With the growth of ontologies used in diverse application areas, the need for module extraction and modularisation techniques has risen. The notion of the modular structure of an ontology, which comprises a suitable set of base modules together with their logical dependencies, has the potential to help users and developers in comprehending, sharing, and maintaining an ontology. We have developed a new modular structure, called atomic decomposition (AD), which is based on modules that provide strong logical properties, such as locality-based modules. In this article, we present the theoretical foundations of AD, review its logical and computational properties, discuss its suitability as a modular structure, and report on an experimental evaluation of AD. In addition, we discuss the concept of a modular structure in ontology engineering and provide a survey of existing decomposition approaches.

We present the first large scale investigation into the modular structure of a substantial collection of state-of-the-art biomedical ontologies, namely those maintained in the NCBO BioPortal repository.1 Using the notion of Atomic Decomposition, we partition BioPortal ontologies into logically coherent subsets (atoms), which are related to each other by a notion of dependency. We analyze various aspects of the resulting structures, and discuss their implications on applications of ontologies. In particular, we describe and investigate the usage of these ontology decompositions to extract modules, for instance, to facilitate matchmaking of semantic Web services in SSWAP (Simple Semantic Web Architecture and Protocol). Descriptions of those services use terms from BioPortal so service discovery requires reasoning with respect to relevant fragments of ontologies (i.e., modules). We present a novel algorithm for extracting modules from decomposed BioPortal ontologies which is able to quickly identify atoms that need to be included in a module to ensure logically complete reasoning. Compared to existing module extraction algorithms, it has a number of benefits, including improved performance and the possibility to avoid loading the entire ontology into memory. The algorithm is also evaluated on BioPortal ontologies and the results are presented and discussed.

Abstract. For ontology reuse and integration, a number of approaches have been devised that aim at identifying modules, i.e., suitably small sets of "relevant" axioms from ontologies. Here we consider three logically sound notions of modules: MEX modules, only applicable to inexpressive ontologies; modules based on semantic locality, a sound approximation of the first; and modules based on syntactic locality, a sound approximation of the second (and thus the first), widely used since these modules can be extracted from SROIQ ontologies in time polynomial in the size of the ontology. In this paper we investigate the quality of both approximations over a large corpus of ontologies. In particular, we show with statistical significance that, in most cases, there is no difference between the two module notions based on locality; where they differ, the additional axioms are in general unproblematic since either they can be easily ruled out or their number is relatively small. Finally, we show that the same can be said about the relation between MEX and locality-based modules.

The Code/Theory workshop explored the process of translating between theory and code, from the perspective of those who do this work on a day to day basis. This report contains individual contributions from participants reflecting on their own experiences, along with summaries of their lightning talks and outputs from the discussion sessions. We conclude that translating between theory and code successfully requires a diversity of roles, all of which are central to the process of research.

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