Gt health2stat 7-22-2010
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Gt health2stat 7-22-2010 Presentation Transcript

  • 1. Data.gov: Web, Data Web, Social Data Web [email_address] 7/22/2010 #health2stat
  • 2.
      • The Web is evolving…
        • From a Web of Linked Documents,
        • To a Web of Linked Data!
  • 3.
      • OK…
      • What does that mean?
      • Bear with me for a quick overview -
  • 4.
      • There’s only one type of link in HTML
        • SourcePage.htm contains markup;
          • <a href='target.html'> hyperlink </a>
  • 5.
      • XML gave us custom tags
      • <myTag> typed data </myTag>
      • Good, but more importantly...
  • 6.
      • The Architecture of the Web
      • (one of the most important and successful inventions of the 20 th Century!)
      • is REST ful
      • (Info) Resource Representations (URI’s vs URL’s), Uniform Interface (CRUD via HTTP methods), server Resource and client App state (via links)...
  • 7.
      • Web + Data = Data Web
      • The Data Web (aka Web of Data) is an innovation that extends the existing Web of Documents
      • Beginning with the Resource Description Framework ( RDF )
      • Which is a Web based data modeling language
  • 8.
      • RDF gives us custom link types :
      • node <arc> node
      • thing <relationship> thing
      • topic <property> topic
      • entity <attribute> value
      • subject <predicate> object
      • the grammar of ‘triples’
  • 9.
      • HTTP GET ’dereferences’ RDF triples in multiple serialization (.htm, .rdf, .json) formats
      • So, the URI
      • http://agency.gov/Subject
      • has a URL representation that returns
      • <http://my.org/predicate> <http://your.com/Object>
  • 10.
      • Grammar needs vocabularies ...
      • Vocabularies can be metadata :
      • Objective quantifies Goal
      • So http://standards.org/vocab/Objective returns;
      • <quantifies> <http://standards.org/vocab/Goal>
  • 11.
      • Instance data (re)uses vocabularies:
      • Meaningful Use 'is a' (type of) Objective
      • http://onc.hhs.gov/Meaningful_Use
      • <type> <http://standards.org/Objective>
      • EHR Exchange 'is a' (type of) Goal
      • http://onc.hhs.gov/EHR_Exchange
      • <type> <http://standards.org/Goal>
  • 12.
      • OK…
      • Now we’ve introduced to the what , but -
      • WHY should we do this Linked (Open Gov) Data stuff?
  • 13.
      • We can (automatically) infer things like;
      • Meaningful Use quantifies EHR Exchange
      • We can traverse (via apps and browsers) the data graph with no apriori domain knowledge …
      • We/others just make links to correlate disparately owned/managed/published data across distinct (some say federated) domains…
  • 14.
      • We can (automatically) integrate disparate data sites/sources via graph merging !
      • If http://hhs.gov/about returns;
      • <owl:sameAs> <http:// dbpedia.org /DHHS>, <http://www. freebase.com /HHS> .
      • All these data from each site is seen as one dataset, substantially lowering coordination costs of integration!
  • 15.
      • Who is doing this in Industry?
      • Google, Facebook, Yahoo
      • NY Times, Newsweek
      • Best Buy, …
      • What about Government Agencies?
      • Library of Congress Subject Headings
      • http://id.loc.gov – pace setting example!
  • 16.
      • So what about Data.gov?
      • (Homepage: ‘Linking Open Government Data’)
      • Data.gov PMO SemWeb and Linked Data Team
      • Collaboration with tw.rpi.edu – SemWeb inventors
      • Federal CIOC-AIC Data Architecture Subcommittee Open Government Vocabulary WG
  • 17.
      • How about at HHS?
      • NLM: UMLS ‘SPARQL endpoint’
      • http://mor.nlm.nih.gov/sparql
      • CMS: Data.gov PMO SemWeb Team members
      • CMS Dashboard vocabulary WIP
      • CHDI: vocabularies and URI schemes
  • 18.
      • Rich linking scenarios to explore;
      • What are successful community intervention tactics to combat childhood obesity?
      • For these geographic health stats, what evidence based provider payment/performance trends emerge?
      • What other Gov data is relevant? Is there something in the air or water?
  • 19.
      • Web + Data = Data Web;
      • Data Web + Social = Social Data Web!
      • Consider the metadata creation (domain SME’s) and instance data curation (info workers) as objects of social collaboration.
      • Activity-stream history feeds, viral expert networking (etc.) will all contribute to enhanced data quality .
      • Think structured data wikis, where tags are suggested and come from SME designed ontologies (vocabularies) instead of user-generated folksonomies.
  • 20.
      • What can YOU do?
      • Get involved with the Data.gov PMO and/or the FCIOC-AIC-DAS-OGV-WG!
      • (Come to DC Semantic Web meetups too...)
      • Contact me 
      • THANKS!!!