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Scalable long-term preservation of relational data through SPARQL queries
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science. (UDBL)
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Science. (UDBL)
2016 (English)In: Semantic Web, ISSN 1570-0844, E-ISSN 2210-4968, Vol. 7, no 2, 117-137 p.Article in journal (Refereed) Published
Place, publisher, year, edition, pages
2016. Vol. 7, no 2, 117-137 p.
National Category
Computer Science
Identifiers
URN: urn:nbn:se:uu:diva-199570DOI: 10.3233/SW-150173ISI: 000373208100002OAI: oai:DiVA.org:uu-199570DiVA: diva2:620103
Projects
eSSENCE
Available from: 2016-02-12 Created: 2013-05-07 Last updated: 2017-12-06Bibliographically approved
In thesis
1. Scalable Preservation, Reconstruction, and Querying of Databases in terms of Semantic Web Representations
Open this publication in new window or tab >>Scalable Preservation, Reconstruction, and Querying of Databases in terms of Semantic Web Representations
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

This Thesis addresses how Semantic Web representations, in particular RDF, can enable flexible and scalable preservation, recreation, and querying of databases.

An approach has been developed for selective scalable long-term archival of relational databases (RDBs) as RDF, implemented in the SAQ (Semantic Archive and Query) system. The archival of user-specified parts of an RDB is specified using an extension of SPARQL, A-SPARQL. SAQ automatically generates an RDF view of the RDB, the RD-view. The result of an archival query is RDF triples stored in: i) a data archive file containing the preserved RDB content, and ii) a schema archive file containing sufficient meta-data to reconstruct the archived database. To achieve scalable data preservation and recreation, SAQ uses special query rewriting optimizations for the archival queries. It was experimentally shown that they improve query execution and archival time compared with naïve processing. The performance of SAQ was compared with that of other systems supporting SPARQL queries to views of existing RDBs.

When an archived RDB is to be recreated, the reloader module of SAQ first reads the schema archive file and executes a schema reconstruction algorithm to automatically construct the RDB schema. The thus created RDB is populated by reading the data archive and converting the read data into relational attribute values. For scalable recreation of RDF archived data we have developed the Triple Bulk Load (TBL) approach where the relational data is reconstructed by using the bulk load facility of the RDBMS. Our experiments show that the TBL approach is substantially faster than the naïve Insert Attribute Value (IAV) approach, despite the added sorting and post-processing.

To view and query semi-structured Topic Maps data as RDF the prototype system TM-Viewer was implemented. A declarative RDF view of Topic Maps, the TM-view, is automatically generated by the TM-viewer using a developed conceptual schema for the Topic Maps data model. To achieve efficient query processing of SPARQL queries to the TM-view query rewrite transformations were developed and evaluated. It was shown that they significantly improve the query execution time.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2013. 59 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1052
Keyword
RDF, RDFS, RDF view, SPARQL, SPARQL query processing, rewrite optimization, Topic Maps, querying of RDF views, archive relational databases, reconstruct archived databases
National Category
Computer Science
Research subject
Computer Science with specialization in Database Technology
Identifiers
urn:nbn:se:uu:diva-199573 (URN)978-91-554-8690-7 (ISBN)
Public defence
2013-06-14, Room 2446, Polacksbacken, Lägerhyddsvägen 2, Uppsala, 13:00 (English)
Opponent
Supervisors
Projects
eSSENCE
Funder
eSSENCE - An eScience Collaboration
Available from: 2013-05-24 Created: 2013-05-07 Last updated: 2014-07-21Bibliographically approved

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Stefanova, SilviaRisch, Tore

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