Dr. Brand Niemann Director and Senior Data Scientist Semantic Community

1. Challenges and Solutions for Big Data in the Public Sector:DGI’s 3rd Annual Government Big Data ConferenceOctober 9, Ronald Reagan Building, Washington, DC Dr. Brand Niemann Director and Senior Data Scientist Semantic Community http://semanticommunity.info/ http://www.meetup.com/Federal-Big-Data-Working-Group/ http://semanticommunity.info/Data_Science/Federal_Big_Data_Working_Group_Meetup October 9, 2014

2. Overview • Related Presentations: • COM.BigData Conference (Keynote and Panel), August 4-6, Washington, DC, and • IEEE 2014 Big Data Conference (Paper and NIST Big Data Workshop), October 27-30, Washington, DC. • Moderator: • Dr. Brand Niemann, Director and Senior Data Scientist, Semantic Community, and Co-organizer, Federal Big Data Working Group Meetup • Panelists: • Dr. Tom Rindflesch, Information Research Specialist at Cognitive Science Branch, National Institutes for Health (NIH): Semantic Medline (Ontology, Cray Graph Appliance, and Relational Databases) • Dr. Kirk Borne, Professor of Astrophysics and Computational Science, George Mason University: NSF Big Data Project of the Decade: LSST http://www.digitalgovernment.com/Events/Conferences/Government-Big-Data-Conference--Expo.shtml

3. Mission Statement • Federal: Supports the Federal Big Data Initiative, but not endorsed by the Federal Government or its Agencies; • Big Data: Supports the Federal Digital Government Strategy which is "treating all content as data", so big data = all your content; • Working Group: Data Science Teams composed of Federal Government and Non-Federal Government experts producing big data products (How was the data collected, Where is it stored, What are the results, and Does the data story persuade?); and • Meetup: The world's largest network of local groups to revitalize local community and help people around the world self-organize like MOOCs (Massive Open On-line Classes) being considered by the White House to reduce the cost of higher education. Co-organizers: Brand Niemann and Katherine Goodier

4. Decisions = Science + Art:The Challenger Accident • Richard Feynman's famous conclusion to his report on the shuttle Challenger accident, which arose again in the Columbia accident, is "For a successful technology, reality must take precedence over public relations, for Nature cannot be fooled." • -- Edward Tufte The Challenger: An Information Disaster Note: These charts appear in Edward Tufte’s book, Visual Explanations: Images and Quantities, Evidence and Narrative.

5. Fourth Paradigm and Fourth Question • The Fourth Paradigm of Science (1): • First Paradigm. Observation, descriptions of natural phenomena, and experimentation. • Second Paradigm. Theoretical science such as Newton’s laws of motion and Maxwell’s equations. • Third Paradigm. Simulation and modelling, such as in astronomy. • Fourth Paradigm. Data-intensive science that exploits the large volumes of data in new ways for scientific exploration, such as the International Virtual Observatory Alliance in astronomy. • The Fourth Question of Big Data for Science (2): • How was the data collected? • Where is the data stored? • What are the data results? • Does the data story persuade? President Obama Discovers Big Data in 2009 Bell G, Hey, T., & Szalay, A. (2009) Beyond the data deluge, Science 323, 6 March 2009, pp. 1297-1298. de Waard, Anita, (2014) About Stories, that Persuade With Data, Federal Big Data Working Group Meetup, 20 May,, 41 slides.

6. Symposium on Predictive Analytics For Defense and Government, November 18-19, Washington, DC Data Science Central

7. NIH Data CommonsDr. Phil Bourne (7/30/2014): Rules, Credit/Not Money, & More Offline http://semanticommunity.info/Data_Science/Data_Science_for_RDA#Slide_50_The_Power_of_the_Commons My Note: Registries, Repositories, Clearinghouses, Portals, GitHubs, Data Commons, & Data FAIRportsto MindTouch and Spotfire

8. Best Practices for Data: A Biologists View BestPracticesForData_PhilipBourne.pdf

9. Examples of Data Publications in Data Browsers for Senior Government People Data Source: Semantic Community NSF BIG DATA PROPOSAL

10. Data Science Central: Meteors Descriptive and Predictive Data Science Data Publications in a Data Browser Web Player

11. Data Science for JHU/NSF DIBBs Project: Knowledge Bases Data Science Publication Index: Index is Linked Open Data! Data Science Data Publication: Table of Contents is An Ontology! Data Science for JHU DIBBs Project SDSS.xlsx

12. Data Science for JHU/NSF DIBBs Project: Analytics & Visualizations Data Science Data Publications in a Data Browser Spotfire Content, Network, and Data Analytics: Spotfire is a Microscope and a Telescope for 77 TB! Web Player

13. Cover Page-Performance Analytics: FDA TRACK Data Science Data Publications in a Data Browser My Note: Most programs do not have a Strategic Plan! Web Player

14. October 6thMeetup Agenda • 6:30 p.m. Welcome and Introduction – Report on Recent Meeting with Dr. TahaKass-Hout, FDA’s First Chief Health Informatics Officer (CHIO) and FDA Data Science Data Publication Tutorial: • Interest in our Meetup on OpenFDA, July 7th • Keynote at AFCEA Bethesda’s Health IT Day, December 2nd • 7:00 p.m. Brooke Aker, Big Data Lens, Predictive Analytics for OpenFDA and Other Examples • 7:45 p.m.​ Brief Member Introductions and Inter-American Development Bank Open Data Portal Examples • 8:30 p.m. Open Discussion • 8:45 p.m. Networking • 9:00 p.m. Depart