Alignment of surface water ontologies: A comparison of manual and automated approaches

Abstract

More data are being collected about the world around us than ever before, but effectively using this information requires different data stores to be integrated in such a way that they can be seamlessly queried and analyzed. Automated alignment algorithms exist to facilitate this data integration challenge. In this paper we examine the utility of two current leading automated alignment systems to integrate four ontologies from the surface water domain. We show that the performance of such systems in this domain lags behind their results on popular benchmarks, and therefore incorporate the alignment task described here into the set of benchmarks used by the alignment community. In addition, we show that, with minor modifications, existing alignment algorithms can be used effectively within a semi-automated alignment system for the surface water domain.