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| Content Provider | ACM Digital Library |
|---|---|
| Author | Sacharidis, Dimitris Auer, Sören Buneman, Peter Bancilhon, François Kotzinos, Dimitris Thiveos, Kostas Flouris, Giorgos Dalamagas, Theodore Stavrakas, Yannis Parkinson, Helen Christophides, Vassilis Papastefanatos, George |
| Abstract | The Linked Data Paradigm is a promising technology for publishing, sharing, and connecting data on the Web, which provides new perspectives for data integration and interoperability. However, the proliferation of distributed, interconnected linked data sources on the Web poses significant new challenges for consistently managing the vast number of potentially large datasets and their interdependencies. In this article we focus on the key problem of preserving evolving structured interlinked data. We argue that a number of issues, which hinder applications and users, are related to the temporal aspect that is intrinsic in Linked Data. We present three use cases to motivate our approach, we discuss problems that occur, and propose a direction for a solution. |
| Starting Page | 31 |
| Ending Page | 39 |
| Page Count | 9 |
| File Format | |
| ISBN | 9781450314046 |
| DOI | 10.1145/2422604.2422610 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2012-05-25 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Data evolution Linked data lifecycle Data preservation Data provenance |
| Content Type | Text |
| Resource Type | Article |
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