Synopsis
This book explores a metadata approach to resolving semantic conflicts in data system environments, merging static and dynamic system perspectives. In the present era of increasingly complex information systems and growing integration of heterogeneous information systems, the book takes up the mantle of the crucial research question: how can methods be developed that consider the meaning of the data used in these systems? The author posits a metadata-based approach to resolving conflicts in data semantics, and additionally, a range of semantic reconciliation query processing techniques, to automatically guarantee correct data semantics. The work discusses the impact of changing data semantics at either the source or application, describing methods for detecting these changes, identifying whether a database can continue to supply meaningful data, and in some instances, resolving newfound semantic conflicts to allow data supply. Timely and thorough, this examination of metadata's role in semantic reconciliation within data system environments will be of high value to academics working on similar investigative paths and industry professionals seeking solutions to real-world data integration woes.
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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.
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A Metadata Approach to Resolving Semantic Conflicts (Classic Reprint)
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Paperback. Condition: New. Print on Demand. This book explores a metadata approach to resolving semantic conflicts in data system environments, merging static and dynamic system perspectives. In the present era of increasingly complex information systems and growing integration of heterogeneous information systems, the book takes up the mantle of the crucial research question: how can methods be developed that consider the meaning of the data used in these systems? The author posits a metadata-based approach to resolving conflicts in data semantics, and additionally, a range of semantic reconciliation query processing techniques, to automatically guarantee correct data semantics. The work discusses the impact of changing data semantics at either the source or application, describing methods for detecting these changes, identifying whether a database can continue to supply meaningful data, and in some instances, resolving newfound semantic conflicts to allow data supply. Timely and thorough, this examination of metadata's role in semantic reconciliation within data system environments will be of high value to academics working on similar investigative paths and industry professionals seeking solutions to real-world data integration woes. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book. print-on-demand item. Seller Inventory # 9781332269808_0
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