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38 Degrees: An AOL Gov Conference Series, September 18-19, Washington, DC.

38 Degrees: An AOL Gov Conference Series, September 18-19, Washington, DC. Dr. Brand Niemann Director and Senior Enterprise Architect – Data Scientist Semantic Community http://semanticommunity.info/ AOL Government Blogger http://gov.aol.com/bloggers/brand-niemann/ July 22, 2012 DRAFT.

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38 Degrees: An AOL Gov Conference Series, September 18-19, Washington, DC.

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  1. 38 Degrees:An AOL Gov Conference Series, September 18-19, Washington, DC. Dr. Brand Niemann Director and Senior Enterprise Architect – Data Scientist Semantic Community http://semanticommunity.info/ AOL Government Blogger http://gov.aol.com/bloggers/brand-niemann/ July 22, 2012 DRAFT http://semanticommunity.info/AOL_Government/AOL_Government_38_Degrees_Unleashing_the_Power_of_Government_Data

  2. Brief Bio • Brand Niemann, former Senior Enterprise Architect and Data Scientist with the US EPA, completed 30 years of federal service in 2010. Since then he has worked as a data scientist for a number of organizations, produced data science products for a large number of data sets, and published data stories for Federal Computer Week, Semantic Community and AOL Government.

  3. Summary • Session 5: Harnessing Data: Lessons From the Front Lines. Learn how developers are testing and scaling solutions in cities across America and the challenges of and opportunities of using government data. • About 15 years ago I was part of a team that built FedStats.gov and FedStats.net to better open high-quality statistics to the citizen for which we got the Gore Hammer Award. The statistics had been available to citizens since 1878 in paper and since 1997 on the Web. • Five years ago I was asked to suggest a design for Data.gov and suggested essentially a “data-driven document approach” based on FedStats.gov and FedStats.net. A “data-driven document approach” is essentially what the new Digital Government Strategy is! So I recently updated FedStats.gov and re-created FedStats.net using the latest 2012 Annual Statistical Abstract. This is essentially turning Web Sites, documents, APIs, etc. into data for data science products and data journalism stories. I am finalizing the two stories about this recent work. • Europe and many other countries have done the same thing for years. • See: http://semanticommunity.info/FedStats.net#Section_30._International_Statistics • http://semanticommunity.info/FedStats.net#Appendix_I._Guide_to_Foreign_Statistical_Abstracts • as described in my recent story on Digital Agenda for Europe: Data as First Class Citizen: http://gov.aol.com/2012/06/29/digital-agenda-for-europe-data-as-first-class-citizen/

  4. Presentation • Specific data sets that the government and the Data.gov community believe have the greatest potential for being exploited for the benefit of the public – and how/where developers can get started! • 2012 IOGDC: Putting Data To Work with Data Science • FedStat.gov: Celebrating over 15 years of making statistics from more than 100 agencies available to citizens everywhere • FedStat.net: Commemorating over 135 years of making statistics available to citizens everywhere

  5. Introduction • Jeanne Holm Tweeted: Nice summary of #IOGDC points via @bniemannsr: Is There a Business Case for Open Government Data?: bit.ly/OjyOTf#opendata • Brand Niemann: Thank you and I have the high quality data sets for the United States in the form that can be used immediately and have many examples of data services and applications to show. Slides • Business Case and Examples: • Big Data Companies: Google, Facebook, and KinkedIn • Modeling and Visualizations (Data Science Class Examples) • Intelligence Community • Semantic Social Network Analytics and Graphics (Bin Laden Letters Example - MindTouch) • Statistical Community • FedStats.gov and FedStats.Net (see above slogans) (Prime Examples of High Quality Data and Metadata Directly Available and as Data-Driven Documents) • Health Data is the most - see my HealthdataPalooza and HealthData.gov Work

  6. Lessons Learned • Content leads technology selection: all that technology is not used unless the content supports it • The lessons I have learned are documented in my Data Science Products and in my Data Journalism Handbook

  7. FedStats Spreadsheet http://semanticommunity.info/@api/deki/files/18601/FedStats.xlsx

  8. FedStats.net Dashboard

  9. Data Sources Index

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