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International open government initiatives are releasing an increasing volume of raw government datasets directly to citizens via the Web. The transparency resulting from these releases creates new application opportunities but also imposes new burdens inherent to large-scale distributed data integration, collaborative data manipulation and transparent data(More)
Data.gov is a website that provides US Government data to the general public to ensure better accountability and transparency. Our recent work on the Data-gov Wiki, which attempts to integrate the datasets published at Data.gov into the Linking Open Data (LOD) cloud (yielding " linked government data "), has produced 5 billion triples covering a range of(More)
The Open Government Directive is making US government data available via websites such as Data.gov for public access. In this paper, we present a Semantic Web based approach that incrementally generates Linked Government Data (LGD) for the US government. In focusing on the trade-off between high quality LGD generation (requiring non-trivial human expert(More)
The Third Provenance Challenge (PC3) offered an opportunity for provenance researchers to evaluate the interoperability of leading provenance models with special emphasis on importing and querying workflow traces generated by others. We investigated interoperability issues related to reusing Open Provenance Model (OPM)-based workflow traces. We compiled(More)
We present a novel ensemble architecture for learning problem-solving techniques from a very small number of expert solutions and demonstrate its effectiveness in a complex real-world domain. The key feature of our “Generalized Integrated Learning Architecture” (GILA) is a set of heterogeneous independent learning and reasoning (ILR) components,(More)
In this paper we describe the application of a novel learning and problem solving architecture to the domain of airspace management, where multiple requests for the use of airspace need to be reconciled and managed automatically. The key feature of our " Generalized Integrated Learning Architecture " (GILA) is a set of integrated learning and reasoning(More)
Provenance has been demonstrated as an important component in web applications such as mashups, as a means of resolving user questions. However, such provenance may not be usable by all members of a given applications user base. In this paper, we discuss how crowd-sourcing could be employed to allow individual users to get questions answered by the greater(More)
The Tetherless World (TW) Wine Agent extends the original Stanford Knowledge Systems Laboratory (KSL) Wine Agent to support collective recommendations on food-wine pairings. This is done to (1) demonstrate the advance of Semantic Web technologies, including OWL DL reasoning, SPARQL, provenance explanation, and semantic wikis, and (2) show how the Semantic(More)
As more data (especially scientific data) is digitized and put on the Web, the importance of tracking and sharing its provenance metadata grows. Besides capturing the annotation properties of data, provenance research also emphasizes interlinking relevant data. Therefore, it is desirable to make provenance metadata easy to access, share, reuse, integrate(More)