Abstract
The acceptance of Triple Stores and the adoption of Triple Store as an alternative to relational database technology has not met the expectations demanded by the Big Data community. In addition, most triple store implementations are unable to store and extract tabular data as fast as many of the alternate Big Data solutions that are currently available. What is missing is a Triple Store implementation that can contain both graphical and tabular data. The SPARQL property path extension which was introduced into the SPARQL 1.1 specification provides the capability to retrieve tabular data through the traversal of unbounded RDF list structures. However, there are no currently available Triple Store implementations that fully support the SPARQL 1.1 property path extension and therefore are unable to traverse large RDF lists using the SPARQL language. This paper will describe a triple store implementation project targeting the property path extension utilizing features found in most columnar storage databases.
Original language | English |
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Title of host publication | Data Mining and Analytics 2014 |
Subtitle of host publication | Proceedings of the 12th Australasian Data Mining Conference (AusDM 2014) |
Editors | Xue Li, Lin Liu, Kok-Leong Ong, Yanchang Zhao |
Publisher | Australian Computer Society |
Pages | 59-67 |
Number of pages | 9 |
Volume | 158 |
ISBN (Print) | 9781921770173 |
Publication status | Published - 2014 |
Event | Twelfth Australasian Data Mining Conference - Brisbane, Brisbane, Australia Duration: 27 Nov 2014 → 28 Nov 2014 http://ausdm14.ausdm.org/ |
Publication series
Name | Conferences in Research and Practice in Information Technology Series |
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Volume | 158 |
ISSN (Print) | 1445-1336 |
Conference
Conference | Twelfth Australasian Data Mining Conference |
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Abbreviated title | AusDM14 |
Country/Territory | Australia |
City | Brisbane |
Period | 27/11/14 → 28/11/14 |
Internet address |