Fast and Simple Data Scaling for OBDA Benchmarks

Davide Lanti, Guohui Xiao, and Diego Calvanese

Proc. of the Workshop on Benchmarking Linked Data (BLINK 2016), co-located with ISWC 2016. Volume 1700 of CEUR Workshop Proceedings, http://ceur-ws.org/. 2016.

In this paper we describe VIG, a data scaler for OBDA benchmarks. Data scaling is a relatively recent approach, proposed in the database community, that allows for quickly scaling an input data instance to n times its size, while preserving certain application-specific characteristics. The advantages of the scaling approach are that the same generator is general, in the sense that it can be re-used on different database schemas, and that users are not required to manually input the data characteristics. In the VIG system, we lift the scaling approach from the pure database level to the OBDA level, where the domain information of ontologies and mappings has to be taken into account as well. VIG is efficient and notably each tuple is generated in constant time. VIG has been successfully used in the NPD benchmark, but it provides a general approach that can be re-used to scale any data instance in any OBDA setting.


@inproceedings{BLINK-2016,
   title = "Fast and Simple Data Scaling for OBDA Benchmarks",
   year = "2016",
   author = "Davide Lanti and Guohui Xiao and Diego Calvanese",
   booktitle = "Proc. of the Workshop on Benchmarking Linked Data
(BLINK 2016), co-located with ISWC 2016",
   volume = "1700",
   series = "CEUR Workshop Proceedings, http://ceur-ws.org/",
}
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