Integrating Online Services to Enhance Ontology Alignment

The main objective of this project is to extend the state of the art in ontology alignment with advanced techniques to exploit the services provided by the European Bioinformatics Institute (EBI) and BioPortal.

Project Background and Scientific Basis

Ontologies are extensively used in biology and medicine. Ontologies such as SNOMED CT, the National Cancer Institute Thesaurus (NCI), and the Foundational Model of Anatomy (FMA) are gradually superseding existing medical classifications and are becoming core platforms for accessing, gathering and sharing bio-medical knowledge and data. These reference biomedical ontologies, however, are being developed independently by different groups of experts and, as a result, they use different entity naming schemes and modelling conventions. As a consequence, to integrate and migrate data among applications, it is crucial to first establish correspondences (or
mappings) between the vocabularies of their respective ontologies.

In the last ten years, the Semantic Web and biomedical research communities have extensively investigated the problem of automatically computing mappings between independently developed ontologies, usually referred to as the ontology matching problem (see [1] for a comprehensive and up-to-date survey). The growing number of available techniques and increasingly mature tools, together with substantial human curation effort and complex auditing protocols, has made the generation of mappings between real-world ontologies possible.

Despite the impressive state of the art, modern (biomedical) ontologies still pose serious challenges to existing ontology matching tools. The use of background knowledge is key to provide high quality alignment sets. Online repositories like Bioportal [3] and the EBI infrastructure [4] can be exploited to enhance the computed alignments. In this MSc we aim at studying different ways of exploiting the EBI and BioPortal services within the ontology alignment system LogMap [5].

Supervision

The thesis will be jointly supervised by Dr. Ernesto Jimenez-Ruiz and Prof. Martin Giese (Logic and Intelligent Data (LogID) group), and Simon Jupp (European Informatics Institute, UK).

The LogID group is also actively contributing to the Ontology Matching community and (co)organises the annual Ontology Alignment Evaluation Initiative (OAEI). The OAEI [2] is an annual campaign for the systematic evaluation of Ontology Alignment systems. Furthermore, the LogID groups has recently started a collaboration with the European Bioinformatics Institute (EBI, Cambridge, UK) to enhance the EBI’s ontology mapping service.

References

[1] Pavel Shvaiko, Jérôme Euzenat: Ontology Matching: State of the Art and Future Challenges. IEEE Trans. Knowl. Data Eng. 25(1): 158-176 (2013)

[2] Manel Achichi, et al.: Results of the Ontology Alignment Evaluation Initiative 2016. OM@ISWC 2016: 73-129

[3] EBI’s Ontology Lookup Service and related tools. http://www.ebi.ac.uk/ols/index

[4] N. F. Noy et al. BioPortal: ontologies and integrated data resources at the click of a mouse. Nucleic Acids Res, 2009

[5] Ernesto Jiménez-Ruiz, Bernardo Cuenca Grau, Yujiao Zhou, Ian Horrocks: Large-scale Interactive Ontology Matching: Algorithms and Implementation. ECAI 2012: 444-449

 

Publisert 11. aug. 2017 11:54 - Sist endret 28. sep. 2017 21:56

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