extends knowledge in the area by relating science learning outside and inside the classroom. This dissertation describes this exploratory research project that adopted a case study strategy. The research involved seven Form Two (tenth grade) students (three boys and four girls) from one public, mixed gender day secondary school in rural Kenya. I collected data from the students through focus group discussions as they engaged in talking about ideas inherent in selected physical science phenomena and activities they encountered in their everyday lives, as well as learned about in their science classrooms. I supplemented these data with data from one-on-one semi-structured interviews with two teachers (one for chemistry and one for physics) on their teaching of ideas investigated in

Frontiers in Laser Cooling, Single-Molecule Biophysics, and Enrgy Science: A Talk from Leo Holberg and Allen Mills

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

Holberg, Leo; Mills, Allen

2008-08-30

Leo Holberg and Allen Mills present a talk at Frontiers in Laser Cooling, Single-Molecule Biophysics and Energy Science, a scientific symposium honoring Steve Chu, director of Lawrence Berkeley National Laboratory and recipient of the 1997 Nobel Prize in Physics. The symposium was held August 30, 2008 in Berkeley.

Frontiers in Laser Cooling, Single-Molecule Biophysics, and Enrgy Science: A Talk from Leo Holberg and Allen Mills

ScienceCinema

Holberg, Leo; Mills, Allen

2018-05-07

Leo Holberg and Allen Mills present a talk at Frontiers in Laser Cooling, Single-Molecule Biophysics and Energy Science, a scientific symposium honoring Steve Chu, director of Lawrence Berkeley National Laboratory and recipient of the 1997 Nobel Prize in Physics. The symposium was held August 30, 2008 in Berkeley.

Big data need big theory too

PubMed Central

Dougherty, Edward R.; Highfield, Roger R.

2016-01-01

The current interest in big data, machine learning and data analytics has generated the widespread impression that such methods are capable of solving most problems without the need for conventional scientific methods of inquiry. Interest in these methods is intensifying, accelerated by the ease with which digitized data can be acquired in virtually all fields of endeavour, from science, healthcare and cybersecurity to economics, social sciences and the humanities. In multiscale modelling, machine learning appears to provide a shortcut to reveal correlations of arbitrary complexity between processes at the atomic, molecular, meso- and macroscales. Here, we point out the weaknesses of pure big data approaches with particular focus on biology and medicine, which fail to provide conceptual accounts for the processes to which they are applied. No matter their ‘depth’ and the sophistication of data-driven methods, such as artificial neural nets, in the end they merely fit curves to existing data. Not only do these methods invariably require far larger quantities of data than anticipated by big data aficionados in order to produce statistically reliable results, but they can also fail in circumstances beyond the range of the data used to train them because they are not designed to model the structural characteristics of the underlying system. We argue that it is vital to use theory as a guide to experimental design for maximal efficiency of data collection and to produce reliable predictive models and conceptual knowledge. Rather than continuing to fund, pursue and promote ‘blind’ big data projects with massive budgets, we call for more funding to be allocated to the elucidation of the multiscale and stochastic processes controlling the behaviour of complex systems, including those of life, medicine and healthcare. This article is part of the themed issue ‘Multiscale modelling at the physics–chemistry–biology interface’. PMID:27698035

Big data need big theory too.

PubMed

Coveney, Peter V; Dougherty, Edward R; Highfield, Roger R

2016-11-13

The current interest in big data, machine learning and data analytics has generated the widespread impression that such methods are capable of solving most problems without the need for conventional scientific methods of inquiry. Interest in these methods is intensifying, accelerated by the ease with which digitized data can be acquired in virtually all fields of endeavour, from science, healthcare and cybersecurity to economics, social sciences and the humanities. In multiscale modelling, machine learning appears to provide a shortcut to reveal correlations of arbitrary complexity between processes at the atomic, molecular, meso- and macroscales. Here, we point out the weaknesses of pure big data approaches with particular focus on biology and medicine, which fail to provide conceptual accounts for the processes to which they are applied. No matter their 'depth' and the sophistication of data-driven methods, such as artificial neural nets, in the end they merely fit curves to existing data. Not only do these methods invariably require far larger quantities of data than anticipated by big data aficionados in order to produce statistically reliable results, but they can also fail in circumstances beyond the range of the data used to train them because they are not designed to model the structural characteristics of the underlying system. We argue that it is vital to use theory as a guide to experimental design for maximal efficiency of data collection and to produce reliable predictive models and conceptual knowledge. Rather than continuing to fund, pursue and promote 'blind' big data projects with massive budgets, we call for more funding to be allocated to the elucidation of the multiscale and stochastic processes controlling the behaviour of complex systems, including those of life, medicine and healthcare.This article is part of the themed issue 'Multiscale modelling at the physics-chemistry-biology interface'. © 2015 The Authors.

Big Data and Perioperative Nursing.

PubMed

Westra, Bonnie L; Peterson, Jessica J

2016-10-01

Big data are large volumes of digital data that can be collected from disparate sources and are challenging to analyze. These data are often described with the five "Vs": volume, velocity, variety, veracity, and value. Perioperative nurses contribute to big data through documentation in the electronic health record during routine surgical care, and these data have implications for clinical decision making, administrative decisions, quality improvement, and big data science. This article explores methods to improve the quality of perioperative nursing data and provides examples of how these data can be combined with broader nursing data for quality improvement. We also discuss a national action plan for nursing knowledge and big data science and how perioperative nurses can engage in collaborative actions to transform health care. Standardized perioperative nursing data has the potential to affect care far beyond the original patient. Copyright © 2016 AORN, Inc. Published by Elsevier Inc. All rights reserved.

Earth science big data at users' fingertips: the EarthServer Science Gateway Mobile

NASA Astrophysics Data System (ADS)

Barbera, Roberto; Bruno, Riccardo; Calanducci, Antonio; Fargetta, Marco; Pappalardo, Marco; Rundo, Francesco

2014-05-01

The EarthServer project (www.earthserver.eu), funded by the European Commission under its Seventh Framework Program, aims at establishing open access and ad-hoc analytics on extreme-size Earth Science data, based on and extending leading-edge Array Database technology. The core idea is to use database query languages as client/server interface to achieve barrier-free "mix & match" access to multi-source, any-size, multi-dimensional space-time data -- in short: "Big Earth Data Analytics" - based on the open standards of the Open Geospatial Consortium Web Coverage Processing Service (OGC WCPS) and the W3C XQuery. EarthServer combines both, thereby achieving a tight data/metadata integration. Further, the rasdaman Array Database System (www.rasdaman.com) is extended with further space-time coverage data types. On server side, highly effective optimizations - such as parallel and distributed query processing - ensure scalability to Exabyte volumes. In this contribution we will report on the EarthServer Science Gateway Mobile, an app for both iOS and Android-based devices that allows users to seamlessly access some of the EarthServer applications using SAML-based federated authentication and fine-grained authorisation mechanisms.

Second BRITE-Constellation Science Conference: Small satellites—big science, Proceedings of the Polish Astronomical Society volume 5

NASA Astrophysics Data System (ADS)

Zwintz, Konstanze; Poretti, Ennio

2017-09-01

In 2016 the BRITE-Constellation mission had been operational for more than two years. At that time, several hundreds of bright stars of various types had been observed successfully in the two BRITE lters and astonishing new discoveries had been made. Therefore, the time was ripe to host the Second BRITE-Constellation Science Conference: Small satellites | big science" from August 22 to 26, 2016, in the beautiful Madonnensaal of the University of Innsbruck, Austria. With this conference, we brought together the scientic community interested in BRITE-Constellation, pro- vided an update on the status of the mission, presented and discussed latest scientic results, shared our experiences with the data, illustrated successful cooperations between professional and amateur ground-based observers and BRITE scientists, and explored new ideas for future BRITE-Constellation observations.

Let's Talk About Water: Film as a Resource to Engage Audiences Around Earth Science Issues

NASA Astrophysics Data System (ADS)

Clark, E.; Hooper, R. P.; Lilienfeld, L.

2017-12-01

Connecting a diverse audience to science can be challenging. Scientists generally publish their findings in ways that are not easily accessible to audiences outside of the science community and translating findings for wider consumption requires a mindful balance of generalization and accuracy. In response to these communication challenges, the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) developed the Let's Talk About Water (LTAW) program as a formula for hosting successful events for Earth Science education. The program uses film as a bridge to open a discussion between scientists and the audience. In this setting, films are powerful educational tools because they use storytelling to engage audiences emotionally, which creates relatable, teachable moments. Originally designed to bring awareness to water issues, the formula can easily be applied to increase literacy on climate change and other critical Earth Science issues facing society. This presentation will discuss the LTAW event formula and the resources that CUAHSI has available to support event organizers in the development of their own LTAW events.

The Big Challenge in Big Earth Science Data: Maturing to Transdisciplinary Data Platforms that are Relevant to Government, Research and Industry

NASA Astrophysics Data System (ADS)

Wyborn, Lesley; Evans, Ben

2016-04-01

Collecting data for the Earth Sciences has a particularly long history going back centuries. Initially scientific data came only from simple human observations recorded by pen on paper. Scientific instruments soon supplemented data capture, and as these instruments became more capable (e.g, automation, more information captured, generation of digitally-born outputs), Earth Scientists entered the 'Big Data' era where progressively data became too big to store and process locally in the old style vaults. To date, most funding initiatives for collection and storage of large volume data sets in the Earth Sciences have been specialised within a single discipline (e.g., climate, geophysics, and Earth Observation) or specific to an individual institution. To undertake interdisciplinary research, it is hard for users to integrate data from these individual repositories mainly due to limitations on physical access to/movement of the data, and/or data being organised without enough information to make sense of it without discipline specialised knowledge. Smaller repositories have also gradually been seen as inefficient in terms of the cost to manage and access (including scarce skills) and effective implementation of new technology and techniques. Within the last decade, the trend is towards fewer and larger data repositories that increasingly are collocated with HPC/cloud resources. There has also been a growing recognition that digital data can be a valuable resource that can be reused and repurposed - publicly funded data from either the academic of government sector is seen as a shared resource, and that efficiencies can be gained by co-location. These new, highly capable, 'transdisciplinary' data repositories are emerging as a fundamental 'infrastructure' both for research and other innovation. The sharing of academic and government data resources on the same infrastructures is enabling new research programmes that will enable integration beyond the traditional physical

A Tour of Big Data, Open Source Data Management Technologies from the Apache Software Foundation

NASA Astrophysics Data System (ADS)

Mattmann, C. A.

2012-12-01

The Apache Software Foundation, a non-profit foundation charged with dissemination of open source software for the public good, provides a suite of data management technologies for distributed archiving, data ingestion, data dissemination, processing, triage and a host of other functionalities that are becoming critical in the Big Data regime. Apache is the world's largest open source software organization, boasting over 3000 developers from around the world all contributing to some of the most pervasive technologies in use today, from the HTTPD web server that powers a majority of Internet web sites to the Hadoop technology that is now projected at over a $1B dollar industry. Apache data management technologies are emerging as de facto off-the-shelf components for searching, distributing, processing and archiving key science data sets both geophysical, space and planetary based, all the way to biomedicine. In this talk, I will give a virtual tour of the Apache Software Foundation, its meritocracy and governance structure, and also its key big data technologies that organizations can take advantage of today and use to save cost, schedule, and resources in implementing their Big Data needs. I'll illustrate the Apache technologies in the context of several national priority projects, including the U.S. National Climate Assessment (NCA), and in the International Square Kilometre Array (SKA) project that are stretching the boundaries of volume, velocity, complexity, and other key Big Data dimensions.

Communicating the Nature of Science through "The Big Bang Theory": Evidence from a Focus Group Study

ERIC Educational Resources Information Center

Li, Rashel; Orthia, Lindy A.

2016-01-01

In this paper, we discuss a little-studied means of communicating about or teaching the nature of science (NOS)--through fiction television. We report some results of focus group research which suggest that the American sitcom "The Big Bang Theory" (2007-present), whose main characters are mostly working scientists, has influenced…

Technology and Science in Classroom and Interview Talk with Swiss Lower Secondary School Students: A Marxist Sociological Approach

ERIC Educational Resources Information Center

Roth, Wolff-Michael

2013-01-01

In much of science education research, the content of talk tends to be attributed to the persons who produce the sound-words in a speech situation. A radically different, sociological perspective on language-in-use grounded in Marxism derives from the work of L. S. Vygotsky and the members of the circle around M. M. Bakhtin. Accordingly, each word…

["Big data" - large data, a lot of knowledge?].

PubMed

Hothorn, Torsten

2015-01-28

Since a couple of years, the term Big Data describes technologies to extract knowledge from data. Applications of Big Data and their consequences are also increasingly discussed in the mass media. Because medicine is an empirical science, we discuss the meaning of Big Data and its potential for future medical research.

IBM Watson: How Cognitive Computing Can Be Applied to Big Data Challenges in Life Sciences Research.

PubMed

Chen, Ying; Elenee Argentinis, J D; Weber, Griff

2016-04-01

Life sciences researchers are under pressure to innovate faster than ever. Big data offer the promise of unlocking novel insights and accelerating breakthroughs. Ironically, although more data are available than ever, only a fraction is being integrated, understood, and analyzed. The challenge lies in harnessing volumes of data, integrating the data from hundreds of sources, and understanding their various formats. New technologies such as cognitive computing offer promise for addressing this challenge because cognitive solutions are specifically designed to integrate and analyze big datasets. Cognitive solutions can understand different types of data such as lab values in a structured database or the text of a scientific publication. Cognitive solutions are trained to understand technical, industry-specific content and use advanced reasoning, predictive modeling, and machine learning techniques to advance research faster. Watson, a cognitive computing technology, has been configured to support life sciences research. This version of Watson includes medical literature, patents, genomics, and chemical and pharmacological data that researchers would typically use in their work. Watson has also been developed with specific comprehension of scientific terminology so it can make novel connections in millions of pages of text. Watson has been applied to a few pilot studies in the areas of drug target identification and drug repurposing. The pilot results suggest that Watson can accelerate identification of novel drug candidates and novel drug targets by harnessing the potential of big data. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Machine learning for Big Data analytics in plants.

PubMed

Ma, Chuang; Zhang, Hao Helen; Wang, Xiangfeng

2014-12-01

Rapid advances in high-throughput genomic technology have enabled biology to enter the era of 'Big Data' (large datasets). The plant science community not only needs to build its own Big-Data-compatible parallel computing and data management infrastructures, but also to seek novel analytical paradigms to extract information from the overwhelming amounts of data. Machine learning offers promising computational and analytical solutions for the integrative analysis of large, heterogeneous and unstructured datasets on the Big-Data scale, and is gradually gaining popularity in biology. This review introduces the basic concepts and procedures of machine-learning applications and envisages how machine learning could interface with Big Data technology to facilitate basic research and biotechnology in the plant sciences. Copyright © 2014 Elsevier Ltd. All rights reserved.

"Air Toxics under the Big Sky": Examining the Effectiveness of Authentic Scientific Research on High School Students' Science Skills and Interest

ERIC Educational Resources Information Center

Ward, Tony J.; Delaloye, Naomi; Adams, Earle Raymond; Ware, Desirae; Vanek, Diana; Knuth, Randy; Hester, Carolyn Laurie; Marra, Nancy Noel; Holian, Andrij

2016-01-01

"Air Toxics Under the Big Sky" is an environmental science outreach/education program that incorporates the Next Generation Science Standards (NGSS) 8 Practices with the goal of promoting knowledge and understanding of authentic scientific research in high school classrooms through air quality research. This research explored: (1)…

SQL is Dead; Long-live SQL: Relational Database Technology in Science Contexts

NASA Astrophysics Data System (ADS)

Howe, B.; Halperin, D.

2014-12-01

Relational databases are often perceived as a poor fit in science contexts: Rigid schemas, poor support for complex analytics, unpredictable performance, significant maintenance and tuning requirements --- these idiosyncrasies often make databases unattractive in science contexts characterized by heterogeneous data sources, complex analysis tasks, rapidly changing requirements, and limited IT budgets. In this talk, I'll argue that although the value proposition of typical relational database systems are weak in science, the core ideas that power relational databases have become incredibly prolific in open source science software, and are emerging as a universal abstraction for both big data and small data. In addition, I'll talk about two open source systems we are building to "jailbreak" the core technology of relational databases and adapt them for use in science. The first is SQLShare, a Database-as-a-Service system supporting collaborative data analysis and exchange by reducing database use to an Upload-Query-Share workflow with no installation, schema design, or configuration required. The second is Myria, a service that supports much larger scale data, complex analytics, and supports multiple back end systems. Finally, I'll describe some of the ways our collaborators in oceanography, astronomy, biology, fisheries science, and more are using these systems to replace script-based workflows for reasons of performance, flexibility, and convenience.

Talking Back to Teacher

ERIC Educational Resources Information Center

Fischman, Josh

2007-01-01

In this article, the author talks about Classroom Presenter, a computer program that aids in student participation during class discussions and makes boring lectures more interactive. The program was created by Richard J. Anderson, a professor of computer science at the University of Washington, in Seattle. Classroom Presenter is now in use in…

Productive Academic Talk during Inquiry-Based Science

ERIC Educational Resources Information Center

Gillies, Robyn M.

2013-01-01

This study reports on the types of academic talk that contribute to enhanced explanatory responses, reasoning, problem-solving and learning. The study involved 10 groups of 3-4 students who were provided with one of three linguistic tools (i.e. Cognitive Questioning, Philosophy for Children and Collaborative Strategic Reading (CSR)) to scaffold…

The Roles of Teachers' Science Talk in Revealing Language Demands within Diverse Elementary School Classrooms: A Study of Teaching Heat and Temperature in Singapore

ERIC Educational Resources Information Center

Seah, Lay Hoon; Yore, Larry D.

2017-01-01

This study of three science teachers' lessons on heat and temperature seeks to characterise classroom talk that highlighted the ways language is used and to examine the nature of the language demands revealed in constructing, negotiating, arguing and communicating science ideas. The transcripts from the entire instructional units for these…

Data Science and its Relationship to Big Data and Data-Driven Decision Making.

PubMed

Provost, Foster; Fawcett, Tom

2013-03-01

Companies have realized they need to hire data scientists, academic institutions are scrambling to put together data-science programs, and publications are touting data science as a hot-even "sexy"-career choice. However, there is confusion about what exactly data science is, and this confusion could lead to disillusionment as the concept diffuses into meaningless buzz. In this article, we argue that there are good reasons why it has been hard to pin down exactly what is data science. One reason is that data science is intricately intertwined with other important concepts also of growing importance, such as big data and data-driven decision making. Another reason is the natural tendency to associate what a practitioner does with the definition of the practitioner's field; this can result in overlooking the fundamentals of the field. We believe that trying to define the boundaries of data science precisely is not of the utmost importance. We can debate the boundaries of the field in an academic setting, but in order for data science to serve business effectively, it is important (i) to understand its relationships to other important related concepts, and (ii) to begin to identify the fundamental principles underlying data science. Once we embrace (ii), we can much better understand and explain exactly what data science has to offer. Furthermore, only once we embrace (ii) should we be comfortable calling it data science. In this article, we present a perspective that addresses all these concepts. We close by offering, as examples, a partial list of fundamental principles underlying data science.

Finding science in students' talk

NASA Astrophysics Data System (ADS)

Yeo, Jennifer

2009-12-01

What does it mean to understand science? This commentary extends Brown and Kloser's argument on the role of native language for science learning by exploring the meaning of understanding in school science and discusses the extent that science educators could tolerate adulterated forms of scientific knowledge. Taking the perspective of social semiotics, this commentary looks at the extent that school science can be represented with other discourse practices. It also offers an example to illustrate how everyday language can present potential hindrance to school science learning.

Playful Talk: Negotiating Opportunities to Learn in Collaborative Groups

ERIC Educational Resources Information Center

Sullivan, Florence R.; Wilson, Nicholas C.

2015-01-01

This case study examines the role of playful talk in negotiating the "how" of collaborative group work in a 6th-grade science classroom. Here we develop and test a Vygotsky-derived hypothesis that postulates playful talk as a mechanism for identity exploration and group status negotiation. Our findings indicate that students utilized the…

Aneesur Rahman Prize Talk

NASA Astrophysics Data System (ADS)

Frenkel, Daan

2007-03-01

During the past decade there has been a unique synergy between theory, experiment and simulation in Soft Matter Physics. In colloid science, computer simulations that started out as studies of highly simplified model systems, have acquired direct experimental relevance because experimental realizations of these simple models can now be synthesized. Whilst many numerical predictions concerning the phase behavior of colloidal systems have been vindicated by experiments, the jury is still out on others. In my talk I will discuss some of the recent technical developments, new findings and open questions in computational soft-matter science.

Examining the Big-Fish-Little-Pond Effect on Students' Self-Concept of Learning Science in Taiwan Based on the TIMSS Databases

ERIC Educational Resources Information Center

Liou, Pey-Yan

2014-01-01

The purpose of this study is to examine the relationship between student self-concept and achievement in science in Taiwan based on the big-fish-little-pond effect (BFLPE) model using the Trends in International Mathematics and Science Study (TIMSS) 2003 and 2007 databases. Hierarchical linear modeling was used to examine the effects of the…

Finding Science in Students' Talk

ERIC Educational Resources Information Center

Yeo, Jennifer

2009-01-01

What does it mean to understand science? This commentary extends Brown and Kloser's argument on the role of native language for science learning by exploring the meaning of understanding in school science and discusses the extent that science educators could tolerate adulterated forms of scientific knowledge. Taking the perspective of social…

Big Data Challenges in Climate Science: Improving the Next-Generation Cyberinfrastructure

NASA Technical Reports Server (NTRS)

Schnase, John L.; Lee, Tsengdar J.; Mattmann, Chris A.; Lynnes, Christopher S.; Cinquini, Luca; Ramirez, Paul M.; Hart, Andre F.; Williams, Dean N.; Waliser, Duane; Rinsland, Pamela;

Big physics quartet win government backing

NASA Astrophysics Data System (ADS)

Banks, Michael

2014-09-01

Four major physics-based projects are among 10 to have been selected by Japan’s Ministry of Education, Culture, Sports, Science and Technology for funding in the coming decade as part of its “roadmap” of big-science projects.

Big Data in Health: a Literature Review from the Year 2005.

PubMed

de la Torre Díez, Isabel; Cosgaya, Héctor Merino; Garcia-Zapirain, Begoña; López-Coronado, Miguel

2016-09-01

The information stored in healthcare systems has increased over the last ten years, leading it to be considered Big Data. There is a wealth of health information ready to be analysed. However, the sheer volume raises a challenge for traditional methods. The aim of this article is to conduct a cutting-edge study on Big Data in healthcare from 2005 to the present. This literature review will help researchers to know how Big Data has developed in the health industry and open up new avenues for research. Information searches have been made on various scientific databases such as Pubmed, Science Direct, Scopus and Web of Science for Big Data in healthcare. The search criteria were "Big Data" and "health" with a date range from 2005 to the present. A total of 9724 articles were found on the databases. 9515 articles were discarded as duplicates or for not having a title of interest to the study. 209 articles were read, with the resulting decision that 46 were useful for this study. 52.6 % of the articles used were found in Science Direct, 23.7 % in Pubmed, 22.1 % through Scopus and the remaining 2.6 % through the Web of Science. Big Data has undergone extremely high growth since 2011 and its use is becoming compulsory in developed nations and in an increasing number of developing nations. Big Data is a step forward and a cost reducer for public and private healthcare.

A Big Bang Lab

ERIC Educational Resources Information Center

Scheider, Walter

2005-01-01

The February 2005 issue of The Science Teacher (TST) reminded everyone that by learning how scientists study stars, students gain an understanding of how science measures things that can not be set up in lab, either because they are too big, too far away, or happened in a very distant past. The authors of "How Far are the Stars?" show how the…

Little ice bodies, huge ice lands, and the up-going of the big water body

NASA Astrophysics Data System (ADS)

Ultee, E.; Bassis, J. N.

2017-12-01

Ice moving out of the huge ice lands causes the big water body to go up. That can cause bad things to happen in places close to the big water body - the land might even disappear! If that happens, people living close to the big water body might lose their homes. Knowing how much ice will come out of the huge ice lands, and when, can help the world plan for the up-going of the big water body. We study the huge ice land closest to us. All around the edge of that huge ice land, there are smaller ice bodies that control how much ice makes it into the big water body. Most ways of studying the huge ice land with computers struggle to tell the computer about those little ice bodies, but we have found a new way. We will talk about our way of studying little ice bodies and how their moving brings about up-going of the big water.

The Role of Big Data in the Social Sciences

ERIC Educational Resources Information Center

Ovadia, Steven

2013-01-01

Big Data is an increasingly popular term across scholarly and popular literature but lacks a formal definition (Lohr 2012). This is beneficial in that it keeps the term flexible. For librarians, Big Data represents a few important ideas. One idea is the idea of balancing accessibility with privacy. Librarians tend to want information to be as open…

Talking Sport and Fitness

ERIC Educational Resources Information Center

Dixon-Watmough, Rebecca; Keogh, Brenda; Naylor, Stuart

2012-01-01

For some time the Association for Science Education (ASE) has been aware that it would be useful to have some resources available to get children talking and thinking about issues related to health, sport and fitness. Some of the questions about pulse, breathing rate and so on are pretty obvious to everyone, and there is a risk of these being…

Opportunities and challenges of big data for the social sciences: The case of genomic data.

PubMed

Liu, Hexuan; Guo, Guang

2016-09-01

In this paper, we draw attention to one unique and valuable source of big data, genomic data, by demonstrating the opportunities they provide to social scientists. We discuss different types of large-scale genomic data and recent advances in statistical methods and computational infrastructure used to address challenges in managing and analyzing such data. We highlight how these data and methods can be used to benefit social science research. Copyright © 2016 Elsevier Inc. All rights reserved.

Big Data Science Cafés: High School Students Experiencing Real Research with Scientists

NASA Astrophysics Data System (ADS)

Walker, C. E.; Pompea, S. M.

2017-12-01

The Education and Public Outreach group at the National Optical Astronomy Observatory has designed an outside-of-school education program to excite the interest of talented youth in future projects like the Large Synoptic Survey Telescope (LSST) and the NOAO (archival) Data Lab - their data approaches and key science projects. Originally funded by the LSST Corporation, the program cultivates talented youth to enter STEM disciplines and serves as a model to disseminate to the 40+ institutions involved in LSST. One Saturday a month during the academic year, high school students have the opportunity to interact with expert astronomers who work with large astronomical data sets in their scientific work. Students learn about killer asteroids, the birth and death of stars, colliding galaxies, the structure of the universe, gravitational waves, dark energy, dark matter, and more. The format for the Saturday science cafés has been a short presentation, discussion (plus food), computer lab activity and more discussion. They last about 2.5 hours and have been planned by a group of interested local high school students, an undergraduate student coordinator, the presenting astronomers, the program director and an evaluator. High school youth leaders help ensure an enjoyable and successful program for fellow students. They help their fellow students with the activities and help evaluate how well the science café went. Their remarks shape the next science café and improve the program. The experience offers youth leaders ownership of the program, opportunities to take on responsibilities and learn leadership and communication skills, as well as foster their continued interests in STEM. The prototype Big Data Science Academy was implemented successfully in the Spring 2017 and engaged almost 40 teens from greater Tucson in the fundamentals of astronomy concepts and research. As with any first implementation there were bumps. However, staff, scientists, and student leaders all

Data Prospecting Framework - a new approach to explore "big data" in Earth Science

NASA Astrophysics Data System (ADS)

Ramachandran, R.; Rushing, J.; Lin, A.; Kuo, K.

2012-12-01

Due to advances in sensors, computation and storage, cost and effort required to produce large datasets have been significantly reduced. As a result, we are seeing a proliferation of large-scale data sets being assembled in almost every science field, especially in geosciences. Opportunities to exploit the "big data" are enormous as new hypotheses can be generated by combining and analyzing large amounts of data. However, such a data-driven approach to science discovery assumes that scientists can find and isolate relevant subsets from vast amounts of available data. Current Earth Science data systems only provide data discovery through simple metadata and keyword-based searches and are not designed to support data exploration capabilities based on the actual content. Consequently, scientists often find themselves downloading large volumes of data, struggling with large amounts of storage and learning new analysis technologies that will help them separate the wheat from the chaff. New mechanisms of data exploration are needed to help scientists discover the relevant subsets We present data prospecting, a new content-based data analysis paradigm to support data-intensive science. Data prospecting allows the researchers to explore big data in determining and isolating data subsets for further analysis. This is akin to geo-prospecting in which mineral sites of interest are determined over the landscape through screening methods. The resulting "data prospects" only provide an interaction with and feel for the data through first-look analytics; the researchers would still have to download the relevant datasets and analyze them deeply using their favorite analytical tools to determine if the datasets will yield new hypotheses. Data prospecting combines two traditional categories of data analysis, data exploration and data mining within the discovery step. Data exploration utilizes manual/interactive methods for data analysis such as standard statistical analysis and

Survey of Cyber Crime in Big Data

NASA Astrophysics Data System (ADS)

Rajeswari, C.; Soni, Krishna; Tandon, Rajat

2017-11-01

Big data is like performing computation operations and database operations for large amounts of data, automatically from the data possessor’s business. Since a critical strategic offer of big data access to information from numerous and various areas, security and protection will assume an imperative part in big data research and innovation. The limits of standard IT security practices are notable, with the goal that they can utilize programming sending to utilize programming designers to incorporate pernicious programming in a genuine and developing risk in applications and working frameworks, which are troublesome. The impact gets speedier than big data. In this way, one central issue is that security and protection innovation are sufficient to share controlled affirmation for countless direct get to. For powerful utilization of extensive information, it should be approved to get to the information of that space or whatever other area from a space. For a long time, dependable framework improvement has arranged a rich arrangement of demonstrated ideas of demonstrated security to bargain to a great extent with the decided adversaries, however this procedure has been to a great extent underestimated as “needless excess” and sellers In this discourse, essential talks will be examined for substantial information to exploit this develop security and protection innovation, while the rest of the exploration difficulties will be investigated.

Taking a 'Big Data' approach to data quality in a citizen science project.

PubMed

Kelling, Steve; Fink, Daniel; La Sorte, Frank A; Johnston, Alison; Bruns, Nicholas E; Hochachka, Wesley M

2015-11-01

Data from well-designed experiments provide the strongest evidence of causation in biodiversity studies. However, for many species the collection of these data is not scalable to the spatial and temporal extents required to understand patterns at the population level. Only data collected from citizen science projects can gather sufficient quantities of data, but data collected from volunteers are inherently noisy and heterogeneous. Here we describe a 'Big Data' approach to improve the data quality in eBird, a global citizen science project that gathers bird observations. First, eBird's data submission design ensures that all data meet high standards of completeness and accuracy. Second, we take a 'sensor calibration' approach to measure individual variation in eBird participant's ability to detect and identify birds. Third, we use species distribution models to fill in data gaps. Finally, we provide examples of novel analyses exploring population-level patterns in bird distributions.

MERRA Analytic Services: Meeting the Big Data Challenges of Climate Science through Cloud-Enabled Climate Analytics-as-a-Service

NASA Astrophysics Data System (ADS)

Schnase, J. L.; Duffy, D.; Tamkin, G. S.; Nadeau, D.; Thompson, J. H.; Grieg, C. M.; McInerney, M.; Webster, W. P.

2013-12-01

Climate science is a Big Data domain that is experiencing unprecedented growth. In our efforts to address the Big Data challenges of climate science, we are moving toward a notion of Climate Analytics-as-a-Service (CAaaS). We focus on analytics, because it is the knowledge gained from our interactions with Big Data that ultimately produce societal benefits. We focus on CAaaS because we believe it provides a useful way of thinking about the problem: a specialization of the concept of business process-as-a-service, which is an evolving extension of IaaS, PaaS, and SaaS enabled by Cloud Computing. Within this framework, Cloud Computing plays an important role; however, we see it as only one element in a constellation of capabilities that are essential to delivering climate analytics as a service. These elements are essential because in the aggregate they lead to generativity, a capacity for self-assembly that we feel is the key to solving many of the Big Data challenges in this domain. MERRA Analytic Services (MERRA/AS) is an example of cloud-enabled CAaaS built on this principle. MERRA/AS enables MapReduce analytics over NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) data collection. The MERRA reanalysis integrates observational data with numerical models to produce a global temporally and spatially consistent synthesis of 26 key climate variables. It represents a type of data product that is of growing importance to scientists doing climate change research and a wide range of decision support applications. MERRA/AS brings together the following generative elements in a full, end-to-end demonstration of CAaaS capabilities: (1) high-performance, data proximal analytics, (2) scalable data management, (3) software appliance virtualization, (4) adaptive analytics, and (5) a domain-harmonized API. The effectiveness of MERRA/AS has been demonstrated in several applications. In our experience, Cloud Computing lowers the barriers and risk to

MERRA Analytic Services: Meeting the Big Data Challenges of Climate Science Through Cloud-enabled Climate Analytics-as-a-service

NASA Technical Reports Server (NTRS)

Schnase, John L.; Duffy, Daniel Quinn; Tamkin, Glenn S.; Nadeau, Denis; Thompson, John H.; Grieg, Christina M.; McInerney, Mark A.; Webster, William P.

2014-01-01

Climate science is a Big Data domain that is experiencing unprecedented growth. In our efforts to address the Big Data challenges of climate science, we are moving toward a notion of Climate Analytics-as-a-Service (CAaaS). We focus on analytics, because it is the knowledge gained from our interactions with Big Data that ultimately produce societal benefits. We focus on CAaaS because we believe it provides a useful way of thinking about the problem: a specialization of the concept of business process-as-a-service, which is an evolving extension of IaaS, PaaS, and SaaS enabled by Cloud Computing. Within this framework, Cloud Computing plays an important role; however, we it see it as only one element in a constellation of capabilities that are essential to delivering climate analytics as a service. These elements are essential because in the aggregate they lead to generativity, a capacity for self-assembly that we feel is the key to solving many of the Big Data challenges in this domain. MERRA Analytic Services (MERRAAS) is an example of cloud-enabled CAaaS built on this principle. MERRAAS enables MapReduce analytics over NASAs Modern-Era Retrospective Analysis for Research and Applications (MERRA) data collection. The MERRA reanalysis integrates observational data with numerical models to produce a global temporally and spatially consistent synthesis of 26 key climate variables. It represents a type of data product that is of growing importance to scientists doing climate change research and a wide range of decision support applications. MERRAAS brings together the following generative elements in a full, end-to-end demonstration of CAaaS capabilities: (1) high-performance, data proximal analytics, (2) scalable data management, (3) software appliance virtualization, (4) adaptive analytics, and (5) a domain-harmonized API. The effectiveness of MERRAAS has been demonstrated in several applications. In our experience, Cloud Computing lowers the barriers and risk to

Big Data and Knowledge Management: A Possible Course to Combine Them Together

ERIC Educational Resources Information Center

Hijazi, Sam

2017-01-01

Big data (BD) is the buzz phrase these days. Everyone is talking about its potential, its volume, its variety, and its velocity. Knowledge management (KM) has been around since the mid-1990s. The goals of KM have been to collect, store, categorize, mine, and process data into knowledge. The methods of knowledge acquisition varied from…

Maniac Talk - Richard Spinrad

NASA Image and Video Library

2015-05-27

Richard Spinrad Maniac Lecture, May 27, 2015 NOAA Chief Scientist Dr. Richard "Rick" Spinrad presented a Maniac Talk entitled "Lately it occurs to me, what a long, strange trip it's been: one technocrat's unguided tour through oceanography." Rick shared his journey and life in science, including tipping points in his career and how he has come to understand the value of transdisciplinarity, odds-weighing, and timing.

Discourse, Power, and Knowledge in the Management of "Big Science": The Production of Consensus in a Nuclear Fusion Research Laboratory.

ERIC Educational Resources Information Center

Kinsella, William J.

1999-01-01

Extends a Foucauldian view of power/knowledge to the archetypical knowledge-intensive organization, the scientific research laboratory. Describes the discursive production of power/knowledge at the "big science" laboratory conducting nuclear fusion research and illuminates a critical incident in which the fusion research…

From Research to Radio: How to Talk to a Science Reporter

NASA Astrophysics Data System (ADS)

Bentley, M. C.

2006-12-01

While there can be misunderstanding between scientists and journalists in communicating scientific research and, in particular, the realities of climate change, the communication gulf is wider between scientists/journalists and the public. Scientists may not be aware just how a journalist decides when and how to report on scientific research so that it might have an impact on the audience since these considerations are not those made when writing a paper for scientists' peers - or, in turn, how scientists can work with reporters to communicate more effectively the significance of their work. For example, polls have shown that while the majority of the American public is aware of climate change, they feel no urgency about it, or feel helpless as to how to respond. A newspaper article that includes new research into increased melt of Artic glaciers, that also includes the relevance the changes have to the individual living outside the Arctic, and how the public might take action, may help scientists break through the psychological barrier that prevents the public from absorbing the consequences of a changing climate. It is also important that scientists describe their research in language that a lay public can understand, without the jargon familiar only to scientists within a particular circle of research. In this talk I will describe my experience reporting on science and climate change for the BBC as to what frustrations reporters have in interviewing scientists, what misconceptions scientists may have about how journalism work, and what scientists should keep in mind when talking to reporters so that both groups can work together to communicate more effectively to the public. I will include audio examples from my radio work, whose concepts are relevant also to other media.

Big biomedical data as the key resource for discovery science

PubMed Central

Toga, Arthur W; Foster, Ian; Kesselman, Carl; Madduri, Ravi; Chard, Kyle; Deutsch, Eric W; Price, Nathan D; Glusman, Gustavo; Heavner, Benjamin D; Dinov, Ivo D; Ames, Joseph; Van Horn, John; Kramer, Roger; Hood, Leroy

2015-01-01

Modern biomedical data collection is generating exponentially more data in a multitude of formats. This flood of complex data poses significant opportunities to discover and understand the critical interplay among such diverse domains as genomics, proteomics, metabolomics, and phenomics, including imaging, biometrics, and clinical data. The Big Data for Discovery Science Center is taking an “-ome to home” approach to discover linkages between these disparate data sources by mining existing databases of proteomic and genomic data, brain images, and clinical assessments. In support of this work, the authors developed new technological capabilities that make it easy for researchers to manage, aggregate, manipulate, integrate, and model large amounts of distributed data. Guided by biological domain expertise, the Center’s computational resources and software will reveal relationships and patterns, aiding researchers in identifying biomarkers for the most confounding conditions and diseases, such as Parkinson’s and Alzheimer’s. PMID:26198305

Big Questions: Missing Antimatter

ScienceCinema

Lincoln, Don

2018-06-08

Einstein's equation E = mc2 is often said to mean that energy can be converted into matter. More accurately, energy can be converted to matter and antimatter. During the first moments of the Big Bang, the universe was smaller, hotter and energy was everywhere. As the universe expanded and cooled, the energy converted into matter and antimatter. According to our best understanding, these two substances should have been created in equal quantities. However when we look out into the cosmos we see only matter and no antimatter. The absence of antimatter is one of the Big Mysteries of modern physics. In this video, Fermilab's Dr. Don Lincoln explains the problem, although doesn't answer it. The answer, as in all Big Mysteries, is still unknown and one of the leading research topics of contemporary science.

Big data in biomedicine.

PubMed

Costa, Fabricio F

2014-04-01

The increasing availability and growth rate of biomedical information, also known as 'big data', provides an opportunity for future personalized medicine programs that will significantly improve patient care. Recent advances in information technology (IT) applied to biomedicine are changing the landscape of privacy and personal information, with patients getting more control of their health information. Conceivably, big data analytics is already impacting health decisions and patient care; however, specific challenges need to be addressed to integrate current discoveries into medical practice. In this article, I will discuss the major breakthroughs achieved in combining omics and clinical health data in terms of their application to personalized medicine. I will also review the challenges associated with using big data in biomedicine and translational science. Copyright © 2013 Elsevier Ltd. All rights reserved.

The BIG Data Center: from deposition to integration to translation

PubMed Central

2017-01-01

Biological data are generated at unprecedentedly exponential rates, posing considerable challenges in big data deposition, integration and translation. The BIG Data Center, established at Beijing Institute of Genomics (BIG), Chinese Academy of Sciences, provides a suite of database resources, including (i) Genome Sequence Archive, a data repository specialized for archiving raw sequence reads, (ii) Gene Expression Nebulas, a data portal of gene expression profiles based entirely on RNA-Seq data, (iii) Genome Variation Map, a comprehensive collection of genome variations for featured species, (iv) Genome Warehouse, a centralized resource housing genome-scale data with particular focus on economically important animals and plants, (v) Methylation Bank, an integrated database of whole-genome single-base resolution methylomes and (vi) Science Wikis, a central access point for biological wikis developed for community annotations. The BIG Data Center is dedicated to constructing and maintaining biological databases through big data integration and value-added curation, conducting basic research to translate big data into big knowledge and providing freely open access to a variety of data resources in support of worldwide research activities in both academia and industry. All of these resources are publicly available and can be found at http://bigd.big.ac.cn. PMID:27899658

The BIG Data Center: from deposition to integration to translation.

PubMed

2017-01-04

Biological data are generated at unprecedentedly exponential rates, posing considerable challenges in big data deposition, integration and translation. The BIG Data Center, established at Beijing Institute of Genomics (BIG), Chinese Academy of Sciences, provides a suite of database resources, including (i) Genome Sequence Archive, a data repository specialized for archiving raw sequence reads, (ii) Gene Expression Nebulas, a data portal of gene expression profiles based entirely on RNA-Seq data, (iii) Genome Variation Map, a comprehensive collection of genome variations for featured species, (iv) Genome Warehouse, a centralized resource housing genome-scale data with particular focus on economically important animals and plants, (v) Methylation Bank, an integrated database of whole-genome single-base resolution methylomes and (vi) Science Wikis, a central access point for biological wikis developed for community annotations. The BIG Data Center is dedicated to constructing and maintaining biological databases through big data integration and value-added curation, conducting basic research to translate big data into big knowledge and providing freely open access to a variety of data resources in support of worldwide research activities in both academia and industry. All of these resources are publicly available and can be found at http://bigd.big.ac.cn. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

What Role for Law, Human Rights, and Bioethics in an Age of Big Data, Consortia Science, and Consortia Ethics? The Importance of Trustworthiness.

PubMed

Dove, Edward S; Özdemir, Vural

2015-09-01

The global bioeconomy is generating new paradigm-shifting practices of knowledge co-production, such as collective innovation; large-scale, data-driven global consortia science (Big Science); and consortia ethics (Big Ethics). These bioeconomic and sociotechnical practices can be forces for progressive social change, but they can also raise predicaments at the interface of law, human rights, and bioethics. In this article, we examine one such double-edged practice: the growing, multivariate exploitation of Big Data in the health sector, particularly by the private sector. Commercial exploitation of health data for knowledge-based products is a key aspect of the bioeconomy and is also a topic of concern among publics around the world. It is exacerbated in the current age of globally interconnected consortia science and consortia ethics, which is characterized by accumulating epistemic proximity, diminished academic independence, "extreme centrism", and conflicted/competing interests among innovation actors. Extreme centrism is of particular importance as a new ideology emerging from consortia science and consortia ethics; this relates to invariably taking a middle-of-the-road populist stance, even in the event of human rights breaches, so as to sustain the populist support needed for consortia building and collective innovation. What role do law, human rights, and bioethics-separate and together-have to play in addressing these predicaments and opportunities in early 21st century science and society? One answer we propose is an intertwined ethico-legal normative construct, namely trustworthiness . By considering trustworthiness as a central pillar at the intersection of law, human rights, and bioethics, we enable others to trust us, which in turns allows different actors (both nonprofit and for-profit) to operate more justly in consortia science and ethics, as well as to access and responsibly use health data for public benefit.

What Role for Law, Human Rights, and Bioethics in an Age of Big Data, Consortia Science, and Consortia Ethics? The Importance of Trustworthiness

PubMed Central

Dove, Edward S.; Özdemir, Vural

2015-01-01

The global bioeconomy is generating new paradigm-shifting practices of knowledge co-production, such as collective innovation; large-scale, data-driven global consortia science (Big Science); and consortia ethics (Big Ethics). These bioeconomic and sociotechnical practices can be forces for progressive social change, but they can also raise predicaments at the interface of law, human rights, and bioethics. In this article, we examine one such double-edged practice: the growing, multivariate exploitation of Big Data in the health sector, particularly by the private sector. Commercial exploitation of health data for knowledge-based products is a key aspect of the bioeconomy and is also a topic of concern among publics around the world. It is exacerbated in the current age of globally interconnected consortia science and consortia ethics, which is characterized by accumulating epistemic proximity, diminished academic independence, “extreme centrism”, and conflicted/competing interests among innovation actors. Extreme centrism is of particular importance as a new ideology emerging from consortia science and consortia ethics; this relates to invariably taking a middle-of-the-road populist stance, even in the event of human rights breaches, so as to sustain the populist support needed for consortia building and collective innovation. What role do law, human rights, and bioethics—separate and together—have to play in addressing these predicaments and opportunities in early 21st century science and society? One answer we propose is an intertwined ethico-legal normative construct, namely trustworthiness. By considering trustworthiness as a central pillar at the intersection of law, human rights, and bioethics, we enable others to trust us, which in turns allows different actors (both nonprofit and for-profit) to operate more justly in consortia science and ethics, as well as to access and responsibly use health data for public benefit. PMID:26345196

A Research Agenda and Vision for Data Science

NASA Astrophysics Data System (ADS)

Mattmann, C. A.

2014-12-01

Big Data has emerged as a first-class citizen in the research community spanning disciplines in the domain sciences - Astronomy is pushing velocity with new ground-based instruments such as the Square Kilometre Array (SKA) and its unprecedented data rates (700 TB/sec!); Earth-science is pushing the boundaries of volume with increasing experiments in the international Intergovernmental Panel on Climate Change (IPCC) and climate modeling and remote sensing communities increasing the size of the total archives into the Exabytes scale; airborne missions from NASA such as the JPL Airborne Snow Observatory (ASO) is increasing both its velocity and decreasing the overall turnaround time required to receive products and to make them available to water managers and decision makers. Proteomics and the computational biology community are sequencing genomes and providing near real time answers to clinicians, researchers, and ultimately to patients, helping to process and understand and create diagnoses. Data complexity is on the rise, and the norm is no longer 100s of metadata attributes, but thousands to hundreds of thousands, including complex interrelationships between data and metadata and knowledge. I published a vision for data science in Nature 2013 that encapsulates four thrust areas and foci that I believe the computer science, Big Data, and data science communities need to attack over the next decade to make fundamental progress in the data volume, velocity and complexity challenges arising from the domain sciences such as those described above. These areas include: (1) rapid and unobtrusive algorithm integration; (2) intelligent and automatic data movement; (3) automated and rapid extraction text, metadata and language from heterogeneous file formats; and (4) participation and people power via open source communities. In this talk I will revisit these four areas and describe current progress; future work and challenges ahead as we move forward in this exciting age

Sense Things in the Big Deep Water Bring the Big Deep Water to Computers so People can understand the Deep Water all the Time without getting wet

NASA Astrophysics Data System (ADS)

Pelz, M.; Heesemann, M.; Scherwath, M.; Owens, D.; Hoeberechts, M.; Moran, K.

2015-12-01

Senses help us learn stuff about the world. We put sense things in, over, and under the water to help people understand water, ice, rocks, life and changes over time out there in the big water. Sense things are like our eyes and ears. We can use them to look up and down, right and left all of the time. We can also use them on top of or near the water to see wind and waves. As the water gets deep, we can use our sense things to see many a layer of different water that make up the big water. On the big water we watch ice grow and then go away again. We think our sense things will help us know if this is different from normal, because it could be bad for people soon if it is not normal. Our sense things let us hear big water animals talking low (but sometimes high). We can also see animals that live at the bottom of the big water and we take lots of pictures of them. Lots of the animals we see are soft and small or hard and small, but sometimes the really big ones are seen too. We also use our sense things on the bottom and sometimes feel the ground shaking. Sometimes, we get little pockets of bad smelling air going up, too. In other areas of the bottom, we feel hot hot water coming out of the rock making new rocks and we watch some animals even make houses and food out of the hot hot water that turns to rock as it cools. To take care of the sense things we use and control water cars and smaller water cars that can dive deep in the water away from the bigger water car. We like to put new things in the water and take things out of the water that need to be fixed at least once a year. Sense things are very cool because you can use the sense things with your computer too. We share everything for free on our computers, which your computer talks to and gets pictures and sounds for you. Sharing the facts from the sense things is the best part about having the sense things because we can get many new ideas about understanding the big water from anyone with a computer!

Big Sib Students' Perceptions of the Educational Environment at the School of Medical Sciences, Universiti Sains Malaysia, using Dundee Ready Educational Environment Measure (DREEM) Inventory.

PubMed

Arzuman, Hafiza; Yusoff, Muhamad Saiful Bahri; Chit, Som Phong

2010-07-01

A cross-sectional descriptive study was conducted among Big Sib students to explore their perceptions of the educational environment at the School of Medical Sciences, Universiti Sains Malaysia (USM) and its weak areas using the Dundee Ready Educational Environment Measure (DREEM) inventory. The DREEM inventory is a validated global instrument for measuring educational environments in undergraduate medical and health professional education. The English version of the DREEM inventory was administered to all Year 2 Big Sib students (n = 67) at a regular Big Sib session. The purpose of the study as well as confidentiality and ethical issues were explained to the students before the questionnaire was administered. The response rate was 62.7% (42 out of 67 students). The overall DREEM score was 117.9/200 (SD 14.6). The DREEM indicated that the Big Sib students' perception of educational environment of the medical school was more positive than negative. Nevertheless, the study also revealed some problem areas within the educational environment. This pilot study revealed that Big Sib students perceived a positive learning environment at the School of Medical Sciences, USM. It also identified some low-scored areas that require further exploration to pinpoint the exact problems. The relatively small study population selected from a particular group of students was the major limitation of the study. This small sample size also means that the study findings cannot be generalised.

Before the Big Bang? A Novel Resolution of a Profound Cosmological Puzzle

ScienceCinema

Penrose, Roger

2018-01-24

The second law of thermodynamics says, in effect, that things get more random as time progresses. Thus, we can deduce that the beginning of the universe - the Big Bang - must have been an extraordinarily precisely organized state. What was the nature of this state? How can such a special state have come about? In Penrose's talk, a novel explanation is suggested.

Everyday science & science every day: Science-related talk & activities across settings

NASA Astrophysics Data System (ADS)

Zimmerman, Heather

To understand the development of science-related thinking, acting, and learning in middle childhood, I studied youth in schools, homes, and other neighborhood settings over a three-year period. The research goal was to analyze how multiple everyday experiences influence children's participation in science-related practices and their thinking about science and scientists. Ethnographic and interaction analysis methodologies were to study the cognition and social interactions of the children as they participated in activities with peers, family, and teachers (n=128). Interviews and participant self-documentation protocols elucidated the participants' understandings of science. An Everyday Expertise (Bell et al., 2006) theoretical framework was employed to study the development of science understandings on three analytical planes: individual learner, social groups, and societal/community resources. Findings came from a cross-case analysis of urban science learners and from two within-case analyses of girls' science-related practices as they transitioned from elementary to middle school. Results included: (1) children participated actively in science across settings---including in their homes as well as in schools, (2) children's interests in science were not always aligned to the school science content, pedagogy, or school structures for participation, yet children found ways to engage with science despite these differences through crafting multiple pathways into science, (3) urban parents were active supporters of STEM-related learning environments through brokering access to social and material resources, (4) the youth often found science in their daily activities that formal education did not make use of, and (5) children's involvement with science-related practices can be developed into design principles to reach youth in culturally relevant ways.

Big Questions: Missing Antimatter

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

Lincoln, Don

2013-08-27

Einstein's equation E = mc2 is often said to mean that energy can be converted into matter. More accurately, energy can be converted to matter and antimatter. During the first moments of the Big Bang, the universe was smaller, hotter and energy was everywhere. As the universe expanded and cooled, the energy converted into matter and antimatter. According to our best understanding, these two substances should have been created in equal quantities. However when we look out into the cosmos we see only matter and no antimatter. The absence of antimatter is one of the Big Mysteries of modern physics.more » In this video, Fermilab's Dr. Don Lincoln explains the problem, although doesn't answer it. The answer, as in all Big Mysteries, is still unknown and one of the leading research topics of contemporary science.« less

LLNL's Big Science Capabilities Help Spur Over $796 Billion in U.S. Economic Activity Sequencing the Human Genome

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

Stewart, Jeffrey S.

LLNL’s successful history of taking on big science projects spans beyond national security and has helped create billions of dollars per year in new economic activity. One example is LLNL’s role in helping sequence the human genome. Over $796 billion in new economic activity in over half a dozen fields has been documented since LLNL successfully completed this Grand Challenge.

Big Biomedical data as the key resource for discovery science

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

Toga, Arthur W.; Foster, Ian; Kesselman, Carl

Modern biomedical data collection is generating exponentially more data in a multitude of formats. This flood of complex data poses significant opportunities to discover and understand the critical interplay among such diverse domains as genomics, proteomics, metabolomics, and phenomics, including imaging, biometrics, and clinical data. The Big Data for Discovery Science Center is taking an “-ome to home” approach to discover linkages between these disparate data sources by mining existing databases of proteomic and genomic data, brain images, and clinical assessments. In support of this work, the authors developed new technological capabilities that make it easy for researchers to manage,more » aggregate, manipulate, integrate, and model large amounts of distributed data. Guided by biological domain expertise, the Center’s computational resources and software will reveal relationships and patterns, aiding researchers in identifying biomarkers for the most confounding conditions and diseases, such as Parkinson’s and Alzheimer’s.« less

What We Talk About When We Talk About Light.

PubMed

Forbes, Malcolm D E

2015-10-28

UNESCO (the United Nations Educational, Scientific, and Cultural Organization) has declared 2015 the "International Year of Light and Light-Based Technologies". In celebration of this proclamation, this Outlook provides a general history of light and its applications, from the earliest moments of the Big Bang through its present impact on all forms of life on the planet. Special emphasis is placed on fundamental advances in the generation and use of artificial light, as well as the harvesting and use of light from the Sun and other natural sources. During the past century, the role of light in the fields of physics, chemistry, and biology has expanded to include emerging fields such as environmental engineering, agriculture, materials science, and biomedicine. In this regard, future research challenges and new potential applications in these areas, in the context of "the central science", are presented and discussed.

Talking Climate Science in a Changing Media Landscape

NASA Astrophysics Data System (ADS)

Cullen, H. M.

2014-12-01

Founded in 2008 by leading scientists and communications experts at Princeton, Yale and Stanford, Climate Central brings together award-winning journalists and internationally recognized scientists to report the science and impacts of climate change through its research and journalism programs. Climate Central works to tackle the misperception that climate change is a distant thing - affecting other people and other places - by demonstrating the local and personal impacts of global warming. This talk will focus on describing three important Climate Central initiatives. First, our Climate Matters program delivers localized climate information at the regional and local level to weathercasters around the U.S., providing ready-to-use, broadcast quality graphics and analyses that put climate change in a local context. After three years, the program has grown from a pilot with just one TV meteorologist in Columbia, South Carolina to a network of more than 150 weathercasters across the country. Climate Central was also closely involved in the development and production of Years of Living Dangerously - a 9-part global warming documentary that premiered in April 2014. Finally, the World Weather Attribution project is a new initiative that aims to identify the human fingerprint in certain types of extreme weather events, including sea level rise and its contribution to storm surges, extreme heat events, heavy rainfall events/flooding, and drought. Our goal is to objectively and transparently assess certain extreme events and equip journalists and scientists with the tools to provide the larger global warming context in real-time while there is still media interest.

Talk aloud problem solving: Exploration of acquisition and frequency building in science text

NASA Astrophysics Data System (ADS)

Dembek, Ginny

Discovering new ways to help students attain higher levels of scientific knowledge and to think critically is a national goal (Educate to Innovate campaign). Despite the best intentions, many students struggle to achieve a basic level of science knowledge (NAEP, 2011). The present study examined Talk Aloud Pair Problem Solving and frequency building with five students who were diagnosed with a disability and receive specialized reading instruction in a special education setting. Acquisition was obtained through scripted lessons and frequency building or practice strengthened the student's verbal repertoire making the problem solving process a durable behavior. Overall, students all demonstrated improvements in problem solving performance when compared to baseline. Students became more significantly accurate in performance and maintenance in learning was demonstrated. Generalization probes indicated improvement in student performance. Implications for practice and future research are discussed.

The Whole Shebang: How Science Produced the Big Bang Model.

ERIC Educational Resources Information Center

Ferris, Timothy

2002-01-01

Offers an account of the accumulation of evidence that has led scientists to have confidence in the big bang theory of the creation of the universe. Discusses the early work of Ptolemy, Copernicus, Kepler, Galileo, and Newton, noting the rise of astrophysics, and highlighting the birth of the big bang model (the cosmic microwave background theory…

Exploiting big data for critical care research.

PubMed

Docherty, Annemarie B; Lone, Nazir I

2015-10-01

Over recent years the digitalization, collection and storage of vast quantities of data, in combination with advances in data science, has opened up a new era of big data. In this review, we define big data, identify examples of critical care research using big data, discuss the limitations and ethical concerns of using these large datasets and finally consider scope for future research. Big data refers to datasets whose size, complexity and dynamic nature are beyond the scope of traditional data collection and analysis methods. The potential benefits to critical care are significant, with faster progress in improving health and better value for money. Although not replacing clinical trials, big data can improve their design and advance the field of precision medicine. However, there are limitations to analysing big data using observational methods. In addition, there are ethical concerns regarding maintaining confidentiality of patients who contribute to these datasets. Big data have the potential to improve medical care and reduce costs, both by individualizing medicine, and bringing together multiple sources of data about individual patients. As big data become increasingly mainstream, it will be important to maintain public confidence by safeguarding data security, governance and confidentiality.

Learning science through talking science in elementary classroom

NASA Astrophysics Data System (ADS)

Tank, Kristina Maruyama; Coffino, Kara

2014-03-01

Elementary students in grade two make sense of science ideas and knowledge through their contextual experiences. Mattis Lundin and Britt Jakobson find in their research that early grade students have sophisticated understandings of human anatomy and physiology. In order to understand what students' know about human body and various systems, both drawings and spoken responses provide rich evidence of their understanding of the connections between science drawings and verbal explanations. In this forum contribution, we present several theoretical connections between everyday language and science communication and argue that building communication skills in science are essential. We also discuss how young participants should be valued and supported in research. Finally we discuss the need for multimodal research methods when the research participants are young.

Towards efficient data exchange and sharing for big-data driven materials science: metadata and data formats

NASA Astrophysics Data System (ADS)

Ghiringhelli, Luca M.; Carbogno, Christian; Levchenko, Sergey; Mohamed, Fawzi; Huhs, Georg; Lüders, Martin; Oliveira, Micael; Scheffler, Matthias

2017-11-01

With big-data driven materials research, the new paradigm of materials science, sharing and wide accessibility of data are becoming crucial aspects. Obviously, a prerequisite for data exchange and big-data analytics is standardization, which means using consistent and unique conventions for, e.g., units, zero base lines, and file formats. There are two main strategies to achieve this goal. One accepts the heterogeneous nature of the community, which comprises scientists from physics, chemistry, bio-physics, and materials science, by complying with the diverse ecosystem of computer codes and thus develops "converters" for the input and output files of all important codes. These converters then translate the data of each code into a standardized, code-independent format. The other strategy is to provide standardized open libraries that code developers can adopt for shaping their inputs, outputs, and restart files, directly into the same code-independent format. In this perspective paper, we present both strategies and argue that they can and should be regarded as complementary, if not even synergetic. The represented appropriate format and conventions were agreed upon by two teams, the Electronic Structure Library (ESL) of the European Center for Atomic and Molecular Computations (CECAM) and the NOvel MAterials Discovery (NOMAD) Laboratory, a European Centre of Excellence (CoE). A key element of this work is the definition of hierarchical metadata describing state-of-the-art electronic-structure calculations.

Biosecurity in the age of Big Data: a conversation with the FBI

PubMed Central

Kozminski, Keith G.

2015-01-01

New scientific frontiers and emerging technologies within the life sciences pose many global challenges to society. Big Data is a premier example, especially with respect to individual, national, and international security. Here a Special Agent of the Federal Bureau of Investigation discusses the security implications of Big Data and the need for security in the life sciences. PMID:26543195

The big data-big model (BDBM) challenges in ecological research

NASA Astrophysics Data System (ADS)

Luo, Y.

2015-12-01

The field of ecology has become a big-data science in the past decades due to development of new sensors used in numerous studies in the ecological community. Many sensor networks have been established to collect data. For example, satellites, such as Terra and OCO-2 among others, have collected data relevant on global carbon cycle. Thousands of field manipulative experiments have been conducted to examine feedback of terrestrial carbon cycle to global changes. Networks of observations, such as FLUXNET, have measured land processes. In particular, the implementation of the National Ecological Observatory Network (NEON), which is designed to network different kinds of sensors at many locations over the nation, will generate large volumes of ecological data every day. The raw data from sensors from those networks offer an unprecedented opportunity for accelerating advances in our knowledge of ecological processes, educating teachers and students, supporting decision-making, testing ecological theory, and forecasting changes in ecosystem services. Currently, ecologists do not have the infrastructure in place to synthesize massive yet heterogeneous data into resources for decision support. It is urgent to develop an ecological forecasting system that can make the best use of multiple sources of data to assess long-term biosphere change and anticipate future states of ecosystem services at regional and continental scales. Forecasting relies on big models that describe major processes that underlie complex system dynamics. Ecological system models, despite great simplification of the real systems, are still complex in order to address real-world problems. For example, Community Land Model (CLM) incorporates thousands of processes related to energy balance, hydrology, and biogeochemistry. Integration of massive data from multiple big data sources with complex models has to tackle Big Data-Big Model (BDBM) challenges. Those challenges include interoperability of multiple

Big Data in Psychology: Introduction to Special Issue

PubMed Central

Harlow, Lisa L.; Oswald, Frederick L.

2016-01-01

The introduction to this special issue on psychological research involving big data summarizes the highlights of 10 articles that address a number of important and inspiring perspectives, issues, and applications. Four common themes that emerge in the articles with respect to psychological research conducted in the area of big data are mentioned, including: 1. The benefits of collaboration across disciplines, such as those in the social sciences, applied statistics, and computer science. Doing so assists in grounding big data research in sound theory and practice, as well as in affording effective data retrieval and analysis. 2. Availability of large datasets on Facebook, Twitter, and other social media sites that provide a psychological window into the attitudes and behaviors of a broad spectrum of the population. 3. Identifying, addressing, and being sensitive to ethical considerations when analyzing large datasets gained from public or private sources. 4. The unavoidable necessity of validating predictive models in big data by applying a model developed on one dataset to a separate set of data or hold-out sample. Translational abstracts that summarize the articles in very clear and understandable terms are included in Appendix A, and a glossary of terms relevant to big data research discussed in the articles is presented in Appendix B. PMID:27918177

Primary Science Interview: Science Sparks

ERIC Educational Resources Information Center

Bianchi, Lynne

2016-01-01

In this "Primary Science" interview, Lynne Bianchi talks with Emma Vanstone about "Science Sparks," which is a website full of creative, fun, and exciting science activity ideas for children of primary-school age. "Science Sparks" started with the aim of inspiring more parents to do science at home with their…

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

PubMed

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

2014-01-01

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

Big Data: You Are Adding to . . . and Using It

ERIC Educational Resources Information Center

Makela, Carole J.

2016-01-01

"Big data" prompts a whole lexicon of terms--data flow; analytics; data mining; data science; smart you name it (cars, houses, cities, wearables, etc.); algorithms; learning analytics; predictive analytics; data aggregation; data dashboards; digital tracks; and big data brokers. New terms are being coined frequently. Are we paying…

Let's Talk about Talking: Accountable Talk and Participatory Learning

ERIC Educational Resources Information Center

Huss, John A.

2007-01-01

Middle-grade students like to talk. This natural "gift of gab" may at times be suppressed by teachers who prefer to impart knowledge rather than allow students to participate in its development. Intelligence is a social practice. Students become adept at socializing their intelligence if they are encouraged to talk in meaningful and constructive…

Considerations on Geospatial Big Data

NASA Astrophysics Data System (ADS)

LIU, Zhen; GUO, Huadong; WANG, Changlin

2016-11-01

Geospatial data, as a significant portion of big data, has recently gained the full attention of researchers. However, few researchers focus on the evolution of geospatial data and its scientific research methodologies. When entering into the big data era, fully understanding the changing research paradigm associated with geospatial data will definitely benefit future research on big data. In this paper, we look deep into these issues by examining the components and features of geospatial big data, reviewing relevant scientific research methodologies, and examining the evolving pattern of geospatial data in the scope of the four ‘science paradigms’. This paper proposes that geospatial big data has significantly shifted the scientific research methodology from ‘hypothesis to data’ to ‘data to questions’ and it is important to explore the generality of growing geospatial data ‘from bottom to top’. Particularly, four research areas that mostly reflect data-driven geospatial research are proposed: spatial correlation, spatial analytics, spatial visualization, and scientific knowledge discovery. It is also pointed out that privacy and quality issues of geospatial data may require more attention in the future. Also, some challenges and thoughts are raised for future discussion.

F*** Yeah Fluid Dynamics: On science outreach and appealing to broad audiences

NASA Astrophysics Data System (ADS)

Sharp, Nicole

2015-11-01

Sharing scientific research with general audiences is important for scientists both in terms of educating the public and in pursuing funding opportunities. But it's not always apparent how to make a big splash. Over the past five years, fluid dynamics outreach blog FYFD has published more than 1300 articles and gained an audience of over 215,000 readers. The site appeals to a wide spectrum of readers in both age and field of study. This talk will utilize five years' worth of site content and reader feedback to examine what makes science appealing to general audiences and suggest methods researchers can use to shape their work's broader impact.

Database Resources of the BIG Data Center in 2018.

PubMed

2018-01-04

The BIG Data Center at Beijing Institute of Genomics (BIG) of the Chinese Academy of Sciences provides freely open access to a suite of database resources in support of worldwide research activities in both academia and industry. With the vast amounts of omics data generated at ever-greater scales and rates, the BIG Data Center is continually expanding, updating and enriching its core database resources through big-data integration and value-added curation, including BioCode (a repository archiving bioinformatics tool codes), BioProject (a biological project library), BioSample (a biological sample library), Genome Sequence Archive (GSA, a data repository for archiving raw sequence reads), Genome Warehouse (GWH, a centralized resource housing genome-scale data), Genome Variation Map (GVM, a public repository of genome variations), Gene Expression Nebulas (GEN, a database of gene expression profiles based on RNA-Seq data), Methylation Bank (MethBank, an integrated databank of DNA methylomes), and Science Wikis (a series of biological knowledge wikis for community annotations). In addition, three featured web services are provided, viz., BIG Search (search as a service; a scalable inter-domain text search engine), BIG SSO (single sign-on as a service; a user access control system to gain access to multiple independent systems with a single ID and password) and Gsub (submission as a service; a unified submission service for all relevant resources). All of these resources are publicly accessible through the home page of the BIG Data Center at http://bigd.big.ac.cn. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Database Resources of the BIG Data Center in 2018

PubMed Central

Xu, Xingjian; Hao, Lili; Zhu, Junwei; Tang, Bixia; Zhou, Qing; Song, Fuhai; Chen, Tingting; Zhang, Sisi; Dong, Lili; Lan, Li; Wang, Yanqing; Sang, Jian; Hao, Lili; Liang, Fang; Cao, Jiabao; Liu, Fang; Liu, Lin; Wang, Fan; Ma, Yingke; Xu, Xingjian; Zhang, Lijuan; Chen, Meili; Tian, Dongmei; Li, Cuiping; Dong, Lili; Du, Zhenglin; Yuan, Na; Zeng, Jingyao; Zhang, Zhewen; Wang, Jinyue; Shi, Shuo; Zhang, Yadong; Pan, Mengyu; Tang, Bixia; Zou, Dong; Song, Shuhui; Sang, Jian; Xia, Lin; Wang, Zhennan; Li, Man; Cao, Jiabao; Niu, Guangyi; Zhang, Yang; Sheng, Xin; Lu, Mingming; Wang, Qi; Xiao, Jingfa; Zou, Dong; Wang, Fan; Hao, Lili; Liang, Fang; Li, Mengwei; Sun, Shixiang; Zou, Dong; Li, Rujiao; Yu, Chunlei; Wang, Guangyu; Sang, Jian; Liu, Lin; Li, Mengwei; Li, Man; Niu, Guangyi; Cao, Jiabao; Sun, Shixiang; Xia, Lin; Yin, Hongyan; Zou, Dong; Xu, Xingjian; Ma, Lina; Chen, Huanxin; Sun, Yubin; Yu, Lei; Zhai, Shuang; Sun, Mingyuan; Zhang, Zhang; Zhao, Wenming; Xiao, Jingfa; Bao, Yiming; Song, Shuhui; Hao, Lili; Li, Rujiao; Ma, Lina; Sang, Jian; Wang, Yanqing; Tang, Bixia; Zou, Dong; Wang, Fan

2018-01-01

Abstract The BIG Data Center at Beijing Institute of Genomics (BIG) of the Chinese Academy of Sciences provides freely open access to a suite of database resources in support of worldwide research activities in both academia and industry. With the vast amounts of omics data generated at ever-greater scales and rates, the BIG Data Center is continually expanding, updating and enriching its core database resources through big-data integration and value-added curation, including BioCode (a repository archiving bioinformatics tool codes), BioProject (a biological project library), BioSample (a biological sample library), Genome Sequence Archive (GSA, a data repository for archiving raw sequence reads), Genome Warehouse (GWH, a centralized resource housing genome-scale data), Genome Variation Map (GVM, a public repository of genome variations), Gene Expression Nebulas (GEN, a database of gene expression profiles based on RNA-Seq data), Methylation Bank (MethBank, an integrated databank of DNA methylomes), and Science Wikis (a series of biological knowledge wikis for community annotations). In addition, three featured web services are provided, viz., BIG Search (search as a service; a scalable inter-domain text search engine), BIG SSO (single sign-on as a service; a user access control system to gain access to multiple independent systems with a single ID and password) and Gsub (submission as a service; a unified submission service for all relevant resources). All of these resources are publicly accessible through the home page of the BIG Data Center at http://bigd.big.ac.cn. PMID:29036542

Talking Black.

ERIC Educational Resources Information Center

Abrahams, Roger D.

This book contains essays which focus on the systems of communication that operate within and between various social segments of Afro-American communities in the United States. The essays are presented under the following headings: (1) "Getting Into It: Black Talk, Black Life and the Academic," (2) "'Talking My Talk': Black Talk Varieties and…

Maniac Talk - Dr. Jack Kaye

NASA Image and Video Library

2014-07-23

Jack Kaye Maniac Lecture, July 23, 2014 Dr. Jack Kaye, Associate Director for Research at NASA Headquarters presented a Maniac Talk entitled, "An Unlikely but Rewarding Journey--From Quantum Chemistry to Earth Science Research Program Leadership." Jack took stock of his 30+ years at NASA, noting the people, opportunities, lessons learned, and choices that helped him get to where he is today and accomplish what he have.

The EarthServer project: Exploiting Identity Federations, Science Gateways and Social and Mobile Clients for Big Earth Data Analysis

NASA Astrophysics Data System (ADS)

Barbera, Roberto; Bruno, Riccardo; Calanducci, Antonio; Messina, Antonio; Pappalardo, Marco; Passaro, Gianluca

2013-04-01

The EarthServer project (www.earthserver.eu), funded by the European Commission under its Seventh Framework Program, aims at establishing open access and ad-hoc analytics on extreme-size Earth Science data, based on and extending leading-edge Array Database technology. The core idea is to use database query languages as client/server interface to achieve barrier-free "mix & match" access to multi-source, any-size, multi-dimensional space-time data -- in short: "Big Earth Data Analytics" - based on the open standards of the Open Geospatial Consortium Web Coverage Processing Service (OGC WCPS) and the W3C XQuery. EarthServer combines both, thereby achieving a tight data/metadata integration. Further, the rasdaman Array Database System (www.rasdaman.com) is extended with further space-time coverage data types. On server side, highly effective optimizations - such as parallel and distributed query processing - ensure scalability to Exabyte volumes. Six Lighthouse Applications are being established in EarthServer, each of which poses distinct challenges on Earth Data Analytics: Cryospheric Science, Airborne Science, Atmospheric Science, Geology, Oceanography, and Planetary Science. Altogether, they cover all Earth Science domains; the Planetary Science use case has been added to challenge concepts and standards in non-standard environments. In addition, EarthLook (maintained by Jacobs University) showcases use of OGC standards in 1D through 5D use cases. In this contribution we will report on the first applications integrated in the EarthServer Science Gateway and on the clients for mobile appliances developed to access them. We will also show how federated and social identity services can allow Big Earth Data Providers to expose their data in a distributed environment keeping a strict and fine-grained control on user authentication and authorisation. The degree of fulfilment of the EarthServer implementation with the recommendations made in the recent TERENA Study on

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.

Nano-Bio-Genesis: tracing the rise of nanotechnology and nanobiotechnology as 'big science'

PubMed Central

Kulkarni, Rajan P

2007-01-01

Nanotechnology research has lately been of intense interest because of its perceived potential for many diverse fields of science. Nanotechnology's tools have found application in diverse fields, from biology to device physics. By the 1990s, there was a concerted effort in the United States to develop a national initiative to promote such research. The success of this effort led to a significant influx of resources and interest in nanotechnology and nanobiotechnology and to the establishment of centralized research programs and facilities. Further government initiatives (at federal, state, and local levels) have firmly cemented these disciplines as 'big science,' with efforts increasingly concentrated at select laboratories and centers. In many respects, these trends mirror certain changes in academic science over the past twenty years, with a greater emphasis on applied science and research that can be more directly utilized for commercial applications. We also compare the National Nanotechnology Initiative and its successors to the Human Genome Project, another large-scale, government funded initiative. These precedents made acceptance of shifts in nanotechnology easier for researchers to accept, as they followed trends already established within most fields of science. Finally, these trends are examined in the design of technologies for detection and treatment of cancer, through the Alliance for Nanotechnology in Cancer initiative of the National Cancer Institute. Federal funding of these nanotechnology initiatives has allowed for expansion into diverse fields and the impetus for expanding the scope of research of several fields, especially biomedicine, though the ultimate utility and impact of all these efforts remains to be seen. PMID:17629932

Value Added: History of Physics in a ``Science, Technology, and Society'' General Education Undergraduate Course

NASA Astrophysics Data System (ADS)

Neuenschwander, Dwight

2016-03-01

In thirty years of teaching a capstone ``Science, Technology, and Society'' course to undergraduate students of all majors, I have found that, upon entering STS, to most of them the Manhattan Project seems about as remote as the Civil War; few can describe the difference between nuclear and large non-nuclear weapons. With similar lack of awareness, many students seem to think the Big Bang was dreamed up by science sorcerers. One might suppose that a basic mental picture of weapons that held entire populations hostage should be part of informed citizenship. One might also suppose that questions about origins, as they are put to nature through evidence-based reasoning, should be integral to a culture's identity. Over the years I have found the history of physics to be an effective tool for bringing such subjects to life for STS students. Upon hearing some of the history behind (for example) nuclear weapons and big bang cosmology, these students can better imagine themselves called upon to help in a Manhattan Project, or see themselves sleuthing about in a forensic science like cosmology. In this talk I share sample student responses to our class discussions on nuclear weapons, and on cosmology. The history of physics is too engaging to be appreciated only by physicists.

Epidemiology in the Era of Big Data

PubMed Central

Mooney, Stephen J; Westreich, Daniel J; El-Sayed, Abdulrahman M

2015-01-01

Big Data has increasingly been promoted as a revolutionary development in the future of science, including epidemiology. However, the definition and implications of Big Data for epidemiology remain unclear. We here provide a working definition of Big Data predicated on the so-called ‘3 Vs’: variety, volume, and velocity. From this definition, we argue that Big Data has evolutionary and revolutionary implications for identifying and intervening on the determinants of population health. We suggest that as more sources of diverse data become publicly available, the ability to combine and refine these data to yield valid answers to epidemiologic questions will be invaluable. We conclude that, while epidemiology as practiced today will continue to be practiced in the Big Data future, a component of our field’s future value lies in integrating subject matter knowledge with increased technical savvy. Our training programs and our visions for future public health interventions should reflect this future. PMID:25756221

Maniac Talk - Dr. James Garvin

NASA Image and Video Library

2014-05-28

James Garvin Maniac Lecture, 28 May 2014 Dr. James Garvin, Chief Scientist, NASA Goddard Space Flight Center, presented a Maniac Talk entitled "From Brownian Motion to Mars, by way of hockey on the rocks." Jim shared how his passion for rocks and landscapes drove him to promote new remote sensing approaches for measuring their topologies and led to founding of the Mars Science Laboratory and its Curiosity Rover.

PANGAEA® - Data Publisher for Earth & Environmental Science - Research data enters scholarly communication and big data analysis

NASA Astrophysics Data System (ADS)

Diepenbroek, Michael; Schindler, Uwe; Riedel, Morris; Huber, Robert

2014-05-01

The ISCU World Data Center PANGAEA is an information system for acquisition, processing, long term storage, and publication of geo-referenced data related to earth science fields. Storing more than 350.000 data sets from all fields of geosciences it belongs to the largest archives for observational earth science data. Standard conform interfaces (ISO, OGC, W3C, OAI) enable access from a variety of data and information portals, among them the search engine of PANGAEA itself ((www.pangaea.de) and e.g. GBIF. All data sets in PANGAEA are citable, fully documented, and can be referenced via persistent identifiers (Digital Object Identifier - DOI) - a premise for data publication. Together with other ICSU World Data Centers (www.icsu-wds.org) and the Technical Information Library in Germany (TIB) PANGAEA had a share in the implementation of a DOI based registry for scientific data, which by now is supported by a worldwide consortium of libraries (www.datacite.org). A further milestone was building up strong co-operations with science publishers as Elsevier, Springer, Wiley, AGU, Nature and others. A common web service allows to reference supplementary data in PANGAEA directly from an articles abstract page (e.g. Science Direct). The next step with science publishers is to further integrate the editorial process for the publication of supplementary data with the publication procedures on the journal side. Data centric research efforts such as environmental modelling or big data analysing approaches represent new challenges for PANGAEA. Integrated data warehouse technologies are used for highly efficient retrievals and compilations of time slices or surface data matrixes on any measurement parameters out of the whole data continuum. Further, new and emerging big data approaches are currently investigated within PANGAEA to e.g. evaluate its usability for quality control or data clustering. PANGAEA is operated as a joint long term facility by MARUM at the University Bremen

Opening the Black Box: Understanding the Science Behind Big Data and Predictive Analytics.

PubMed

Hofer, Ira S; Halperin, Eran; Cannesson, Maxime

2018-05-25

Big data, smart data, predictive analytics, and other similar terms are ubiquitous in the lay and scientific literature. However, despite the frequency of usage, these terms are often poorly understood, and evidence of their disruption to clinical care is hard to find. This article aims to address these issues by first defining and elucidating the term big data, exploring the ways in which modern medical data, both inside and outside the electronic medical record, meet the established definitions of big data. We then define the term smart data and discuss the transformations necessary to make big data into smart data. Finally, we examine the ways in which this transition from big to smart data will affect what we do in research, retrospective work, and ultimately patient care.

Big Computing in Astronomy: Perspectives and Challenges

NASA Astrophysics Data System (ADS)

Pankratius, Victor

2014-06-01

Hardware progress in recent years has led to astronomical instruments gathering large volumes of data. In radio astronomy for instance, the current generation of antenna arrays produces data at Tbits per second, and forthcoming instruments will expand these rates much further. As instruments are increasingly becoming software-based, astronomers will get more exposed to computer science. This talk therefore outlines key challenges that arise at the intersection of computer science and astronomy and presents perspectives on how both communities can collaborate to overcome these challenges.Major problems are emerging due to increases in data rates that are much larger than in storage and transmission capacity, as well as humans being cognitively overwhelmed when attempting to opportunistically scan through Big Data. As a consequence, the generation of scientific insight will become more dependent on automation and algorithmic instrument control. Intelligent data reduction will have to be considered across the entire acquisition pipeline. In this context, the presentation will outline the enabling role of machine learning and parallel computing.BioVictor Pankratius is a computer scientist who joined MIT Haystack Observatory following his passion for astronomy. He is currently leading efforts to advance astronomy through cutting-edge computer science and parallel computing. Victor is also involved in projects such as ALMA Phasing to enhance the ALMA Observatory with Very-Long Baseline Interferometry capabilities, the Event Horizon Telescope, as well as in the Radio Array of Portable Interferometric Detectors (RAPID) to create an analysis environment using parallel computing in the cloud. He has an extensive track record of research in parallel multicore systems and software engineering, with contributions to auto-tuning, debugging, and empirical experiments studying programmers. Victor has worked with major industry partners such as Intel, Sun Labs, and Oracle. He holds

New to Teaching: Small Changes Can Produce Big Results!

ERIC Educational Resources Information Center

Shenton, Megan

2017-01-01

In this article, Megan Shenton, a final-year trainee teacher at Nottinghom Trent University, describes using "The Big Question" in her science teaching in a move away from objectives. The Big Question is an innovative pedagogical choice, where instead of implementing a learning objective, a question is posed at the start of the session…

Big biomedical data as the key resource for discovery science.

PubMed

Toga, Arthur W; Foster, Ian; Kesselman, Carl; Madduri, Ravi; Chard, Kyle; Deutsch, Eric W; Price, Nathan D; Glusman, Gustavo; Heavner, Benjamin D; Dinov, Ivo D; Ames, Joseph; Van Horn, John; Kramer, Roger; Hood, Leroy

2015-11-01

Modern biomedical data collection is generating exponentially more data in a multitude of formats. This flood of complex data poses significant opportunities to discover and understand the critical interplay among such diverse domains as genomics, proteomics, metabolomics, and phenomics, including imaging, biometrics, and clinical data. The Big Data for Discovery Science Center is taking an "-ome to home" approach to discover linkages between these disparate data sources by mining existing databases of proteomic and genomic data, brain images, and clinical assessments. In support of this work, the authors developed new technological capabilities that make it easy for researchers to manage, aggregate, manipulate, integrate, and model large amounts of distributed data. Guided by biological domain expertise, the Center's computational resources and software will reveal relationships and patterns, aiding researchers in identifying biomarkers for the most confounding conditions and diseases, such as Parkinson's and Alzheimer's. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The Data Science Landscape

NASA Astrophysics Data System (ADS)

Mentzel, C.

2017-12-01

Modern scientific data continue to increase in volume, variety, and velocity, and though the hype of big data has subsided, its usefulness for scientific discovery has only just begun. Harnessing these data for new insights, more efficient decision making, and other mission critical uses requires a combination of skills and expertise, often labeled data science. Data science can be thought of as a combination of statistics, computation and the domain from which the data relate, and so is a true interdisciplinary pursuit. Though it has reaped large benefits in companies able to afford the high cost of the severely limited talent pool, it suffers from lack of support in mission driven organizations. Not purely in any one historical field, data science is proving difficult to find a home in traditional university academic departments and other research organizations. The landscape of data science efforts, from academia, industry and government, can be characterized as nascent, enthusiastic, uneven, and highly competitive. Part of the challenge in documenting these trends is the lack of agreement about what data science is, and who is a data scientist. Defining these terms too closely and too early runs the risk of cutting off a tremendous amount of productive creativity, but waiting too long leaves many people without a sustainable career, and many organizations without the necessary skills to gain value from their data. This talk will explore the landscape of data science efforts in the US, including how organizations are building and sustaining data science teams.

Making big sense from big data in toxicology by read-across.

PubMed

Hartung, Thomas

2016-01-01

Modern information technologies have made big data available in safety sciences, i.e., extremely large data sets that may be analyzed only computationally to reveal patterns, trends and associations. This happens by (1) compilation of large sets of existing data, e.g., as a result of the European REACH regulation, (2) the use of omics technologies and (3) systematic robotized testing in a high-throughput manner. All three approaches and some other high-content technologies leave us with big data--the challenge is now to make big sense of these data. Read-across, i.e., the local similarity-based intrapolation of properties, is gaining momentum with increasing data availability and consensus on how to process and report it. It is predominantly applied to in vivo test data as a gap-filling approach, but can similarly complement other incomplete datasets. Big data are first of all repositories for finding similar substances and ensure that the available data is fully exploited. High-content and high-throughput approaches similarly require focusing on clusters, in this case formed by underlying mechanisms such as pathways of toxicity. The closely connected properties, i.e., structural and biological similarity, create the confidence needed for predictions of toxic properties. Here, a new web-based tool under development called REACH-across, which aims to support and automate structure-based read-across, is presented among others.

Big Opportunities and Big Concerns of Big Data in Education

ERIC Educational Resources Information Center

Wang, Yinying

2016-01-01

Against the backdrop of the ever-increasing influx of big data, this article examines the opportunities and concerns over big data in education. Specifically, this article first introduces big data, followed by delineating the potential opportunities of using big data in education in two areas: learning analytics and educational policy. Then, the…

A Quantum Universe Before the Big Bang(s)?

NASA Astrophysics Data System (ADS)

Veneziano, Gabriele

2017-08-01

The predictions of general relativity have been verified by now in a variety of different situations, setting strong constraints on any alternative theory of gravity. Nonetheless, there are strong indications that general relativity has to be regarded as an approximation of a more complete theory. Indeed theorists have long been looking for ways to connect general relativity, which describes the cosmos and the infinitely large, to quantum physics, which has been remarkably successful in explaining the infinitely small world of elementary particles. These two worlds, however, come closer and closer to each other as we go back in time all the way up to the big bang. Actually, modern cosmology has changed completely the old big bang paradigm: we now have to talk about (at least) two (big?) bangs. If we know quite something about the one closer to us, at the end of inflation, we are much more ignorant about the one that may have preceded inflation and possibly marked the beginning of time. No one doubts that quantum mechanics plays an essential role in answering these questions: unfortunately a unified theory of gravity and quantum mechanics is still under construction. Finding such a synthesis and confirming it experimentally will no doubt be one of the biggest challenges of this century’s physics.

The End of "Chalk and Talk"

ERIC Educational Resources Information Center

Barlow, Tim

2012-01-01

"Chalk and talk" had been the staple pedagogical approach of my Science teaching practice since entering the profession. I felt that there was a great deal of information that I must impart to my students. My tried and tested way to deliver information to my students had always been simply to stand in front of them and tell it to them... So what…

MODEL2TALK: An Intervention to Promote Productive Classroom Talk

ERIC Educational Resources Information Center

van der Veen, Chiel; van der Wilt, Femke; van Kruistum, Claudia; van Oers, Bert; Michaels, Sarah

2017-01-01

This article describes the MODEL2TALK intervention, which aims to promote young children's oral communicative competence through productive classroom talk. Productive classroom talk provides children in early childhood education with many opportunities to talk and think together. Results from a large-scale study show that productive classroom talk…

Science News and the Science Classroom

ERIC Educational Resources Information Center

McCullough, Laura

2006-01-01

Using "Science News" as a teaching tool promotes writing about science, talking about science, and broadening students' views about what science is. This article describes an ongoing assignment in which students choose one article from "Science News" each week and write a brief summary and explanation of why they picked that article. (Contains 1…

A Proposed Concentration Curriculum Design for Big Data Analytics for Information Systems Students

ERIC Educational Resources Information Center

Molluzzo, John C.; Lawler, James P.

2015-01-01

Big Data is becoming a critical component of the Information Systems curriculum. Educators are enhancing gradually the concentration curriculum for Big Data in schools of computer science and information systems. This paper proposes a creative curriculum design for Big Data Analytics for a program at a major metropolitan university. The design…

Coaching Science Stars. Pep Talk and Play Book for Real-World Problem Solving.

ERIC Educational Resources Information Center

Barkman, Robert C.

This manual adapts the pedagogy used on the playing field, the studio, and the stage to the classroom. This method, called "Pep Talk," encourages teachers to: (1) create a need to know; (2) challenge students to know; (3) show how to know; (4) apply know-how; and (5) know how to inspire cooperation. Pep talk is the method coaches use when they…

Maniac Talk - Dr. William Lau

NASA Image and Video Library

2014-01-24

William Lau Maniac Lecture, 24 January, 2014 Dr. William Lau, Deputy Director for Atmospheres, Earth Science Division at NASA Goddard, presented a Maniac Talk entitled "My Story: A Tale of Three Continents." Bill shared his early childhood under a colonial education system with strong Chinese cultural influence and how world events, cultural and education system of three major continents, Europe, Asia and North America shaped his upbringing career goals and work ethics.

Advancing Climate Change Education: Student Engagement and Teacher Talk in the Classroom

NASA Astrophysics Data System (ADS)

Holthuis, N.; Saltzman, J.; Lotan, R.; Mastrandrea, M. D.; Diffenbaugh, P.; Gray, S.; Kloser, M.

2011-12-01

Stanford's Global Climate Change: Professional Development for K-12 Teachers is a unique collaboration between the Stanford School of Education and School of Earth Sciences to provide teacher professional development on the science of global climate change, pedagogical strategies, and curriculum materials. Scientists and education specialists developed a curriculum for middle and high school science classrooms. It addresses the fundamental issues of climate science, the impacts of climate change on society and on global resources, mitigation and adaptation strategies. This project documents in detail the full circle of curriculum development, teacher professional development, classroom implementation, analysis of student achievement data, and curriculum revision. Ongoing evaluation has provided understanding of the unique conditions and requirements of climate change education. In a sample of 750 secondary students in 25 Bay Area classrooms, we found statistically significant differences between post- (x=11.56, sd=4.75) and pre- (x=8.64, sd=4.58) test scores on standardized items and short open-ended essay questions. Through systematic classroom observations (300 observations in 25 classrooms), we documented student engagement and interactions, and the nature of teachers' talk in the classroom. We found that on average, 73.4% of the students were engaged, 14.4% were interacting with peers, and about 12.1% were disengaged. We also documented teacher talk (165 observations) and found that on the average, teachers delivered factual content and talked about classroom processes and spent less time on scientific argumentation, reasoning and/ or analysis. We documented significant differences in the quality of implementation among the teachers. Our study suggests that in addition to strengthening content knowledge and pedagogical content knowledge, professional development for teachers needs to include classroom management strategies, explicit modeling of collaborative

Talking About Antismoking Campaigns: What Do Smokers Talk About, and How Does Talk Influence Campaign Effectiveness?

PubMed

Brennan, Emily; Durkin, Sarah J; Wakefield, Melanie A; Kashima, Yoshihisa

2016-01-01

Campaign-stimulated conversations have been shown to increase the effectiveness of antismoking campaigns. In order to explore why such effects occur, in the current study we coded the content of naturally occurring conversations. We also examined whether the short-term effects of talking, and of different types of talk, on quitting intentions were mediated through intrapersonal message responses. Using the Natural Exposure(SM) methodology, we exposed 411 smokers to 1 of 6 antismoking advertisements while they were watching television at home. Responses to the advertisement-conversation participation and content, emotional responses, personalized perceived effectiveness, and changes in intentions to quit-were measured within 3 days of exposure. Conversations were coded for appraisal of the advertisement (favorable, neutral, or unfavorable) and the presence of quitting talk and emotion talk. Mediation analyses indicated that the positive effects of talking on intention change were mediated through personalized perceived effectiveness and that the positive effects were driven by conversations that contained a favorable appraisal and/or quitting talk. Conversely, conversations that contained an unfavorable appraisal of the advertisement were negatively associated with campaign effectiveness. These findings highlight the importance of measuring interpersonal communication when evaluating campaigns and the need for further research to identify the message characteristics that predict when smokers talk and when they talk only in desirable ways.

Integrating the Apache Big Data Stack with HPC for Big Data

NASA Astrophysics Data System (ADS)

Fox, G. C.; Qiu, J.; Jha, S.

2014-12-01

There is perhaps a broad consensus as to important issues in practical parallel computing as applied to large scale simulations; this is reflected in supercomputer architectures, algorithms, libraries, languages, compilers and best practice for application development. However, the same is not so true for data intensive computing, even though commercially clouds devote much more resources to data analytics than supercomputers devote to simulations. We look at a sample of over 50 big data applications to identify characteristics of data intensive applications and to deduce needed runtime and architectures. We suggest a big data version of the famous Berkeley dwarfs and NAS parallel benchmarks and use these to identify a few key classes of hardware/software architectures. Our analysis builds on combining HPC and ABDS the Apache big data software stack that is well used in modern cloud computing. Initial results on clouds and HPC systems are encouraging. We propose the development of SPIDAL - Scalable Parallel Interoperable Data Analytics Library -- built on system aand data abstractions suggested by the HPC-ABDS architecture. We discuss how it can be used in several application areas including Polar Science.

The Nature of Elementary Student Science Discourse in the Context of the Science Writing Heuristic Approach

NASA Astrophysics Data System (ADS)

Cavagnetto, Andy; Hand, Brian M.; Norton-Meier, Lori

2010-03-01

This case study aimed to determine the nature of student interactions in small groups in an elementary classroom utilizing the Science Writing Heuristic approach. Fifth grade students were audio-recorded over four units of study while working in small groups to generate knowledge claims after conducting student-directed investigations. Analysis consisted of (1) identifying amount of on/off task talk, (2) categorizing on-task talk as generative (talk associated with generating an argument) or representational (talk associated with representing an argument in a final written form), (3) characterizing the generative components of argument, and (4) determining the functions of language used. Results indicate that students were on task 98% of the time. Students engaged in generative talk an average of 25% of the time and representational talk an average of 71% of the time. Students engaged in components of Toulmin's model of argument, but challenging of each other's ideas was not commonplace. Talk was dominated by the informative function (representing one's ideas) of language as it was found 78.3% of the time and to a lesser extent (11.7%) the heuristic function (inquiring through questions). These functions appear to be intimately tied to the task of generating knowledge claims in small groups. The results suggest that both talking and writing are critical to using science discourse as an embedded strategy to learning science. Further, nature and structure of the task are important pedagogical considerations when moving students toward participation in science discourse.

From ecological records to big data: the invention of global biodiversity.

PubMed

Devictor, Vincent; Bensaude-Vincent, Bernadette

2016-12-01

This paper is a critical assessment of the epistemological impact of the systematic quantification of nature with the accumulation of big datasets on the practice and orientation of ecological science. We examine the contents of big databases and argue that it is not just accumulated information; records are translated into digital data in a process that changes their meanings. In order to better understand what is at stake in the 'datafication' process, we explore the context for the emergence and quantification of biodiversity in the 1980s, along with the concept of the global environment. In tracing the origin and development of the global biodiversity information facility (GBIF) we describe big data biodiversity projects as a techno-political construction dedicated to monitoring a new object: the global diversity. We argue that, biodiversity big data became a powerful driver behind the invention of the concept of the global environment, and a way to embed ecological science in the political agenda.

Maniac Talk - Dr. Lorraine Remer

NASA Image and Video Library

2013-09-13

Lorraine Remer Maniac Lecture, 9 September 2013 NASA climate scientist Dr. Lorraine Remer presented a Maniac Talk entitled "Girls Just Wanna Have Fun: Why I came to NASA and Why I left." Lorraine shared some of the aerosol science she has been involved in at NASA Goddard over the past 21 years, as well as a reflection on her route to becoming a NASA scientist and key factors that influenced her to leave a tenured job.

Commentary: Epidemiology in the era of big data.

PubMed

Mooney, Stephen J; Westreich, Daniel J; El-Sayed, Abdulrahman M

2015-05-01

Big Data has increasingly been promoted as a revolutionary development in the future of science, including epidemiology. However, the definition and implications of Big Data for epidemiology remain unclear. We here provide a working definition of Big Data predicated on the so-called "three V's": variety, volume, and velocity. From this definition, we argue that Big Data has evolutionary and revolutionary implications for identifying and intervening on the determinants of population health. We suggest that as more sources of diverse data become publicly available, the ability to combine and refine these data to yield valid answers to epidemiologic questions will be invaluable. We conclude that while epidemiology as practiced today will continue to be practiced in the Big Data future, a component of our field's future value lies in integrating subject matter knowledge with increased technical savvy. Our training programs and our visions for future public health interventions should reflect this future.

The International Big History Association

ERIC Educational Resources Information Center

Duffy, Michael; Duffy, D'Neil

2013-01-01

IBHA, the International Big History Association, was organized in 2010 and "promotes the unified, interdisciplinary study and teaching of history of the Cosmos, Earth, Life, and Humanity." This is the vision that Montessori embraced long before the discoveries of modern science fleshed out the story of the evolving universe. "Big…

Big data in psychology: Introduction to the special issue.

PubMed

Harlow, Lisa L; Oswald, Frederick L

2016-12-01

The introduction to this special issue on psychological research involving big data summarizes the highlights of 10 articles that address a number of important and inspiring perspectives, issues, and applications. Four common themes that emerge in the articles with respect to psychological research conducted in the area of big data are mentioned, including: (a) The benefits of collaboration across disciplines, such as those in the social sciences, applied statistics, and computer science. Doing so assists in grounding big data research in sound theory and practice, as well as in affording effective data retrieval and analysis. (b) Availability of large data sets on Facebook, Twitter, and other social media sites that provide a psychological window into the attitudes and behaviors of a broad spectrum of the population. (c) Identifying, addressing, and being sensitive to ethical considerations when analyzing large data sets gained from public or private sources. (d) The unavoidable necessity of validating predictive models in big data by applying a model developed on 1 dataset to a separate set of data or hold-out sample. Translational abstracts that summarize the articles in very clear and understandable terms are included in Appendix A, and a glossary of terms relevant to big data research discussed in the articles is presented in Appendix B. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

The Axion Dark Matter Experiment: Big Science with a (relatively) Small Team

NASA Astrophysics Data System (ADS)

Carosi, Gianpaolo

2016-03-01

The idea of the solitary physicist tinkering alone in a lab was my image of how science was done growing up (mostly influenced by popular culture). Of course this is not generally how experimental physics is done now days with examples of experiments at the LHC now involving thousands of scientists. In this talk I will describe my experience in a relatively modest project, the Axion Dark Matter eXperiment (ADMX), which involves only a few dozen scientists at various universities and national labs. I will outline ADMX's humble beginnings at Lawrence Livermore National Laboratory (LLNL), where it began in the mid-1990s, and describe how the collaboration has evolved and grown throughout the years, as we pursue our elusive quarry: the dark-matter axion. Supported by DOE Grants DE-FG02-97ER41029, DE-FG02-96ER40956, DE- AC52-07NA27344, DE-AC03-76SF00098, and the Livermore LDRD program.

Young "Science Ambassadors" Raise the Profile of Science

ERIC Educational Resources Information Center

Ridley, Katie

2014-01-01

Katie Ridley, science coordinator at St. Gregory's Catholic Primary School, Liverpool, UK, states that the inspiration for "science ambassadors" came after embarking on the Primary Science Quality Mark programme at their school. Ridley realized that science was just not recognised as such by the children, they talked about scientific…

Exascale computing and big data

DOE PAGES

Reed, Daniel A.; Dongarra, Jack

2015-06-25

Scientific discovery and engineering innovation requires unifying traditionally separated high-performance computing and big data analytics. The tools and cultures of high-performance computing and big data analytics have diverged, to the detriment of both; unification is essential to address a spectrum of major research domains. The challenges of scale tax our ability to transmit data, compute complicated functions on that data, or store a substantial part of it; new approaches are required to meet these challenges. Finally, the international nature of science demands further development of advanced computer architectures and global standards for processing data, even as international competition complicates themore » openness of the scientific process.« less

Exascale computing and big data

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

Reed, Daniel A.; Dongarra, Jack

Scientific discovery and engineering innovation requires unifying traditionally separated high-performance computing and big data analytics. The tools and cultures of high-performance computing and big data analytics have diverged, to the detriment of both; unification is essential to address a spectrum of major research domains. The challenges of scale tax our ability to transmit data, compute complicated functions on that data, or store a substantial part of it; new approaches are required to meet these challenges. Finally, the international nature of science demands further development of advanced computer architectures and global standards for processing data, even as international competition complicates themore » openness of the scientific process.« less

Science's Big Picture

ERIC Educational Resources Information Center

Sapp, Gregg

2007-01-01

The state of science is a moving target, and its ever-shifting horizons can best be gleaned by the contents of scientific journals. However, the bigger picture of the scientific enterprise, which also encompasses its past, its future, and its overarching philosophies, can often be better represented through the more reflective pace of popular…

Teacher Talk Patterns in Science Lessons: Use in Teacher Education

ERIC Educational Resources Information Center

Viiri, Jouni; Saari, Heikki

2006-01-01

This paper presents an innovative and useful methodology to analyze instructional talk. In teacher education, there is a lack of practical methods that the tutor teacher can use to discuss and reflect on student teachers' lessons. The student teacher cannot remember what actually happened during the lesson, and the feedback and discussions are…

Quantifying athlete self-talk.

PubMed

Hardy, James; Hall, Craig R; Hardy, Lew

2005-09-01

Two studies were conducted. The aims of Study 1 were (a) to generate quantitative data on the content of athletes' self-talk and (b) to examine differences in the use of self-talk in general as well as the functions of self-talk in practice and competition settings. Differences in self-talk between the sexes, sport types and skill levels were also assessed. Athletes (n = 295, mean age = 21.9 years) from a variety of sports and competitive levels completed the Self-Talk Use Questionnaire (STUQ), which was developed specifically for the study. In Study 1, single-factor between-group multivariate analyses of variance revealed significant differences across sex and sport type for the content of self-talk. Mixed-model multivariate analyses of variance revealed overall greater use of self-talk, as well as increased use of the functions of self-talk, in competition compared with practice. Moreover, individual sport athletes reported greater use of self-talk, as well as the functions of self-talk, than their team sport counterparts. In Study 2, recreational volleyball players (n = 164, mean age = 21.5 years) completed a situationally modified STUQ. The results were very similar to those of Study 1. That the content of athlete self-talk was generally positive, covert and abbreviated lends support to the application of Vygotsky's (1986) verbal self-regulation theory to the study of self-talk in sport. Researchers are encouraged to examine the effectiveness of self-talk in future studies.

Neuroblastoma, a Paradigm for Big Data Science in Pediatric Oncology

PubMed Central

Salazar, Brittany M.; Balczewski, Emily A.; Ung, Choong Yong; Zhu, Shizhen

2016-01-01

Pediatric cancers rarely exhibit recurrent mutational events when compared to most adult cancers. This poses a challenge in understanding how cancers initiate, progress, and metastasize in early childhood. Also, due to limited detected driver mutations, it is difficult to benchmark key genes for drug development. In this review, we use neuroblastoma, a pediatric solid tumor of neural crest origin, as a paradigm for exploring “big data” applications in pediatric oncology. Computational strategies derived from big data science–network- and machine learning-based modeling and drug repositioning—hold the promise of shedding new light on the molecular mechanisms driving neuroblastoma pathogenesis and identifying potential therapeutics to combat this devastating disease. These strategies integrate robust data input, from genomic and transcriptomic studies, clinical data, and in vivo and in vitro experimental models specific to neuroblastoma and other types of cancers that closely mimic its biological characteristics. We discuss contexts in which “big data” and computational approaches, especially network-based modeling, may advance neuroblastoma research, describe currently available data and resources, and propose future models of strategic data collection and analyses for neuroblastoma and other related diseases. PMID:28035989

Planning for Sea Level Rise: An AGU Talk in the Form of a Co-Production Experiment Exploring Recent Science

NASA Astrophysics Data System (ADS)

Behar, D. H.; Kopp, R. E.; DeConto, R.; Weaver, C. P.; White, K. D.; May, K.; Bindschadler, R.

2017-12-01

Global sea level rise (SLR) may present the most urgent climate change adaptation challenge facing coastal communities today. The direction is clear, impacts are manifesting now, and the pace of rise is likely to accelerate. As a result, many coastal communities have begun planning their adaptation response and some are quite far along in the process. At the same time, evolving science provides new observations, models, and understanding of land-ocean dynamics that can increase clarity while also in many ways increase uncertainty about the scope, timing, and regional nature of SLR. The planning, design, and construction of water infrastructure has a relatively long timeline (up to 30 years), and thus the evolution of scientific knowledge presents challenges for communities already planning for SLR based on previous information. When does science become actionable for decision-makers? Are there characteristics or thresholds that could cause communities decide to move from one set of scenarios to another, or change approaches altogether? This talk focuses on two important studies different in kind but dominating the conversation about SLR adaptation planning today. First, DeConto and Pollard (2016) have suggested significantly higher upper end projections for Antarctic ice sheet melt, which increase both global and regional SLR above most previously assumed upper limits. Second, probabilistic projections using model output and expert elicitation as presented in Kopp et al (2014) are increasingly appearing in federal reports and planning-related documents. These two papers are pushing the boundaries of the science-to-planning interface, while the application of this work as actionable science is far from settled. This talk will present the outcome of recent conversations among our diverse author team. The authors are engaged in SLR planning related contexts from many angles and perspectives and include the aforementioned Kopp and DeConto as well as representatives of

The Big Bang Theory and the Nature of Science

NASA Astrophysics Data System (ADS)

Arthury, Luiz Henrique Martins; Peduzzi, Luiz O. Q.

2015-12-01

Modern cosmology was constituted, throughout the twentieth century to the present days, as a very productive field of research, resulting in major discoveries that attest to its explanatory power. The Big Bang Theory, the generic and popular name of the standard model of cosmology, is probably the most daring research program of physics and astronomy, trying to recreate the evolution of our observable universe. But contrary to what you might think, its conjectures are of a degree of refinement and corroborative evidence that make it our best explanation for the history of our cosmos. The Big Bang Theory is also an excellent field to discuss issues regarding the scientific activity itself. In this paper we discuss the main elements of this theory with an epistemological look, resulting in a text quite useful to work on educational activities with related goals.

Science Fiction and the Big Questions

NASA Astrophysics Data System (ADS)

O'Keefe, M.

Advocates of space science promote investment in science education and the development of new technologies necessary for space travel. Success in these areas requires an increase of interest and support among the general public. What role can entertainment media play in inspiring the public ­ especially young people ­ to support the development of space science? Such inspiration is badly needed. Science education and funding in the United States are in a state of crisis. This bleak situation exists during a boom in the popularity of science-oriented television shows and science fiction movies. This paper draws on interviews with professionals in science, technology, engineering and mathematics (STEM) fields, as well as students interested in those fields. The interviewees were asked about their lifelong media-viewing habits. Analysis of these interviews, along with examples from popular culture, suggests that science fiction can be a valuable tool for space advocates. Specifically, the aspects of character, story, and special effects can provide viewers with inspiration and a sense of wonder regarding space science and the prospect of long-term human space exploration.

The Promise and Potential Perils of Big Data for Advancing Symptom Management Research in Populations at Risk for Health Disparities.

PubMed

Bakken, Suzanne; Reame, Nancy

2016-01-01

Symptom management research is a core area of nursing science and one of the priorities for the National Institute of Nursing Research, which specifically focuses on understanding the biological and behavioral aspects of symptoms such as pain and fatigue, with the goal of developing new knowledge and new strategies for improving patient health and quality of life. The types and volume of data related to the symptom experience, symptom management strategies, and outcomes are increasingly accessible for research. Traditional data streams are now complemented by consumer-generated (i.e., quantified self) and "omic" data streams. Thus, the data available for symptom science can be considered big data. The purposes of this chapter are to (a) briefly summarize the current drivers for the use of big data in research; (b) describe the promise of big data and associated data science methods for advancing symptom management research; (c) explicate the potential perils of big data and data science from the perspective of the ethical principles of autonomy, beneficence, and justice; and (d) illustrate strategies for balancing the promise and the perils of big data through a case study of a community at high risk for health disparities. Big data and associated data science methods offer the promise of multidimensional data sources and new methods to address significant research gaps in symptom management. If nurse scientists wish to apply big data and data science methods to advance symptom management research and promote health equity, they must carefully consider both the promise and perils.

Icarus Investigations: A Model for Engaging Citizen Scientists to Solve Solar Big Data Challenges

NASA Astrophysics Data System (ADS)

Winter, H. D., III; Loftus, K.

2017-12-01

Solar data is growing at an exponential rate. NASA's Atmospheric Imaging Assembly (AIA) has produced a data volume of over 6 petabytes to date, and that volume is growing. The initial suite of instruments on DKIST are expected to generate approximately 25TB of data per day, with bursts up to 50TB. Making sense of this deluge of solar data is as formidable a task as collecting it. New techniques and new ways of thinking are needed in order to optimize the value of this immense amount of data. While machine learning algorithms are a natural tool to sift through Big Data, those tools need to be carefully constructed and trained in order to provide meaningful results. Trained volunteers are needed to provide a large volume of initial classifications in order to properly train machine learning algorithms. To retain a highly trained pool of volunteers to teach machine learning algorithms, we propose to host an ever-changing array of solar-based citizen science projects under a single collaborative project banner: Icarus Investigations. Icarus Investigations would build and retain a dedicated user base within Zooniverse, the most popular citizen science website with over a million registered users. Volunteers will become increasingly comfortable with solar images and solar features of interest as they work on projects that focus on a wide array of solar phenomena. Under a unified framework, new solar citizen science projects submitted to Icarus Investigations will build on the successes, and learn from the missteps, of their predecessors. In this talk we discuss the importance and benefits of engaging the public in citizen science projects and call for collaborators on future citizen science projects. We will also demonstrate the initial Icarus Investigations project, The Where of the Flare. This demonstration will allow us to highlight the workflow of a Icarus Investigations citizen science project with a concrete example.

Clocks to Computers: A Machine-Based “Big Picture” of the History of Modern Science.

PubMed

van Lunteren, Frans

2016-12-01

Over the last few decades there have been several calls for a “big picture” of the history of science. There is a general need for a concise overview of the rise of modern science, with a clear structure allowing for a rough division into periods. This essay proposes such a scheme, one that is both elementary and comprehensive. It focuses on four machines, which can be seen to have mediated between science and society during successive periods of time: the clock, the balance, the steam engine, and the computer. Following an extended developmental phase, each of these machines came to play a highly visible role in Western societies, both socially and economically. Each of these machines, moreover, was used as a powerful resource for the understanding of both inorganic and organic nature. More specifically, their metaphorical use helped to construe and refine some key concepts that would play a prominent role in such understanding. In each case the key concept would at some point be considered to represent the ultimate building block of reality. Finally, in a refined form, each of these machines would eventually make its entry in scientific research, thereby strengthening the ties between these machines and nature.

BIG: a large-scale data integration tool for renal physiology.

PubMed

Zhao, Yue; Yang, Chin-Rang; Raghuram, Viswanathan; Parulekar, Jaya; Knepper, Mark A

2016-10-01

Due to recent advances in high-throughput techniques, we and others have generated multiple proteomic and transcriptomic databases to describe and quantify gene expression, protein abundance, or cellular signaling on the scale of the whole genome/proteome in kidney cells. The existence of so much data from diverse sources raises the following question: "How can researchers find information efficiently for a given gene product over all of these data sets without searching each data set individually?" This is the type of problem that has motivated the "Big-Data" revolution in Data Science, which has driven progress in fields such as marketing. Here we present an online Big-Data tool called BIG (Biological Information Gatherer) that allows users to submit a single online query to obtain all relevant information from all indexed databases. BIG is accessible at http://big.nhlbi.nih.gov/.

How Big is Earth?

NASA Astrophysics Data System (ADS)

Thurber, Bonnie B.

2015-08-01

How Big is Earth celebrates the Year of Light. Using only the sunlight striking the Earth and a wooden dowel, students meet each other and then measure the circumference of the earth. Eratosthenes did it over 2,000 years ago. In Cosmos, Carl Sagan shared the process by which Eratosthenes measured the angle of the shadow cast at local noon when sunlight strikes a stick positioned perpendicular to the ground. By comparing his measurement to another made a distance away, Eratosthenes was able to calculate the circumference of the earth. How Big is Earth provides an online learning environment where students do science the same way Eratosthenes did. A notable project in which this was done was The Eratosthenes Project, conducted in 2005 as part of the World Year of Physics; in fact, we will be drawing on the teacher's guide developed by that project.How Big Is Earth? expands on the Eratosthenes project by providing an online learning environment provided by the iCollaboratory, www.icollaboratory.org, where teachers and students from Sweden, China, Nepal, Russia, Morocco, and the United States collaborate, share data, and reflect on their learning of science and astronomy. They are sharing their information and discussing their ideas/brainstorming the solutions in a discussion forum. There is an ongoing database of student measurements and another database to collect data on both teacher and student learning from surveys, discussions, and self-reflection done online.We will share our research about the kinds of learning that takes place only in global collaborations.The entrance address for the iCollaboratory is http://www.icollaboratory.org.

Talking to Foucault: Examining Marginalization and Exclusion in Academic Science

ERIC Educational Resources Information Center

McClam, Sherie

2006-01-01

In this article, the author invites everyone to join her as she follows Laurel Richardson's advice to use writing as a method of inquiry. To do so, she engages in a fictional conversation with Michel Foucault--later joined by actor-network theorist Michel Callon--in which she talks through and constructs understanding(s) of and from her research…

Technology Needs for the Next Generation of NASA Science Missions

NASA Technical Reports Server (NTRS)

Anderson, David J.

2013-01-01

In-Space propulsion technologies relevant to Mars presentation is for the 14.03 Emerging Technologies for Mars Exploration panel. The talk will address propulsion technology needs for future Mars science missions, and will address electric propulsion, Earth entry vehicles, light weight propellant tanks, and the Mars ascent vehicle. The second panel presentation is Technology Needs for the Next Generation of NASA Science Missions. This talk is for 14.02 Technology Needs for the Next Generation of NASA Science Missions panel. The talk will summarize the technology needs identified in the NAC's Planetary Science Decadal Survey, and will set the stage for the talks for the 4 other panelist.

Rethinking big data: A review on the data quality and usage issues

NASA Astrophysics Data System (ADS)

Liu, Jianzheng; Li, Jie; Li, Weifeng; Wu, Jiansheng

2016-05-01

The recent explosive publications of big data studies have well documented the rise of big data and its ongoing prevalence. Different types of ;big data; have emerged and have greatly enriched spatial information sciences and related fields in terms of breadth and granularity. Studies that were difficult to conduct in the past time due to data availability can now be carried out. However, big data brings lots of ;big errors; in data quality and data usage, which cannot be used as a substitute for sound research design and solid theories. We indicated and summarized the problems faced by current big data studies with regard to data collection, processing and analysis: inauthentic data collection, information incompleteness and noise of big data, unrepresentativeness, consistency and reliability, and ethical issues. Cases of empirical studies are provided as evidences for each problem. We propose that big data research should closely follow good scientific practice to provide reliable and scientific ;stories;, as well as explore and develop techniques and methods to mitigate or rectify those 'big-errors' brought by big data.

We Are All Talking: A Whole-School Approach to Professional Development for Teachers of English Learners

ERIC Educational Resources Information Center

Shea, Lauren M.; Sandholtz, Judith Haymore; Shanahan, Therese B.

2018-01-01

This study investigates the impact of a professional development program that included two distinct components: strategies for infusing student-talk into grade-level lessons in science and mathematics; and school-level learning communities focused on readings and discussions of student-talk research. This article reports the program's impact on…

DEVELOPING THE TRANSDISCIPLINARY AGING RESEARCH AGENDA: NEW DEVELOPMENTS IN BIG DATA.

PubMed

Callaghan, Christian William

2017-07-19

In light of dramatic advances in big data analytics and the application of these advances in certain scientific fields, new potentialities exist for breakthroughs in aging research. Translating these new potentialities to research outcomes for aging populations, however, remains a challenge, as underlying technologies which have enabled exponential increases in 'big data' have not yet enabled a commensurate era of 'big knowledge,' or similarly exponential increases in biomedical breakthroughs. Debates also reveal differences in the literature, with some arguing big data analytics heralds a new era associated with the 'end of theory' or which makes the scientific method obsolete, where correlation supercedes causation, whereby science can advance without theory and hypotheses testing. On the other hand, others argue theory cannot be subordinate to data, no matter how comprehensive data coverage can ultimately become. Given these two tensions, namely between exponential increases in data absent exponential increases in biomedical research outputs, and between the promise of comprehensive data coverage and data-driven inductive versus theory-driven deductive modes of enquiry, this paper seeks to provide a critical review of certain theory and literature that offers useful perspectives of certain developments in big data analytics and their theoretical implications for aging research. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Marshburn talks to kids in North Carolina

NASA Image and Video Library

2013-02-05

ISS034-E-040247 (5 Feb. 2013) --- In the International Space Station’s Kibo laboratory, NASA astronaut Tom Marshburn, Expedition 34 flight engineer, uses a microphone to talk with students from his native home state. Speaking from the North Carolina Museum of Natural Sciences in Raleigh, the kids asked questions such as what it’s like to eat in space and work in stiff spacesuits.

Lowering the barriers for accessing distributed geospatial big data to advance spatial data science: the PolarHub solution

NASA Astrophysics Data System (ADS)

Li, W.

2017-12-01

Data is the crux of science. The widespread availability of big data today is of particular importance for fostering new forms of geospatial innovation. This paper reports a state-of-the-art solution that addresses a key cyberinfrastructure research problem—providing ready access to big, distributed geospatial data resources on the Web. We first formulate this data-access problem and introduce its indispensable elements, including identifying the cyber-location, space and time coverage, theme, and quality of the dataset. We then propose strategies to tackle each data-access issue and make the data more discoverable and usable for geospatial data users and decision makers. Among these strategies is large-scale web crawling as a key technique to support automatic collection of online geospatial data that are highly distributed, intrinsically heterogeneous, and known to be dynamic. To better understand the content and scientific meanings of the data, methods including space-time filtering, ontology-based thematic classification, and service quality evaluation are incorporated. To serve a broad scientific user community, these techniques are integrated into an operational data crawling system, PolarHub, which is also an important cyberinfrastructure building block to support effective data discovery. A series of experiments were conducted to demonstrate the outstanding performance of the PolarHub system. We expect this work to contribute significantly in building the theoretical and methodological foundation for data-driven geography and the emerging spatial data science.

How Big Are "Martin's Big Words"? Thinking Big about the Future.

ERIC Educational Resources Information Center

Gardner, Traci

"Martin's Big Words: The Life of Dr. Martin Luther King, Jr." tells of King's childhood determination to use "big words" through biographical information and quotations. In this lesson, students in grades 3 to 5 explore information on Dr. King to think about his "big" words, then they write about their own…

The Good, The Bad, and The Ugly: Using Movies to Teach Science

NASA Astrophysics Data System (ADS)

Budzien, Joanne

2013-03-01

Can the plane outrun the explosion? Could the heroes escape injury from the bomb by hiding in the bathtub? Are we in danger of being overrun by 50-foot-tall bugs that have been exposed to radiation? Many people in the general public do want to know the science behind much of what they see in the movies and on television. However, those people are unlikely to take a whole class because ``everyone knows'' that science classes are boring and irrelevant. On the other hand, an evening with an hour or so of video clips interspersed with explanations of the science can be a big hit both to raise general science fluency and recruit students into general education science classes. Film-editing technology has advanced to the point that anyone who has a computer and is willing to invest a couple days in learning to use the software can make a clips-with-PowerPoint DVD that can be shown to a local audience for discussion or used in a science class to show the exact scenes to save time. In this presentation, I'll show an example of my work and talk about how you can make your own DVD.

A community of curious souls: an analysis of commenting behavior on TED talks videos.

PubMed

Tsou, Andrew; Thelwall, Mike; Mongeon, Philippe; Sugimoto, Cassidy R

2014-01-01

The TED (Technology, Entertainment, Design) Talks website hosts video recordings of various experts, celebrities, academics, and others who discuss their topics of expertise. Funded by advertising and members but provided free online, TED Talks have been viewed over a billion times and are a science communication phenomenon. Although the organization has been derided for its populist slant and emphasis on entertainment value, no previous research has assessed audience reactions in order to determine the degree to which presenter characteristics and platform affect the reception of a video. This article addresses this issue via a content analysis of comments left on both the TED website and the YouTube platform (on which TED Talks videos are also posted). It was found that commenters were more likely to discuss the characteristics of a presenter on YouTube, whereas commenters tended to engage with the talk content on the TED website. In addition, people tended to be more emotional when the speaker was a woman (by leaving comments that were either positive or negative). The results can inform future efforts to popularize science amongst the public, as well as to provide insights for those looking to disseminate information via Internet videos.

Big Science, Team Science, and Open Science for Neuroscience.

PubMed

Koch, Christof; Jones, Allan

2016-11-02

The Allen Institute for Brain Science is a non-profit private institution dedicated to basic brain science with an internal organization more commonly found in large physics projects-large teams generating complete, accurate and permanent resources for the mouse and human brain. It can also be viewed as an experiment in the sociology of neuroscience. We here describe some of the singular differences to more academic, PI-focused institutions. Copyright © 2016 Elsevier Inc. All rights reserved.

Beyond Einstein: from the Big Bang to black holes

NASA Astrophysics Data System (ADS)

White, Nicholas E.; Diaz, Alphonso V.

2004-01-01

How did the Universe begin? Does time have a beginning and an end? Does space have edges? Einstein's theory of relativity replied to these ancient questions with three startling predictions: that the Universe is expanding from a Big Bang; that black holes so distort space and time that time stops at their edges; and that a dark energy could be pulling space apart, sending galaxies forever beyond the edge of the visible Universe. Observations confirm these remarkable predictions, the last finding only four years ago. Yet Einstein's legacy is incomplete. His theory raises - but cannot answer - three profound questions: What powered the Big Bang? What happens to space, time and matter at the edge of a black hole? and, What is the mysterious dark energy pulling the Universe apart? The Beyond Einstein program within NASA's office of space science aims to answer these questions, employing a series of missions linked by powerful new technologies and complementary approaches to shared science goals. The program also serves as a potent force with which to enhance science education and science literacy.

BIG: a large-scale data integration tool for renal physiology

PubMed Central

Zhao, Yue; Yang, Chin-Rang; Raghuram, Viswanathan; Parulekar, Jaya

2016-01-01

Due to recent advances in high-throughput techniques, we and others have generated multiple proteomic and transcriptomic databases to describe and quantify gene expression, protein abundance, or cellular signaling on the scale of the whole genome/proteome in kidney cells. The existence of so much data from diverse sources raises the following question: “How can researchers find information efficiently for a given gene product over all of these data sets without searching each data set individually?” This is the type of problem that has motivated the “Big-Data” revolution in Data Science, which has driven progress in fields such as marketing. Here we present an online Big-Data tool called BIG (Biological Information Gatherer) that allows users to submit a single online query to obtain all relevant information from all indexed databases. BIG is accessible at http://big.nhlbi.nih.gov/. PMID:27279488

Adapting bioinformatics curricula for big data

PubMed Central

Greene, Anna C.; Giffin, Kristine A.; Greene, Casey S.

2016-01-01

Modern technologies are capable of generating enormous amounts of data that measure complex biological systems. Computational biologists and bioinformatics scientists are increasingly being asked to use these data to reveal key systems-level properties. We review the extent to which curricula are changing in the era of big data. We identify key competencies that scientists dealing with big data are expected to possess across fields, and we use this information to propose courses to meet these growing needs. While bioinformatics programs have traditionally trained students in data-intensive science, we identify areas of particular biological, computational and statistical emphasis important for this era that can be incorporated into existing curricula. For each area, we propose a course structured around these topics, which can be adapted in whole or in parts into existing curricula. In summary, specific challenges associated with big data provide an important opportunity to update existing curricula, but we do not foresee a wholesale redesign of bioinformatics training programs. PMID:25829469

Computational Science in Armenia (Invited Talk)

NASA Astrophysics Data System (ADS)

Marandjian, H.; Shoukourian, Yu.

This survey is devoted to the development of informatics and computer science in Armenia. The results in theoretical computer science (algebraic models, solutions to systems of general form recursive equations, the methods of coding theory, pattern recognition and image processing), constitute the theoretical basis for developing problem-solving-oriented environments. As examples can be mentioned: a synthesizer of optimized distributed recursive programs, software tools for cluster-oriented implementations of two-dimensional cellular automata, a grid-aware web interface with advanced service trading for linear algebra calculations. In the direction of solving scientific problems that require high-performance computing resources, examples of completed projects include the field of physics (parallel computing of complex quantum systems), astrophysics (Armenian virtual laboratory), biology (molecular dynamics study of human red blood cell membrane), meteorology (implementing and evaluating the Weather Research and Forecast Model for the territory of Armenia). The overview also notes that the Institute for Informatics and Automation Problems of the National Academy of Sciences of Armenia has established a scientific and educational infrastructure, uniting computing clusters of scientific and educational institutions of the country and provides the scientific community with access to local and international computational resources, that is a strong support for computational science in Armenia.

Big Data: Next-Generation Machines for Big Science

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

Hack, James J.; Papka, Michael E.

Addressing the scientific grand challenges identified by the US Department of Energy’s (DOE’s) Office of Science’s programs alone demands a total leadership-class computing capability of 150 to 400 Pflops by the end of this decade. The successors to three of the DOE’s most powerful leadership-class machines are set to arrive in 2017 and 2018—the products of the Collaboration Oak Ridge Argonne Livermore (CORAL) initiative, a national laboratory–industry design/build approach to engineering nextgeneration petascale computers for grand challenge science. These mission-critical machines will enable discoveries in key scientific fields such as energy, biotechnology, nanotechnology, materials science, and high-performance computing, and servemore » as a milestone on the path to deploying exascale computing capabilities.« less

Let's Talk... Analytics

ERIC Educational Resources Information Center

Oblinger, Diana G.

2012-01-01

Talk about analytics seems to be everywhere. Everyone is talking about analytics. Yet even with all the talk, many in higher education have questions about--and objections to--using analytics in colleges and universities. In this article, the author explores the use of analytics in, and all around, higher education. (Contains 1 note.)

The Puzzle of Science; Making Sense of Incomplete Information

NASA Astrophysics Data System (ADS)

Shorey, B. U.

2015-12-01

There are many topics within Earth science including evolution, historical geology, and climate change, which have gained the status of theory becuse they have overwhelming evidence, yet there is still fragmentary information which can frustrate a student from coming to solid conclusions. Using a jigsaw puzzle whose image has been hidden, and the pieces only given out sparingly, students go though the process of getting more information. How does one get more puzzle pieces and what is the interpretive process? Experience with this exercise demonstrates how students can sketch out an incredibly accurate conception of the "big picture", despite not having all the puzzle pieces. The goal of this talk is to give a complete tool kit to perform as a comprehensive lesson plan. Guiding questions and copies of lesson plans and materials are supplied for this exercise.

Why Talk Is Important

ERIC Educational Resources Information Center

Barnes, Douglas

2010-01-01

In this brief retrospective essay, the value of a particular kind of classroom talk is extolled--not the kind of talk that simply feeds back information, but rather talk that has the power to shape knowledge through participant engagement with a range of processes: hypothesising, exploration, debate and synthesis. This kind of talk is the…

A Sea of Talk.

ERIC Educational Resources Information Center

Dwyer, John, Ed.

Arguing that talk has an important place in the English language arts curriculum and across the whole curriculum, this book presents examples of children and teachers talking together, talking about what they are doing "here and now," and talking about what they know and feel about events shaping the world beyond the classroom. Chapter…

Talking, Listening, Learning

ERIC Educational Resources Information Center

Myhill, Debra; Jones, Susan; Hopper, Rosemary

2005-01-01

This book looks at an issue which is at the heart of every classroom, the role that talk plays in children's learning. Drawing on a substantial research base, the book provides useful suggestions to facilitate successful talk between teachers and children to improve learning and raise standards. Through analysing the talk that goes on in primary…

Reviews Book: Extended Project Student Guide Book: My Inventions Book: ASE Guide to Research in Science Education Classroom Video: The Science of Starlight Software: SPARKvue Book: The Geek Manifesto Ebook: A Big Ball of Fire Apps

NASA Astrophysics Data System (ADS)

2014-05-01

WE RECOMMEND Level 3 Extended Project Student Guide A non-specialist, generally useful and nicely put together guide to project work ASE Guide to Research in Science Education Few words wasted in this handy introduction and reference The Science of Starlight Slow but steady DVD covers useful ground SPARKvue Impressive software now available as an app WORTH A LOOK My Inventions and Other Writings Science, engineering, autobiography, visions and psychic phenomena mixed in a strange but revealing concoction The Geek Manifesto: Why Science Matters More enthusiasm than science, but a good motivator and interesting A Big Ball of Fire: Your questions about the Sun answered Free iTunes download made by and for students goes down well APPS Collider visualises LHC experiments ... Science Museum app enhances school trips ... useful information for the Cambridge Science Festival

News Conference: Take a hold of Hands-on Science Meeting: Prize-winning physics-education talks are a highlight of the DPG spring meeting in Jena Event: Abstracts flow in for ICPE-EPEC 2013 Schools: A new Schools Physics Partnership in Oxfordshire Conference: 18th MPTL is forum for multimedia in education Meeting: Pursuing playful science with Science on Stage Forthcoming events

NASA Astrophysics Data System (ADS)

2013-03-01

Conference: Take a hold of Hands-on Science Meeting: Prize-winning physics-education talks are a highlight of the DPG spring meeting in Jena Event: Abstracts flow in for ICPE-EPEC 2013 Schools: A new Schools Physics Partnership in Oxfordshire Conference: 18th MPTL is forum for multimedia in education Meeting: Pursuing playful science with Science on Stage Forthcoming events

The Big Bang, Genesis, and Knocking on Heaven's Door

NASA Astrophysics Data System (ADS)

Gentry, Robert

2012-03-01

Michael Shermer recently upped the ante in the big bang-Genesis controversy by citing Lisa Randall's provocative claim (Science 334, 762 (2011)) that ``it is inconceivable that God could continue to intervene without introducing a material trace of his actions.'' So does Randall's and Shermer's agreement that no such evidence exists disprove God's existence? Not in my view because my 1970s Science, Nature and ARNS publications, and my article in the 1982 AAAS Western Division's Symposium Proceedings, Evolution Confronts Creation, all contain validation of God's existence via discovery of His Fingerprints of Creation and falsification of the big bang and geological evolution. These results came to wide public/scientific attention in my testimony at the 1981 Arkansas creation/evolution trial. There ACLU witness G Brent Dalrymple from the USGS -- and 2005 Medal of Science recipient from President Bush -- admitted I had discovered a tiny mystery (primordial polonium radiohalos) in granite rocks that indicated their almost instant creation. As a follow-up in 1992 and 1995 he sent out SOS letters to the entire AGU membership that the polonium halo evidence for fiat creation still existed and that someone needed to urgently find a naturalistic explanation for them. Is the physics community guilty of a Watergate-type cover-up of this discovery of God's existence and falsification of the big bang? For the answer see www.halos.tv.

The phytotronist and the phenotype: plant physiology, Big Science, and a Cold War biology of the whole plant.

PubMed

Munns, David P D

2015-04-01

This paper describes how, from the early twentieth century, and especially in the early Cold War era, the plant physiologists considered their discipline ideally suited among all the plant sciences to study and explain biological functions and processes, and ranked their discipline among the dominant forms of the biological sciences. At their apex in the late-1960s, the plant physiologists laid claim to having discovered nothing less than the "basic laws of physiology." This paper unwraps that claim, showing that it emerged from the construction of monumental big science laboratories known as phytotrons that gave control over the growing environment. Control meant that plant physiologists claimed to be able to produce a standard phenotype valid for experimental biology. Invoking the standards of the physical sciences, the plant physiologists heralded basic biological science from the phytotronic produced phenotype. In the context of the Cold War era, the ability to pursue basic science represented the highest pinnacle of standing within the scientific community. More broadly, I suggest that by recovering the history of an underappreciated discipline, plant physiology, and by establishing the centrality of the story of the plant sciences in the history of biology can historians understand the massive changes wrought to biology by the conceptual emergence of the molecular understanding of life, the dominance of the discipline of molecular biology, and the rise of biotechnology in the 1980s. Copyright © 2015 Elsevier Ltd. All rights reserved.

Beyond Einstein: From the Big Bang to Black Holes

NASA Astrophysics Data System (ADS)

White, N.

Beyond Einstein is a science-driven program of missions, education and outreach, and technology, to address three questions: What powered the Big Bang? What happens to space, time, and matter at the edge of a Black Hole? What is the mysterious Dark Energy pulling the universe apart? To address the science objectives, Beyond Einstein contains several interlinked elements. The strategic missions Constellation-X and LISA primarily investigate the nature of black holes. Constellation-X is a spectroscopic observatory that uses X-ray emitting atoms as clocks to follow the fate of matter falling into black holes. LISA will be the first space-based gravitational wave observatory uses gravitational waves to measure the dynamic structure of space and time around black holes. Moderate sized probes that are fully competed, peer-reviewed missions (300M-450M) launched every 3-5 years to address the focussed science goals: 1) Determine the nature of the Dark Energy that dominates the universe, 2) Search for the signature of the beginning of the Big Bang in the microwave background and 3) Take a census of Black Holes of all sizes and ages in the universe. The final element is a Technology Program to enable ultimate Vision Missions (after 2015) to directly detect gravitational waves echoing from the beginning of the Big Bang, and to directly image matter near the event horizon of a Black Hole. An associated Education and Public Outreach Program will inspire the next generation of scientists, and support national science standards and benchmarks.

Don't Dumb Me down

ERIC Educational Resources Information Center

Goldacre, Ben

2007-01-01

In this article, the author talks about pseudoscientific quack, or a big science story in a national newspaper and explains why science in the media is so often pointless, simplistic, boring, or just plain wrong. It is the author's hypothesis that in their choice of stories, and the way they cover them, the media create a parody of science, for…

Big Bend National Park

NASA Image and Video Library

2017-12-08

Alternately known as a geologist’s paradise and a geologist’s nightmare, Big Bend National Park in southwestern Texas offers a multitude of rock formations. Sparse vegetation makes finding and observing the rocks easy, but they document a complicated geologic history extending back 500 million years. On May 10, 2002, the Enhanced Thematic Mapper Plus on NASA’s Landsat 7 satellite captured this natural-color image of Big Bend National Park. A black line delineates the park perimeter. The arid landscape appears in muted earth tones, some of the darkest hues associated with volcanic structures, especially the Rosillos and Chisos Mountains. Despite its bone-dry appearance, Big Bend National Park is home to some 1,200 plant species, and hosts more kinds of cacti, birds, and bats than any other U.S. national park. Read more: go.nasa.gov/2bzGaZU Credit: NASA/Landsat7 NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Enhancing Teachers' Awareness About Relations Between Science and Religion. The Debate Between Steady State and Big Bang Theories

NASA Astrophysics Data System (ADS)

Bagdonas, Alexandre; Silva, Cibelle Celestino

2015-11-01

Educators advocate that science education can help the development of more responsible worldviews when students learn not only scientific concepts, but also about science, or "nature of science". Cosmology can help the formation of worldviews because this topic is embedded in socio-cultural and religious issues. Indeed, during the Cold War period, the cosmological controversy between Big Bang and Steady State theory was tied up with political and religious arguments. The present paper discusses a didactic sequence developed for and applied in a pre-service science teacher-training course on history of science. After studying the historical case, pre-service science teachers discussed how to deal with possible conflicts between scientific views and students' personal worldviews related to religion. The course focused on the study of primary and secondary sources about cosmology and religion written by cosmologists such as Georges Lemaître, Fred Hoyle and the Pope Pius XII. We used didactic strategies such as short seminars given by groups of pre-service teachers, videos, computer simulations, role-play, debates and preparation of written essays. Along the course, most pre-service teachers emphasized differences between science and religion and pointed out that they do not feel prepared to conduct classroom discussions about this topic. Discussing the relations between science and religion using the history of cosmology turned into an effective way to teach not only science concepts but also to stimulate reflections about nature of science. This topic may contribute to increasing students' critical stance on controversial issues, without the need to explicitly defend certain positions, or disapprove students' cultural traditions. Moreover, pre-service teachers practiced didactic strategies to deal with this kind of unusual content.

Computational Social Science: Exciting Progress and Future Challenges

NASA Astrophysics Data System (ADS)

Watts, Duncan

The past 15 years have witnessed a remarkable increase in both the scale and scope of social and behavioral data available to researchers, leading some to herald the emergence of a new field: ``computational social science.'' Against these exciting developments stands a stubborn fact: that in spite of many thousands of published papers, there has been surprisingly little progress on the ``big'' questions that motivated the field in the first place--questions concerning systemic risk in financial systems, problem solving in complex organizations, and the dynamics of epidemics or social movements, among others. In this talk I highlight some examples of research that would not have been possible just a handful of years ago and that illustrate the promise of CSS. At the same time, they illustrate its limitations. I then conclude with some thoughts on how CSS can bridge the gap between its current state and its potential.

A Guided Inquiry on Hubble Plots and the Big Bang

ERIC Educational Resources Information Center

Forringer, Ted

2014-01-01

In our science for non-science majors course "21st Century Physics," we investigate modern "Hubble plots" (plots of velocity versus distance for deep space objects) in order to discuss the Big Bang, dark matter, and dark energy. There are two potential challenges that our students face when encountering these topics for the…

A Big Data Task Force Review of Advances in Data Access and Discovery Within the Science Disciplines of the NASA Science Mission Directorate (SMD)

NASA Astrophysics Data System (ADS)

Walker, R. J.; Beebe, R. F.

2017-12-01

One of the basic problems the NASA Science Mission Directorate (SMD) faces when dealing with preservation of scientific data is the variety of the data. This stems from the fact that NASA's involvement in the sciences spans a broad range of disciplines across the Science Mission Directorate: Astrophysics, Earth Sciences, Heliophysics and Planetary Science. As the ability of some missions to produce large data volumes has accelerated, the range of problems associated with providing adequate access to the data has demanded diverse approaches for data access. Although mission types, complexity and duration vary across the disciplines, the data can be characterized by four characteristics: velocity, veracity, volume, and variety. The rate of arrival of the data (velocity) must be addressed at the individual mission level, validation and documentation of the data (veracity), data volume and the wide variety of data products present huge challenges as the science disciplines strive to provide transparent access to their available data. Astrophysics, supports an integrated system of data archives based on frequencies covered (UV, visible, IR, etc.) or subject areas (extrasolar planets, extra galactic, etc.) and is accessed through the Astrophysics Data Center (https://science.nasa.gov/astrophysics/astrophysics-data-centers/). Earth Science supports the Earth Observing System (https://earthdata.nasa.gov/) that manages the earth science satellite data. The discipline supports 12 Distributed Active Archive Centers. Heliophysics provides the Space Physics Data Facility (https://spdf.gsfc.nasa.gov/) that supports the heliophysics community and Solar Data Analysis Center (https://umbra.nascom.nasa.gov/index.html) that allows access to the solar data. The Planetary Data System (https://pds.nasa.gov) is the main archive for planetary science data. It consists of science discipline nodes (Atmospheres, Geosciences, Cartography and Imaging Sciences, Planetary Plasma Interactions

Challenges of Big Data in Educational Assessment

ERIC Educational Resources Information Center

Gibson, David C.; Webb, Mary; Ifenthaler, Dirk

2015-01-01

This paper briefly discusses four measurement challenges of data science or "big data" in educational assessments that are enabled by technology: 1. Dealing with change over time via time-based data. 2. How a digital performance space's relationships interact with learner actions, communications and products. 3. How layers of…

Technical challenges for big data in biomedicine and health: data sources, infrastructure, and analytics.

PubMed

Peek, N; Holmes, J H; Sun, J

2014-08-15

To review technical and methodological challenges for big data research in biomedicine and health. We discuss sources of big datasets, survey infrastructures for big data storage and big data processing, and describe the main challenges that arise when analyzing big data. The life and biomedical sciences are massively contributing to the big data revolution through secondary use of data that were collected during routine care and through new data sources such as social media. Efficient processing of big datasets is typically achieved by distributing computation over a cluster of computers. Data analysts should be aware of pitfalls related to big data such as bias in routine care data and the risk of false-positive findings in high-dimensional datasets. The major challenge for the near future is to transform analytical methods that are used in the biomedical and health domain, to fit the distributed storage and processing model that is required to handle big data, while ensuring confidentiality of the data being analyzed.

A Community of Curious Souls: An Analysis of Commenting Behavior on TED Talks Videos

PubMed Central

Tsou, Andrew; Thelwall, Mike; Mongeon, Philippe; Sugimoto, Cassidy R.

2014-01-01

The TED (Technology, Entertainment, Design) Talks website hosts video recordings of various experts, celebrities, academics, and others who discuss their topics of expertise. Funded by advertising and members but provided free online, TED Talks have been viewed over a billion times and are a science communication phenomenon. Although the organization has been derided for its populist slant and emphasis on entertainment value, no previous research has assessed audience reactions in order to determine the degree to which presenter characteristics and platform affect the reception of a video. This article addresses this issue via a content analysis of comments left on both the TED website and the YouTube platform (on which TED Talks videos are also posted). It was found that commenters were more likely to discuss the characteristics of a presenter on YouTube, whereas commenters tended to engage with the talk content on the TED website. In addition, people tended to be more emotional when the speaker was a woman (by leaving comments that were either positive or negative). The results can inform future efforts to popularize science amongst the public, as well as to provide insights for those looking to disseminate information via Internet videos. PMID:24718634

The National Institutes of Health's Big Data to Knowledge (BD2K) initiative: capitalizing on biomedical big data.

PubMed

Margolis, Ronald; Derr, Leslie; Dunn, Michelle; Huerta, Michael; Larkin, Jennie; Sheehan, Jerry; Guyer, Mark; Green, Eric D

2014-01-01

Biomedical research has and will continue to generate large amounts of data (termed 'big data') in many formats and at all levels. Consequently, there is an increasing need to better understand and mine the data to further knowledge and foster new discovery. The National Institutes of Health (NIH) has initiated a Big Data to Knowledge (BD2K) initiative to maximize the use of biomedical big data. BD2K seeks to better define how to extract value from the data, both for the individual investigator and the overall research community, create the analytic tools needed to enhance utility of the data, provide the next generation of trained personnel, and develop data science concepts and tools that can be made available to all stakeholders. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Creation a Geo Big Data Outreach and Training Collaboratory for Wildfire Community

NASA Astrophysics Data System (ADS)

Altintas, I.; Sale, J.; Block, J.; Cowart, C.; Crawl, D.

2015-12-01

A major challenge for the geoscience community is the training and education of current and next generation big data geoscientists. In wildfire research, there are an increasing number of tools, middleware and techniques to use for data science related to wildfires. The necessary computing infrastructures are often within reach and most of the software tools for big data are freely available. But what has been lacking is a transparent platform and training program to produce data science experts who can use these integrated tools effectively. Scientists well versed to take advantage of big data technologies in geoscience applications is of critical importance to the future of research and knowledge advancement. To address this critical need, we are developing learning modules to teach process-based thinking to capture the value of end-to-end systems of reusable blocks of knowledge and integrate the tools and technologies used in big data analysis in an intuitive manner. WIFIRE is an end-to-end cyberinfrastructure for dynamic data-driven simulation, prediction and visualization of wildfire behavior.To this end, we are openly extending an environment we have built for "big data training" (biobigdata.ucsd.edu) to similar MOOC-based approaches to the wildfire community. We are building an environment that includes training modules for distributed platforms and systems, Big Data concepts, and scalable workflow tools, along with other basics of data science including data management, reproducibility and sharing of results. We also plan to provide teaching modules with analytical and dynamic data-driven wildfire behavior modeling case studies which address the needs not only of standards-based K-12 science education but also the needs of a well-educated and informed citizenry.Another part our outreach mission is to educate our community on all aspects of wildfire research. One of the most successful ways of accomplishing this is through high school and undergraduate

[Sleep talking].

PubMed

Challamel, M J

2001-11-01

Sleep talking is very common in the general population. Its prevalence remains stable from childhood through adulthood. Sleep talking is often associated with other parasomnias: sleep walking, sleep terrors or REM sleep behavior disorders. It may arise from either REM or non REM sleep, when associated with REM sleep it is more comprehensible and often associated with clear sentences and recall of sleep mentation. Sleep talking is a benign entity and does not require any treatment; however an exceptional organic cause or psychopathology should be suspected if the onset is late (after 25 years); if the mental content is too violent or too emotional.

The Higgs and All That: How the Universe Works and Why We Should Care

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

Hinchliffe, Ian

2013-10-31

Berkeley Lab's Ian Hinchliffe discusses "The Higgs and all that. How the universe works and why we should care" in this Oct. 28, 2013 talk, which is part of a Science at the Theater event entitled Eight Big Ideas.

The Higgs and All That: How the Universe Works and Why We Should Care

ScienceCinema

Hinchliffe, Ian

2018-01-16

Berkeley Lab's Ian Hinchliffe discusses "The Higgs and all that. How the universe works and why we should care" in this Oct. 28, 2013 talk, which is part of a Science at the Theater event entitled Eight Big Ideas.

Upgrade of the Cherenkov Detector of the JLab Hall A BigBite Spectrometer

NASA Astrophysics Data System (ADS)

Nycz, Michael

2015-04-01

The BigBite Spectrometer of the Hall A Facility of Jefferson Lab will be used in the upcoming MARATHON experiment at Jefferson Lab to measure the ratio of neutron to proton F2 inelastic structure functions and the ratio of up to down, d/u, quark nucleon distributions at medium and large values of Bjorken x. In preparation for this experiment, the BigBite Cherenkov detector is being modified to increase its overall efficiency for detecting electrons. This large volume counter is based on a dual system of segmented mirrors reflecting Cherenkov radiation to twenty photomultipliers. In this talk, a description of the detector and its past performance will be presented, along with the motivations for improvements and their implementation. An update on the status of the rest of the BigBite detector package, will be also presented. Additionally, current issues related to obtaining C4 F8 O, the commonly used radiator gas, which has been phased out of production by U.S. gas producers, will be discussed. This work is supported by Kent State University, NSF Grant PHY-1405814, and DOE Contract DE-AC05-06OR23177.

Making a Big Bang on the small screen

NASA Astrophysics Data System (ADS)

Thomas, Nick

2010-01-01

While the quality of some TV sitcoms can leave viewers feeling cheated out of 30 minutes of their lives, audiences and critics are raving about the science-themed US comedy The Big Bang Theory. First shown on the CBS network in 2007, the series focuses on two brilliant postdoc physicists, Leonard and Sheldon, who are totally absorbed by science. Adhering to the stereotype, they also share a fanatical interest in science fiction, video-gaming and comic books, but unfortunately lack the social skills required to connect with their 20-something nonacademic contemporaries.

Let's Talk

ERIC Educational Resources Information Center

Woodard, Carol; Haskins, Guy; Schaefer, Grace; Smolen, Linda

2004-01-01

This article presents the Let's Talk project as a different approach to oral language development. This approach was based on observations of classrooms in the Netherlands where children talked at large tables while playing with miniature figures representing people and objects they were familiar with in their daily lives. It was also influenced…

Adapting bioinformatics curricula for big data.

PubMed

Greene, Anna C; Giffin, Kristine A; Greene, Casey S; Moore, Jason H

2016-01-01

Modern technologies are capable of generating enormous amounts of data that measure complex biological systems. Computational biologists and bioinformatics scientists are increasingly being asked to use these data to reveal key systems-level properties. We review the extent to which curricula are changing in the era of big data. We identify key competencies that scientists dealing with big data are expected to possess across fields, and we use this information to propose courses to meet these growing needs. While bioinformatics programs have traditionally trained students in data-intensive science, we identify areas of particular biological, computational and statistical emphasis important for this era that can be incorporated into existing curricula. For each area, we propose a course structured around these topics, which can be adapted in whole or in parts into existing curricula. In summary, specific challenges associated with big data provide an important opportunity to update existing curricula, but we do not foresee a wholesale redesign of bioinformatics training programs. © The Author 2015. Published by Oxford University Press.

Methodological challenges and analytic opportunities for modeling and interpreting Big Healthcare Data.

PubMed

Dinov, Ivo D

2016-01-01

Managing, processing and understanding big healthcare data is challenging, costly and demanding. Without a robust fundamental theory for representation, analysis and inference, a roadmap for uniform handling and analyzing of such complex data remains elusive. In this article, we outline various big data challenges, opportunities, modeling methods and software techniques for blending complex healthcare data, advanced analytic tools, and distributed scientific computing. Using imaging, genetic and healthcare data we provide examples of processing heterogeneous datasets using distributed cloud services, automated and semi-automated classification techniques, and open-science protocols. Despite substantial advances, new innovative technologies need to be developed that enhance, scale and optimize the management and processing of large, complex and heterogeneous data. Stakeholder investments in data acquisition, research and development, computational infrastructure and education will be critical to realize the huge potential of big data, to reap the expected information benefits and to build lasting knowledge assets. Multi-faceted proprietary, open-source, and community developments will be essential to enable broad, reliable, sustainable and efficient data-driven discovery and analytics. Big data will affect every sector of the economy and their hallmark will be 'team science'.

Learning Science through Talking Science in Elementary Classroom

ERIC Educational Resources Information Center

Tank, Kristina Maruyama; Coffino, Kara

2014-01-01

Elementary students in grade two make sense of science ideas and knowledge through their contextual experiences. Mattis Lundin and Britt Jakobson find in their research that early grade students have sophisticated understandings of human anatomy and physiology. In order to understand what students' know about human body and various systems,…

Analyzing Big Data in Psychology: A Split/Analyze/Meta-Analyze Approach

PubMed Central

Cheung, Mike W.-L.; Jak, Suzanne

2016-01-01

Big data is a field that has traditionally been dominated by disciplines such as computer science and business, where mainly data-driven analyses have been performed. Psychology, a discipline in which a strong emphasis is placed on behavioral theories and empirical research, has the potential to contribute greatly to the big data movement. However, one challenge to psychologists—and probably the most crucial one—is that most researchers may not have the necessary programming and computational skills to analyze big data. In this study we argue that psychologists can also conduct big data research and that, rather than trying to acquire new programming and computational skills, they should focus on their strengths, such as performing psychometric analyses and testing theories using multivariate analyses to explain phenomena. We propose a split/analyze/meta-analyze approach that allows psychologists to easily analyze big data. Two real datasets are used to demonstrate the proposed procedures in R. A new research agenda related to the analysis of big data in psychology is outlined at the end of the study. PMID:27242639

Analyzing Big Data in Psychology: A Split/Analyze/Meta-Analyze Approach.

PubMed

Cheung, Mike W-L; Jak, Suzanne

2016-01-01

Big data is a field that has traditionally been dominated by disciplines such as computer science and business, where mainly data-driven analyses have been performed. Psychology, a discipline in which a strong emphasis is placed on behavioral theories and empirical research, has the potential to contribute greatly to the big data movement. However, one challenge to psychologists-and probably the most crucial one-is that most researchers may not have the necessary programming and computational skills to analyze big data. In this study we argue that psychologists can also conduct big data research and that, rather than trying to acquire new programming and computational skills, they should focus on their strengths, such as performing psychometric analyses and testing theories using multivariate analyses to explain phenomena. We propose a split/analyze/meta-analyze approach that allows psychologists to easily analyze big data. Two real datasets are used to demonstrate the proposed procedures in R. A new research agenda related to the analysis of big data in psychology is outlined at the end of the study.

Using an Inquiry Approach to Teach Science to Secondary School Science Teachers

ERIC Educational Resources Information Center

McBride, John W.; Bhatti, Muhammad I.; Hannan, Mohammad A.; Feinberg, Martin

2004-01-01

Leaders in science education have actively promoted inquiry science since the 1960s and continue to do so today. The US National Science Education Standards recommend that science instruction and learning should be well grounded in inquiry. In spite of these efforts, however, little has changed in the way science is taught. Teacher-talk and…

Burton Award Talk: Science Under Attack: Intelligent Design

NASA Astrophysics Data System (ADS)

Krauss, Lawrence

2005-04-01

Science is under attack in many places throughout our society, from the White House to the classroom. I will concentrate my remarks here on the emerging threat to science education associated with the effort to have Intelligent Design incorporated into high school science curricula. While this may appear to be primarily an attack on evolutionary biology, it is in fact motivated by an effort to undermine the teaching of science itself as a discipline based on the scientific method. Moreover, the key proponents of this methodology are not misguided scientists, they are highly refined political operatives who are motivated by a desire to incorporate religion directly in science classes.

Biosecurity in the age of Big Data: a conversation with the FBI.

PubMed

You, Edward; Kozminski, Keith G

2015-11-05

New scientific frontiers and emerging technologies within the life sciences pose many global challenges to society. Big Data is a premier example, especially with respect to individual, national, and international security. Here a Special Agent of the Federal Bureau of Investigation discusses the security implications of Big Data and the need for security in the life sciences. © 2015 Kozminski. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

The Quantified Self: Fundamental Disruption in Big Data Science and Biological Discovery.

PubMed

Swan, Melanie

2013-06-01

A key contemporary trend emerging in big data science is the quantified self (QS)-individuals engaged in the self-tracking of any kind of biological, physical, behavioral, or environmental information as n=1 individuals or in groups. There are opportunities for big data scientists to develop new models to support QS data collection, integration, and analysis, and also to lead in defining open-access database resources and privacy standards for how personal data is used. Next-generation QS applications could include tools for rendering QS data meaningful in behavior change, establishing baselines and variability in objective metrics, applying new kinds of pattern recognition techniques, and aggregating multiple self-tracking data streams from wearable electronics, biosensors, mobile phones, genomic data, and cloud-based services. The long-term vision of QS activity is that of a systemic monitoring approach where an individual's continuous personal information climate provides real-time performance optimization suggestions. There are some potential limitations related to QS activity-barriers to widespread adoption and a critique regarding scientific soundness-but these may be overcome. One interesting aspect of QS activity is that it is fundamentally a quantitative and qualitative phenomenon since it includes both the collection of objective metrics data and the subjective experience of the impact of these data. Some of this dynamic is being explored as the quantified self is becoming the qualified self in two new ways: by applying QS methods to the tracking of qualitative phenomena such as mood, and by understanding that QS data collection is just the first step in creating qualitative feedback loops for behavior change. In the long-term future, the quantified self may become additionally transformed into the extended exoself as data quantification and self-tracking enable the development of new sense capabilities that are not possible with ordinary senses. The

Which Individual Therapist Behaviors Elicit Client Change Talk and Sustain Talk in Motivational Interviewing?

PubMed

Apodaca, Timothy R; Jackson, Kristina M; Borsari, Brian; Magill, Molly; Longabaugh, Richard; Mastroleo, Nadine R; Barnett, Nancy P

2016-02-01

To identify individual therapist behaviors which elicit client change talk or sustain talk in motivational interviewing sessions. Motivational interviewing sessions from a single-session alcohol intervention delivered to college students were audio-taped, transcribed, and coded using the Motivational Interviewing Skill Code (MISC), a therapy process coding system. Participants included 92 college students and eight therapists who provided their treatment. The MISC was used to code 17 therapist behaviors related to the use of motivational interviewing, and client language reflecting movement toward behavior change (change talk), away from behavior change (sustain talk), or unrelated to the target behavior (follow/neutral). Client change talk was significantly more likely to immediately follow individual therapist behaviors [affirm (p=.013), open question (p<.001), simple reflection (p<.001), and complex reflection (p<.001)], but significantly less likely to immediately follow others (giving information (p<.001) and closed question (p<.001)]. Sustain talk was significantly more likely to follow therapist use of open questions (p<.001), simple reflections (p<.001), and complex reflections (p<.001), and significantly less likely to occur following therapist use of therapist affirm (p=.012), giving information (p<.001), and closed questions (p<.001). Certain individual therapist behaviors within motivational interviewing can either elicit both client change talk and sustain talk or suppress both types of client language. Affirm was the only therapist behavior that both increased change talk and also reduced sustain talk. Copyright © 2015 Elsevier Inc. All rights reserved.

Big Data in HEP: A comprehensive use case study

DOE PAGES

Gutsche, Oliver; Cremonesi, Matteo; Elmer, Peter; ...

2017-11-23

Experimental Particle Physics has been at the forefront of analyzing the worlds largest datasets for decades. The HEP community was the first to develop suitable software and computing tools for this task. In recent times, new toolkits and systems collectively called Big Data technologies have emerged to support the analysis of Petabyte and Exabyte datasets in industry. While the principles of data analysis in HEP have not changed (filtering and transforming experiment-specific data formats), these new technologies use different approaches and promise a fresh look at analysis of very large datasets and could potentially reduce the time-to-physics with increased interactivity.more » In this talk, we present an active LHC Run 2 analysis, searching for dark matter with the CMS detector, as a testbed for Big Data technologies. We directly compare the traditional NTuple-based analysis with an equivalent analysis using Apache Spark on the Hadoop ecosystem and beyond. In both cases, we start the analysis with the official experiment data formats and produce publication physics plots. Lastly, we will discuss advantages and disadvantages of each approach and give an outlook on further studies needed.« less

Big Data in HEP: A comprehensive use case study

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

Gutsche, Oliver; Cremonesi, Matteo; Elmer, Peter

Experimental Particle Physics has been at the forefront of analyzing the worlds largest datasets for decades. The HEP community was the first to develop suitable software and computing tools for this task. In recent times, new toolkits and systems collectively called Big Data technologies have emerged to support the analysis of Petabyte and Exabyte datasets in industry. While the principles of data analysis in HEP have not changed (filtering and transforming experiment-specific data formats), these new technologies use different approaches and promise a fresh look at analysis of very large datasets and could potentially reduce the time-to-physics with increased interactivity.more » In this talk, we present an active LHC Run 2 analysis, searching for dark matter with the CMS detector, as a testbed for Big Data technologies. We directly compare the traditional NTuple-based analysis with an equivalent analysis using Apache Spark on the Hadoop ecosystem and beyond. In both cases, we start the analysis with the official experiment data formats and produce publication physics plots. Lastly, we will discuss advantages and disadvantages of each approach and give an outlook on further studies needed.« less

Big Data in HEP: A comprehensive use case study

NASA Astrophysics Data System (ADS)

Gutsche, Oliver; Cremonesi, Matteo; Elmer, Peter; Jayatilaka, Bo; Kowalkowski, Jim; Pivarski, Jim; Sehrish, Saba; Mantilla Surez, Cristina; Svyatkovskiy, Alexey; Tran, Nhan

2017-10-01

Experimental Particle Physics has been at the forefront of analyzing the worlds largest datasets for decades. The HEP community was the first to develop suitable software and computing tools for this task. In recent times, new toolkits and systems collectively called Big Data technologies have emerged to support the analysis of Petabyte and Exabyte datasets in industry. While the principles of data analysis in HEP have not changed (filtering and transforming experiment-specific data formats), these new technologies use different approaches and promise a fresh look at analysis of very large datasets and could potentially reduce the time-to-physics with increased interactivity. In this talk, we present an active LHC Run 2 analysis, searching for dark matter with the CMS detector, as a testbed for Big Data technologies. We directly compare the traditional NTuple-based analysis with an equivalent analysis using Apache Spark on the Hadoop ecosystem and beyond. In both cases, we start the analysis with the official experiment data formats and produce publication physics plots. We will discuss advantages and disadvantages of each approach and give an outlook on further studies needed.

What We Talk About When We Talk About Light†

PubMed Central

2015-01-01

UNESCO (the United Nations Educational, Scientific, and Cultural Organization) has declared 2015 the “International Year of Light and Light-Based Technologies”. In celebration of this proclamation, this Outlook provides a general history of light and its applications, from the earliest moments of the Big Bang through its present impact on all forms of life on the planet. Special emphasis is placed on fundamental advances in the generation and use of artificial light, as well as the harvesting and use of light from the Sun and other natural sources. During the past century, the role of light in the fields of physics, chemistry, and biology has expanded to include emerging fields such as environmental engineering, agriculture, materials science, and biomedicine. In this regard, future research challenges and new potential applications in these areas, in the context of “the central science”, are presented and discussed. PMID:27162995

Big Crater as Viewed by Pathfinder Lander

NASA Technical Reports Server (NTRS)

1997-01-01

The 'Big Crater' is actually a relatively small Martian crater to the southeast of the Mars Pathfinder landing site. It is 1500 meters (4900 feet) in diameter, or about the same size as Meteor Crater in Arizona. Superimposed on the rim of Big Crater (the central part of the rim as seen here) is a smaller crater nicknamed 'Rimshot Crater.' The distance to this smaller crater, and the nearest portion of the rim of Big Crater, is 2200 meters (7200 feet). To the right of Big Crater, south from the spacecraft, almost lost in the atmospheric dust 'haze,' is the large streamlined mountain nicknamed 'Far Knob.' This mountain is over 450 meters (1480 feet) tall, and is over 30 kilometers (19 miles) from the spacecraft. Another, smaller and closer knob, nicknamed 'Southeast Knob' can be seen as a triangular peak to the left of the flanks of the Big Crater rim. This knob is 21 kilometers (13 miles) southeast from the spacecraft.

The larger features visible in this scene - Big Crater, Far Knob, and Southeast Knob - were discovered on the first panoramas taken by the IMP camera on the 4th of July, 1997, and subsequently identified in Viking Orbiter images taken over 20 years ago. The scene includes rocky ridges and swales or 'hummocks' of flood debris that range from a few tens of meters away from the lander to the distance of South Twin Peak. The largest rock in the nearfield, just left of center in the foreground, nicknamed 'Otter', is about 1.5 meters (4.9 feet) long and 10 meters (33 feet) from the spacecraft.

This view of Big Crater was produced by combining 6 individual 'Superpan' scenes from the left and right eyes of the IMP camera. Each frame consists of 8 individual frames (left eye) and 7 frames (right eye) taken with different color filters that were enlarged by 500% and then co-added using Adobe Photoshop to produce, in effect, a super-resolution panchromatic frame that is sharper than an individual frame would be.

Mars Pathfinder is the second in NASA

Introducing the Big Knowledge to Use (BK2U) challenge.

PubMed

Perl, Yehoshua; Geller, James; Halper, Michael; Ochs, Christopher; Zheng, Ling; Kapusnik-Uner, Joan

2017-01-01

The purpose of the Big Data to Knowledge initiative is to develop methods for discovering new knowledge from large amounts of data. However, if the resulting knowledge is so large that it resists comprehension, referred to here as Big Knowledge (BK), how can it be used properly and creatively? We call this secondary challenge, Big Knowledge to Use. Without a high-level mental representation of the kinds of knowledge in a BK knowledgebase, effective or innovative use of the knowledge may be limited. We describe summarization and visualization techniques that capture the big picture of a BK knowledgebase, possibly created from Big Data. In this research, we distinguish between assertion BK and rule-based BK (rule BK) and demonstrate the usefulness of summarization and visualization techniques of assertion BK for clinical phenotyping. As an example, we illustrate how a summary of many intracranial bleeding concepts can improve phenotyping, compared to the traditional approach. We also demonstrate the usefulness of summarization and visualization techniques of rule BK for drug-drug interaction discovery. © 2016 New York Academy of Sciences.

Signs of taste for science: a methodology for studying the constitution of interest in the science classroom

NASA Astrophysics Data System (ADS)

Anderhag, P.; Wickman, P.-O.; Hamza, K. M.

2015-06-01

In this paper we present a methodological approach for analyzing the transformation of interest in science through classroom talk and action. To this end, we use the construct of taste for science as a social and communicative operationalization, or proxy, to the more psychologically oriented construct of interest. To gain a taste for science as part of school science activities means developing habits of performing and valuing certain distinctions about ways to talk, act and be that are jointly construed as belonging in the school science classroom. In this view, to learn science is not only about learning the curriculum content, but also about learning a normative and aesthetic content in terms of habits of distinguishing and valuing. The approach thus complements previous studies on students' interest in science, by making it possible to analyze how taste for science is constituted, moment-by-moment, through talk and action in the science classroom. In developing the method, we supplement theoretical constructs coming from pragmatism and Pierre Bourdieu with empirical data from a lower secondary science classroom. The application of the method to this classroom demonstrates the potential that the approach has for analyzing how conceptual, normative, and aesthetic distinctions within the science classroom interact in the constitution of taste for, and thereby potentially also in the development of interest in science among students.

The Rise of Big Data in Oncology.

PubMed

Fessele, Kristen L

2018-05-01

To describe big data and data science in the context of oncology nursing care. Peer-reviewed and lay publications. The rapid expansion of real-world evidence from sources such as the electronic health record, genomic sequencing, administrative claims and other data sources has outstripped the ability of clinicians and researchers to manually review and analyze it. To promote high-quality, high-value cancer care, big data platforms must be constructed from standardized data sources to support extraction of meaningful, comparable insights. Nurses must advocate for the use of standardized vocabularies and common data elements that represent terms and concepts that are meaningful to patient care. Copyright © 2018 Elsevier Inc. All rights reserved.

Vectors into the Future of Mass and Interpersonal Communication Research: Big Data, Social Media, and Computational Social Science.

PubMed

Cappella, Joseph N

2017-10-01

Simultaneous developments in big data, social media, and computational social science have set the stage for how we think about and understand interpersonal and mass communication. This article explores some of the ways that these developments generate 4 hypothetical "vectors" - directions - into the next generation of communication research. These vectors include developments in network analysis, modeling interpersonal and social influence, recommendation systems, and the blurring of distinctions between interpersonal and mass audiences through narrowcasting and broadcasting. The methods and research in these arenas are occurring in areas outside the typical boundaries of the communication discipline but engage classic, substantive questions in mass and interpersonal communication.

How Big Is Too Big?

ERIC Educational Resources Information Center

Cibes, Margaret; Greenwood, James

2016-01-01

Media Clips appears in every issue of Mathematics Teacher, offering readers contemporary, authentic applications of quantitative reasoning based on print or electronic media. This issue features "How Big is Too Big?" (Margaret Cibes and James Greenwood) in which students are asked to analyze the data and tables provided and answer a…

The SAMI Galaxy Survey: A prototype data archive for Big Science exploration

NASA Astrophysics Data System (ADS)

Konstantopoulos, I. S.; Green, A. W.; Foster, C.; Scott, N.; Allen, J. T.; Fogarty, L. M. R.; Lorente, N. P. F.; Sweet, S. M.; Hopkins, A. M.; Bland-Hawthorn, J.; Bryant, J. J.; Croom, S. M.; Goodwin, M.; Lawrence, J. S.; Owers, M. S.; Richards, S. N.

2015-11-01

We describe the data archive and database for the SAMI Galaxy Survey, an ongoing observational program that will cover ≈3400 galaxies with integral-field (spatially-resolved) spectroscopy. Amounting to some three million spectra, this is the largest sample of its kind to date. The data archive and built-in query engine use the versatile Hierarchical Data Format (HDF5), which precludes the need for external metadata tables and hence the setup and maintenance overhead those carry. The code produces simple outputs that can easily be translated to plots and tables, and the combination of these tools makes for a light system that can handle heavy data. This article acts as a contextual companion to the SAMI Survey Database source code repository, samiDB, which is freely available online and written entirely in Python. We also discuss the decisions related to the selection of tools and the creation of data visualisation modules. It is our aim that the work presented in this article-descriptions, rationale, and source code-will be of use to scientists looking to set up a maintenance-light data archive for a Big Science data load.

Met The Press: What It's LIke to Talk to Reporters about Physics

NASA Astrophysics Data System (ADS)

Thompson, Rebecca

2013-03-01

Someone from the Huffington Post just called you because they are doing a story about science and you are a physicist. The problem is that they need you to take time away from your grapheme experiments to talk about the physics of exploding anvils. It's been a long time since you've shot an anvil in the air so you think you might not be right for this. But, as long as you understand general physics and can explain things well, you can be a real asset. This talk will recount first-hand experiences talking to a range of news outlets from the PBS New Hour to Real Simple Magazine about everything from quick-freezing water to pumpkin boats. It will include helpful information about preparing for an interview, learning new physics fast, timelines and follow-up.

Department of Energy's Virtual Lab Infrastructure for Integrated Earth System Science Data

NASA Astrophysics Data System (ADS)

Williams, D. N.; Palanisamy, G.; Shipman, G.; Boden, T.; Voyles, J.

2014-12-01

The U.S. Department of Energy (DOE) Office of Biological and Environmental Research (BER) Climate and Environmental Sciences Division (CESD) produces a diversity of data, information, software, and model codes across its research and informatics programs and facilities. This information includes raw and reduced observational and instrumentation data, model codes, model-generated results, and integrated data products. Currently, most of this data and information are prepared and shared for program specific activities, corresponding to CESD organization research. A major challenge facing BER CESD is how best to inventory, integrate, and deliver these vast and diverse resources for the purpose of accelerating Earth system science research. This talk provides a concept for a CESD Integrated Data Ecosystem and an initial roadmap for its implementation to address this integration challenge in the "Big Data" domain. Towards this end, a new BER Virtual Laboratory Infrastructure will be presented, which will include services and software connecting the heterogeneous CESD data holdings, and constructed with open source software based on industry standards, protocols, and state-of-the-art technology.

BigDog

NASA Astrophysics Data System (ADS)

Playter, R.; Buehler, M.; Raibert, M.

2006-05-01

BigDog's goal is to be the world's most advanced quadruped robot for outdoor applications. BigDog is aimed at the mission of a mechanical mule - a category with few competitors to date: power autonomous quadrupeds capable of carrying significant payloads, operating outdoors, with static and dynamic mobility, and fully integrated sensing. BigDog is about 1 m tall, 1 m long and 0.3 m wide, and weighs about 90 kg. BigDog has demonstrated walking and trotting gaits, as well as standing up and sitting down. Since its creation in the fall of 2004, BigDog has logged tens of hours of walking, climbing and running time. It has walked up and down 25 & 35 degree inclines and trotted at speeds up to 1.8 m/s. BigDog has walked at 0.7 m/s over loose rock beds and carried over 50 kg of payload. We are currently working to expand BigDog's rough terrain mobility through the creation of robust locomotion strategies and terrain sensing capabilities.

News Conference: The Big Bangor Day Meeting Lecture: Charterhouse plays host to a physics day Festival: Science on Stage festival 2013 arrives in Poland Event: Scottish Physics Teachers' Summer School Meeting: Researchers and educators meet at Lund University Conference: Exeter marks the spot Recognition: European Physical Society uncovers an historic site Education: Initial teacher education undergoes big changes Forthcoming events

NASA Astrophysics Data System (ADS)

2013-09-01

Conference: The Big Bangor Day Meeting Lecture: Charterhouse plays host to a physics day Festival: Science on Stage festival 2013 arrives in Poland Event: Scottish Physics Teachers' Summer School Meeting: Researchers and educators meet at Lund University Conference: Exeter marks the spot Recognition: European Physical Society uncovers an historic site Education: Initial teacher education undergoes big changes Forthcoming events

On talking-as-dreaming.

PubMed

Ogden, Thomas H

2007-06-01

Many patients are unable to engage in waking-dreaming in the analytic setting in the form of free association or in any other form. The author has found that "talking-as-dreaming" has served as a form of waking-dreaming in which such patients have been able to begin to dream formerly undreamable experience. Such talking is a loosely structured form of conversation between patient and analyst that is often marked by primary process thinking and apparent non sequiturs. Talking-as-dreaming superficially appears to be "unanalytic" in that it may seem to consist "merely" of talking about such topics as books, films, etymology, baseball, the taste of chocolate, the structure of light, and so on. When an analysis is "a going concern," talking-as-dreaming moves unobtrusively into and out of talking about dreaming. The author provides two detailed clinical examples of analytic work with patients who had very little capacity to dream in the analytic setting. In the first clinical example, talking-as-dreaming served as a form of thinking and relating in which the patient was able for the first time to dream her own (and, in a sense, her father's) formerly unthinkable, undreamable experience. The second clinical example involves the use of talking-as-dreaming as an emotional experience in which the formerly "invisible" patient was able to begin to dream himself into existence. The analyst, while engaging with a patient in talking-as-dreaming, must remain keenly aware that it is critical that the difference in roles of patient and analyst be a continuously felt presence; that the therapeutic goals of analysis be firmly held in mind; and that the patient be given the opportunity to dream himself into existence (as opposed to being dreamt up by the analyst).

Big data and tactical analysis in elite soccer: future challenges and opportunities for sports science.

PubMed

Rein, Robert; Memmert, Daniel

2016-01-01

Until recently tactical analysis in elite soccer were based on observational data using variables which discard most contextual information. Analyses of team tactics require however detailed data from various sources including technical skill, individual physiological performance, and team formations among others to represent the complex processes underlying team tactical behavior. Accordingly, little is known about how these different factors influence team tactical behavior in elite soccer. In parts, this has also been due to the lack of available data. Increasingly however, detailed game logs obtained through next-generation tracking technologies in addition to physiological training data collected through novel miniature sensor technologies have become available for research. This leads however to the opposite problem where the shear amount of data becomes an obstacle in itself as methodological guidelines as well as theoretical modelling of tactical decision making in team sports is lacking. The present paper discusses how big data and modern machine learning technologies may help to address these issues and aid in developing a theoretical model for tactical decision making in team sports. As experience from medical applications show, significant organizational obstacles regarding data governance and access to technologies must be overcome first. The present work discusses these issues with respect to tactical analyses in elite soccer and propose a technological stack which aims to introduce big data technologies into elite soccer research. The proposed approach could also serve as a guideline for other sports science domains as increasing data size is becoming a wide-spread phenomenon.

What Difference Does Quantity Make? On the Epistemology of Big Data in Biology

PubMed Central

Leonelli, Sabina

2015-01-01

Is big data science a whole new way of doing research? And what difference does data quantity make to knowledge production strategies and their outputs? I argue that the novelty of big data science does not lie in the sheer quantity of data involved, but rather in (1) the prominence and status acquired by data as commodity and recognised output, both within and outside of the scientific community; and (2) the methods, infrastructures, technologies, skills and knowledge developed to handle data. These developments generate the impression that data-intensive research is a new mode of doing science, with its own epistemology and norms. To assess this claim, one needs to consider the ways in which data are actually disseminated and used to generate knowledge. Accordingly, this paper reviews the development of sophisticated ways to disseminate, integrate and re-use data acquired on model organisms over the last three decades of work in experimental biology. I focus on online databases as prominent infrastructures set up to organise and interpret such data; and examine the wealth and diversity of expertise, resources and conceptual scaffolding that such databases draw upon. This illuminates some of the conditions under which big data need to be curated to support processes of discovery across biological subfields, which in turn highlights the difficulties caused by the lack of adequate curation for the vast majority of data in the life sciences. In closing, I reflect on the difference that data quantity is making to contemporary biology, the methodological and epistemic challenges of identifying and analyzing data given these developments, and the opportunities and worries associated to big data discourse and methods. PMID:25729586

What Difference Does Quantity Make? On the Epistemology of Big Data in Biology.

PubMed

Leonelli, Sabina

2014-06-01

Is big data science a whole new way of doing research? And what difference does data quantity make to knowledge production strategies and their outputs? I argue that the novelty of big data science does not lie in the sheer quantity of data involved, but rather in (1) the prominence and status acquired by data as commodity and recognised output, both within and outside of the scientific community; and (2) the methods, infrastructures, technologies, skills and knowledge developed to handle data. These developments generate the impression that data-intensive research is a new mode of doing science, with its own epistemology and norms. To assess this claim, one needs to consider the ways in which data are actually disseminated and used to generate knowledge. Accordingly, this paper reviews the development of sophisticated ways to disseminate, integrate and re-use data acquired on model organisms over the last three decades of work in experimental biology. I focus on online databases as prominent infrastructures set up to organise and interpret such data; and examine the wealth and diversity of expertise, resources and conceptual scaffolding that such databases draw upon. This illuminates some of the conditions under which big data need to be curated to support processes of discovery across biological subfields, which in turn highlights the difficulties caused by the lack of adequate curation for the vast majority of data in the life sciences. In closing, I reflect on the difference that data quantity is making to contemporary biology, the methodological and epistemic challenges of identifying and analyzing data given these developments, and the opportunities and worries associated to big data discourse and methods.

Air Toxics Under the Big Sky: Examining the Effectiveness of Authentic Scientific Research on High School Students' Science Skills and Interest.

PubMed

Ward, Tony J; Delaloye, Naomi; Adams, Earle Raymond; Ware, Desirae; Vanek, Diana; Knuth, Randy; Hester, Carolyn Laurie; Marra, Nancy Noel; Holian, Andrij

2016-01-01

Air Toxics Under the Big Sky is an environmental science outreach/education program that incorporates the Next Generation Science Standards (NGSS) 8 Practices with the goal of promoting knowledge and understanding of authentic scientific research in high school classrooms through air quality research. A quasi-experimental design was used in order to understand: 1) how the program affects student understanding of scientific inquiry and research and 2) how the open inquiry learning opportunities provided by the program increase student interest in science as a career path . Treatment students received instruction related to air pollution (airborne particulate matter), associated health concerns, and training on how to operate air quality testing equipment. They then participated in a yearlong scientific research project in which they developed and tested hypotheses through research of their own design regarding the sources and concentrations of air pollution in their homes and communities. Results from an external evaluation revealed that treatment students developed a deeper understanding of scientific research than did comparison students, as measured by their ability to generate good hypotheses and research designs, and equally expressed an increased interest in pursuing a career in science. These results emphasize the value of and need for authentic science learning opportunities in the modern science classroom.

Air Toxics Under the Big Sky: examining the effectiveness of authentic scientific research on high school students' science skills and interest

NASA Astrophysics Data System (ADS)

Ward, Tony J.; Delaloye, Naomi; Adams, Earle Raymond; Ware, Desirae; Vanek, Diana; Knuth, Randy; Hester, Carolyn Laurie; Marra, Nancy Noel; Holian, Andrij

2016-04-01

Air Toxics Under the Big Sky is an environmental science outreach/education program that incorporates the Next Generation Science Standards (NGSS) 8 Practices with the goal of promoting knowledge and understanding of authentic scientific research in high school classrooms through air quality research. This research explored: (1) how the program affects student understanding of scientific inquiry and research and (2) how the open-inquiry learning opportunities provided by the program increase student interest in science as a career path. Treatment students received instruction related to air pollution (airborne particulate matter), associated health concerns, and training on how to operate air quality testing equipment. They then participated in a yearlong scientific research project in which they developed and tested hypotheses through research of their own design regarding the sources and concentrations of air pollution in their homes and communities. Results from an external evaluation revealed that treatment students developed a deeper understanding of scientific research than did comparison students, as measured by their ability to generate good hypotheses and research designs, and equally expressed an increased interest in pursuing a career in science. These results emphasize the value of and need for authentic science learning opportunities in the modern science classroom.

Air Toxics Under the Big Sky: Examining the Effectiveness of Authentic Scientific Research on High School Students’ Science Skills and Interest

PubMed Central

Delaloye, Naomi; Adams, Earle Raymond; Ware, Desirae; Vanek, Diana; Knuth, Randy; Hester, Carolyn Laurie; Marra, Nancy Noel; Holian, Andrij

2016-01-01

Air Toxics Under the Big Sky is an environmental science outreach/education program that incorporates the Next Generation Science Standards (NGSS) 8 Practices with the goal of promoting knowledge and understanding of authentic scientific research in high school classrooms through air quality research. A quasi-experimental design was used in order to understand: 1) how the program affects student understanding of scientific inquiry and research and 2) how the open inquiry learning opportunities provided by the program increase student interest in science as a career path. Treatment students received instruction related to air pollution (airborne particulate matter), associated health concerns, and training on how to operate air quality testing equipment. They then participated in a yearlong scientific research project in which they developed and tested hypotheses through research of their own design regarding the sources and concentrations of air pollution in their homes and communities. Results from an external evaluation revealed that treatment students developed a deeper understanding of scientific research than did comparison students, as measured by their ability to generate good hypotheses and research designs, and equally expressed an increased interest in pursuing a career in science. These results emphasize the value of and need for authentic science learning opportunities in the modern science classroom. PMID:28286375

Brookhaven Women in Science Lecture

ScienceCinema

Johanna Levelt Sengers

2017-12-09

Sponsored by Brookhaven Women in Science (BWIS), Johanna Levelt Sengers, Scientist Emeritus at the National Institute of Standards & Technology (NIST), presents a talk titled "The World's Science Academies Address the Under-Representation of Women in Science and Technology."

Fixing the Big Bang Theory's Lithium Problem

NASA Astrophysics Data System (ADS)

Kohler, Susanna

2017-02-01

How did our universe come into being? The Big Bang theory is a widely accepted and highly successful cosmological model of the universe, but it does introduce one puzzle: the cosmological lithium problem. Have scientists now found a solution?Too Much LithiumIn the Big Bang theory, the universe expanded rapidly from a very high-density and high-temperature state dominated by radiation. This theory has been validated again and again: the discovery of the cosmic microwave background radiation and observations of the large-scale structure of the universe both beautifully support the Big Bang theory, for instance. But one pesky trouble-spot remains: the abundance of lithium.The arrows show the primary reactions involved in Big Bang nucleosynthesis, and their flux ratios, as predicted by the authors model, are given on the right. Synthesizing primordial elements is complicated! [Hou et al. 2017]According to Big Bang nucleosynthesis theory, primordial nucleosynthesis ran wild during the first half hour of the universes existence. This produced most of the universes helium and small amounts of other light nuclides, including deuterium and lithium.But while predictions match the observed primordial deuterium and helium abundances, Big Bang nucleosynthesis theory overpredicts the abundance of primordial lithium by about a factor of three. This inconsistency is known as the cosmological lithium problem and attempts to resolve it using conventional astrophysics and nuclear physics over the past few decades have not been successful.In a recent publicationled by Suqing Hou (Institute of Modern Physics, Chinese Academy of Sciences) and advisorJianjun He (Institute of Modern Physics National Astronomical Observatories, Chinese Academy of Sciences), however, a team of scientists has proposed an elegant solution to this problem.Time and temperature evolution of the abundances of primordial light elements during the beginning of the universe. The authors model (dotted lines

Big Earth Data: the Film, the Experience, and some Thoughts

NASA Astrophysics Data System (ADS)

Baumann, P.

2016-12-01

Scientists have to get out of the ivory tower and tell society, which ultimately finances them, about their work, their results, and implications, be they good or bad. This is commonly accepted ethics. But how would you "tell society" at large what you are doing? Scientific work typically is difficult to confer to lay people, and finding suitable simplifications and paraphrasings requires considerable effort. Estimating societal implications is dangerous as swimming with sharks, some of which are your own colleagues. Media tend to be not always interested - unless results are particularly spectacular, well, in a press sense. Again, sharks are luring. All this makes informing the public a tedious, time-consuming task which tends to receive not much appreciation in tenure negotiations where indexed publications are the first and foremost measure.As part of the EU funded EarthServer initiative we tried it. Having promised a "video about the project" we found it boring to do another 10 minute repetition from the grant contract and started aiming at a full TV documentary explaining "Big Earth Data" to the interested citizens. It took more than one year to convince a TV producing company and TV stations that this is not another feature about the beauty of nature or catastrophies, but a bout human insight from computer-supported sifting through all those observations and simulations available. After they got the gist they were fully on board and supported financially with a substantial amount. The final 53 minutes "Big Earth Data" movie was broadcast in February 2015 in German and French (English version available from ). Several smaller spin-off features originated around it, such as an uptake of the theme (and material) in a popular German science TV series.Of course, this is but one contribution and cannot be made a continuous activity. In the talk we want to present and discuss the "making of" from a scientist's perspective, highlighting the ups and downs in the

Big Earth Data: the Film, the Experience, and some Thoughts

NASA Astrophysics Data System (ADS)

Baumann, P.; Hoenig, H.

2015-12-01

Scientists have to get out of the ivory tower and tell society, which ultimately finances them, about their work, their results, and implications, be they good or bad. This is commonly accepted ethics. But how would you "tell society" at large what you are doing? Scientific work typically is difficult to confer to lay people, and finding suitable simplifications and paraphrasings requires considerable effort. Estimating societal implications is dangerous as swimming with sharks, some of which are your own colleagues. Media tend to be not always interested - unless results are particularly spectacular, well, in a press sense. Again, sharks are luring. All this makes informing the public a tedious, time-consuming task which tends to receive not much appreciation in tenure negotiations where indexed publications are the first and foremost measure.As part of the EU funded EarthServer initiative we tried it. Having promised a "video about the project" we found it boring to do another 10 minute repetition from the grant contract and started aiming at a full TV documentary explaining "Big Earth Data" to the interested citizens. It took more than one year to convince a TV producing company and TV stations that this is not another feature about the beauty of nature or catastrophies, but about human insight from computer-supported sifting through all those observations and simulations available. After they got the gist they were fully on board and supported financially with a substantial amount. The final 53 minutes "Big Earth Data" movie was broadcast in February 2015 in German and French (English version available from ). Several smaller spin-off features originated around it, such as an uptake of the theme (and material) in a popular German science TV series.Of course, this is but one contribution and cannot be made a continuous activity. In the talk we want to present and discuss the "making of" from a scientist's perspective, highlighting the ups and downs in the

Science Talk: Preservice Teachers Facilitating Science Learning in Diverse Afterschool Environments

ERIC Educational Resources Information Center

Cartwright, Tina Johnson

2012-01-01

The purpose of this study was to assess the impact a community-based service learning program might have on preservice teachers' science instruction during student teaching. Designed to promote science inquiry, preservice teachers learned how to offer students more opportunities to develop their own ways of thinking through utilization of an…

Advanced Research and Data Methods in Women's Health: Big Data Analytics, Adaptive Studies, and the Road Ahead.

PubMed

Macedonia, Christian R; Johnson, Clark T; Rajapakse, Indika

2017-02-01

Technical advances in science have had broad implications in reproductive and women's health care. Recent innovations in population-level data collection and storage have made available an unprecedented amount of data for analysis while computational technology has evolved to permit processing of data previously thought too dense to study. "Big data" is a term used to describe data that are a combination of dramatically greater volume, complexity, and scale. The number of variables in typical big data research can readily be in the thousands, challenging the limits of traditional research methodologies. Regardless of what it is called, advanced data methods, predictive analytics, or big data, this unprecedented revolution in scientific exploration has the potential to dramatically assist research in obstetrics and gynecology broadly across subject matter. Before implementation of big data research methodologies, however, potential researchers and reviewers should be aware of strengths, strategies, study design methods, and potential pitfalls. Examination of big data research examples contained in this article provides insight into the potential and the limitations of this data science revolution and practical pathways for its useful implementation.

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

Abergel, Rebecca

Berkeley Lab's Rebecca Abergel discusses "A pill to treat people exposed to radioactive materials" in this Oct. 28, 2013 talk, which is part of a Science at the Theater event entitled Eight Big Ideas. Go here to watch the entire event with all 8 speakers:

A Pill to Treat People Exposed to Radioactive Materials

ScienceCinema

Abergel, Rebecca

2018-01-16

Berkeley Lab's Rebecca Abergel discusses "A pill to treat people exposed to radioactive materials" in this Oct. 28, 2013 talk, which is part of a Science at the Theater event entitled Eight Big Ideas. Go here to watch the entire event with all 8 speakers:

Eliciting Student-Talk.

ERIC Educational Resources Information Center

Rudder, Michael E.

1999-01-01

The communicative approach to language instruction emphasizes ways to increase student-talk and decrease teacher-talk. It necessitates including the production or performance stage in lesson plans to give students the opportunity to use the new language in simulated real-life situations. (Author/VWL)

Data science, learning, and applications to biomedical and health sciences.

PubMed

Adam, Nabil R; Wieder, Robert; Ghosh, Debopriya

2017-01-01

The last decade has seen an unprecedented increase in the volume and variety of electronic data related to research and development, health records, and patient self-tracking, collectively referred to as Big Data. Properly harnessed, Big Data can provide insights and drive discovery that will accelerate biomedical advances, improve patient outcomes, and reduce costs. However, the considerable potential of Big Data remains unrealized owing to obstacles including a limited ability to standardize and consolidate data and challenges in sharing data, among a variety of sources, providers, and facilities. Here, we discuss some of these challenges and potential solutions, as well as initiatives that are already underway to take advantage of Big Data. © 2017 New York Academy of Sciences.

Embers of society: Firelight talk among the Ju/'hoansi Bushmen.

PubMed

Wiessner, Polly W

2014-09-30

Much attention has been focused on control of fire in human evolution and the impact of cooking on anatomy, social, and residential arrangements. However, little is known about what transpired when firelight extended the day, creating effective time for social activities that did not conflict with productive time for subsistence activities. Comparison of 174 day and nighttime conversations among the Ju/'hoan (!Kung) Bushmen of southern Africa, supplemented by 68 translated texts, suggests that day talk centers on economic matters and gossip to regulate social relations. Night activities steer away from tensions of the day to singing, dancing, religious ceremonies, and enthralling stories, often about known people. Such stories describe the workings of entire institutions in a small-scale society with little formal teaching. Night talk plays an important role in evoking higher orders of theory of mind via the imagination, conveying attributes of people in broad networks (virtual communities), and transmitting the "big picture" of cultural institutions that generate regularity of behavior, cooperation, and trust at the regional level. Findings from the Ju/'hoan are compared with other hunter-gatherer societies and related to the widespread human use of firelight for intimate conversation and our appetite for evening stories. The question is raised as to what happens when economically unproductive firelit time is turned to productive time by artificial lighting.

Data Discovery of Big and Diverse Climate Change Datasets - Options, Practices and Challenges

NASA Astrophysics Data System (ADS)

Palanisamy, G.; Boden, T.; McCord, R. A.; Frame, M. T.

2013-12-01

Developing data search tools is a very common, but often confusing, task for most of the data intensive scientific projects. These search interfaces need to be continually improved to handle the ever increasing diversity and volume of data collections. There are many aspects which determine the type of search tool a project needs to provide to their user community. These include: number of datasets, amount and consistency of discovery metadata, ancillary information such as availability of quality information and provenance, and availability of similar datasets from other distributed sources. Environmental Data Science and Systems (EDSS) group within the Environmental Science Division at the Oak Ridge National Laboratory has a long history of successfully managing diverse and big observational datasets for various scientific programs via various data centers such as DOE's Atmospheric Radiation Measurement Program (ARM), DOE's Carbon Dioxide Information and Analysis Center (CDIAC), USGS's Core Science Analytics and Synthesis (CSAS) metadata Clearinghouse and NASA's Distributed Active Archive Center (ORNL DAAC). This talk will showcase some of the recent developments for improving the data discovery within these centers The DOE ARM program recently developed a data discovery tool which allows users to search and discover over 4000 observational datasets. These datasets are key to the research efforts related to global climate change. The ARM discovery tool features many new functions such as filtered and faceted search logic, multi-pass data selection, filtering data based on data quality, graphical views of data quality and availability, direct access to data quality reports, and data plots. The ARM Archive also provides discovery metadata to other broader metadata clearinghouses such as ESGF, IASOA, and GOS. In addition to the new interface, ARM is also currently working on providing DOI metadata records to publishers such as Thomson Reuters and Elsevier. The ARM

Diverse Grains in Mars Sandstone Target Big Arm

NASA Image and Video Library

2015-07-01

This view of a sandstone target called "Big Arm" covers an area about 1.3 inches (33 millimeters) wide in detail that shows differing shapes and colors of sand grains in the stone. Three separate images taken by the Mars Hand Lens Imager (MAHLI) camera on NASA's Curiosity Mars rover, at different focus settings, were combined into this focus-merge view. The Big Arm target on lower Mount Sharp is at a location near "Marias Pass" where a mudstone bedrock is in contact with overlying sandstone bedrock. MAHLI recorded the component images on May 29, 2015, during the 999th Martian day, or sol, of Curiosity's work on Mars. The rounded shape of some grains visible here suggests they traveled long distances before becoming part of the sediment that later hardened into sandstone. Other grains are more angular and may have originated closer to the rock's current location. Lighter and darker grains may have different compositions. MAHLI was built by Malin Space Science Systems, San Diego. NASA's Jet Propulsion Laboratory, a division of the California Institute of Technology in Pasadena, manages the Mars Science Laboratory Project for the NASA Science Mission Directorate, Washington. http://photojournal.jpl.nasa.gov/catalog/PIA19677

Evaluation of Big Data Containers for Popular Storage, Retrieval, and Computation Primitives in Earth Science Analysis

NASA Astrophysics Data System (ADS)

Das, K.; Clune, T.; Kuo, K. S.; Mattmann, C. A.; Huang, T.; Duffy, D.; Yang, C. P.; Habermann, T.

2015-12-01

Data containers are infrastructures that facilitate storage, retrieval, and analysis of data sets. Big data applications in Earth Science require a mix of processing techniques, data sources and storage formats that are supported by different data containers. Some of the most popular data containers used in Earth Science studies are Hadoop, Spark, SciDB, AsterixDB, and RasDaMan. These containers optimize different aspects of the data processing pipeline and are, therefore, suitable for different types of applications. These containers are expected to undergo rapid evolution and the ability to re-test, as they evolve, is very important to ensure the containers are up to date and ready to be deployed to handle large volumes of observational data and model output. Our goal is to develop an evaluation plan for these containers to assess their suitability for Earth Science data processing needs. We have identified a selection of test cases that are relevant to most data processing exercises in Earth Science applications and we aim to evaluate these systems for optimal performance against each of these test cases. The use cases identified as part of this study are (i) data fetching, (ii) data preparation for multivariate analysis, (iii) data normalization, (iv) distance (kernel) computation, and (v) optimization. In this study we develop a set of metrics for performance evaluation, define the specifics of governance, and test the plan on current versions of the data containers. The test plan and the design mechanism are expandable to allow repeated testing with both new containers and upgraded versions of the ones mentioned above, so that we can gauge their utility as they evolve.

Observatories, think tanks, and community models in the hydrologic and environmental sciences: How does it affect me?

NASA Astrophysics Data System (ADS)

Torgersen, Thomas

2006-06-01

Multiple issues in hydrologic and environmental sciences are now squarely in the public focus and require both government and scientific study. Two facts also emerge: (1) The new approach being touted publicly for advancing the hydrologic and environmental sciences is the establishment of community-operated "big science" (observatories, think tanks, community models, and data repositories). (2) There have been important changes in the business of science over the last 20 years that make it important for the hydrologic and environmental sciences to demonstrate the "value" of public investment in hydrological and environmental science. Given that community-operated big science (observatories, think tanks, community models, and data repositories) could become operational, I argue that such big science should not mean a reduction in the importance of single-investigator science. Rather, specific linkages between the large-scale, team-built, community-operated big science and the single investigator should provide context data, observatory data, and systems models for a continuing stream of hypotheses by discipline-based, specialized research and a strong rationale for continued, single-PI ("discovery-based") research. I also argue that big science can be managed to provide a better means of demonstrating the value of public investment in the hydrologic and environmental sciences. Decisions regarding policy will still be political, but big science could provide an integration of the best scientific understanding as a guide for the best policy.

The Need for a Definition of Big Data for Nursing Science: A Case Study of Disaster Preparedness.

PubMed

Wong, Ho Ting; Chiang, Vico Chung Lim; Choi, Kup Sze; Loke, Alice Yuen

2016-10-17

The rapid development of technology has made enormous volumes of data available and achievable anytime and anywhere around the world. Data scientists call this change a data era and have introduced the term "Big Data", which has drawn the attention of nursing scholars. Nevertheless, the concept of Big Data is quite fuzzy and there is no agreement on its definition among researchers of different disciplines. Without a clear consensus on this issue, nursing scholars who are relatively new to the concept may consider Big Data to be merely a dataset of a bigger size. Having a suitable definition for nurse researchers in their context of research and practice is essential for the advancement of nursing research. In view of the need for a better understanding on what Big Data is, the aim in this paper is to explore and discuss the concept. Furthermore, an example of a Big Data research study on disaster nursing preparedness involving six million patient records is used for discussion. The example demonstrates that a Big Data analysis can be conducted from many more perspectives than would be possible in traditional sampling, and is superior to traditional sampling. Experience gained from the process of using Big Data in this study will shed light on future opportunities for conducting evidence-based nursing research to achieve competence in disaster nursing.

The Need for a Definition of Big Data for Nursing Science: A Case Study of Disaster Preparedness

PubMed Central

Wong, Ho Ting; Chiang, Vico Chung Lim; Choi, Kup Sze; Loke, Alice Yuen

2016-01-01

The rapid development of technology has made enormous volumes of data available and achievable anytime and anywhere around the world. Data scientists call this change a data era and have introduced the term “Big Data”, which has drawn the attention of nursing scholars. Nevertheless, the concept of Big Data is quite fuzzy and there is no agreement on its definition among researchers of different disciplines. Without a clear consensus on this issue, nursing scholars who are relatively new to the concept may consider Big Data to be merely a dataset of a bigger size. Having a suitable definition for nurse researchers in their context of research and practice is essential for the advancement of nursing research. In view of the need for a better understanding on what Big Data is, the aim in this paper is to explore and discuss the concept. Furthermore, an example of a Big Data research study on disaster nursing preparedness involving six million patient records is used for discussion. The example demonstrates that a Big Data analysis can be conducted from many more perspectives than would be possible in traditional sampling, and is superior to traditional sampling. Experience gained from the process of using Big Data in this study will shed light on future opportunities for conducting evidence-based nursing research to achieve competence in disaster nursing. PMID:27763525

Talk about Talk with Young Children: Pragmatic Socialization in Two Communities in Norway and the US

ERIC Educational Resources Information Center

Aukrust, Vibeke Grover

2004-01-01

Recent studies have suggested that cultures vary in subtle ways in the talk about talk that children hear and learn to produce. Twenty-two three-year-old children and their families in respectively Oslo, Norway and Cambridge, Massachusetts were observed during mealtime with the aim of identifying talk-focused talk. The analysis distinguished talk…

Technology for Mining the Big Data of MOOCs

ERIC Educational Resources Information Center

O'Reilly, Una-May; Veeramachaneni, Kalyan

2014-01-01

Because MOOCs bring big data to the forefront, they confront learning science with technology challenges. We describe an agenda for developing technology that enables MOOC analytics. Such an agenda needs to efficiently address the detailed, low level, high volume nature of MOOC data. It also needs to help exploit the data's capacity to reveal, in…

How to give a good talk.

PubMed

Alon, Uri

2009-10-23

We depend on talks to communicate our work, and we spend much of our time as audience members in talks. However, few scientists are taught the well-established principles of giving good talks. Here, I describe how to prepare, present, and answer questions in a scientific talk. We will see how a talk prepared with a single premise and delivered with good eye contact is clear and enjoyable.

Envisioning the future of 'big data' biomedicine.

PubMed

Bui, Alex A T; Van Horn, John Darrell

2017-05-01

Through the increasing availability of more efficient data collection procedures, biomedical scientists are now confronting ever larger sets of data, often finding themselves struggling to process and interpret what they have gathered. This, while still more data continues to accumulate. This torrent of biomedical information necessitates creative thinking about how the data are being generated, how they might be best managed, analyzed, and eventually how they can be transformed into further scientific understanding for improving patient care. Recognizing this as a major challenge, the National Institutes of Health (NIH) has spearheaded the "Big Data to Knowledge" (BD2K) program - the agency's most ambitious biomedical informatics effort ever undertaken to date. In this commentary, we describe how the NIH has taken on "big data" science head-on, how a consortium of leading research centers are developing the means for handling large-scale data, and how such activities are being marshalled for the training of a new generation of biomedical data scientists. All in all, the NIH BD2K program seeks to position data science at the heart of 21 st Century biomedical research. Copyright © 2017 Elsevier Inc. All rights reserved.

The smart-talk trap.

PubMed

Pfeffer, J; Sutton, R I

1999-01-01

In today's business world, there's no shortage of know-how. When companies get into trouble, their executives have vast resources at their disposal: their own experiences, colleagues' ideas, reams of computer-generated data, thousands of publications, and consultants armed with the latest managerial concepts and tools. But all too often, even with all that knowledge floating around, companies are plagued with an inertia that comes from knowing too much and doing too little--a phenomenon the authors call the knowing-doing gap. The gap often can be traced to a basic human propensity: the willingness to let talk substitute for action. When confronted with a problem, people act as though discussing it, formulating decisions, and hashing out plans for action are the same as actually fixing it. And after researching organizations of all shapes and sizes, the authors concluded that a particular kind of talk is an especially insidious inhibitor of action: "smart talk." People who can engage in such talk generally sound confident and articulate; they can spout facts and may even have interesting ideas. But such people often exhibit the less benign aspects of smart talk as well: They focus on the negative, and they favor unnecessarily complex or abstract language. The former lapses into criticism for criticism's sake; the latter confuses people. Both tendencies can stop action in its tracks. How can you shut the smart-talk trap and close the knowing-doing gap? The authors lay out five methods that successful companies employ in order to translate the right kind of talk into intelligent action.

Thematic Continuities: Talking and Thinking about Adaptation in a Socially Complex Classroom

ERIC Educational Resources Information Center

Ash, Doris

2008-01-01

In this study I rely on sociocultural views of learning and teaching to describe how fifth- sixth-grade students in a Fostering a Community of Learners (FCL) classroom gradually adopted scientific ideas and language in a socially complex classroom. Students practiced talking science together, using everyday, scientific, and hybrid discourses as…

Concurrence of big data analytics and healthcare: A systematic review.

PubMed

Mehta, Nishita; Pandit, Anil

2018-06-01

The application of Big Data analytics in healthcare has immense potential for improving the quality of care, reducing waste and error, and reducing the cost of care. This systematic review of literature aims to determine the scope of Big Data analytics in healthcare including its applications and challenges in its adoption in healthcare. It also intends to identify the strategies to overcome the challenges. A systematic search of the articles was carried out on five major scientific databases: ScienceDirect, PubMed, Emerald, IEEE Xplore and Taylor & Francis. The articles on Big Data analytics in healthcare published in English language literature from January 2013 to January 2018 were considered. Descriptive articles and usability studies of Big Data analytics in healthcare and medicine were selected. Two reviewers independently extracted information on definitions of Big Data analytics; sources and applications of Big Data analytics in healthcare; challenges and strategies to overcome the challenges in healthcare. A total of 58 articles were selected as per the inclusion criteria and analyzed. The analyses of these articles found that: (1) researchers lack consensus about the operational definition of Big Data in healthcare; (2) Big Data in healthcare comes from the internal sources within the hospitals or clinics as well external sources including government, laboratories, pharma companies, data aggregators, medical journals etc.; (3) natural language processing (NLP) is most widely used Big Data analytical technique for healthcare and most of the processing tools used for analytics are based on Hadoop; (4) Big Data analytics finds its application for clinical decision support; optimization of clinical operations and reduction of cost of care (5) major challenge in adoption of Big Data analytics is non-availability of evidence of its practical benefits in healthcare. This review study unveils that there is a paucity of information on evidence of real-world use of

Hubble Spies Big Bang Frontiers

NASA Image and Video Library

2017-12-08

Observations by the NASA/ESA Hubble Space Telescope have taken advantage of gravitational lensing to reveal the largest sample of the faintest and earliest known galaxies in the universe. Some of these galaxies formed just 600 million years after the big bang and are fainter than any other galaxy yet uncovered by Hubble. The team has determined for the first time with some confidence that these small galaxies were vital to creating the universe that we see today. An international team of astronomers, led by Hakim Atek of the Ecole Polytechnique Fédérale de Lausanne, Switzerland, has discovered over 250 tiny galaxies that existed only 600-900 million years after the big bang— one of the largest samples of dwarf galaxies yet to be discovered at these epochs. The light from these galaxies took over 12 billion years to reach the telescope, allowing the astronomers to look back in time when the universe was still very young. Read more: www.nasa.gov/feature/goddard/hubble-spies-big-bang-frontiers Credit: NASA/ESA NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

The community-driven BiG CZ software system for integration and analysis of bio- and geoscience data in the critical zone

NASA Astrophysics Data System (ADS)

Aufdenkampe, A. K.; Mayorga, E.; Horsburgh, J. S.; Lehnert, K. A.; Zaslavsky, I.; Valentine, D. W., Jr.; Richard, S. M.; Cheetham, R.; Meyer, F.; Henry, C.; Berg-Cross, G.; Packman, A. I.; Aronson, E. L.

2014-12-01

Here we present the prototypes of a new scientific software system designed around the new Observations Data Model version 2.0 (ODM2, https://github.com/UCHIC/ODM2) to substantially enhance integration of biological and Geological (BiG) data for Critical Zone (CZ) science. The CZ science community takes as its charge the effort to integrate theory, models and data from the multitude of disciplines collectively studying processes on the Earth's surface. The central scientific challenge of the CZ science community is to develop a "grand unifying theory" of the critical zone through a theory-model-data fusion approach, for which the key missing need is a cyberinfrastructure for seamless 4D visual exploration of the integrated knowledge (data, model outputs and interpolations) from all the bio and geoscience disciplines relevant to critical zone structure and function, similar to today's ability to easily explore historical satellite imagery and photographs of the earth's surface using Google Earth. This project takes the first "BiG" steps toward answering that need. The overall goal of this project is to co-develop with the CZ science and broader community, including natural resource managers and stakeholders, a web-based integration and visualization environment for joint analysis of cross-scale bio and geoscience processes in the critical zone (BiG CZ), spanning experimental and observational designs. We will: (1) Engage the CZ and broader community to co-develop and deploy the BiG CZ software stack; (2) Develop the BiG CZ Portal web application for intuitive, high-performance map-based discovery, visualization, access and publication of data by scientists, resource managers, educators and the general public; (3) Develop the BiG CZ Toolbox to enable cyber-savvy CZ scientists to access BiG CZ Application Programming Interfaces (APIs); and (4) Develop the BiG CZ Central software stack to bridge data systems developed for multiple critical zone domains into a single

NASA EOSDIS Evolution in the BigData Era

NASA Technical Reports Server (NTRS)

Lynnes, Christopher

2015-01-01

NASA's EOSDIS system faces several challenges in the Big Data Era. Although volumes are large (but not unmanageably so), the variety of different data collections is daunting. That variety also brings with it a large and diverse user community. One key evolution EOSDIS is working toward is to enable more science analysis to be performed close to the data.

Mary Poppin's Approach to Human Mars Mission Entry, Descent and Landing

NASA Technical Reports Server (NTRS)

Venkatapathy, Ethiraj

2014-01-01

This is a talk on Human Mars Mission Challenges and the effort that is on-going at NASA ARC. The presentation will be used as part of the talk I will give at Purdue University on 8th April, 2016. This talk is based on the Director's colloquium I gave in 2014 at Ames, as part of the Center Director's Colloquium Series of the 75th Anniversary of Ames. Few additional charts have been added and these were from presentation made by Brandon Smith at the IEEE Aerospace Sciences 2016 meeting in Big Sky Montana, March, 2016.

Data Mining Citizen Science Results

NASA Astrophysics Data System (ADS)

Borne, K. D.

2012-12-01

Scientific discovery from big data is enabled through multiple channels, including data mining (through the application of machine learning algorithms) and human computation (commonly implemented through citizen science tasks). We will describe the results of new data mining experiments on the results from citizen science activities. Discovering patterns, trends, and anomalies in data are among the powerful contributions of citizen science. Establishing scientific algorithms that can subsequently re-discover the same types of patterns, trends, and anomalies in automatic data processing pipelines will ultimately result from the transformation of those human algorithms into computer algorithms, which can then be applied to much larger data collections. Scientific discovery from big data is thus greatly amplified through the marriage of data mining with citizen science.

The Next Big Thing - Eric Haseltine

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

Eric Haseltine

2009-09-16

Eric Haseltine, Haseltine Partners president and former chief of Walt Disney Imagineering, presented "The Next Big Thing," on Sept. 11, at the ORNL. He described the four "early warning signs" that a scientific breakthrough is imminent, and then suggested practical ways to turn these insights into breakthrough innovations. Haseltine is former director of research at the National Security Agency and associate director for science and technology for the director of National Intelligence, former executive vice president of Walt Disney Imagineering and director of engineering for Hughes Aircraft. He has 15 patents in optics, special effects and electronic media, and moremore » than 100 publications in science and technical journals, the web and Discover Magazine.« less

The Next Big Thing - Eric Haseltine

ScienceCinema

Eric Haseltine

2017-12-09

Eric Haseltine, Haseltine Partners president and former chief of Walt Disney Imagineering, presented "The Next Big Thing," on Sept. 11, at the ORNL. He described the four "early warning signs" that a scientific breakthrough is imminent, and then suggested practical ways to turn these insights into breakthrough innovations. Haseltine is former director of research at the National Security Agency and associate director for science and technology for the director of National Intelligence, former executive vice president of Walt Disney Imagineering and director of engineering for Hughes Aircraft. He has 15 patents in optics, special effects and electronic media, and more than 100 publications in science and technical journals, the web and Discover Magazine.

Talk at Mealtimes

ERIC Educational Resources Information Center

Clark, Christina

2013-01-01

This short report explores how many young people sit down with their family at mealtimes, how often they talk with their family when they do and the relationship between mealtime talk and young people's confidence in and attitudes towards communication skills. Using data from the latest annual survey of 34,910 children and young people, it shows…

BigBWA: approaching the Burrows-Wheeler aligner to Big Data technologies.

PubMed

Abuín, José M; Pichel, Juan C; Pena, Tomás F; Amigo, Jorge

2015-12-15

BigBWA is a new tool that uses the Big Data technology Hadoop to boost the performance of the Burrows-Wheeler aligner (BWA). Important reductions in the execution times were observed when using this tool. In addition, BigBWA is fault tolerant and it does not require any modification of the original BWA source code. BigBWA is available at the project GitHub repository: https://github.com/citiususc/BigBWA. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Therapy Talk: Analyzing Therapeutic Discourse

ERIC Educational Resources Information Center

Leahy, Margaret M.

2004-01-01

Therapeutic discourse is the talk-in-interaction that represents the social practice between clinician and client. This article invites speech-language pathologists to apply their knowledge of language to analyzing therapy talk and to learn how talking practices shape clinical roles and identities. A range of qualitative research approaches,…

The PACA Project: Convergence of Scientific Research, Social Media and Citizen Science in the Era of Astronomical Big Data

NASA Astrophysics Data System (ADS)

Yanamandra-Fisher, Padma A.

2015-08-01

The Pro-Am Collaborative Astronomy (PACA) project promotes and supports the professional-amateur astronomer collaboration in scientific research via social media and has been implemented in several comet observing campaigns. In 2014, two comet observing campaigns involving pro-am collaborations were initiated: (1) C/2013 A1 (C/SidingSpring) and (2) 67P/Churyumov-Gerasimenko (CG), target for ESA/Rosetta mission. The evolving need for individual customized observing campaigns has been incorporated into the evolution of The PACA Project that currently is focused on comets: from supporting observing campaigns of current comets, legacy data, historical comets; interconnected with social media and a set of shareable documents addressing observational strategies; consistent standards for data; data access, use, and storage, to align with the needs of professional observers in the era of astronmical big data. The empowerment of amateur astronomers vis-à-vis their partnerships with the professional scientists creates a new demographic of data scientists, enabling citizen science of the integrated data from both the professional and amateur communities.While PACA identifies a consistent collaborative approach to pro-am collaborations, given the volume of data generated for each campaign, new ways of rapid data analysis, mining access and storage are needed. Several interesting results emerged from the synergistic inclusion of both social media and amateur astronomers. The PACA Project is expanding to include pro-am collaborations on other solar system objects; allow for immersive outreach and include various types of astronomical communities, ranging from individuals, to astronmical societies and telescopic networks. Enabling citizen science research in the era of astronomical big data is a challenge which requires innovative approaches and integration of professional and amateur astronomers with data scientists and some examples of recent projects will be highlighted.

Next Generation Astronomical Data Processing using Big Data Technologies from the Apache Software Foundation

NASA Astrophysics Data System (ADS)

Mattmann, Chris

2014-04-01

In this era of exascale instruments for astronomy we must naturally develop next generation capabilities for the unprecedented data volume and velocity that will arrive due to the veracity of these ground-based sensor and observatories. Integrating scientific algorithms stewarded by scientific groups unobtrusively and rapidly; intelligently selecting data movement technologies; making use of cloud computing for storage and processing; and automatically extracting text and metadata and science from any type of file are all needed capabilities in this exciting time. Our group at NASA JPL has promoted the use of open source data management technologies available from the Apache Software Foundation (ASF) in pursuit of constructing next generation data management and processing systems for astronomical instruments including the Expanded Very Large Array (EVLA) in Socorro, NM and the Atacama Large Milimetre/Sub Milimetre Array (ALMA); as well as for the KAT-7 project led by SKA South Africa as a precursor to the full MeerKAT telescope. In addition we are funded currently by the National Science Foundation in the US to work with MIT Haystack Observatory and the University of Cambridge in the UK to construct a Radio Array of Portable Interferometric Devices (RAPID) that will undoubtedly draw from the rich technology advances underway. NASA JPL is investing in a strategic initiative for Big Data that is pulling in these capabilities and technologies for astronomical instruments and also for Earth science remote sensing. In this talk I will describe the above collaborative efforts underway and point to solutions in open source from the Apache Software Foundation that can be deployed and used today and that are already bringing our teams and projects benefits. I will describe how others can take advantage of our experience and point towards future application and contribution of these tools.

Making the Most of Talk

ERIC Educational Resources Information Center

Gilles, Carol

2010-01-01

Research supports what many teachers have long known: talk is a valuable tool for learning. But how can we incorporate talk and still keep students on task, thinking collectively and deeply? Gillis offers a solid theoretical foundation for incorporating talk throughout the curriculum, and then provides practical help for implementing it, with…

Measuring adolescent science motivation

NASA Astrophysics Data System (ADS)

Schumm, Maximiliane F.; Bogner, Franz X.

2016-02-01

To monitor science motivation, 232 tenth graders of the college preparatory level ('Gymnasium') completed the Science Motivation Questionnaire II (SMQ-II). Additionally, personality data were collected using a 10-item version of the Big Five Inventory. A subsequent exploratory factor analysis based on the eigenvalue-greater-than-one criterion, extracted a loading pattern, which in principle, followed the SMQ-II frame. Two items were dropped due to inappropriate loadings. The remaining SMQ-II seems to provide a consistent scale matching the findings in literature. Nevertheless, also possible shortcomings of the scale are discussed. Data showed a higher perceived self-determination in girls which seems compensated by their lower self-efficacy beliefs leading to equality of females and males in overall science motivation scores. Additionally, the Big Five personality traits and science motivation components show little relationship.

Embers of society: Firelight talk among the Ju/’hoansi Bushmen

PubMed Central

Wiessner, Polly W.

2014-01-01

Much attention has been focused on control of fire in human evolution and the impact of cooking on anatomy, social, and residential arrangements. However, little is known about what transpired when firelight extended the day, creating effective time for social activities that did not conflict with productive time for subsistence activities. Comparison of 174 day and nighttime conversations among the Ju/’hoan (!Kung) Bushmen of southern Africa, supplemented by 68 translated texts, suggests that day talk centers on economic matters and gossip to regulate social relations. Night activities steer away from tensions of the day to singing, dancing, religious ceremonies, and enthralling stories, often about known people. Such stories describe the workings of entire institutions in a small-scale society with little formal teaching. Night talk plays an important role in evoking higher orders of theory of mind via the imagination, conveying attributes of people in broad networks (virtual communities), and transmitting the “big picture” of cultural institutions that generate regularity of behavior, cooperation, and trust at the regional level. Findings from the Ju/’hoan are compared with other hunter-gatherer societies and related to the widespread human use of firelight for intimate conversation and our appetite for evening stories. The question is raised as to what happens when economically unproductive firelit time is turned to productive time by artificial lighting. PMID:25246574

Mash-up of techniques between data crawling/transfer, data preservation/stewardship and data processing/visualization technologies on a science cloud system designed for Earth and space science: a report of successful operation and science projects of the NICT Science Cloud

NASA Astrophysics Data System (ADS)

Murata, K. T.

2014-12-01

Data-intensive or data-centric science is 4th paradigm after observational and/or experimental science (1st paradigm), theoretical science (2nd paradigm) and numerical science (3rd paradigm). Science cloud is an infrastructure for 4th science methodology. The NICT science cloud is designed for big data sciences of Earth, space and other sciences based on modern informatics and information technologies [1]. Data flow on the cloud is through the following three techniques; (1) data crawling and transfer, (2) data preservation and stewardship, and (3) data processing and visualization. Original tools and applications of these techniques have been designed and implemented. We mash up these tools and applications on the NICT Science Cloud to build up customized systems for each project. In this paper, we discuss science data processing through these three steps. For big data science, data file deployment on a distributed storage system should be well designed in order to save storage cost and transfer time. We developed a high-bandwidth virtual remote storage system (HbVRS) and data crawling tool, NICTY/DLA and Wide-area Observation Network Monitoring (WONM) system, respectively. Data files are saved on the cloud storage system according to both data preservation policy and data processing plan. The storage system is developed via distributed file system middle-ware (Gfarm: GRID datafarm). It is effective since disaster recovery (DR) and parallel data processing are carried out simultaneously without moving these big data from storage to storage. Data files are managed on our Web application, WSDBank (World Science Data Bank). The big-data on the cloud are processed via Pwrake, which is a workflow tool with high-bandwidth of I/O. There are several visualization tools on the cloud; VirtualAurora for magnetosphere and ionosphere, VDVGE for google Earth, STICKER for urban environment data and STARStouch for multi-disciplinary data. There are 30 projects running on the NICT

Characterizing the changes in teaching practice during first semester implementation of an argument-based inquiry approach in a middle school science classroom

NASA Astrophysics Data System (ADS)

Pinney, Brian Robert John

classroom video with transcripts, teacher interview, researcher field notes, student journals, teacher lesson plans from previous years, and a student questionnaire. Data analysis used a basic qualitative approach. The results showed (1) only the first time period had a true big idea, while the other two units contained topics, (2) each semester contained a similar use for the given big idea, though its role in the class was reduced after the opening activity, (3) the types of teacher questions shifted toward students explaining their comprehension of ideas and more students were involved in discussing each idea and for more turns of talk than in earlier time periods, (4) understanding science term definitions became more prominent later in the semester, with more stating science terms occurring earlier in the semester, (5) no significant changes were seen to the use of argument or claims and evidence throughout the study. The findings have informed theory and practice about science argumentation, the practice of whole-class dialogue, and the understanding of practice along four aspects: (1) apparent lack of understanding about big ideas and how to utilize them as the central organizing feature of a unit, (2) independent development of dialogue and argument, (3) apparent lack of understanding about the structure of argument and use of basic terminology with argument and big ideas, (4) challenges of ABI implementation. This study provides insight into the importance of prolonged and persistent professional development with ABI in teaching practice.

[Big data in imaging].

PubMed

Sewerin, Philipp; Ostendorf, Benedikt; Hueber, Axel J; Kleyer, Arnd

2018-04-01

Until now, most major medical advancements have been achieved through hypothesis-driven research within the scope of clinical trials. However, due to a multitude of variables, only a certain number of research questions could be addressed during a single study, thus rendering these studies expensive and time consuming. Big data acquisition enables a new data-based approach in which large volumes of data can be used to investigate all variables, thus opening new horizons. Due to universal digitalization of the data as well as ever-improving hard- and software solutions, imaging would appear to be predestined for such analyses. Several small studies have already demonstrated that automated analysis algorithms and artificial intelligence can identify pathologies with high precision. Such automated systems would also seem well suited for rheumatology imaging, since a method for individualized risk stratification has long been sought for these patients. However, despite all the promising options, the heterogeneity of the data and highly complex regulations covering data protection in Germany would still render a big data solution for imaging difficult today. Overcoming these boundaries is challenging, but the enormous potential advances in clinical management and science render pursuit of this goal worthwhile.

How Does National Scientific Funding Support Emerging Interdisciplinary Research: A Comparison Study of Big Data Research in the US and China.

PubMed

Huang, Ying; Zhang, Yi; Youtie, Jan; Porter, Alan L; Wang, Xuefeng

2016-01-01

How do funding agencies ramp-up their capabilities to support research in a rapidly emerging area? This paper addresses this question through a comparison of research proposals awarded by the US National Science Foundation (NSF) and the National Natural Science Foundation of China (NSFC) in the field of Big Data. Big data is characterized by its size and difficulties in capturing, curating, managing and processing it in reasonable periods of time. Although Big Data has its legacy in longstanding information technology research, the field grew very rapidly over a short period. We find that the extent of interdisciplinarity is a key aspect in how these funding agencies address the rise of Big Data. Our results show that both agencies have been able to marshal funding to support Big Data research in multiple areas, but the NSF relies to a greater extent on multi-program funding from different fields. We discuss how these interdisciplinary approaches reflect the research hot-spots and innovation pathways in these two countries.

What's so different about big data?. A primer for clinicians trained to think epidemiologically.

PubMed

Iwashyna, Theodore J; Liu, Vincent

2014-09-01

The Big Data movement in computer science has brought dramatic changes in what counts as data, how those data are analyzed, and what can be done with those data. Although increasingly pervasive in the business world, it has only recently begun to influence clinical research and practice. As Big Data draws from different intellectual traditions than clinical epidemiology, the ideas may be less familiar to practicing clinicians. There is an increasing role of Big Data in health care, and it has tremendous potential. This Demystifying Data Seminar identifies four main strands in Big Data relevant to health care. The first is the inclusion of many new kinds of data elements into clinical research and operations, in a volume not previously routinely used. Second, Big Data asks different kinds of questions of data and emphasizes the usefulness of analyses that are explicitly associational but not causal. Third, Big Data brings new analytic approaches to bear on these questions. And fourth, Big Data embodies a new set of aspirations for a breaking down of distinctions between research data and operational data and their merging into a continuously learning health system.

Disproof of Big Bang's Foundational Expansion Redshift Assumption Overthrows the Big Bang and Its No-Center Universe and Is Replaced by a Spherically Symmetric Model with Nearby Center with the 2.73 K CMR Explained by Vacuum Gravity and Doppler Effects

NASA Astrophysics Data System (ADS)

Gentry, Robert

2015-04-01

Big bang theory holds its central expansion redshift assumption quickly reduced the theorized radiation flash to ~ 1010 K, and then over 13.8 billion years reduced it further to the present 2.73 K CMR. Weinberg claims this 2.73 K value agrees with big bang theory so well that ``...we can be sure that this radiation was indeed left over from a time about a million years after the `big bang.' '' (TF3M, p180, 1993 ed.) Actually his conclusion is all based on big bang's in-flight wavelength expansion being a valid physical process. In fact all his surmising is nothing but science fiction because our disproof of GR-induced in-flight wavelength expansion [1] definitely proves the 2.73 K CMR could never have been the wavelength-expanded relic of any radiation, much less the presumed big bang's. This disproof of big bang's premier prediction is a death blow to the big bang as it is also to the idea that the redshifts in Hubble's redshift relation are expansion shifts; this negates Friedmann's everywhere-the-same, no-center universe concept and proves it does have a nearby Center, a place which can be identified in Psalm 103:19 and in Revelation 20:11 as the location of God's eternal throne. Widely published (Science, Nature, ARNS) evidence of Earth's fiat creation will also be presented. The research is supported by the God of Creation. This paper [1] is in for publication.

Benchmarking Big Data Systems and the BigData Top100 List.

PubMed

Baru, Chaitanya; Bhandarkar, Milind; Nambiar, Raghunath; Poess, Meikel; Rabl, Tilmann

2013-03-01

"Big data" has become a major force of innovation across enterprises of all sizes. New platforms with increasingly more features for managing big datasets are being announced almost on a weekly basis. Yet, there is currently a lack of any means of comparability among such platforms. While the performance of traditional database systems is well understood and measured by long-established institutions such as the Transaction Processing Performance Council (TCP), there is neither a clear definition of the performance of big data systems nor a generally agreed upon metric for comparing these systems. In this article, we describe a community-based effort for defining a big data benchmark. Over the past year, a Big Data Benchmarking Community has become established in order to fill this void. The effort focuses on defining an end-to-end application-layer benchmark for measuring the performance of big data applications, with the ability to easily adapt the benchmark specification to evolving challenges in the big data space. This article describes the efforts that have been undertaken thus far toward the definition of a BigData Top100 List. While highlighting the major technical as well as organizational challenges, through this article, we also solicit community input into this process.

The use of big data in transfusion medicine.

PubMed

Pendry, K

2015-06-01

'Big data' refers to the huge quantities of digital information now available that describe much of human activity. The science of data management and analysis is rapidly developing to enable organisations to convert data into useful information and knowledge. Electronic health records and new developments in Pathology Informatics now support the collection of 'big laboratory and clinical data', and these digital innovations are now being applied to transfusion medicine. To use big data effectively, we must address concerns about confidentiality and the need for a change in culture and practice, remove barriers to adopting common operating systems and data standards and ensure the safe and secure storage of sensitive personal information. In the UK, the aim is to formulate a single set of data and standards for communicating test results and so enable pathology data to contribute to national datasets. In transfusion, big data has been used for benchmarking, detection of transfusion-related complications, determining patterns of blood use and definition of blood order schedules for surgery. More generally, rapidly available information can monitor compliance with key performance indicators for patient blood management and inventory management leading to better patient care and reduced use of blood. The challenges of enabling reliable systems and analysis of big data and securing funding in the restrictive financial climate are formidable, but not insurmountable. The promise is that digital information will soon improve the implementation of best practice in transfusion medicine and patient blood management globally. © 2015 British Blood Transfusion Society.

Big data, big knowledge: big data for personalized healthcare.

PubMed

Viceconti, Marco; Hunter, Peter; Hose, Rod

2015-07-01

The idea that the purely phenomenological knowledge that we can extract by analyzing large amounts of data can be useful in healthcare seems to contradict the desire of VPH researchers to build detailed mechanistic models for individual patients. But in practice no model is ever entirely phenomenological or entirely mechanistic. We propose in this position paper that big data analytics can be successfully combined with VPH technologies to produce robust and effective in silico medicine solutions. In order to do this, big data technologies must be further developed to cope with some specific requirements that emerge from this application. Such requirements are: working with sensitive data; analytics of complex and heterogeneous data spaces, including nontextual information; distributed data management under security and performance constraints; specialized analytics to integrate bioinformatics and systems biology information with clinical observations at tissue, organ and organisms scales; and specialized analytics to define the "physiological envelope" during the daily life of each patient. These domain-specific requirements suggest a need for targeted funding, in which big data technologies for in silico medicine becomes the research priority.

Booktalking Science Fiction to Young Adults.

ERIC Educational Resources Information Center

Klause, Annette Curtis

1990-01-01

Identifies the elements of science fiction that might appeal to adolescent readers and offers suggestions for developing innovative book talks on science fiction books. A bibliography of 133 books, categorized by subgenres such as hard science, space travel, and mysteries, is provided. (eight references) (CLB)

Talk and community: The place of reporting in a life sciences laboratory

NASA Astrophysics Data System (ADS)

Swieringa, Robert Cecil

This study investigates the routine situated communicative practice within the weekly meetings of a life sciences laboratory. The key, constitutive discourse of "reporting" is examined as an activity in which participants jointly sustain the work community of the laboratory and manage their own work within this community. This study seeks to contribute to studies of small groups by focusing upon the multifunctionality and situated nature of the meeting interactions within this enduring "bona fide" group as participants undertake multiple goals associated with their own progress and with the overlapping contexts of the setting. It also seeks to contribute to investigations of institutional talk and activity by examining "reporting" as interaction with institutional and community consequences for members of the community. This study takes a practice-oriented perspective to investigate the laboratory as a community of practice, focusing upon the "activity" of interaction as the overall unit of analysis. Ethnographic materials (involving observation, interviews, conversations, and activity logs) and discourse analysis techniques (involving audiotaping and transcriptions of meetings) were used to locate and record data within a university entomology laboratory over a two year period. Through triangulation of data, "reporting" is identified as a key discourse activity within the laboratory. As situated communicative practice within the weekly meetings, reporting is found to be compelled discourse through which interactants interactively manage one's ongoing goals and activity while temporally situating that activity within the broader stream of laboratory work. This study provides an example of how engagement in situated discursive activity provides for the coordination of individual lines of progress within the ongoing work of a community.

Talk to Your Kids about Sex

MedlinePlus

... Topic En español Talk to Your Kids about Sex Browse Sections The Basics Overview Bodies and Puberty ... healthy expectations for their relationships. Talk about opposite-sex and same-sex relationships. When you talk about ...

Big agronomic data validates an oxymoron: Sustainable intensification under climate change

USDA-ARS?s Scientific Manuscript database

Crop science is increasingly embracing big data to reconcile the apparent rift between intensification of food production and sustainability of a steadily stressed production base. A strategy based on long-term agroecosystem research and modeling simulation of crops, crop rotations and cropping sys...

Economics and econophysics in the era of Big Data

NASA Astrophysics Data System (ADS)

Cheong, Siew Ann

2016-12-01

There is an undeniable disconnect between theory-heavy economics and the real world, and some cross polination of ideas with econophysics, which is more balanced between data and models, might help economics along the way to become a truly scientific enterprise. With the coming of the era of Big Data, this transformation of economics into a data-driven science is becoming more urgent. In this article, I use the story of Kepler's discovery of his three laws of planetary motion to enlarge the framework of the scientific approach, from one that focuses on experimental sciences, to one that accommodates observational sciences, and further to one that embraces data mining and machine learning. I distinguish between the ontological values of Kepler's Laws vis-a-vis Newton's Laws, and argue that the latter is more fundamental because it is able to explain the former. I then argue that the fundamental laws of economics lie not in mathematical equations, but in models of adaptive economic agents. With this shift in mind set, it becomes possible to think about how interactions between agents can lead to the emergence of multiple stable states and critical transitions, and complex adaptive policies and regulations that might actually work in the real world. Finally, I discuss how Big Data, exploratory agent-based modeling, and predictive agent-based modeling can come together in a unified framework to make economics a true science.

Strategic Talk in Film.

PubMed

Payr, Sabine; Skowron, Marcin; Dobrosovestnova, Anna; Trapp, Martin; Trappl, Robert

2017-01-01

Conversational robots and agents are being designed for educational and/or persuasive tasks, e.g., health or fitness coaching. To pursue such tasks over a long time, they will need a complex model of the strategic goal, a variety of strategies to implement it in interaction, and the capability of strategic talk. Strategic talk is incipient ongoing conversation in which at least one participant has the objective of changing the other participant's attitudes or goals. The paper is based on the observation that strategic talk can stretch over considerable periods of time and a number of conversational segments. Film dialogues are taken as a source to develop a model of the strategic talk of mentor characters. A corpus of film mentor utterances is annotated on the basis of the model, and the data are interpreted to arrive at insights into mentor behavior, especially into the realization and sequencing of strategies.

Talking to the Pharmacist (For Parents)

MedlinePlus

... for Educators Search English Español Talking to the Pharmacist KidsHealth / For Parents / Talking to the Pharmacist What's ... and families privately. Reasons to Talk to the Pharmacist Pharmacists cannot diagnose medical conditions. But they can ...

[Big Data and Public Health - Results of the Working Group 1 of the Forum Future Public Health, Berlin 2016].

PubMed

Moebus, Susanne; Kuhn, Joseph; Hoffmann, Wolfgang

2017-11-01

Big Data is a diffuse term, which can be described as an approach to linking gigantic and often unstructured data sets. Big Data is used in many corporate areas. For Public Health (PH), however, Big Data is not a well-developed topic. In this article, Big Data is explained according to the intention of use, information efficiency, prediction and clustering. Using the example of application in science, patient care, equal opportunities and smart cities, typical challenges and open questions of Big Data for PH are outlined. In addition to the inevitable use of Big Data, networking is necessary, especially with knowledge-carriers and decision-makers from politics and health care practice. © Georg Thieme Verlag KG Stuttgart · New York.

Most science spared big budget bite

NASA Astrophysics Data System (ADS)

Richman, Barbara T.

Most science budgets emerged unscathed from President Ronald Reagan's fiscal 1983 budget proposal. Total funding for research and development came out slightly ahead of inflation, as did funding for basic research (Eos, February 16, p. 162). The National Science Foundation (NSF) edged past the projected 7.3% inflation rate for 1982, and the National Aeronautics and Space Administration (NASA) budget is to be increased by 10.6%. However, the U.S. Geological Survey (USGS) is budgeted for a 4.2% increase in funding, and the National Oceanic and Atmospheric Administration (NOAA) will take an 8.3% cut.

Automated protocols for spaceborne sub-meter resolution "Big Data" products for Earth Science

NASA Astrophysics Data System (ADS)

Neigh, C. S. R.; Carroll, M.; Montesano, P.; Slayback, D. A.; Wooten, M.; Lyapustin, A.; Shean, D. E.; Alexandrov, O.; Macander, M. J.; Tucker, C. J.

2017-12-01

The volume of available remotely sensed data has grown exceeding Petabytes per year and the cost for data, storage systems and compute power have both dropped exponentially. This has opened the door for "Big Data" processing systems with high-end computing (HEC) such as the Google Earth Engine, NASA Earth Exchange (NEX), and NASA Center for Climate Simulation (NCCS). At the same time, commercial very high-resolution (VHR) satellites have grown into a constellation with global repeat coverage that can support existing NASA Earth observing missions with stereo and super-spectral capabilities. Through agreements with the National Geospatial-Intelligence Agency NASA-Goddard Space Flight Center is acquiring Petabytes of global sub-meter to 4 meter resolution imagery from WorldView-1,2,3 Quickbird-2, GeoEye-1 and IKONOS-2 satellites. These data are a valuable no-direct cost for the enhancement of Earth observation research that supports US government interests. We are currently developing automated protocols for generating VHR products to support NASA's Earth observing missions. These include two primary foci: 1) on demand VHR 1/2° ortho mosaics - process VHR to surface reflectance, orthorectify and co-register multi-temporal 2 m multispectral imagery compiled as user defined regional mosaics. This will provide an easy access dataset to investigate biodiversity, tree canopy closure, surface water fraction, and cropped area for smallholder agriculture; and 2) on demand VHR digital elevation models (DEMs) - process stereo VHR to extract VHR DEMs with the NASA Ames stereo pipeline. This will benefit Earth surface studies on the cryosphere (glacier mass balance, flow rates and snow depth), hydrology (lake/water body levels, landslides, subsidence) and biosphere (forest structure, canopy height/cover) among others. Recent examples of products used in NASA Earth Science projects will be provided. This HEC API could foster surmounting prior spatial-temporal limitations while

Evolution of the Air Toxics under the Big Sky Program

ERIC Educational Resources Information Center

Marra, Nancy; Vanek, Diana; Hester, Carolyn; Holian, Andrij; Ward, Tony; Adams, Earle; Knuth, Randy

2011-01-01

As a yearlong exploration of air quality and its relation to respiratory health, the "Air Toxics Under the Big Sky" program offers opportunities for students to learn and apply science process skills through self-designed inquiry-based research projects conducted within their communities. The program follows a systematic scope and sequence…

Strategic Talk in Film

PubMed Central

Payr, Sabine; Skowron, Marcin; Dobrosovestnova, Anna; Trapp, Martin; Trappl, Robert

2017-01-01

ABSTRACT Conversational robots and agents are being designed for educational and/or persuasive tasks, e.g., health or fitness coaching. To pursue such tasks over a long time, they will need a complex model of the strategic goal, a variety of strategies to implement it in interaction, and the capability of strategic talk. Strategic talk is incipient ongoing conversation in which at least one participant has the objective of changing the other participant’s attitudes or goals. The paper is based on the observation that strategic talk can stretch over considerable periods of time and a number of conversational segments. Film dialogues are taken as a source to develop a model of the strategic talk of mentor characters. A corpus of film mentor utterances is annotated on the basis of the model, and the data are interpreted to arrive at insights into mentor behavior, especially into the realization and sequencing of strategies. PMID:29375243

Science in the Trump era

NASA Astrophysics Data System (ADS)

Durrani, Matin

2017-04-01

US physicist Rush Holt, who spent 16 years as a Democrat in the US Congress and is now chief executive of the American Association for the Advancement of Science, talks to Matin Durrani about the prospects for science with Donald Trump as president

Geologic map of Big Bend National Park, Texas

USGS Publications Warehouse

Turner, Kenzie J.; Berry, Margaret E.; Page, William R.; Lehman, Thomas M.; Bohannon, Robert G.; Scott, Robert B.; Miggins, Daniel P.; Budahn, James R.; Cooper, Roger W.; Drenth, Benjamin J.; Anderson, Eric D.; Williams, Van S.

2011-01-01

The purpose of this map is to provide the National Park Service and the public with an updated digital geologic map of Big Bend National Park (BBNP). The geologic map report of Maxwell and others (1967) provides a fully comprehensive account of the important volcanic, structural, geomorphological, and paleontological features that define BBNP. However, the map is on a geographically distorted planimetric base and lacks topography, which has caused difficulty in conducting GIS-based data analyses and georeferencing the many geologic features investigated and depicted on the map. In addition, the map is outdated, excluding significant data from numerous studies that have been carried out since its publication more than 40 years ago. This report includes a modern digital geologic map that can be utilized with standard GIS applications to aid BBNP researchers in geologic data analysis, natural resource and ecosystem management, monitoring, assessment, inventory activities, and educational and recreational uses. The digital map incorporates new data, many revisions, and greater detail than the original map. Although some geologic issues remain unresolved for BBNP, the updated map serves as a foundation for addressing those issues. Funding for the Big Bend National Park geologic map was provided by the United States Geological Survey (USGS) National Cooperative Geologic Mapping Program and the National Park Service. The Big Bend mapping project was administered by staff in the USGS Geology and Environmental Change Science Center, Denver, Colo. Members of the USGS Mineral and Environmental Resources Science Center completed investigations in parallel with the geologic mapping project. Results of these investigations addressed some significant current issues in BBNP and the U.S.-Mexico border region, including contaminants and human health, ecosystems, and water resources. Funding for the high-resolution aeromagnetic survey in BBNP, and associated data analyses and

Recombinant Science: The Birth of the Relativistic Heavy Ion Collider (431st Brookhaven Lecture)

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

Crease, Robert P.

2007-12-12

As part of the celebration of Brookhaven Lab's 60th anniversary, Robert P. Crease, the Chair of the Philosophy Department at Stony Brook University and BNL's historian, will present the second of two talks on the Lab's history. In "Recombinant Science: The Birth of the Relativistic Heavy Ion Collider," Dr. Crease will focus on the creation of the world's most powerful colliding accelerator for nuclear physics. Known as RHIC, the collider, as Dr. Crease will recount, was formally proposed in 1984, received initial construction funding from the U.S. Department of Energy in 1991, and started operating in 2000. In 2005, themore » discovery at RHIC of the world's most perfect liquid, a state of matter that last existed just moments after the Big Bang, was announced, and, since then, this perfect liquid of quarks and gluons has been the subject of intense study.« less

Get Them Talking! Using Student-Led Book Talks in the Primary Grades

ERIC Educational Resources Information Center

Hudson, Alida K.

2016-01-01

This teaching tip details one teacher's implementation of student-led book talks in her primary-grade classroom. The author describes a simple gradual-release method that she has successfully used with her students in order to get them talking about the books that they are reading independently. She found that when used in the readers' workshop…

Big Crater as Viewed by Pathfinder Lander - Anaglyph

NASA Technical Reports Server (NTRS)

1997-01-01

The 'Big Crater' is actually a relatively small Martian crater to the southeast of the Mars Pathfinder landing site. It is 1500 meters (4900 feet) in diameter, or about the same size as Meteor Crater in Arizona. Superimposed on the rim of Big Crater (the central part of the rim as seen here) is a smaller crater nicknamed 'Rimshot Crater.' The distance to this smaller crater, and the nearest portion of the rim of Big Crater, is 2200 meters (7200 feet). To the right of Big Crater, south from the spacecraft, almost lost in the atmospheric dust 'haze,' is the large streamlined mountain nicknamed 'Far Knob.' This mountain is over 450 meters (1480 feet) tall, and is over 30 kilometers (19 miles) from the spacecraft. Another, smaller and closer knob, nicknamed 'Southeast Knob' can be seen as a triangular peak to the left of the flanks of the Big Crater rim. This knob is 21 kilometers (13 miles) southeast from the spacecraft.

The larger features visible in this scene - Big Crater, Far Knob, and Southeast Knob - were discovered on the first panoramas taken by the IMP camera on the 4th of July, 1997, and subsequently identified in Viking Orbiter images taken over 20 years ago. The scene includes rocky ridges and swales or 'hummocks' of flood debris that range from a few tens of meters away from the lander to the distance of South Twin Peak. The largest rock in the nearfield, just left of center in the foreground, nicknamed 'Otter', is about 1.5 meters (4.9 feet) long and 10 meters (33 feet) from the spacecraft.

This view of Big Crater was produced by combining 6 individual 'Superpan' scenes from the left and right eyes of the IMP camera. Each frame consists of 8 individual frames (left eye) and 7 frames (right eye) taken with different color filters that were enlarged by 500% and then co-added using Adobe Photoshop to produce, in effect, a super-resolution panchromatic frame that is sharper than an individual frame would be.

The anaglyph view of Big Crater was

Classroom Talk: Co-Constructing a "Difficult Student"

ERIC Educational Resources Information Center

Graff, Nelson

2009-01-01

Background: Research on teacher-student relationships has focused logically on classroom talk. Investigations of classroom talk range from broad consideration of the structures of such talk to a somewhat narrower focus on the interpersonal dimensions of such talk, and their consequences for student achievement and motivation. Purpose: This study…

Big Ideas in Volcanology-a new way to teach and think about the subject?

NASA Astrophysics Data System (ADS)

Rose, W. I.

2011-12-01

As intense work with identifying and presenting earth science to middle school science teachers in the MiTEP project advances, I have realized that tools used to connect with teachers and students of earth science in general and especially to promote higher levels of learning, should be advantageous in graduate teaching as well. In my last of 40 years of teaching graduate volcanology, I have finally organized the class around ideas based on Earth Science Literacy Principles and on common misconceptions. As such, I propose and fully explore the twelve "big ideas" of volcanology at the rate of one per week. This curricular organization highlights the ideas in volcanology that have major impact beyond volcanology itself and explores the roots and global ramifications of these ideas. Together they show how volcanology interfaces with the science world and the "real" world or how volcanologists interface with "real" people. In addition to big ideas we explore difficult and misunderstood concepts and the public misconceptions associated with each. The new organization and its focus on understanding relevant and far reaching concepts and hypotheses provides a refreshing context for advanced learning. It is planned to be the basis for an interactive website.

Unlocking the Power of Big Data at the National Institutes of Health.

PubMed

Coakley, Meghan F; Leerkes, Maarten R; Barnett, Jason; Gabrielian, Andrei E; Noble, Karlynn; Weber, M Nick; Huyen, Yentram

2013-09-01

The era of "big data" presents immense opportunities for scientific discovery and technological progress, with the potential to have enormous impact on research and development in the public sector. In order to capitalize on these benefits, there are significant challenges to overcome in data analytics. The National Institute of Allergy and Infectious Diseases held a symposium entitled "Data Science: Unlocking the Power of Big Data" to create a forum for big data experts to present and share some of the creative and innovative methods to gleaning valuable knowledge from an overwhelming flood of biological data. A significant investment in infrastructure and tool development, along with more and better-trained data scientists, may facilitate methods for assimilation of data and machine learning, to overcome obstacles such as data security, data cleaning, and data integration.

What’s So Different about Big Data?. A Primer for Clinicians Trained to Think Epidemiologically

PubMed Central

Liu, Vincent

2014-01-01

The Big Data movement in computer science has brought dramatic changes in what counts as data, how those data are analyzed, and what can be done with those data. Although increasingly pervasive in the business world, it has only recently begun to influence clinical research and practice. As Big Data draws from different intellectual traditions than clinical epidemiology, the ideas may be less familiar to practicing clinicians. There is an increasing role of Big Data in health care, and it has tremendous potential. This Demystifying Data Seminar identifies four main strands in Big Data relevant to health care. The first is the inclusion of many new kinds of data elements into clinical research and operations, in a volume not previously routinely used. Second, Big Data asks different kinds of questions of data and emphasizes the usefulness of analyses that are explicitly associational but not causal. Third, Big Data brings new analytic approaches to bear on these questions. And fourth, Big Data embodies a new set of aspirations for a breaking down of distinctions between research data and operational data and their merging into a continuously learning health system. PMID:25102315

Big data uncertainties.

PubMed

Maugis, Pierre-André G

2018-07-01

Big data-the idea that an always-larger volume of information is being constantly recorded-suggests that new problems can now be subjected to scientific scrutiny. However, can classical statistical methods be used directly on big data? We analyze the problem by looking at two known pitfalls of big datasets. First, that they are biased, in the sense that they do not offer a complete view of the populations under consideration. Second, that they present a weak but pervasive level of dependence between all their components. In both cases we observe that the uncertainty of the conclusion obtained by statistical methods is increased when used on big data, either because of a systematic error (bias), or because of a larger degree of randomness (increased variance). We argue that the key challenge raised by big data is not only how to use big data to tackle new problems, but to develop tools and methods able to rigorously articulate the new risks therein. Copyright © 2016. Published by Elsevier Ltd.

Birth talk in second stage labor.

PubMed

Bergstrom, Linda; Richards, Lori; Proctor, Adele; Avila, Leticia Bohrer; Morse, Janice M; Roberts, Joyce E

2009-07-01

In this secondary analysis of videotape data, we describe birth talk demonstrated by caregivers to women during the second stage of labor. Birth talk is a distinctive verbal register or a set of linguistic features that are used with particular behaviors during specific situations, has a particular communication purpose, and is characterized by distinctive language features. Birth talk is found cross-culturally among speakers of diverse languages. Our findings show that birth talk occurred mainly during contractions and co-occurred with two general styles of caregiving: "directed toward forced bearing down" and "supportive of physiologic bearing down." We also describe talk that occurred during rest periods, which was similar across the two styles. Caregivers' use of language tended to be either procedural (giving directions, instructions) or comfort related (encouraging and supporting). Linguistic features of the talk consisted of utterances of short duration, level pitch patterns with no sudden pitch shifts, and a restricted pitch range.

NASA at the Space & Science Festival

NASA Image and Video Library

2017-08-05

NASA Acting Chief Technologist Douglas Terrier gives a talk to teachers attending a professional development workshop held in tandem with the Intrepid Space & Science Festival, Saturday, Aug. 5, 2017 at the Intrepid Sea, Air & Space Museum in New York City. The week-long festival featured talks, films and cutting-edge displays showcasing NASA technology. Photo Credit: (NASA/Bill Ingalls)

Has the time come for big science in wildlife health?

USGS Publications Warehouse

Sleeman, Jonathan M.

2013-01-01

The consequences of wildlife emerging diseases are global and profound with increased burden on the public health system, negative impacts on the global economy, declines and extinctions of wildlife species, and subsequent loss of ecological integrity. Examples of health threats to wildlife include Batrachochytrium dendrobatidis, which causes a cutaneous fungal infection of amphibians and is linked to declines of amphibians globally; and the recently discovered Pseudogymnoascus (Geomyces) destructans, the etiologic agent of white nose syndrome which has caused precipitous declines of North American bat species. Of particular concern are the novel pathogens that have emerged as they are particularly devastating and challenging to manage. A big science approach to wildlife health research is needed if we are to make significant and enduring progress in managing these diseases. The advent of new analytical models and bench assays will provide us with the mathematical and molecular tools to identify and anticipate threats to wildlife, and understand the ecology and epidemiology of these diseases. Specifically, new molecular diagnostic techniques have opened up avenues for pathogen discovery, and the application of spatially referenced databases allows for risk assessments that can assist in targeting surveillance. Long-term, systematic collection of data for wildlife health and integration with other datasets is also essential. Multidisciplinary research programs should be expanded to increase our understanding of the drivers of emerging diseases and allow for the development of better disease prevention and management tools, such as vaccines. Finally, we need to create a National Fish and Wildlife Health Network that provides the operational framework (governance, policies, procedures, etc.) by which entities with a stake in wildlife health cooperate and collaborate to achieve optimal outcomes for human, animal, and ecosystem health.

The Big Bang: UK Young Scientists' and Engineers' Fair 2010

ERIC Educational Resources Information Center

Allison, Simon

2010-01-01

The Big Bang: UK Young Scientists' and Engineers' Fair is an annual three-day event designed to promote science, technology, engineering and maths (STEM) careers to young people aged 7-19 through experiential learning. It is supported by stakeholders from business and industry, government and the community, and brings together people from various…

Science Is A Laughing Matter

NASA Astrophysics Data System (ADS)

Weissman, P. R.

2017-12-01

Humor can be a powerful tool in communicating science to a professional or lay audience. Humor relaxes the audience and encourages them to pay better attention, lest they miss the next funny comment or slide (and be sure that you provide it for them). Humor sends the message that the speaker is so confident in his/her material that the speaker can joke about it; this tends to deter spurious or trivial questions after the talk. But humor is not for the faint of heart. It requires planning, practice, and especially, good timing. Good humorists are always on the lookout for new material that they can use in a talk, be it a funny image, a cartoon, or a quip from a movie or from a professional comedian. But the humorist must also be a strict self-censor. Politically incorrect material can be extremely dangerous and can backfire on the speaker. Don't ever use material that insults some faction in the audience, even if that faction is not present at the moment or too stupid to notice. Don't include so much humor that the science in your talk gets lost in the laughter. Lastly, speakers who are not funny, should never attempt humor. There is nothing so damaging to a talk as poor humor that falls flat on its face. But if you have a good sense of humor, go for it. Life should be fun and so should science.

Population-based imaging biobanks as source of big data.

PubMed

Gatidis, Sergios; Heber, Sophia D; Storz, Corinna; Bamberg, Fabian

2017-06-01

Advances of computational sciences over the last decades have enabled the introduction of novel methodological approaches in biomedical research. Acquiring extensive and comprehensive data about a research subject and subsequently extracting significant information has opened new possibilities in gaining insight into biological and medical processes. This so-called big data approach has recently found entrance into medical imaging and numerous epidemiological studies have been implementing advanced imaging to identify imaging biomarkers that provide information about physiological processes, including normal development and aging but also on the development of pathological disease states. The purpose of this article is to present existing epidemiological imaging studies and to discuss opportunities, methodological and organizational aspects, and challenges that population imaging poses to the field of big data research.

Functional connectomics from a "big data" perspective.

PubMed

Xia, Mingrui; He, Yong

2017-10-15

In the last decade, explosive growth regarding functional connectome studies has been observed. Accumulating knowledge has significantly contributed to our understanding of the brain's functional network architectures in health and disease. With the development of innovative neuroimaging techniques, the establishment of large brain datasets and the increasing accumulation of published findings, functional connectomic research has begun to move into the era of "big data", which generates unprecedented opportunities for discovery in brain science and simultaneously encounters various challenging issues, such as data acquisition, management and analyses. Big data on the functional connectome exhibits several critical features: high spatial and/or temporal precision, large sample sizes, long-term recording of brain activity, multidimensional biological variables (e.g., imaging, genetic, demographic, cognitive and clinic) and/or vast quantities of existing findings. We review studies regarding functional connectomics from a big data perspective, with a focus on recent methodological advances in state-of-the-art image acquisition (e.g., multiband imaging), analysis approaches and statistical strategies (e.g., graph theoretical analysis, dynamic network analysis, independent component analysis, multivariate pattern analysis and machine learning), as well as reliability and reproducibility validations. We highlight the novel findings in the application of functional connectomic big data to the exploration of the biological mechanisms of cognitive functions, normal development and aging and of neurological and psychiatric disorders. We advocate the urgent need to expand efforts directed at the methodological challenges and discuss the direction of applications in this field. Copyright © 2017 Elsevier Inc. All rights reserved.

SOFIA Update and Science Vision

NASA Technical Reports Server (NTRS)

Smith, Kimberly

2017-01-01

I will present an overview of the SOFIA program, its science vision and upcoming plans for the observatory. The talk will feature several scientific highlights since full operations, along with summaries of planned science observations for this coming year, platform enhancements and new instrumentation.

Performance Comparison of Big Data Analytics With NEXUS and Giovanni

NASA Astrophysics Data System (ADS)

Jacob, J. C.; Huang, T.; Lynnes, C.

2016-12-01

NEXUS is an emerging data-intensive analysis framework developed with a new approach for handling science data that enables large-scale data analysis. It is available through open source. We compare performance of NEXUS and Giovanni for 3 statistics algorithms applied to NASA datasets. Giovanni is a statistics web service at NASA Distributed Active Archive Centers (DAACs). NEXUS is a cloud-computing environment developed at JPL and built on Apache Solr, Cassandra, and Spark. We compute global time-averaged map, correlation map, and area-averaged time series. The first two algorithms average over time to produce a value for each pixel in a 2-D map. The third algorithm averages spatially to produce a single value for each time step. This talk is our report on benchmark comparison findings that indicate 15x speedup with NEXUS over Giovanni to compute area-averaged time series of daily precipitation rate for the Tropical Rainfall Measuring Mission (TRMM with 0.25 degree spatial resolution) for the Continental United States over 14 years (2000-2014) with 64-way parallelism and 545 tiles per granule. 16-way parallelism with 16 tiles per granule worked best with NEXUS for computing an 18-year (1998-2015) TRMM daily precipitation global time averaged map (2.5 times speedup) and 18-year global map of correlation between TRMM daily precipitation and TRMM real time daily precipitation (7x speedup). These and other benchmark results will be presented along with key lessons learned in applying the NEXUS tiling approach to big data analytics in the cloud.

The dynamics of big data and human rights: the case of scientific research.

PubMed

Vayena, Effy; Tasioulas, John

2016-12-28

In this paper, we address the complex relationship between big data and human rights. Because this is a vast terrain, we restrict our focus in two main ways. First, we concentrate on big data applications in scientific research, mostly health-related research. And, second, we concentrate on two human rights: the familiar right to privacy and the less well-known right to science. Our contention is that human rights interact in potentially complex ways with big data, not only constraining it, but also enabling it in various ways; and that such rights are dynamic in character, rather than fixed once and for all, changing in their implications over time in line with changes in the context we inhabit, and also as they interact among themselves in jointly responding to the opportunities and risks thrown up by a changing world. Understanding this dynamic interaction of human rights is crucial for formulating an ethic tailored to the realities-the new capabilities and risks-of the rapidly evolving digital environment.This article is part of the themed issue 'The ethical impact of data science'. © 2016 The Author(s).

How Does National Scientific Funding Support Emerging Interdisciplinary Research: A Comparison Study of Big Data Research in the US and China

PubMed Central

Huang, Ying; Zhang, Yi; Youtie, Jan; Porter, Alan L.; Wang, Xuefeng

2016-01-01

How do funding agencies ramp-up their capabilities to support research in a rapidly emerging area? This paper addresses this question through a comparison of research proposals awarded by the US National Science Foundation (NSF) and the National Natural Science Foundation of China (NSFC) in the field of Big Data. Big data is characterized by its size and difficulties in capturing, curating, managing and processing it in reasonable periods of time. Although Big Data has its legacy in longstanding information technology research, the field grew very rapidly over a short period. We find that the extent of interdisciplinarity is a key aspect in how these funding agencies address the rise of Big Data. Our results show that both agencies have been able to marshal funding to support Big Data research in multiple areas, but the NSF relies to a greater extent on multi-program funding from different fields. We discuss how these interdisciplinary approaches reflect the research hot-spots and innovation pathways in these two countries. PMID:27219466

The LHC's Next Big Mystery

NASA Astrophysics Data System (ADS)

Lincoln, Don

2015-03-01

When the sun rose over America on July 4, 2012, the world of science had radically changed. The Higgs boson had been discovered. Mind you, the press releases were more cautious than that, with "a new particle consistent with being the Higgs boson" being the carefully constructed phrase of the day. But, make no mistake, champagne corks were popped and backs were slapped. The data had spoken and a party was in order. Even if the observation turned out to be something other than the Higgs boson, the first big discovery from data taken at the Large Hadron Collider had been made.

Hack the Planet: What we Talk About When we Talk About Geoengineering

NASA Astrophysics Data System (ADS)

Kintisch, E.

2010-12-01

Hack the Planet (Wiley, 2010) explores how an idea once basically anathema to meetings like AGU has, in the space of a few years, become part of the geoscience mainstream. Through chapters involving researchers like David Battisti, Stephen Salter, Edward Teller and Brent Constanz the book documents the roots of this shift and how scientists are breaking new ground in the controversial field. And it shows how trying to engineer the planet's climate or manage its carbon poses novel scientific, geopolitical and moral risks and rewards. This session will cover how the topic of climate engineering has moved from something geoscientists don't talk about to something geoscientists can talk about, to something, in my view, that geoscientists must talk about.

Classroom Talk in Bilingual Class Interaction

ERIC Educational Resources Information Center

Puasa, Kuran; Asrifan, Andi; Chen, Yan

2017-01-01

This study reveals how the classroom talk was in the bilingual classroom interaction. The classroom talk comprises teacher and pupil talk--in which they cover teacher's explanation, teacher's question, teacher's feedback, and modification to teacher's speech; as well as pupil's responses and pupil's questions. The research findings show that the…

Five Big Ideas

ERIC Educational Resources Information Center

Morgan, Debbie

2012-01-01

Designing quality continuing professional development (CPD) for those teaching mathematics in primary schools is a challenge. If the CPD is to be built on the scaffold of five big ideas in mathematics, what might be these five big ideas? Might it just be a case of, if you tell me your five big ideas, then I'll tell you mine? Here, there is…

Science Teaching Methods: A Rationale for Practices

ERIC Educational Resources Information Center

Osborne, Jonathan

2011-01-01

This article is a version of the talk given by Jonathan Osborne as the Association for Science Education (ASE) invited lecturer at the National Science Teachers' Association Annual Convention in San Francisco, USA, in April 2011. The article provides an explanatory justification for teaching about the practices of science in school science that…

Extreme Science (LBNL Science at the Theater)

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

Ajo-Franklin, Caroline; Klein, Spencer; Minor, Andrew

On Feb. 27, 2012 at the Berkeley Repertory Theatre, four Berkeley Lab scientists presented talks related to extreme science - and what it means to you. Topics include: Neutrino hunting in Antarctica. Learn why Spencer Klein goes to the ends of the Earth to search for these ghostly particles. From Chernobyl to Central Asia, Tamas Torok travels the globe to study microbial diversity in extreme environments. Andrew Minor uses the world's most advanced electron microscopes to explore materials at ultrahigh stresses and in harsh environments. And microbes that talk to computers? Caroline Ajo-Franklin is pioneering cellular-electrical connections that could helpmore » transform sunlight into fuel.« less

Measuring Adolescent Science Motivation

ERIC Educational Resources Information Center

Schumm, Maximiliane F.; Bogner, Franz X.

2016-01-01

To monitor science motivation, 232 tenth graders of the college preparatory level ("Gymnasium") completed the Science Motivation Questionnaire II (SMQ-II). Additionally, personality data were collected using a 10-item version of the Big Five Inventory. A subsequent exploratory factor analysis based on the eigenvalue-greater-than-one…

From WHAT We Know to HOW We Know It: Students Talk about Climate Change

NASA Astrophysics Data System (ADS)

Holthuis, N.; Lotan, R.; Saltzman, J.; Mastrandrea, M. D.

2012-12-01

The climate change community has begun to look carefully at how the public understands, or fails to understand, climate change data and the scientific claims made based on these data. Researchers (Bowen et al, 2008) have found that a deficit model of knowledge doesn't fully explain why people continue to disagree about climate change or are unwilling to change their behaviors. "Deniers" do not become "acceptors" simply by filling up their cognitive data banks with more information. This suggests that teachers need to provide scaffolding that supports not only students' understanding of how climate systems work or the causes and effects of climate change but includes how we know what we know. That is, instruction shifts from an exclusive focus on content knowledge to one that aims to develop critical analytic skills and scientific habits of mind. For example, students need to not only understand the effects of human activity on climate change, but also learn to identify and analyze the evidence for anthropogenic climate change and how that evidence has built over time. They can then evaluate the evidence as well as whether the claims made are justified given the data. Climate literacy then includes content knowledge as well as understanding of the scientific practices that lead to building that knowledge. In this study, we report on the research and evaluation of the NASA-funded Stanford Global Climate Change: Professional Development for K-12 Teachers. We focus on data from the last year of a three-year project in which climate scientists and science educators collaborated to develop curriculum and provide professional development for secondary school teachers on the science and the pedagogy of global climate change. As teachers implemented the curriculum in their classrooms, we collected pre- and post-tests, classroom observations, video recordings, and post-implementation interviews with the teachers. Our analyses serve to document: 1) how students talk about HOW

Real Talk, Real Teaching

ERIC Educational Resources Information Center

Nichols, Maria

2014-01-01

What happens in classrooms when we create the time and space for authentic talk about texts? Extended, collaborative conversations that allow understanding to unfold over time can be messy and dynamic. As students wrestle with complex texts and ideas, talk can become lively--and predictable problems can arise. In this article, Marie Nichols uses…

Alaska Satellite Facility: The Quest to Stay Ahead of the Big Data Wave

NASA Astrophysics Data System (ADS)

Labelle-Hamer, A. L.; Nicoll, J.; Munk, S.

2014-12-01

Big Data is getting bigger. Fast enough is getting faster. The number and type of products produced is growing. The ideas on how to handle the day-to-day management of data and data systems need to scale with the data and the demand. We have seen the effects of rapid growth spurts at the Alaska Satellite Facility (ASF) and anticipate we are not done yet. Looking back, ASF was conceived in 1982 to be a single-purpose imaging radar receiving station supporting a science team focused on geophysical processes. The primary construction at the University of Alaska Fairbanks (UAF) was completed in 1988 and full operational status achieved in 1991. The expected supports were estimated at 10 minutes per day and quickly grew to 70 minutes per day. In 1994, a Memorandum of Agreement (MOA) between NASA and UAF formed the ASF Distributed Active Archive Center (DAAC) complementing, the existing agreement for ASF. The demand for the use of ASF as a receiving station and as a data center grew as fast as, and at times faster, than the capabilities. Looking forward, as demand drives the system larger just adding on more of the same often complicates rather than simplifies the system. A growing percentage of efforts and resources spent on dealing with problems that originate from a legacy system can creep up on an organization. This in turn limits the ability to keep the overall sustaining costs under control and leads to a crisis. Such growth means more-of-the-same philosophy has to shift into change-or-die philosophy in order to boot strap up to the next level. In this talk, we review how ASF has faced this several times in the past as the volume and demand of data grew along with the technology to acquire and disseminate it. We will look at what is coming for ASF as a data center and what we think are the next steps to stay ahead of the Big Data wave.

Talking Glossary of Genetic Terms

MedlinePlus

... Y Z Test Your Knowledge Talking Glossary of Genetic Terms Designed to help learners at any level ... in a reference paper. The Talking Glossary of Genetic Terms The Human Genome Defined by Professionals at ...