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Learning from the History of Distributed Query Processing - A Heretic View on Linked Data Management

Published on 2012-12-032367 Views

The vision of the Semantic Web has triggered the development of various new applications and opened up new directions in research. Recently, much e ffort has been put into the development of technique

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LEARNING FROM THE HISTORY OF DISTRIBUTED QUERY PROCESSING00:00
Motivation00:12
Agenda01:28
DISTRIBUTED AND FEDERATED DATABASES01:53
Systems02:01
Techniques02:52
Still Unsolved Problems (1)03:09
Still Unsolved Problems (2)04:06
THESES04:12
1. The Volume of Linked Data Is Too Big for Centralized Management04:23
2. Materialization in Centralized Repositories Violates Data Authority05:50
3. Scalability Can Be Achieved Only by Distributed Query Processing06:55
4. Linked Data Processing Is only about SPARQL Processing07:41
5. The Problem of Semantic Heterogeneity Can Be Solved by Using Ontologies08:22
6. HTTP URIs Can Be Used to Identify Relevant Endpoints09:14
7. The Freshness of Data Is Guaranteed only with Distributed Query Processing09:59
8. Open Data Is Accessible as Linked Data10:53
9. Centralized Linked Data Is not Linked Data anymore11:34
RESEARCH AGENDA12:08
Linked Data as a Service12:25
1. Linked Data Processing beyond SPARQL Processing13:54
2. Exploit Newly Available Infrastructure/Platform as a Service14:26
3. Address the Opportunities of Modern Hardware Architectures for Query Processing15:06
4. Realistic Benchmarking and Metrics15:42
5. Simplify Publishing and Exploit Crowdsourcing16:27
CONCLUSION16:54
Conclusion 116:56
CLOSING WORDS17:44