.png){kind=icon}
.png){kind=icon}
Return
Consistent query answers from virtually integrated XML data
.png){kind=icon}
PRE
AI
DOI：10.1016/j.jss.2010.08.018.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
When data sources are virtually integrated, there is no common and centralized method to maintain global consistency, so inconsistencies with regard to global integrity constraints are very likely to occur. In this paper, we consider the problem of defining and computing consistent query answers when queries are posed to virtual XML data integration systems, which are specified following the local-as-view approach. We propose a powerful XML constraint model to define global constraints, which can express keys and functional dependencies, and which also extends the newly introduced conditional functional dependencies to XML We provide an approach to defining XML views, which supports not only edge-path mappings but also data-value bindings to express the join operator. We give formal definitions of repair and consistent query answers with the XML data integration settings. Given a query on the global system, we present a two-step method to compute consistent query answers. First, the given query is transformed using the global constraints, such that to run the transformed query on the original global system will generate exactly the consistent query answers. Because the global instance is not materialized, the query on the global instance is then rewritten in the form of queries on the underlying data sources by reversing rules in view definitions. We illustrate that the XPath query transformations can be implemented in XQuery. Finally, we implement prototypes of our method and evaluate our algorithms in the experiments. (C) 2010 Elsevier Inc. All rights reserved.
Keywords:
XML
inconsistent
Query
Constraint
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
4.1
Papers:
5.4K
Citations:
8.4K