Elsevier

Journal of Web Semantics

Volume 4, Issue 3, September 2006, Pages 181-195
Journal of Web Semantics

The foundational model of anatomy in OWL: Experience and perspectives

https://doi.org/10.1016/j.websem.2006.05.007Get rights and content

Abstract

We present the method developed for migrating the Foundational Model of Anatomy (FMA) from its representation with frames in Protégé to its logical representation in OWL and our experience in reasoning with it. Despite the extensive use of metaclasses in Protégé, it proved possible to convert the FMA from Protégé into OWL DL, while capturing most of its original features. The conversion relies on a set of translation and enrichment rules implemented with flexible options. Unsurprisingly, reasoning with the FMA in OWL proved to be a real challenge, due to its sheer size and complexity, and raised significant inference problems in terms of time and memory requirements. However, various smaller versions have been successfully handled by Racer. Some inconsistencies were identified and several classes reclassified. The results obtained so far show the advantage of OWL DL over frames and, more generally, the usefulness of DLs reasoners for building and maintaining the large-scale biomedical ontologies of the future Semantic Web.

Introduction

Life sciences have a long tradition of controlled vocabularies. Extensive terminologies, classifications and ontologies have been developed for many years in various biomedical domains. These resources have the potential to contribute to the Semantic Web for Life Sciences, but need to be adapted for it. A large library of biomedical ontologies has been developed in frames, often with Protégé [12]. As OWL is the W3C recommended standard for ontologies [1], converting frame-based ontologies to OWL becomes an important need. Representing ontologies in OWL provides several advantages. Once converted to OWL, ontologies currently developed with frames become easier to integrate with other ontologies and can be used as resources for the Semantic Web. Interoperability of Web ontologies is important for shared use across different biological and medical domains, as expected for example from the Open Biomedical Ontologies (OBO) library. Also of interest is OWL higher expressiveness, and precise formal semantics. Another important advantage of OWL is the existence of powerful reasoning services, based on its underlying description logics. Several major ontological and terminological resources in biomedicine have been recently converted to OWL DL, including the Medical Subject Headings (MeSH) [8], the Gene Ontology [9] and the National Cancer Institute Thesaurus [10]. The conversion of other ontologies to OWL has also been investigated, e.g., the UMLS® Metathesaurus® [2] and Semantic Network [11]. Our long term goal is to provide a Web service assisting the conversion of frame-based and OBO ontologies to OWL. Meanwhile, the present study investigates the conversion of a large frame-based ontology into OWL and the reasoning services enabled by this conversion.

The frame-based ontology under investigation is the Digital Anatomist Foundational Model of Anatomy (FMA). It was converted from Protégé 2.1 to OWL DL. The FMA is the most comprehensive ontology of human ‘canonical’ anatomy [3]. The version used in this study, dated of July 2004, contains 70,169 concepts and more than 1.5 million relations. The FMA was selected for two major reasons. First, anatomy plays a prominent role in biomedicine and many biomedical ontologies and applications refer to anatomical ontologies. As its authors claim, the FMA is “a reference ontology in biomedical informatics for correlating different views of anatomy, aligning existing and emerging ontologies in bioinformatics …” [3]. Anatomy, together with Gene and Disease reference ontologies, constitute the backbone of the future Semantic Web for Life Sciences. Second, representing the FMA into OWL poses a real challenge from a knowledge representation perspective. It is important to investigate if OWL DL, which is a first order language, has sufficient expressiveness to represent what was originally represented with frames and metaclasses in Protégé. The capacity of OWL editors (e.g., Protégé OWL) and reasoners (e.g., Racer) to deal with the sheer size and complexity of the FMA and the scalability of OWL DL inference techniques to such a large biomedical ontology must be evaluated. Rather than OWL Full used in [5], we selected OWL DL because a main component of our study is to investigate the benefits of a DL representation over frames in terms of reasoning supported by the underlying description logic. OWL DL provides completeness and decidability of the interesting reasoning problems (satisfiability and subsumption) and supports consistency checking and automatic classification. OWL DL reasoners are available (e.g., Racer [16] and Pellet [17]). In contrast, OWL Full is undecidable, offers no computational guarantees and lacks suitable reasoners.

The rest of this paper is organized as follows. The method used to automatically convert the FMA from Protégé 2.1 into OWL DL is first presented (Section 2). Our experience in reasoning with OWL is reported next (Section 3). The choices of conversion, as well as possible perspectives for the FMA and open questions for large-scale ontologies of the future Semantic Web are finally discussed (Section 4).

Section snippets

Conversion to OWL DL

As DLs and frames share the same object paradigm, it might be thought that converting a Protégé frame-based1 ontology into OWL is straightforward and could be achieved by a simple export function mapping Protégé primitives to OWL

Reasoning with OWL

Reasoning with OWL proved to be a real challenge, due to the sheer size and complexity of the FMA. Processing the full-fledged FMA in OWL DL raised significant inference problems in terms of time and memory requirements. For this reason, an incremental approach to investigating reasoning services was adopted.

Discussion and perspectives

This study is a first step towards the representation of the FMA in OWL. Several issues remain open and different perspectives shall be considered in the future.

Acknowledgments

This research was supported in part by the Intramural Research Program of the National Institutes of Health (NIH), National Library of Medicine (NLM), while Pr. Christine Golbreich and Dr. Songmao Zhang were visiting scholars at the Lister Hill National Center for Biomedical Communications, NLM, NIH. Our thanks to Volker Haarslev and Ralf Möller for their valuable advice and help on OWL and Racer, to Cornelius Rosse, José Mejino and Todd Detwiler for the FMA, and to other helpful advice.

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