Abstract
Data integration aims at providing a unified view over data coming from various sources. One of the most challenging tasks for data integration is handling the inconsistencies that appear in the integrated data in an efficient and effective manner. In this chapter, we provide a survey on techniques introduced for handling inconsistencies in data integration, focusing on two groups. The first group contains techniques for computing consistent query answers, and includes mechanisms for the compact representation of repairs, query rewriting, and logic programs. The second group contains techniques focusing on the resolution of inconsistencies. This includes methodologies for computing similarity between atomic values as well as similarity between groups of data,
collective techniques, scaling to large datasets, and dealing with uncertainty that is related to inconsistencies.
collective techniques, scaling to large datasets, and dealing with uncertainty that is related to inconsistencies.
| Original language | English |
|---|---|
| Title of host publication | Data Exchange, Integration, and Streams |
| Subtitle of host publication | A volume from DEIS’10 – GI-Dagstuhl Seminar 10452 |
| Place of Publication | Saarbuecken/Wadern |
| Publisher | Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik |
| Chapter | 8 |
| Pages | 217-225 |
| ISBN (Print) | 978-3-939897-61-3 |
| Publication status | Published - 2013 |
| Externally published | Yes |