|Author||Madnick, Stuart E. ♦ Wp, Sloan|
|Subject Domain (in DDC)||Computer science, information & general works ♦ Data processing & computer science|
|Subject Keyword||Various Form ♦ Large-scale Semantic Heterogeneity ♦ Different Context ♦ Particular Problem ♦ Data Semantics Acquisition ♦ Context Characteristic ♦ Context Definition ♦ Implicit Assumption ♦ Significant Challenge ♦ Potential Context Mediation Service ♦ Information Superhighway ♦ Data Quality Attribute ♦ Many Large Data Base ♦ Potential Receiver ♦ Context Challenge ♦ Data Base ♦ Context Interchange|
|Description||The popularity of distributed computing environments and the growth of the "Information SuperHighway " have dramatically increased the number of data bases available for use. Unfortunately, there are significant challenges to be overcome. One particular problem is context interchange, whereby each source of information and potential receiver of that information may operate with a different context, leading to large-scale semantic heterogeneity. A context is the collection of implicit assumptions about the context definition (i.e., meaning) and context characteristics (i.e., quality) of the information. This paper describes various forms of context challenges and examples of potential context mediation services, such as data semantics acquisition, data quality attributes, and evolving semantics and quality, that can mitigate the problem. 1.|
|Educational Role||Student ♦ Teacher|
|Age Range||above 22 year|
|Education Level||UG and PG ♦ Career/Technical Study|
|Learning Resource Type||Article|
|Publisher Institution||Proceedings of the 21st VLDB Conference|
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