  In this paper we describe VIG, a data scaler for benchmarks in the context of
ontology-based data access (OBDA). Data scaling is a relatively recent
approach, proposed in the database community, that allows for quickly scaling
up an input data instance to s times its size, while preserving certain
application-specific characteristics. The advantage of the approach is that the
user is not required to manually input the characteristics of the data to be
produced, making it particularly suitable for OBDA benchmarks, where the
complexity of database schemas might pose a challenge for manual input (e.g.,
the NPD benchmark contains 70 tables with some containing more than 60
columns). As opposed to a traditional data scaler, VIG includes domain
information provided by the OBDA mappings and the ontology in order to produce
data. VIG is currently used in the NPD benchmark, but it is not NPD-specific
and can be seeded with any data instance. The distinguishing features of VIG
are (1) its simple and clear generation strategy; (2) its efficiency, as each
value is generated in constant time, without accesses to the disk or to RAM to
retrieve previously generated values; (3) and its generality, as the data is
exported in CSV files that can be easily imported by any RDBMS system. VIG is a
java implementation licensed under Apache 2.0, and its source code is available
on GitHub (https://github.com/ontop/vig) in the form of a Maven project. The
code is being maintained since two years by the -ontop- team at the Free
University of Bozen-Bolzano.
