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dc.contributor.authorDing, Li
dc.contributor.authorMichaelis, James
dc.contributor.authorMcGuinness, Deborah L.
dc.contributor.authorHendler, James A.
dc.date.accessioned2022-02-18T02:38:34Z
dc.date.available2022-02-18T02:38:34Z
dc.date.issued2010-04-26
dc.identifier.other231
dc.identifier.urihttp://archive.tw.rpi.edu/media/latest/websci10_submission_112.pdf
dc.identifier.urihttps://hdl.handle.net/20.500.13015/4633
dc.description.abstractData.gov, a major distributor of raw US government data, has published thousands of raw datasets on the Web for public access. While these datasets provide useful information, their potential has not yet been fully realized due to usability-related issues. In this work, we investigate potential ways to make sense of existing open government data using semantic web technologies. In our study, we demonstrate strategies for turning open government data into linked government data and present several case studies to illustrate the role of linked government data in making sense of government data.
dc.relation.urihttps://tw.rpi.edu/project/LOGD
dc.subjectLinking Open Government Data
dc.titleMaking Sense of Open Government Data


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