Data Accuracy as Knowledge in Ontology Based Data Access (preliminary report)
Marco Console · IRIS Research product catalog (Sapienza University of Rome) · 2016
In the context of Ontology Based Data Access (OBDA), consistency of data ensures that the data sources are coherent with the rules of the domain of interest represented by the ontology. However, even when consistency holds, the data underlying an OBDA system can still be in a state that users perceive of poor quality, according to some intuitive requirements. In many of these cases, the mechanism currently used to specify an OBDA system seems to lack of the ability to express such requirements. In this work, we argue that those requirements are often not about the world that the ontology represents, but about the knowledge that the system possesses on the world. Thus, with the aim of formalizing data quality specifications in the OBDA context, we propose the usage of a language of modal constraints, and show how they can be used in practice to capture cases of poor data quality. For this novel class of assertions, and for OBDA systems where the ontology is expressed in DL-Lite, we present algorithms and complexity results for the problem of checking the accuracy of the knowledge that the system posses, i.e., whether the system respects the modal constraints in the specification.