Gt health2stat 7-22-2010
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Gt health2stat 7-22-2010






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

    • Web, Data Web, Social Data Web [email_address] 7/22/2010 #health2stat
        • The Web is evolving…
          • From a Web of Linked Documents,
          • To a Web of Linked Data!
        • OK…
        • What does that mean?
        • Bear with me for a quick overview -
        • There’s only one type of link in HTML
          • SourcePage.htm contains markup;
            • <a href='target.html'> hyperlink </a>
        • XML gave us custom tags
        • <myTag> typed data </myTag>
        • Good, but more importantly...
        • 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)...
        • 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
        • 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’
        • HTTP GET ’dereferences’ RDF triples in multiple serialization (.htm, .rdf, .json) formats
        • So, the URI
        • has a URL representation that returns
        • <> <>
        • Grammar needs vocabularies ...
        • Vocabularies can be metadata :
        • Objective quantifies Goal
        • So returns;
        • <quantifies> <>
        • Instance data (re)uses vocabularies:
        • Meaningful Use 'is a' (type of) Objective
        • <type> <>
        • EHR Exchange 'is a' (type of) Goal
        • <type> <>
        • OK…
        • Now we’ve introduced to the what , but -
        • WHY should we do this Linked (Open Gov) Data stuff?
        • 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…
        • We can (automatically) integrate disparate data sites/sources via graph merging !
        • If returns;
        • <owl:sameAs> <http:// /DHHS>, <http://www. /HHS> .
        • All these data from each site is seen as one dataset, substantially lowering coordination costs of integration!
        • Who is doing this in Industry?
        • Google, Facebook, Yahoo
        • NY Times, Newsweek
        • Best Buy, …
        • What about Government Agencies?
        • Library of Congress Subject Headings
        • – pace setting example!
        • So what about
        • (Homepage: ‘Linking Open Government Data’)
        • PMO SemWeb and Linked Data Team
        • Collaboration with – SemWeb inventors
        • Federal CIOC-AIC Data Architecture Subcommittee Open Government Vocabulary WG
        • How about at HHS?
        • NLM: UMLS ‘SPARQL endpoint’
        • CMS: PMO SemWeb Team members
        • CMS Dashboard vocabulary WIP
        • CHDI: vocabularies and URI schemes
        • 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?
        • 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.
        • What can YOU do?
        • Get involved with the PMO and/or the FCIOC-AIC-DAS-OGV-WG!
        • (Come to DC Semantic Web meetups too...)
        • Contact me 
        • THANKS!!!