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AIC Seminar Series

Linked Open Government Data: Opportunities and Challenges

Li DingRensselaer Polytechnic Institute

Notice:  Hosted by Vinay Chaudhri

Date:  2011-04-12 at 16:00

Location:  EK255 (SRI E building)  (Directions)

   Abstract

Data.gov, the official US open government data portal, leverages the Web to promote transparency and help citizens to find, access, and understand government data. This talk shows the use of Semantic Web technologies (RDF, RDFS, SPARQL and RDFa) in the ongoing open government activities, especially in Data.gov. We will then discuss the opportunities and challenges of linked open government data (LOGD) ecosystem in supporting large-scale distributed data integration, collaborative data manipulation and transparent data consumption. First, LOGD enables “web-scale mash-ups”; therefore, applications are no longer limited to one or several datasets but can use all the inter-connected data (including non-government data) distributed on the Web. Second, LOGD enables “data-as-interface” which complements service oriented architecture in decoupling the work load of large-scale government data processing activities to independent human experts and users, e.g. data curators, analysts, UI developers, and end users. Last but not the least; LOGD accommodates government together with the corresponding provenance and context metadata, allowing follow-up automated data consumption and analysis, e.g. policy validation, quality assurance, cross-domain knowledge discovery and social network analysis.

   Bio for Li Ding

Dr. Li Ding is a research scientist in the Tetherless World Constellation (TWC) at Rensselaer Polytechnic Institute (RPI). He is currently the technical lead of the TWC Linking Open Government Data (LOGD) project which has helped Data.gov, the US open government data web portal, in adopting semantic web technologies for data publishing and data integration. He is a former Kodak postdoctoral fellow in the Knowledge Systems, Artificial Intelligence Laboratory (KSL) at Stanford University where he built ontology-based provenance and trust infrastructure for collaborative online knowledge management systems. He received Ph.D. in computer science from University of Maryland Baltimore County with his pioneer work on Swoogle, the first web-scale semantic web search engine. He received B.S. and M.S. in computer science from Peking University where he started applying semantic web technologies to geographical information systems in 2000. As an early adopter of the Semantic Web, he has published over 70 refereed papers and received over 1600 citations (source: Google Scholar). He is current or past program committee member of international conferences including WWW, ISWC, AAAI and CIKM.

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