Behavioral and Social Sciences Research

Transcription

1 Behavioral and Social Sciences Research Opportunities in Visualization and Data Analytics January 30, 2012 Contact: Science Advisor JOSEPHKIELMAN

2 FOR MORE INFORMATION: PIE: ivac: NVAC: VACCINE: CCICADA: VA Community: DHS University Programs:

3 U.S. Department of Homeland Security

4 Science and Technology Directorate Chief Scientist Under Secretary for S&T Chief of Staff Knowledge Management Office Deputy Under Secretary Office of Corporate Commumications Associate General Counsel Director of Finance and Budget Director of Administration and Support Executive Secretary Director of Support to the Homeland Security Enterprise and First Responders Director of Homeland Security Advanced Research Projects Agency Director of Acquisition Support and Operations Analysis Director of Research & Development Partnerships Office of Interoperability and Compatibility Borders & Maritime Security Division Capstone Analysis & Requirements Office Interagency Office Technology Clearinghouse/R-Tech Chemical/Biological Defense Division HSSAI SEDI International Cooperative Programs Office NUSTL Cyber Security Division Office of Systems Engineering Office of National Labs Explosives Division Test & Evaluation and Standards Office PIADC NBACC NBAF CSAC Human Factors/Behavioral Sciences Division Infrastructure Protection & Disaster Management Division TSL Office of Public-Private Partnerships SBIR LRBAA Safety Act Office Special Projects Office Office of University Programs HSSTAC Executive Director & NSTC Liaison

5 The Formation and Growth of Visualization and Data Analytics PIE Transition VACCINE & CCICADA ACI UACs RVACs FODAVA NVAC The Idea 2004: NVAC Formed Dec, 2004: USA-UK MOA on S&T signed Nov, 2007: USA-Canada CAA signed Nov, 2009: VACCIN E Kickoff Dec, 2009: PIE Kick-off Feb, 2011: VASA Kick-off and beyond! 2007: IN-SPIRE to IC and PANYNJ 2007: NSF- S&T FODAVA Initiative begins March, 2009: USA- Germany MOA signed Dec, 2009: CCICADA Kick-off Dec, 2010: STARE 2011: IN-SPIRE to ICE BCSC June 2011: ERE CAUSE 2007: COMPSTAT II to PANYNJ 2011: IN-SPIRE to ICE OCIO SRS to PNW

6 New Homeland Security Concerns Environmental Stability Slow Catastrophes Resource Constraints Threat (All-Hazards) Awareness Population Dynamics and Ethnic Conflict Financial Stability Terrorism Natural and Manmade Disasters Disease Development Economic Stability Climate Change

7 The Problem: Big Data In 2002, recorded media and electronic information flows generated about 22 exabytes (10 18 bytes) of information In 2006, the amount of digital information created, captured, and replicated was 161 EB In 2010, the amount of information added annually to the digital universe was estimated at 1,600 EB (1.6 ZB) Annual global consumer internet traffic was 140 EB in 2010; estimated to rise to about 600 EB in % of the Digital Universe s information is unstructured 25% of the digital information produced in 2010 was images By 2014 file sharing and video will represent about 25% and 35%, respectively, of internet traffic Ref: IDC, UC-Berkeley, and Cisco

8 Data Volumes in 60 Minutes of Emergency Response

9 Products and Tools

10 Information in Homeland Security What part is relevant? Am I missing something? What does it mean? When will I need it? How do I use it? Can I trust it? Is it private or personal? How do I convey it to others? When can I take actions with it? And which ones? How will others see it? Are risks, threats, and consequences absolute?

11 Science and Technology Principles What Is the Problem? Information -There are real-world resiliency issues for which the availability and usefulness of information is problematic How Do We Structure the Solution? Utility -The capabilities being developed must address at least four information-related concerns: increasing amounts and diversity of data compounded by multiplicity of users; indeterminate nature of relevance coupled with multiplicity and complexity of threats What Is the Value of the Work? Outcome -The improvements being provided must have real-world outcomes or implications for the homeland security enterprise

12 Principles and Vision What is the Problem? Information How do we Structure the Solution? Utility What is the Value of the Work? Outcome Operational Reasons Assist in understanding the relationships among components of the enterprise addressing and affected by a homeland security incident Help planners make communities more resilient Enable quicker, more effective response, recovery, and remediation Help decision-makers evaluate implemented strategies and tactics and plan for improvement Technical Reasons More analytical capacity to deal with lots of heterogeneous information A common platform providing tailored information across distributed teams Anytime, anywhere visibility into enterprise data Real-time analysis of dynamic data

13 Research Complex

14 The Visualization and Data Analytics Enterprise: a coordinated research activity

15 The Integrated Visualization and Analytics Community (ivac) Newsletter The ivac is distributed monthly, highlighting projects, events and activities of interest to the VAPr-funded community and its partners to be added to the distribution list Or visit

16 FOR MORE INFORMATION: PIE: ivac: NVAC: VACCINE: CCICADA: VA Community: DHS University Programs:

17 A Bit of History: the NVAC Established in 2004 as a national and international resource Unique research partnerships with universities, industry, and other government organizations Strategic leadership and coordination for research in and development of visual analytics technologies and tools Operational partnerships with local, state, and federal agencies Focus on predictive analytics for public safety, law enforcement, public health, and emergency response Man-made or natural disasters Terrorist incidents or attacks Longer term catastrophes or larger scale problems Tools, technologies, and techniques to identify and assess threats and vulnerabilities; detect, prevent, or reduce the potential effects of multiple threats; and aid recovery from incidents or disasters Website:

18 Analytics for Complex Information (ACI) ACI NS F IDD PTI PIE ACI products seek to enable users to harness and utilize Massive data, which comes in Multiple modes and Multiple types, through Multiple devices, in Diverse user environments, In order to make decisions in real-time.

19 Analytics for Complex Information (ACI) NS F ACI IDD PTI PIE Focus on predictive analytics for public safety, law enforcement, public health, and emergency response Man-made or natural disasters Terrorist incidents or attacks Longer term catastrophes or larger scale problems Tools, technologies, and techniques to identify and assess threats and vulnerabilities; detect, prevent, or reduce the potential effects of multiple threats; and aid recovery from incidents or disasters Dynamic Information Made Actionable In Real-Time

20 Precision Information Environments (PIE) NS F ACI IDD PTI PIE Improve collaborative decision making across the emergency management lifecycle, from planning to response and recovery. Objectives: Ensure that responders, planners, and decision makers have access to relevant, actionable information in context-appropriate interfaces. Enable coordination of effort among distributed users with partial information. Support online what-if analysis of response strategies and decision deconfliction.

21 Enterprise Resiliency Experiments (ERE) Series of annual, regionally-based experiments to guide research and development activities, as well as operational and outreach activities Integrate a limited set of developed, established technical solutions Using an earthquake scenario, the first ERE Canada-US Experiment (CAUSE) demonstrated the integration of numerous tools developed by the Visualization and Data Analysis program through national laboratories, universities, research organizations, and industry partners Operators, First Responders, and the Public (the Homeland Security Enterprise) using the technologies Demonstrate and measure value and utility S&T technologies Incorporate planning, integration, after action analysis, and of experiment, outreach activities

22 CAUSE (Canada-US Enhanced) ERE The first ERE CA/US Enhanced (CAUSE) Resilience took place June 21, 2011, in Seattle and Richland, WA, and in 3 Canadian locations near Vancouver Exploration of cross-border communications and collaboration Excellent participation from broad range of emergency managers and operators Significant integration of multiple technologies Solid input on technology strengths, weaknesses, opportunities Significant interest in piloting most of the technologies Developers have clearer picture of complexity of inserting new capabilities into other environments

23 Staging and Testing Analytics for Real Environments (STARE) Capability for bringing staff, users, and industry together to evaluate and guide the transition of technologies developed Leveraged relationships with users in the Northwest USERS Develop and institutionalize approach that effectively transitions demonstrated technologies into broad use in a sustainable manner with appropriate documentation, warranties, training, and technical support. RESEARCHERS INDUSTRY

24 Command, Control, and Interoperability Center of Excellence (CCI COE) VACCI NE CCI COE CCICA DA

25 Visual Analytics for Command, Control, and Interoperability Environments (VACCINE) VACCI NE CCI COE CCICA DA Led by Purdue University, VACCINE focuses on research, development, and deployment of interactive visual analytic environments for communicating and disseminating information and deriving insight from massive amounts of homeland security data VACCINE develops novel tools to help people make sense of this diverse and diffuse mix of text, geospatial, transaction, sensor, audio, and video data by creating powerful analytical tools and interactive visual decision making environments VACCINE encompasses 3 fundamental areas of research: 1. Interactive Visual Analytic Foundations, 2. Visually Adapted Analytical Techniques, and 3. Investigative Analysis and Decision Making Environments Robust academic program VACCINE website: CCI.org

26 Command, Control, and Interoperability Center for Advanced Data Analysis (CCICADA) VACCI NE CCI COE CCICA DA Focuses on algorithmic methods for challenging problems in data analysis Developing capabilities to reveal patterns and draw inferences from massive amounts of unstructured data contained in books, newspapers, reports, blogs, images, geospatial data, sensor readings, and audio and video streams Building the mathematical foundations for a new generation of computational methods Partners with a wide variety of agencies in local, state, and Federal government, as well as in the private sector Committed to building pioneering educational programs, which are fully integrated with ongoing research and designed to meet a broad spectrum of educational needs CCICADA website: