Data-gov Wiki: Towards Linking Government Data Li Ding, Dominic DiFranzo, Alvaro Graves, James R. Michaelis, Xian Li, Deborah L. McGuinness and Jim Hendler Tetherless World Constellation March 22, 2010

Outline Background –Open Government Data Initiative –data.gov The Data-gov Wiki –Making Government Linkable –Linking and Using Government Data –Provenance Issues

Background

Open Government Data Initiative Transparency Participation Collaboration Open Government Directive (Dec 8, 2009) Publish Government Information Online Improve the Quality of Government Information Create and Institutionalize a Culture of Open Government Create an Enabling Policy Framework for Open Government

data.gov, data.gov.uk and beyond What’s next? More datasets More links More provenance £30 million to fund "Institute of Web Science"

Statistics about data.gov 50 participating agencies: USDA, DOC, DOD, ED, DOE, HHS, DHS, HUD, DOI, DOJ, DOL, STATE, DOT, TREAS, VA, EPA, GSA, NASA, NSF, NRC, OPM, SBA, SSA, USAID, BBG, CFTC, CNS, EXIM, EOP, FCC, FDIC, FEC, FRB, IMLS, MSPB, NARA, NEA, NEH, NLRB, NTSB, OSHRC, ONHIR, OPIC, PBGC, RRB, SEC, SSS, TVA, CPSC, EEOC Source: accessed March 21, 2010http://

The Data-gov Wiki

About the data-gov Wiki Mission The data-gov project investigates the role of semantic web technologies, esp. linked data, in producing, processing and utilizing government data found in data.gov. Objectives Support linked government data publishing, applications and provenance using semantic technologies Educate potential developers and users Enable social collaborations on linked government data This project is run by the Tetherless World Constellation at RPI, headed by Profressor Jim Hendler and Deborah McGuinness and led by Li Ding. Other team members include: Dominic DiFranzo, Sarah Magidson,James Michaelis, Alvaro Graves, Adam Bell, Jin Guang Zheng, Xian Li, Tim Lebo, Gregory Todd Williams, and Peter Coons.

Data-gov Wiki Architecture Data Web Linked Data Linked Data LGD in RDF Enhancement Conversion Knowledge Provenance … Usage LGD: Linked government data

Data-gov Cloud (Oct 2009) US-COMMUNITY ( ) CASTNET (1990 – Present) RECS (2005) GOV-BUDGET ( ) TOXIC-RELEASE ( ) EARTHQUAKE (Present) STATE-LIB ( ) PUBLIC-LIB ( ) MED-COST ( ) LABOR-STAT (19xx-Present) DATA-GOV-CATALOG (present) Government Community Services Environment CASTNET sites RECS code US agency US location Linked Data USAspending ( ) GeoNames

data.gov + uk gov data + NY times + DBpedia

From Open Government Data (OGD) to Linked Government Data (LGD)

Make government data linkable Account nameAgency name Donations, Donations for the Official Residence of the Vice President Executive Office of the President RDF Conversion *Minimal and extensible * Web accessible Donations, Donations for the Official Residence of the Vice President … Executive Office of the President Raw RDF: Raw Data:

Linking at Conversion Time Reuse Property Defense Vessel Transfer Receipt Account … Department of Defense--Military Raw RDF: Donations, Donations for the Official Residence of the Vice President … Executive Office of the President Raw RDF:

Linking using Semantic Wiki enrich ontology definition Property Definition: [[rdfs:subPropertyOf::Property:rdfs:label]] 92/title … Property Definition:

Linking using Semantic Wiki connect entities using owl:sameAs X Wrong Wikipedia Name  Correct Wikipedia Name

Incremental Data Enhancement ….. Enhance raw RDF with links: Link to DBpedia: Executive Office of the President ……

Runtime Linking in Applications Link datasets by common literal value Link datasets by overlapping time –Align multiple time series –Support users to comment on time series data

Provenance Issues

Provenance Annotation Descriptions Relations Dataset Demo Agency

Provenance Events CSV2RDF SemDiff Archive Enhance visualize derive create derive revision

Results from Revision Provenance The number of datasets published at data.gov has been tripled since July 2009 Dataset updates on data.gov are not limited to additions.

Conclusion

Conclusion - Observations  Minimal and extensible RDF conversion is useful for generate linked government data in a timely fashion  Literal name is still useful in linking data, especially if we know the context of data  Social semantic web technologies can help distributing high cost tasks, e.g. mapping entity names, to the crowd.  Provenance is a growing requirement to the transparency of open data applications

Conclusions – Ongoing Work build hub datasets GOV-BUDGET ( ) PUBLIC-LIB ( ) CASTNET sites US agency US location USAspending ( ) Employment statistics Medicare cost IRS annual Tax report DATA-GOV-CATALOG (present) US Census State population Blah, blah… … ….. skos:altLabel owl:sameAs

Conclusions – Ongoing Work Making Sense of LGD AI + CI ! To appear in Web Sci 2010 conference – co-located with WWW 2010

Conclusions – Ongoing Work incremental knowledge on social semantic web A social semantic web website can substantially promote collaborations on knowledge accumulation (ontology as well as instance linkage) We need a tradeoff on costly high quality conversion and ugly minimal conversion #a dgp92:title “my title” dgp92:title rdfs:subPropertyOf rdfs:label #a rdfs:label “my title” #a skos:prefLabel “my title” #a foaf:name “my title” ?

Conclusions – Ongoing Work provenance is everywhere Evaluate issues on exposing provenance data and improve semantic-difference computation.  provenance vocabulary  provenance awareness  provenance reasoning  provenance mining  …

Ok, it is really the final conclusion The data-gov project does not use much AI for now (most on representation side), but even little semantics goes a long way The massive knowledge accumulated in this project is now raising a number of challenges to AI (especially the computation side) Semantic technologies are not far from us, undergraduate students can build a demo quickly!

BTW,…. Questions? Shameless self-promotions Link: “Browsing and Finding Linked Data” by Shangguan this afternoon See us at demo/poster session, we have more exciting demos to show you IPAW 2010 (June 2010, Troy, NY) will be looking for late breaking news from you!