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In this paper we compare these formats and evaluate them with respect to their underlying models, information content and possibilities for easy creation of tools. The evaluation shows that the main structure of the formats is similar. However, SBML is tuned towards simulation models of molecular pathways while PSI MI is more suitable for representing details about particular interactions and experiments. BioPAX is the most general and expressive of the formats. These differences are apparent in allowed information and the structure for representation of interactions. We discuss the impact of these differences both with respect to information content in existing databases and computational properties for import and analysis of data.

Abstract. Developing ontologies is not an easy task and often the resulting ontologies are not consistent or complete. Such ontologies, although often useful, also lead to problems when used in semantically-enabled applications. Wrong conclusions may be derived or valid conclusions may be missed. To deal with this problem we may want to repair the ontologies. Up to date most work has been performed on finding and repairing the semantic defects such as unsatisfiable concepts and inconsistent ontologies. In this paper we tackle the problem of repairing modeling defects and in particular, the repairing of structural relations (is-a hierarchy) in the ontologies. We study the case where missing is-a relations are given. We define the notion of a structural repair and develop algorithms to compute repairing actions that would allow deriving the missing is-a relations in the repaired ontology. Further, we define preferences between repairs. We also look at how we can use external knowledge to recommend repairing actions to a domain expert. Further, we discuss an implemented prototype and its use as well as an experiment using the ontologies of the Anatomy track of the Ontology Alignment Evaluation Initiative. This is a preprint of the paper published by

Abstract. User validation is one of the challenges facing the ontology alignment community, as there are limits to the quality of automated alignment algorithms. In this paper we present a broad study on user validation of ontology alignments that encompasses three distinct but interrelated aspects: the profile of the user, the services of the alignment system, and its user interface. We discuss key issues pertaining to the alignment validation process under each of these aspects, and provide an overview of how current systems address them. Finally, we use experiments from the Interactive Matching track of the Ontology Alignment Evaluation Initiative (OAEI) 2015 to assess the impact of errors in alignment validation, and how systems cope with them as function of their services.