dc.contributor.author | Ding, Li | |
dc.contributor.author | Michaelis, James | |
dc.contributor.author | McGuinness, Deborah L. | |
dc.contributor.author | Hendler, James A. | |
dc.date.accessioned | 2022-02-18T02:38:34Z | |
dc.date.available | 2022-02-18T02:38:34Z | |
dc.date.issued | 2010-04-26 | |
dc.identifier.other | 231 | |
dc.identifier.uri | http://archive.tw.rpi.edu/media/latest/websci10_submission_112.pdf | |
dc.identifier.uri | https://hdl.handle.net/20.500.13015/4633 | |
dc.description.abstract | Data.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.uri | https://tw.rpi.edu/project/LOGD | |
dc.subject | Linking Open Government Data | |
dc.title | Making Sense of Open Government Data | |