Synopsis
Discover how metadata helps systems agree on data meaning and avoid semantic conflicts.
This book explains a practical approach to describing data semantics and using that description to ensure a database can supply meaningful data to an application.
It presents a flexible model for data semantics that is independent of any single data model. You’ll see how metadata can be linked to data attributes, how semantic comparisons are used to verify meanings, and how query processing can adapt to changing semantics in dynamic environments. The text also outlines strategies for handling conflicts before or during query execution and how run-time checks can support semantic equivalence.- What metadata is and why it matters for data meaning.
- A rule-based approach to linking metadata with data attributes and applications.
- How to compare the semantics of a database and an application to detect conflicts.
- Query processing techniques that guarantee meaningful results, even as semantics change.
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About the Author
About the Editor:
Stuart E. Madnick is Associate Professor of Management Science at the Sloan School of Management, M.I.T., and the principal investigator of a major research effort, funded by DOD and Citibank, to identify the key strategic, organizational, and technology issues in large-scale information systems.
"About this title" may belong to another edition of this title.
