Werner Ceusters

Relations in biomedical ontologies

To enhance the treatment of relations in biomedical ontologies we advance a methodology for providing consistent and unambiguous formal definitions of the relational expressions used in such ontologies in a way designed to assist developers and users in avoiding errors in coding and annotation. The resulting Relation Ontology can promote interoperability of ontologies and support new types of automated reasoning about the spatial and temporal dimensions of biological and medical phenomena.

Ontological realism: A methodology for coordinated evolution of scientific ontologies

Since 2002 we have been testing and refining a methodology for ontology development that is now being used by multiple groups of researchers in different life science domains. Gary Merrill, in a recent paper in this journal, describes some of the reasons why this methodology has been found attractive by researchers in the biological and biomedical sciences. At the same time he assails the methodology on philosophical grounds, focusing specifically on our recommendation that ontologies developed for scientific purposes should be constructed in such a way that their terms are seen as referring to what we call universals or types in reality. As we show, Merrills critique is of little relevance to the success of our realist project, since it not only reveals no actual errors in our work but also criticizes views on universals that we do not in fact hold. However, it nonetheless provides us with a valuable opportunity to clarify the realist methodology, and to show how some of its principles are being applied, especially within the framework of the OBO (Open Biomedical Ontologies) Foundry initiative.

Classifying orofacial pains: a new proposal of taxonomy based on ontology.

We propose a new taxonomy model based on ontological principles for disorders that manifest themselves through the symptom of persistent orofacial pain and are commonly seen in clinical practice and difficult to manage. Consensus meeting of eight experts from various geographic areas representing different perspectives (orofacial pain, headache, oral medicine and ontology) as an initial step towards improving the taxonomy. Ontological principles were introduced, reviewed and applied during the consensus building process. Diagnostic criteria for persistent dento-alveolar pain disorder (PDAP) were formulated as an example to be used to model the taxonomical structure of all orofacial pain conditions. These criteria have the advantage of being (i) anatomically defined, (ii) in accordance with other classification systems for the provision of clinical care, (iii) descriptive and succinct, (iv) easy to adapt for applications in varying settings, (v) scalable and (vi) transferable for the description of pain disorders in other orofacial regions of interest. Limitations are that the criteria introduce new terminology, do not have widespread acceptance and have yet to be tested. These results were presented to the greater conference membership and were unanimously accepted. Consensus for the diagnostic criteria of PDAP was established within this working group. This is an initial first step towards developing a coherent taxonomy for orofacial pain disorders, which is needed to improve clinical research and care.

The Evaluation of Ontologies

Recent years have seen rapid progress in the development of ontologies as semantic models intended to capture and represent aspects of the real world. There is, however, great variation in the quality of ontologies. If ontologies are to become progressively better in the future, more rigorously developed, and more appropriately compared, then a systematic discipline of ontology evaluation must be created to ensure quality of content and methodology. Systematic methods for ontology evaluation will take into account representation of individual ontologies, performance (in terms of accuracy, domain coverage and the efficiency and quality of automated reasoning using the ontologies) on tasks for which the ontology is designed and used, degree of alignment with other ontologies and their compatibility with automated reasoning. A sound and systematic approach to ontology evaluation is required to transform ontology engineering into a true scientific and engineering discipline. This chapter discusses issues and problems in ontology evaluation, describes some current strategies, and suggests some approaches that might be useful in the future.

Applying evolutionary terminology auditing to the Gene Ontology

Evolutionary Terminology Auditing (ETA) is a novel way to assess the quality of terminologies using reality as benchmark. The key idea is that terms added to each new version of a terminology reflect unjustified absences and terms that are deleted unjustified presences in previous versions of the terminology. The method requires that terminology authors not only keep track of changes in successive versions, but also motivate the changes introduced. In this paper, we report on how our method has been applied to the Gene Ontology (GO), a collection of three structured, controlled vocabularies for use in annotating genes, gene products and sequences. We demonstrate that even where the basic requirements for its application are only partially satisfied, the approach can still yield results which are useful for quantifying and forecasting the evolution of a terminologys quality over time.

LinkSuiteTM: Formally Robust Ontology-Based Data and Information Integration

The integration of information resources in the life sciences is one of the most challenging problems facing bioinformatics today. We describe how Language and Computing nv, originally a developer of ontology-based natural language understanding systems for the healthcare domain, is developing a framework for the integration of structured data with unstructured information contained in natural language texts. L&C’s LinkSuiteTM combines the flexibility of a modular software architecture with an ontology based on rigorous philosophical and logical principles that is designed to comprehend the basic formal relationships that structure both reality and the ways humans perceive and communicate about reality.

Ontology-Assisted Database Integration to Support Natural Language Processing and Biomedical Data-mining

Summary Successful biomedical data mining and information extraction require a complete picture of biological phenomena such as genes, biological processes, and diseases; as these exist on different levels of granularity. To realize this goal, several freely available heterogeneous databases as well as proprietary structured datasets have to be integrated into a single global customizable scheme. We will present a tool to integrate different biological data sources by mapping them to a proprietary biomedical ontology that has been developed for the purposes of making computers understand medical natural language.

Syntactic-semantic tagging as a mediator between linguistic representations and formal models: an exercise in linking SNOMED to GALEN

Natural language understanding applications are good candidates to solve the knowledge acquisition bottleneck when designing large scale concept systems. However, a necessary condition is that systems are built that transform sentences into a meaning representation that is independent of the subtleties of linguistic structure that nevertheless underly the way language works. The Cassandra II syntactic-semantic tagging system fulfills this goal partially. Within the GALEN-IN-USE project, it is used to transform linguistic representations of surgical procedure expressions into conceptual representations. In this paper, the proctology chapter of the SNOMED V3.1 procedure axis was used as a testbed to evaluate the usefulness of this approach. A quantitative and qualitative analysis of the data obtained is presented, showing that the Cassandra system can indeed complement the manual modelling efforts being conducted in the GALEN-IN-USE project. The different requirements related to linguistic modelling versus conceptual modelling can partly be accounted for by using an interface ontology, of which the fine tuning will however remain an important effort.

A novel view on information content of concepts in a large ontology and a view on the structure and the quality of the ontology.

Semantic distance and semantic similarity are two important information retrieval measures used in word sense disambiguation as well as for the assessment of how relevant concepts are with respect to the documents in which they are found. A variety of calculation methods have been proposed in the literature, whereby methods taking into account the information content of an individual concept outperform those that do not. In this paper, we present a novel recursive approach to calculate a concepts information content based on the information content of the concepts to which it relates. The method is applicable to extremely large ontologies containing several million concepts and relationships amongst them. It is shown that a concepts information content as calculated by this method provides additional information with respect to an ontology that cannot be approximated by hierarchical edge-counting or human insight. In addition, it is suggested that the method can be used for quality control within large ontologies and that it can give you an impression on the structure and the quality of the ontology.

The emotion ontology: enabling interdisciplinary research in the affective sciences

Affective science conducts interdisciplinary research into the emotions and other affective phenomena. Currently, such research is hampered by the lack of common definitions of terms used to describe, cate-gorise and report both individual emotional experiences and the results of scientific investigations of such experiences. High quality ontologies provide formal definitions for types of entities in reality and for the relationships between such entities, definitions which can be used to disambiguate and unify data across different disciplines. Heretofore, there has been little effort directed towards such formal representation for affective phenomena, in part because of widespread debates within the affective science community on matters of definition and categorization. To address this requirement, we are developing an Emotion Ontology (EMO). The full ontology and generated OWLDoc documentation are available for download from https://emotion-ontology.googlecode.com/svn/trunk/ under the Creative Commons - Attribution license (CC BY 3.0).