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Issue No.01 - January/February (2011 vol.15)
pp: 31-39
Yannis Theoharis , Forth-ICS
Irini Fundulaki , Forth-ICS
Capturing trustworthiness, reputation, and reliability of Semantic Web data manipulated by SPARQL requires researchers to represent adequate provenance information, usually modeled as source data annotations and propagated to query results along with a query evaluation. Alternatively, abstract provenance models can capture the relationship between query results and source data by taking into account the employed query operators. The authors argue the benefits of the latter for settings in which query results are materialized in several repositorwies and analyzed by multiple users. They also investigate how relational provenance models can be leveraged for SPARQL queries, and advocate for new provenance models.
Provenance, SPARQL, Semantic Web, trustworthiness, reliability, relational provenance
Yannis Theoharis, Irini Fundulaki, Grigoris Karvounarakis, Vassilis Christophides, "On Provenance of Queries on Semantic Web Data", IEEE Internet Computing, vol.15, no. 1, pp. 31-39, January/February 2011, doi:10.1109/MIC.2010.127
1. D. Artz and Y. Gil, "A Survey of Trust in Computer Science and the Semantic Web," Web Semantics, vol. 5, no. 2, 2007, pp. 58–71.
2. H. Huang and C. Liu, "Query Evaluation on Probabilistic RDF Databases," Proc. Conf. Web Information Systems Eng., LNCS 5802, Springer-Verlag, 2009, pp. 307–320.
3. N. Fuhr and T. Rölleke, "A Probabilistic Relational Algebra for the Integration of Information Retrieval and Database Systems," ACM Trans. Information Systems, vol. 14, no. 1, 1997, pp. 32–66.
4. T. Imielinski and W. Lipski, "Incomplete Information in Relational Databases," J. ACM, vol. 31, no. 4, 1984, pp. 761–791.
5. I.S. Mumick and O. Shmueli, "Finiteness Properties of Database Queries," Proc. Australasian Database Conf., Australian Computer Soc., 1993, pp. 761–791.
6. T.J. Green et al., "Update Exchange with Mappings and Provenance," Proc. Very Large Databases, ACM Press, 2007, pp. 375–686.
7. G. Karvounarakis, Z.G. Ives, and V. Tannen, "Querying Data Provenance," Proc. Conf. Special Interest Group on Management of Data (SIGMOD), ACM Press, 2010, pp. 951–962.
8. J. Cheney, L. Chiticariu, and W.C. Tan, "Provenance in Databases: Why, How, and Where," Foundations and Trends in Databases, vol. 1, no. 4, 2009, pp. 379–474.
9. J. Freire et al., "Provenance for Computational Tasks: A Survey," Computing in Science & Eng., vol. 10, no. 3, 2008, pp. 11–21.
10. D. Srivastava and Y. Velegrakis, "Intensional Associations between Data and Metadata," Proc. Conf. Special Interest Group on Management of Data (SIGMOD), ACM Press, 2007, pp. 401–412.
11. P. Buneman, J. Cheney, and S. Vansummeren, "On the Expressiveness of Implicit Provenance in Query and Update Languages," ACM Trans. Database Systems, vol. 33, no. 4, 2008;
12. O. Benjelloun et al., "ULDBs: Databases with Uncertainty and Lineage," Proc. Very Large Databases, ACM Press, 2006, pp. 953–964.
13. S. Miles et al., "Provenance-Based Validation of E–Science Experiments," Web Semantics, vol. 5, no. 1, 2007, pp. 801–815.
14. J.J. Carroll et al., "Named Graphs," Web Semantics, vol. 3, no. 4, 2005, pp. 62–71.
15. R. Dividino et al., "Querying for Provenance, Trust, Uncertainty and Other Meta Knowledge in RDF," Web Semantics, vol. 7, no. 3, 2009, pp. 204–219.
16. T.J. Green, G. Karvounarakis, and V. Tannen, "Provenance Semirings," Proc. Principles on Database Systems, ACM Press, 2007, pp. 31–40.
17. P. Buneman, S. Khanna, and W. Tan, "Why and Where: A Characterization of Data Provenance," Proc. Int'l Conf. Database Theory, Springer-Verlag, 2001, pp. 316–330.
18. F. Geerts, A. Kementsietsidis, and D. Milano, "Mondrian: Annotating and Querying Databases through Colors and Blocks," Proc. Int'l Conf. Data Eng., IEEE CS Press, 2006, p. 82.
19. Y. Cui and J. Widom, "Lineage Tracing for General Data Warehouse Transformations," Proc. Very Large Databases, ACM Press, 2001, pp. 41–58.
20. B. Glavic and G. Alonso, "Perm: Processing Provenance and Data on the Same Data Model through Query Rewriting," Proc. Int'l Conf. Data Eng., IEEE CS Press, 2009, pp. 174–185.
21. T.J. Green, "Containment of Conjunctive Queries on Annotated Relations," Proc. Int'l Conf. Database Theory, Springer-Verlag, 2009, pp. 296–309.
22. J. Pérez, M. Arenas, and C. Gutierrez, "Semantics and Complexity of SPARQL," ACM Trans. Database Systems, vol. 34, no. 3, 2009;
23. F. Geerts and A. Poggi, "On Database Query Languages for K-Relations," J. Applied Logic, vol. 8, no. 2, 2010, pp. 173–185.
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