Producing and Using Linked Open Government Data in the TWC LOGD Portal

As open government initiatives around the world pub- lish an increasing number of raw datasets, citizens and communities face daunting challenges when organiz- ing, understanding, and associating disparate data re- lated to their interests. Immediate and incremental so- lutions are needed to integrate, collaboratively manipu- late, and transparently consume large-scale distributed data. The Tetherless World Constellation (TWC) at Rensselaer Polytechnic Institute (RPI) has developed the TWC LOGD Portal based on Semantic Web prin- ciples to support the deployment of Linked Open Gov- ernment Data. This chapter1 introduces the informatic challenges faced while developing the portal over the past two years and describes the design solutions em- ployed by the portal’s LOGD production infrastructure.

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Associated Projects

The NSF funded Theory and Practice of Accountable Systems (TPAS) Project investigates computational and social properties of information networks necessary to provide reliable assessments of compliance with rules and policies governing the use of information. In past research, we have demonstrated that achieving basic social policy goals in open information networks will require increased reliance on information accountability through after-the-fact detection of rule violations.

The LOGD project investigates the role of Semantic Web technologies, especially Linked Data, in producing, enhancing and utilizing government data published on Data.gov and other websites. Large portion of government data published on the Web are not necessarily ready for mashups. The Tetherless World Constellation (TWC) is now publishing over 8 billions RDF triples converted from hundreds of government-related datasets from Data.gov and other sources (e.g.

The Inference Web is a Semantic Web based knowledge provenance infrastructure that supports interoperable explanations of sources, assumptions, learned information, and answers as an enabler for trust.

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