Abstract
BackgroundWith the increasing presence of biomedical data sources on the Internet more and more research effort is put into finding possible ways for integrating and searching such often heterogeneous sources. Ontologies are a key technology in this effort. However, developing ontologies is not an easy task and often the resulting ontologies are not complete. In addition to being problematic for the correct modelling of a domain, such incomplete ontologies, when used in semantically-enabled applications, can lead to valid conclusions being missed.ResultsWe consider the problem of repairing missing is-a relations in ontologies. We formalize the problem as a generalized TBox abduction problem. Based on this abduction framework, we present complexity results for the existence, relevance and necessity decision problems for the generalized TBox abduction problem with and without some specific preference relations for ontologies that can be represented using a member of the nttttttt{mathcal {EL}}ntttttt family of description logics. Further, we present algorithms for finding solutions, a system as well as experiments.ConclusionsSemantically-enabled applications need high quality ontologies and one key aspect is their completeness. We have introduced a framework and system that provides an environment for supporting domain experts to complete the is-a structure of ontologies. We have shown the usefulness of the approach in different experiments. For the two Anatomy ontologies from the Ontology Alignment Evaluation Initiative, we repaired 94 and 58 initial given missing is-a relations, respectively, and detected and repaired additionally, 47 and 10 missing is-a relations. In an experiment with BioTop without given missing is-a relations, we detected and repaired 40 new missing is-a relations.
Highlights
With the increasing presence of biomedical data sources on the Internet more and more research effort is put into finding possible ways for integrating and searching such often heterogeneous sources
We present an algorithm for RepairSingleIsa for ontologies that are represented in EL and where the TBox is normalized as described in [6]
Algorithm - EL++ We present an algorithm for RepairSingleIsa for ontologies that are represented in EL++ (Algorithm 3) and where the TBox is normalized as described in [6]
Summary
With the increasing presence of biomedical data sources on the Internet more and more research effort is put into finding possible ways for integrating and searching such often heterogeneous sources. In addition to being problematic for the correct modelling of a domain, such incomplete ontologies, when used in semantically-enabled applications, can lead to valid conclusions being missed. Ontologies provide a means for modelling the domain of interest and they allow for information reuse, portability and sharing across multiple platforms Efforts such as the Open Biological and Biomedical Ontologies (OBO) Foundry [1], BioPortal [2] and Unified Medical Language System (UMLS) [3] aim at providing repositories for biomedical ontologies and relations between. Developing ontologies is not an easy task and often the resulting ontologies (including their is-a structures) are Lambrix et al Journal of Biomedical Semantics (2015) 6:12 not complete. In addition to being problematic for the correct modelling of a domain, such incomplete ontologies influence the quality of semantically-enabled applications. Incomplete structure in ontologies influences the quality of the search results. Most current ontology alignment systems use structure-based strategies to find mappings between the terms in different ontologies (e.g. overview in [10]) and the modeling defects in the structure of the ontologies have an important influence on the quality of the ontology alignment results
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