Data integration is one of the most significant IT problems facing government today. Using information technology, government agencies have collected vastly more data than was ever possible to collect before. Unfortunately, for lack of standardization, most government data today exists in thousands of different formats and resides in hundreds of systems and versions, spread across dozens of agencies. This situation makes the data almost impossible to find, re-use, and build upon after further data collection. A considerable amount of research has been performed over the past decades to overcome this problem. Within Digital Government, several projects have focused on government data collections. Three principal approaches have been followed: (1) direct access, using information retrieval techniques; (2) metadata reconciliation, using ontology alignment techniques; and (3) data mapping, using information theoretic techniques. This chapter discusses each approach, and provides specific examples of the last two.
Keywords
- Inductive Logic Programming
- Energy Information Administration
- Energy Information Administration
- Pointwise Mutual Information
- Information Retrieval Technique
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© 2008 Springer Science+Business Media, LLC
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Hovy, E. (2008). Data and Knowledge Integration for e-Government. In: Chen, H., et al. Digital Government. Integrated Series In Information Systems, vol 17. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-71611-4_12
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DOI: https://doi.org/10.1007/978-0-387-71611-4_12
Publisher Name: Springer, Boston, MA
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