Cross-querying LOD data sets using complex alignments: an experiment using AgronomicTaxon, Agrovoc, DBpedia and TAXREF-LD

Abstract

An increasing amount of data sets have being published on the Linked Open Data (LOD), covering different aspects of overlapping domains. This is typically the case of agronomy and related fields, where several LOD data sets describing different points of view on scientific classifications have been published. This opens emerging opportunities in the field, providing to practitioners new knowledge sources. However, without help, querying the different datasets is a time-consuming task for LOD users as they need to know the ontologies describing the data of each of them. Rewriting queries can be automated with the help of ontology alignments. This paper presents a query rewriting approach that relies on complex alignments. This kind of alignment, opposite to simple ones, better deals with ontology modelling heterogeneities. We evaluate our approach on a scenario of query rewriting on agronomic information needs across four different datasets: AgronomicTaxon, AGROVOC, DBpedia, and TAXREF-LD.