1 Big Data R&D Initiative Suzi Iacono CISE Directorate National Science Foundation National Academies of Science Integrating Environmental Health Data to Advance Discovery January 11, 2013 Image Credit: Exploratorium.
2 Advances in information technologies are transforming the fabric of our society and data represents a transformative new currency for science, engineering, education and commerce. Image Credit: CCC and SIGACT CATCS
3 Where do the data come from? Why do we have a national initiative?
4 The Big Data Landscape I: Big Science Science gathers data at an ever-increasing rate across all scales and complexities of natural phenomena Sloan Digital Sky Survey in 2000 collected more data in its 1 st few weeks than had been amassed in the entire history of astronomy Within a decade, over 140 terabytes of information collected Large Hadron Collider generates scores of petabytes a year The proposed Large Synoptic Survey Telescope (3.3 gigapixel digital camera) will generate 40 terabytes of data nightly By 2015, the world will generate the equivalent of approximately 93 million Libraries of Congress
5 The Big Data Landscape II: Smart Sensing, Reasoning and Decisionmaking Environment Sensing Emergency Response Percepts (sensors) Agent (Reasoning) Situation Awareness: Humans as sensors feed multimodal data streams Credit: Photo by US Geological Survey People Centric Sensing Actions (controllers ) Pervasive Computing Social Informatics Smart Health Care Evaluate Sense Personal Sensing Public Sensing Social Sensing Intervene Assess Identify Source: Sajal Das, Keith Marzullo
6 The Big Data Landscape III: New Paradigms for Communications 1988 Remarkable Pace of Innovation Today MOBILE SOCIAL NETWORKS VIDEO VOIP BLOGS
7 Communications Volume & Traffic Diversity VoIP Video Twitter Broadband 663M registered Skype users in Represents 20% of long distance minutes world-wide. If Skype were a carrier, it would be the 3rd largest in the world (behind China Mobile and Vodaphone). Largest provider of cross-border communication. Recent estimates as high as 60% of internet traffic is video and music sharing; 35 hours of new videos are uploaded every minute in 2011; 2 billion views per day. Currently 175 million registered users. 20% of global internet users have residential broadband; d; 68% in US subscribe be to broadband. d Mobile 5.3 billion mobile phone subscribers; 85% of new handsets will be able to access the mobile web; 1 in 5 has access to fast service, 3G or better; IM, MMS, SMS expected to exceed 10 trillion message by 2013.
8 The Big Data Landscape IV: The Long Tail of fscience Hundreds of thousands of scientists and engineers work individually or in small, distributed, disconnected groups all generating data that collectively represent an enormous, largely untapped scientific resource From running simulations, experiments, etc. Making heterogeneous data across many areas of science more homogeneous could give way to breakthroughs across all areas of science and engineering Estimated 40 exabytes of unique new information generated worldwide in 2010 Only 5% of the information created is structured, however, in a standard format of words or numbers; the rest are unstructured text, voice, images, etc.
9 How Big is Big? Big Data : Datasets whose size are beyond the ability of typical database software tools to capture, store, manage, and analyze -McKinsey Global Institute, Big data: the next frontier for innovation, competition, and productivity, May Image Credit: Sigrid Knemeyer
10 Not Just Volumes of Data The science of big data is not just about volumes and velocity of data, but also Heterogeneity and diversity Levels of granularity Media formats Scientific ifi disciplines i Complexity Uncertainty Incompleteness Representation types
11 Why is Big Data Important? Critical to transforming how science is done and to accelerating the pace of discovery in almost every science and engineering discipline Transformative implications for commerce and economy Potential for addressing some of society s most pressing challenges Image Credit: Chi Birmingham
12 Paradigm Shift: from Hypothesis-driven to Data-driven Discovery The Economist, The data deluge and how to handle it: A 14 page special report (Feb 25, 2010). The Fourth Paradigm: Data Intensive Scientific Discovery (2009, Microsoft Corporation).
13 The Age of Data: From Data to Knowledge to Action Data-driven discovery is revolutionizing i i scientific exploration and engineering innovations Automatic extraction of new knowledge about the physical, biological and cyber world continues to accelerate Multi-cores, concurrent and parallel algorithms, virtualization and advanced server architectures will enable data mining and machine learning, and discovery and visualization of Big Data
14 Potential for Transformational Science & Engineering: From Data to Knowledge to Action Integration ti of discipline i (or media format ) specific data, examine for relationships Disaster informatics 3D toxic fume images Simulations of gas spread Maps of census concentrations First responder on-the- ground findings Evacuation routing
15 From Data to Knowledge to Action Researchers seek to fundamentally transform understanding of spinning giants The task involves assembling data from more storm variables-such as updraft, downdraft and vorticity or g p, y regions of spin--than what can be observed from ground tornado chasers or even actually produced in the atmosphere. For example, researchers need to better understand how changes in wind direction with height cause the updrafts in a storm to rotate, preceding the formation of a tornado. To solve the quandary, Amy McGovern, an associate professor in OU's School of Computer Science, and her team create tornado models with super computers that can process vast amounts of data. McGovern and her colleagues use the models to analyze how storm variables interact in order to identify tornadic and nontornadic storms.
16 Examples of Research Challenges More data are being collected than we can store Analyze the data as it becomes available Decide what to archive and what to discard Many data sets are too large to download Analyze the data wherever it resides Many data sets are too poorly organized to be usable Better organize and retrieve data Many data sets are heterogeneous in type, structure, semantics, organization, granularity, accessibility Integrate and customize access to federate data Utility of data is limited by our ability to interpret and use it Extract and visualize actionable knowledge Evaluate results Large and linked datasets may be exploited to identify individuals Design management and analysis with built-in i privacy preserving characteristics
17 A National Imperative PCAST calls on the Federal government to increase R&D investments for collecting, storing, preserving, managing, g, analyzing, and sharing the increasing quantities of data. Furthermore, PCAST observed that the potential to gain new insights to move from data to knowledge to action has tremendous potential to transform all areas of national priority. Source: PCAST (December 2010), Report to the President and Congress: Designing a Digital Future a periodic congressionally-mandated review of the Federal Networking and Information Technology Research and Development (NITRD) Program.
18 Administration s Big Data Research and Development Initiative Big Data Senior Steering Group chartered in spring 2011 under the Networking and Information Technology R&D (NITRD) Program Members from DARPA, DOD OSD, DHS, DOE-Science, HHS, NARA, NASA, NIST, NOAA, NSA, OFR, USGS, etc. Co-chaired by NSF (and NIH) Initial charge was to come up with a plan, a strategy 18 Image Credit: Fuqing Zhang and Yonghui Weng, Pennsylvania State University; Frank Marks, NOAA; Gregory P. Johnson, Romy Schneider, John Cazes, Karl Schulz, Bill Barth, The University of Texas at Austin
19 Big Data Membership Biven Laura DOE Science Blatecki Alan NSFNational Science Foundation Collica Leslie NISTNational Institute of Standards and Technology Deift Abby NSFNational Science Foundation Downing Gregory HHSDepartment of Health and Human Services Espina Pedro OSTPWhite House Office of Science and Technology Policy Gerr Neil DARPADefense Advanced Research Projects Agency Gundersen Linda USGSU.S. Geological Survey NOAANational Oceanic and Atmospheric Hall Alan Administration Iacono Suzanne NSFNational Science Foundation Jakubek David OSDOffice of the Secretary of Defense ATL Kaufman Daniel DARPADefense Advanced Research Projects Agency Larson OSTPWhite House Office of Science and Technology Phillip P. Policy Lee Tsengdar NASANational Aeronautics and Space Administration NIHNational Institutes of Health /NLMNIH s National Lipman David Library of Medicine /NCBI Little Michael NASANational Aeronautics and Space Administration Luker Mark NCONational Coordination Office for NITRD /NITRDNetworking and Information Technology Research and Development Marth Lisa NISTNational Institute of Standards and Technology Muoio Patricia A. DNI Pantula Sastry NSFNational Science Foundation NIHNational Institutes of Health /NLMNIH s National Preuss Don Library of Medicine /NCBI Quade Brittany NSFNational Science Foundation Romine Charles NISTNational Institute of Standards and Technology Smith Darren NOAANational Oceanic and Atmospheric Administration Spengler Sylvia NSFNational Science Foundation Statler Tom NSFNational Science Foundation Strawn George NCONational Coordination Office for NITRD /NITRDNetworking and Information Technology Research and Development Suskin Mark NSFNational Science Foundation Villani Jennifer NIHNational Institutes of Health /NIGMS Wigen Wendy NCONational Coordination Office for NITRD /NITRDNetworking and Information Technology Research and Development Zhao Fen NSFNational Science Foundation Nowell Lucy DOE Science
20 Big Data Membership Bristol Sky USGSU.S. G eological Survey usg s.gov Kielm an Joseph DHSDepartment o f H om eland Security jo Petters Jonathan DOE Science science.doe.gov Carver Doris NSFNational Science Found ation d v Adolfie Laura O SD O ffice of the Secretary of Defense osd.mil Chadduck Robert NSFNational Science Foundation nsf.gov Crow der Grace NSANational Security Agency nsa.gov Dunn M ich e lle NIHNational In st itu t es of Health dunnm mail.nih.gov Florance V a le rie NIHN a tional In stitu t es o f H ealth mail.n ih.go v Frehill Lisa O SD O ffice of the Secretary of Defense lisa.fr eh ill.c d ar p a.m il Helland Barbara DOEDepartment of Energy Science science.doe.gov Hoang Thuc DOEDepartment of Energy NNSA nnsa.doe.gov Kannan Nandini NSFNational Science Foundation W arnow T and y NSFN a tional S c ie nce F ound a tion t nsf.g o v Dean David DOE Science science.doe.gov Ly ster Peter NIHNational In st itu t es of Health m ail.n ih.go v M ille m a ci John O SD O ffice of the Secretary of Defense jo osd.m il Pearce Claudia NSANational Security A gency nsa.gov Allen M arc NASANationalAeronautics Aeronautics and Space Administration marc.a nasa.gov Pearl Jennifer NSFNational Science Foundation jslim ow nsf.gov Blaszkowsky David TreasuryDepartment of the Treasury OFR david.blaszkow treasury.gov Szykm an James EPAEnvironm ental Protection Agency ja Tom pkins Jerry NSANational Security Agency gsto m p rad ium.ncs c.m il Flood M ark TreasuryDepartment of the Treasury OFR ry.g ov Holm Jeanne Data.gov je anne.m.holm.jpl.nasa.gov Misawa Eduardo NSFNational Science Foundation
21 Big Data Launch Federal Big Data R&D Initiative launched by White House OSTP on March 29, 2012 at AAAS Federal Announcements: NSF Subra Suresh NIH Francis Collins USGS Marcia McNutt DoD Zach Lemnios DARPA - Ken Gabriel DOE William Brinkman Panel Discussion: Moderator - Steve Lohr, New York Times Daphne Koller, Stanford University James Manyika, McKinsey & Company Lucila Ohno-Machado, UC San Diego Alex Szalay, Johns Hopkins University Image Credit: National Science Foundation More information available at:
22 Strategy to Address Big Data Foundational research to develop new techniques and technologies to derive knowledge from data New cyberinfrastructure to manage, curate, and serve data to research communities ii Policy New approaches for education and workforce development New types of inter disciplinary collaborations, grand challenges, and competitions
23 Core Techniques and Technologies for Advancing Big Data Science & Engineering (BIG DATA) Program Solicitation: NSF Foundational research to extract knowledge from data Foundational research to advance the core techniques and dtechnologies for managing, analyzing, visualizing, and extracting useful information from large, diverse, distributed and heterogeneous data sets. Image Credit: Jurgen Schulze, Calit2, UC San Diego Cross Directorate t Program: NSF Wide Multi agency Commitment: NSF and NIH
24 BIG DATA Research Thrusts Collection, Storage, and Management of Big Data 3 awards Foundations of big data management Mitigating tradeoffs among speed of data ingestion, quicker answers and the freshness of data through the design of new storage devices with extreme capacities 4 awards Data Analytics Novel machine learning where multi-dimensional vector data points are replaced by distributions Design and test mathematical and statistical techniques for large-scale heterogeneous data in DNA repositories Research in Data Sharing and Collaboration 1 award (+1 shared with data collection) Open source tools for infrastructure for improving discovery through use of social analytic data Databridge linking data, human interactions, and usage practices for the long-tail of science Databridge linking data, human interactions and usage practices for the long-tail of science Data analytics problems in next generation sequencing Theory and algorithms fro couples tensors and associated software toolkits to make analysis possible Credit: Fermilab Photo Eight mid scale (up to $1M a year) awards out of over 136 projects announced on Oct. 3.
25 Award Citations DCM: Dan Suciu University of WA A formal foundation for big data management Michael Bender SUNY at Stony Brook & Martin Farach-Colton Rutgers University Eliminating the data ingestion bottleneck in big data applications Arcot Rajasekar University of North Carolina, Chapel Hill & Gary King Harvard University & Justin Zhan North Carolina Agriculture & Technical State University it Databridge A sociometric system for long-tail science data collections 25
26 Data Analytics Award Citations Eli Upfal Brown University Analytic approaches to massive data computation with applications to genomics Aarti Singh Carnegie-Mellon University Distribution-based machine learning for high dimensional datasets Srinvas Aluru Iowa State University & Wuchun Feng Virginia Polytechnic Institute & State University & Oyekunie Olukotun Stanford University Genomes Galore Core techniques, libraries, and domain specific languages for high throughput DNA sequencing
27 Award Citations Data Analytics (continued) Christos Faloutsos Carnegie Mellon University & Nikolaos Sidiropoulos University of Minnesota Twin Cities Big Tensor Mining: Theory Scalable Algorithms and Applications 27
28 Award Citations E-Science Collaboration Environments Thorsten Joachim Cornell University & Paul Kantor Rutgers University Discovery and social analysis for large-scale scientific literature 28
29 Ideation Contest Launch Opportunity to expand the innovation ecosystem Joint among NASA, NSF and DOE Office of Science A contest focused on How to make heterogeneous data seem more homogeneous? 5 judges 5 criteria Launched on Challenge.gov and the Top Coder platform on Oct. 3 with a two week window topcoder com/coeci/nitrd/
30 Ongoing Big Data Programs at NSF Dear Colleague Letters: Encourage CIF21 IGERTs to educate and support a new generation of researchers able to address fundamental Big Data challenges: Data-Intensive t Education-Related t d Research Funding Opportunities announcing an Ideas Lab, for which cross disciplinary participation will be solicited, to generate transformative ideas for using large datasets to enhance the effectiveness of teaching and learning environments: Data Citation to the Geosciences Community to encourage transparency and increased opportunities for the use and analysis of data sets:
31 Earthcube: GEO Science Infrastructure EAGER awards announced as part of White House Big Data Launch Integrates geosciences data and high-performance computing technologies in an open, adaptable and sustainable framework to enable transformative research and education in Earth System Science Innovative Model: Community designed, community owned, community governed Interdisciplinary research: Building and sustaining new communities Workshops to bring together (GEO, SBE, CISE) communities EAGER awards to seed new research
32 A Complex Policy Setting Researchers want data. Public policy requires access to data. Public policy also requires protection of privacy and intellectual property and other sensitive information. Much more to be done: Policy on data management and data access.
33 Data Privacy Never more important than today However, not all data contain people s identities (as in data landscape III) Not a Big Brother scenario Government (NSF) invests in privacy research Values in design research community: Identity cloaking, anonymization Do-not-track cookie management Obfuscation, blurring Privacy preserving data mining, search, payment Just-in-time crypto Secure data distribution. Privacy in technology; privacy inspired technology
34 Opportunities for the Future Our investments in research and education have already returned exceptional dividends to the Nation. Many of tomorrow s breakthroughs will occur as a result of new techniques and technologies for advancing Big Data science and engineering. In turn, Big Data scientific discovery and technological innovation are at the core of our response to national and societal challenges from environment, energy, transportation, sustainability, and healthcare to cyber security and national defense.
Big Data R&D Initiative Howard Wactlar CISE Directorate National Science Foundation NIST Big Data Meeting June, 2012 Image Credit: Exploratorium. The Landscape: Smart Sensing, Reasoning and Decision Environment
CISE Overview and Big Data Suzi Iacono CISE Directorate National Science Foundation SI^2 Workshop January 17, 2013 Image&Credit:&Exploratorium.& Economic Impact of IT Growth of IT industry coupled with
Big Data R&D Initiative Mhyron Gutmann Directorate for the Social, Behavioral and Economic Sciences National Science Foundation Image Credit: Exploratorium. Digital Preservation 2012 July 25, 2012 Advances
Core Techniques and Technologies for Advancing Big Data Science & Engineering (BIGDATA) NSF 12-499 Vasant Honavar Program Director Information & Intelligent Systems (IIS) Division Computer and Information
National Big Data R&D Initiative Suzi Iacono, PhD National Science Foundation Co-chair NITRD Big Data Senior Steering Group for CASC Spring Meeting April 23, 2014 Why is Big Data Important? Transformative
Symposium on the Interagency Strategic Plan for Big Data: Focus on R&D NAS Board on Research Data and Information October 23, 2014 Big Data Senior Steering Group (BDSSG) Allen Dearry, NIH, Co-Chair Suzi
CYBERINFRASTRUCTURE FRAMEWORK FOR 21 ST CENTURY SCIENCE, ENGINEERING, AND EDUCATION (CIF21) Overview The Cyberinfrastructure Framework for 21 st Century Science, Engineering, and Education (CIF21) investment
Good morning. It is a pleasure to be with you here today to talk about the value and promise of Big Data. 1 Advances in information technologies are transforming the fabric of our society and data represent
CC-NIE PI Workshop Plenary Farnam Jahanian April 30, 2014 Image Credit: Exploratorium. Pervasive Impact We are at the center of an ongoing societal transformation and will be for decades to come. Advances
NITRD and Big Data George O. Strawn NITRD Caveat auditor The opinions expressed in this talk are those of the speaker, not the U.S. government Outline What is Big Data? Who is NITRD? NITRD's Big Data Research
Big Data George O. Strawn NITRD Caveat auditor The opinions expressed in this talk are those of the speaker, not the U.S. government Outline What is Big Data? NITRD's Big Data Research Initiative Big Data
CASC Spring Meeting 2014 Federal Agency Panel Update on Big Data Robert Chadduck Program Director, Data & CI CISE Division of Advanced Cyberinfrastructure 23 April 2014 ACI data focused CI - A view towards
Information Technology R&D and U.S. Innovation Peter Harsha Computing Research Association Ed Lazowska University of Washington Version 9: December 18, 2008 1 Peter Lee Carnegie Mellon University Advances
Big Data a threat or a chance? Helwig Hauser University of Bergen, Dept. of Informatics Big Data What is Big Data? well, lots of data, right? we come back to this in a moment. certainly, a buzz-word but
BIG DATA Funding Opportunities Jill Morris Morris.email@example.com 688-5423 Institute for Population Research The Ohio State University NSF firstname.lastname@example.org NSF Big Data Initiatives Core Techniques and Technologies
CYBERINFRASTRUCTURE FRAMEWORK FOR 21 st CENTURY SCIENCE AND ENGINEERING (CIF21) Goal Develop and deploy comprehensive, integrated, sustainable, and secure cyberinfrastructure (CI) to accelerate research
NITRD: National Big Data Strategic Plan Summary of Request for Information Responses Introduction: Demographics Summary of Responses Next generation Capabilities Data to Knowledge to Action Access to Big
CYBERINFRASTRUCTURE FRAMEWORK $143,060,000 FOR 21 ST CENTURY SCIENCE, ENGINEERING, +$14,100,000 / 10.9% AND EDUCATION (CIF21) Overview The Cyberinfrastructure Framework for 21 st Century Science, Engineering,
2013 Esri International User Conference July 8 12, 2013 San Diego, California Technical Workshop Big Data: Using ArcGIS with Apache Hadoop David Kaiser Erik Hoel Offering 1330 Esri UC2013. Technical Workshop.
CYBERINFRASTRUCTURE FRAMEWORK FOR 21 ST CENTURY SCIENCE, ENGINEERING, AND EDUCATION (CIF21) $100,070,000 -$32,350,000 / -24.43% Overview The Cyberinfrastructure Framework for 21 st Century Science, Engineering,
Testimony of Farnam Jahanian, Ph.D. Assistant Director Computer and Information Science and Engineering Directorate National Science Foundation Before the Committee on Science, Space, and Technology Subcommittee
COGNITIVE SCIENCE AND NEUROSCIENCE Overview Cognitive Science and Neuroscience is a multi-year effort that includes NSF s participation in the Administration s Brain Research through Advancing Innovative
The Past, Present, and Future of Data Science Education Kirk Borne @KirkDBorne http://kirkborne.net George Mason University School of Physics, Astronomy, & Computational Sciences Outline Research and Application
! Efficiency in scientific discovery through curation, analyses and interpretation of massive datasets! Uptake level and concentration on Big Data opportunities are varied across disciplines The nature
Government Technology Trends to Watch in 2014: Big Data OVERVIEW The federal government manages a wide variety of civilian, defense and intelligence programs and services, which both produce and require
RISK AND RESILIENCE $58,000,000 +$38,000,000 / 190.0% Overview The economic competiveness and societal well-being of the United States depend on the affordability, availability, quality, and reliability
Data Driven Discovery In the Social, Behavioral, and Economic Sciences Simon Appleford, Marshall Scott Poole, Kevin Franklin, Peter Bajcsy, Alan B. Craig, Institute for Computing in the Humanities, Arts,
Challenges in e-science: Research in a Digital World Thom Dunning National Center for Supercomputing Applications National Center for Supercomputing Applications University of Illinois at Urbana-Champaign
The Research Data Revolution 2015 Harvard/Purdue Data Symposium Sayeed Choudhury Data Conservancy (DC) One of five awards through US National Science Foundation s (NSF) DataNet program $10 million award
SECURE AND TRUSTWORTHY CYBERSPACE (SaTC) Overview The Secure and Trustworthy Cyberspace (SaTC) investment is aimed at building a cybersecure society and providing a strong competitive edge in the Nation
Overcoming the Technical and Policy Constraints That Limit Large-Scale Data Integration Revised Proposal from The National Academies Summary An NRC-appointed committee will plan and organize a cross-disciplinary
Data Intensive Scalable Computing Harnessing the Power of Cloud Computing Randal E. Bryant February, 2009 Our world is awash in data. Millions of devices generate digital data, an estimated one zettabyte
Photo courtesy of Justin Reuter Center for Dynamic Data Analytics (CDDA) An NSF Supported Industry / University Cooperative Research Center (I/UCRC) Photo courtesy of Justin Reuter University Consortium
The Packard Fellowships for Science and Engineering 2016 Guidelines The Packard Fellowships for Science and Engineering program invests in future leaders who have the freedom to take risks, explore new
Cloud Computing for Research Roger Barga Cloud Computing Futures, Microsoft Research Trends: Data on an Exponential Scale Scientific data doubles every year Combination of inexpensive sensors + exponentially
Collaborations between Official Statistics and Academia in the Era of Big Data World Statistics Day October 20-21, 2015 Budapest Vijay Nair University of Michigan Past-President of ISI email@example.com What
An analysis of Big Data ecosystem from an HCI perspective. Jay Sanghvi Rensselaer Polytechnic Institute For: Theory and Research in Technical Communication and HCI Rensselaer Polytechnic Institute Wednesday,
The National Consortium for Data Science (NCDS) A Public-Private Partnership to Advance Data Science Ashok Krishnamurthy PhD Deputy Director, RENCI University of North Carolina, Chapel Hill What is NCDS?
Is Big Data a Big Deal? What Big Data Does to Science Netherlands escience Center Wilco Hazeleger Wilco Hazeleger Student @ Wageningen University and Reading University Meteorology PhD @ Utrecht University,
Piyush Chaudhary Technical Computing Solutions Data Centric Computing Revisited SPXXL/SCICOMP Summer 2013 Bottom line: It is a time of Powerful Information Data volume is on the rise Dimensions of data
Big Data and Smart Government Institute for Public Administration Australia Nov 20, 2014 Ramayya Krishnan W.W. Cooper and Ruth F. Cooper Professor of Information Systems H. John Heinz III College, Carnegie
Big-Data Computing: Creating revolutionary breakthroughs in commerce, science, and society Randal E. Bryant Carnegie Mellon University Randy H. Katz University of California, Berkeley Version 8: December
1 11.1 Definitions and Motivation Lot of research and papers in this emerging field: Visual Analytics: Scope and Challenges of Keim et al. Illuminating the path of Thomas and Cook 2 11.1 Definitions and
CIS492 Special Topics: Cloud Computing د. منذر الطزاونة Big Data Definition No single standard definition Big Data is data whose scale, diversity, and complexity require new architecture, techniques, algorithms,
Introducing the federal cybersecurity R&D strategic plan Douglas Maughan, Bill Newhouse, and Tomas Vagoun In December 2011, the White House Office of Science and Technology Policy (OSTP) released the document,
Big Data to Knowledge () potential funding agency synergies Jennie Larkin, PhD Office of the Associate Director of Data Science National Institutes of Health idash-pscanner meeting UCSD September 16, 2014
Government Perspectives on the Future of Advanced Networking Technologies Combined briefings presented at: GLOBALCOMM GLOBALCOMM Government Summit and Innovations Summit June 5, 2006 June 7, 2006 Simon
Grand Challenges, Federal Priorities and Funding an NSF/CISE view Jim Kurose Assistant Director, NSF Computer & Information Science & Engineering Distinguished Professor College of Information and Computer
IBM Announces Eight Universities Contributing to the Watson Computing System's Development Press release Related XML feeds Contact(s) information Related resources ARMONK, N.Y. - 11 Feb 2011: IBM (NYSE:
Rutgers Discovery Informatics Institute (RDI 2 ) New Jersey s Center for Advanced Computation New Jersey Big Data Alliance Manish Parashar Director, Rutgers Discovery Informatics Institute (RDI 2 ) Professor,
MEDICAL DATA MINING Timothy Hays, PhD Health IT Strategy Executive Dynamics Research Corporation (DRC) December 13, 2012 2 Healthcare in America Is a VERY Large Domain with Enormous Opportunities for Data
Global Research Data Infrastructure: Path Forward for Progress Dr. Chris Greer Senior Executive for Cyber Physical Systems R. Rathe NIST: Basic Stats and Facts Major assets ~ 3,000 employees ~ 2,800 associates
Challenges and Solutions for Big Data in the Public Sector: Digital Government Institute s Annual Big Data Conference, October 9, Washington, DC Reagan Building Dr. Brand Niemann Director and Senior Data
SDN Security Challenges Anita Nikolich National Science Foundation Program Director, Advanced Cyberinfrastructure July 2015 Cybersecurity Enhancement Act 2014 Public-Private Collaboration on Security (NIST
Big Data Challenges in Bioinformatics BARCELONA SUPERCOMPUTING CENTER COMPUTER SCIENCE DEPARTMENT Autonomic Systems and ebusiness Pla?orms Jordi Torres Jordi.Torres@bsc.es Talk outline! We talk about Petabyte?
Danny Wang, Ph.D. Vice President of Business Strategy and Risk Management Republic Bank Agenda» Overview» What is Big Data?» Accelerates advances in computer & technologies» Revolutionizes data measurement»
Community of Science: Strategies for Coordinating Integration of Data USGS Community for Data Integration Kevin T. Gallagher USGS Core Science Systems January 11, 2013 U.S. Department of the Interior U.S.
UC AND THE NATIONAL RESEARCH COUNCIL RATINGS OF GRADUATE PROGRAMS In the Fall of 1995, the University of California was the subject of some stunning news when the National Research Council (NRC) announced
Exploring the roles and responsibilities of data centres and institutions in curating research data a preliminary briefing. Dr Liz Lyon, UKOLN, University of Bath Introduction and Objectives UKOLN is undertaking
Knowledge Discovery from patents using KMX Text Analytics Dr. Anton Heijs firstname.lastname@example.org Treparel Abstract In this white paper we discuss how the KMX technology of Treparel can help searchers
George E. Brown Jr. Network for Earthquake Engineering Simulation Facility Access Challenges: Data Management Rudi Eigenmann NEES Operations Headquarters NEEScomm Center Purdue University Why Data Management?
Astrophysics with Terabyte Datasets Alex Szalay, JHU and Jim Gray, Microsoft Research Living in an Exponential World Astronomers have a few hundred TB now 1 pixel (byte) / sq arc second ~ 4TB Multi-spectral,
Critical Information Infrastructure Research in the U.S. An informal status report The 2nd US-Japan Experts Workshop on Critical Information Infrastructure Protection (CIIP) Tokyo, Japan Outline Definitions,
Big Data in the context of Preservation and Value Adding R. Leone, R. Cosac, I. Maggio, D. Iozzino ESRIN 06/11/2013 ESA UNCLASSIFIED Big Data Background ESA/ESRIN organized a 'Big Data from Space' event
American Association for the Advancement of Science Annual Meeting Meeting Global Challenges: Discovery and Innovation Librarians Orientation Climate Action Plan Challenge for Librarians: Supporting Sound
Data Science Master s programs 1 1 Who are we? Willem-Jan van den Heuvel Tilburg University Ksenia Podoynitsyna Eindhoven University of Technology 2 2 Program What is Data Science? The Data Science Initiative
Stampede supercomputer enables discoveries throughout science and engineering 20 June 2014, by Aaron Dubrow Volume rendering of the entropy in a full 3-D GRMHD simulation of a differentially rotating and
Panel on Big Data Challenges and Opportunities Dr. Chaitan Baru Senior Advisor for Data Science, Directorate for Computer & Information Science & Engineering National Science Foundation NSF s Perspective
Accelerating Cross-Sectoral Collaboration on Data in Climate, Education and Health A Workshop on Data Sharing and Emerging Data Collaboratives U.S. General Services Administration Building 1800 F Street,
The Tonnabytes Big Data Challenge: Transforming Science and Education Kirk Borne George Mason University Ever since we first began to explore our world humans have asked questions and have collected evidence
Proposal for the Theme on Big Data Analytics May 2015 Qiang Yang, HKUST Jiannong Cao, PolyU Qi-man Shao, CUHK Motivation The world's technological per-capita capacity to store information doubled every
Big Data Hope or Hype? David J. Hand Imperial College, London and Winton Capital Management Big data science, September 2013 1 Google trends on big data Google search 1 Sept 2013: 1.6 billion hits on big
+ Databases & Data Infrastructure Kerstin Lehnert + Access to Data is Needed 2 to allow verification of research results to allow re-use of data + The road to reuse is perilous (1) 3 Accessibility Discovery,
White Paper Analyzing Big Data: The Path to Competitive Advantage by Marcia Kaplan Contents Introduction....2 How Big is Big Data?................................................................................
Volume 3, Issue 9, September 2013 ISSN: 2277 128X International Journal of Advanced Research in Computer Science and Software Engineering Research Paper Available online at: www.ijarcsse.com A Real Time
1 st Symposium on Colossal Data and Networking (CDAN-2016) March 18-19, 2016 Medicaps Group of Institutions, Indore, India Call for Papers Colossal Data Analysis and Networking has emerged as a de facto
Data Publishing Workflows with Dataverse Mercè Crosas, Ph.D. Twitter: @mercecrosas Director of Data Science Institute for Quantitative Social Science, Harvard University MIT, May 6, 2014 Intro to our Data
Understanding Big Data Analytics for Research Hye-Chung Kum Texas A&M Health Science Center, Dept. of Health Policy & Management University of North Carolina at Chapel Hill, Dept. of Computer Science (email@example.com)
Survey of Canadian and International Data Management Initiatives By Diego Argáez and Kathleen Shearer on behalf of the CARL Data Management Working Group (Working paper) April 28, 2008 Introduction Today,
Data Science at U of U Je M. Phillips Assistant Professor, School of Computing Center for Extreme Data Management, Analysis, and Visualization Director, Data Management and Analysis Track University of
White Paper Make the Most of Big Data to Drive Innovation Through Reseach Bob Burwell, NetApp November 2012 WP-7172 Abstract Monumental data growth is a fact of life in research universities. The ability
Standard Big Data Architecture and Infrastructure Wo Chang Digital Data Advisor Information Technology Laboratory (ITL) National Institute of Standards and Technology (NIST) firstname.lastname@example.org May 20, 2016
ISSN: 2454-2377, October 2015 Big Data and Hadoop Simmi Bagga 1 Satinder Kaur 2 1 Assistant Professor, Sant Hira Dass Kanya MahaVidyalaya, Kala Sanghian, Distt Kpt. INDIA E-mail: email@example.com
THE FEDERAL BIG DATA RESEARCH AND DEVELOPMENT STRATEGIC PLAN THE NETWORKING AND INFORMATION TECHNOLOGY RESEARCH AND DEVELOPMENT PROGRAM April 2016 MAY 2016 About this Document This report was developed
Statistical Analysis and Visualization for Cyber Security Joanne Wendelberger, Scott Vander Wiel Statistical Sciences Group, CCS-6 Los Alamos National Laboratory Quality and Productivity Research Conference
EXECUTIVE SUMMARY Big Data is not an uncommon term in the technology industry anymore. It s of big interest to many leading IT providers and archiving companies. But what is Big Data? While many have formed