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Experiences from the Anatomy track in the Ontology Alignment Evaluation Initiative
Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-9084-0470
2017 (English)In: Journal of Biomedical Semantics, ISSN 2041-1480, E-ISSN 2041-1480, Vol. 8, article id 56Article, review/survey (Refereed) Published
Abstract [en]

Background: One of the longest running tracks in the Ontology Alignment Evaluation Initiative is the Anatomy track which focuses on aligning two anatomy ontologies. The Anatomy track was started in 2005. In 2005 and 2006 the task in this track was to align the Foundational Model of Anatomy and the OpenGalen Anatomy Model. Since 2007 the ontologies used in the track are the Adult Mouse Anatomy and a part of the NCI Thesaurus. Since 2015 the data in the Anatomy track is also used in the Interactive track of the Ontology Alignment Evaluation Initiative.

Results: In this paper we focus on the Anatomy track in the years 2007-2016 and the Anatomy part of the Interactive track in 2015-2016. We describe the data set and the changes it went through during the years. Further, we give an overview of all systems that participated in the track and the techniques they have used. We discuss the performance results of the systems and summarize the general trends.

Conclusions: About 50 systems have participated in the Anatomy track. Many different techniques were used. The most popular matching techniques are string-based strategies and structure-based techniques. Many systems also use auxiliary information. The quality of the alignment has increased for the best performing systems since the beginning of the track and more and more systems check the coherence of the proposed alignment and implement a repair strategy.Further, interacting with an oracle is beneficial.

Place, publisher, year, edition, pages
BioMed Central, 2017. Vol. 8, article id 56
Keywords [en]
ontologies, ontology matching, OAEI, anatomy
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:liu:diva-139775DOI: 10.1186/s13326-017-0166-5ISI: 000416915300001PubMedID: 29202830OAI: oai:DiVA.org:liu-139775DiVA, id: diva2:1134718
Funder
Swedish e‐Science Research CenterCUGS (National Graduate School in Computer Science)EU, FP7, Seventh Framework Programme, FP7-IP-608142
Note

Funding agencies: Swedish e-Science Research Centre (SeRC); Swedish national graduate school in computer science (CUGS); EU project VALCRI [FP7-IP-608142]

Available from: 2017-08-21 Created: 2017-08-21 Last updated: 2018-01-13
In thesis
1. Completion of Ontologies and Ontology Networks
Open this publication in new window or tab >>Completion of Ontologies and Ontology Networks
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The World Wide Web contains large amounts of data, and in most cases this data has no explicit structure. The lack of structure makes it difficult for automated agents to understand and use such data. A step towards a more structured World Wide Web is the Semantic Web, which aims at introducing semantics to data on the World Wide Web. One of the key technologies in this endeavour are ontologies, which provide a means for modeling a domain of interest and are used for search and integration of data.

In recent years many ontologies have been developed. To be able to use multiple ontologies it is necessary to align them, i.e., find inter-ontology relationships. However, developing and aligning ontologies is not an easy task and it is often the case that ontologies and their alignments are incorrect and incomplete. This can be a problem for semantically-enabled applications. Incorrect and incomplete ontologies and alignments directly influence the quality of the results of such applications, as wrong results can be returned and correct results can be missed. This thesis focuses on the problem of completing ontologies and ontology networks.

The contributions of the thesis are threefold. First, we address the issue of completing the is-a structure and alignment in ontologies and ontology networks. We have formalized the problem of completing the is-a structure in ontologies as an abductive reasoning problem and developed algorithms as well as systems for dealing with the problem. With respect to the completion of alignments, we have studied system performance in the Ontology Alignment Evaluation Initiative, a yearly evaluation campaign for ontology alignment systems. We have also addressed the scalability of ontology matching, which is one of the current challenges, by developing an approach for reducing the search space when generating the alignment.Second, high quality completion requires user involvement. As users' time and effort are a limited resource we address the issue of limiting and facilitating user interaction in the completion process. We have conducted a broad study of state-of-the-art ontology alignment systems and identified different issues related to the process. We have also conducted experiments to assess the impact of user errors in the completion process.

While the completion of ontologies and ontology networks can be done at any point in the life-cycle of ontologies and ontology networks, some of the issues can be addressed already in the development phase. The third contribution of the thesis addresses this by introducing ontology completion and ontology alignment into an existing ontology development methodology.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2017. p. 65
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1852
Keywords
knowledge representation, ontology, ontology engineering, ontology debugging, ontology completion, ontology matching, description logics
National Category
Computer Sciences
Identifiers
urn:nbn:se:liu:diva-139487 (URN)10.3384/diss.diva-139487 (DOI)978-91-7685-522-5 (ISBN)
Public defence
2017-09-26, Ada Lovelace, Linköping University, Linköping, 13:15 (English)
Opponent
Supervisors
Funder
Swedish e‐Science Research CenterSwedish Research Council, 2010-4759CUGS (National Graduate School in Computer Science)EU, FP7, Seventh Framework Programme, FP7-IP-608142
Available from: 2017-08-22 Created: 2017-08-21 Last updated: 2018-01-13Bibliographically approved
2. Fostering User Involvement in Ontology Alignment and Alignment Evaluation
Open this publication in new window or tab >>Fostering User Involvement in Ontology Alignment and Alignment Evaluation
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The abundance of data at our disposal empowers data-driven applications and decision making. The knowledge captured in the data, however, has not been utilized to full potential, as it is only accessible to human interpretation and data are distributed in heterogeneous repositories.

Ontologies are a key technology unlocking the knowledge in the data by providing means to model the world around us and infer knowledge implicitly captured in the data. As data are hosted by independent organizations we often need to use several ontologies and discover the relationships between them in order to support data and knowledge transfer. Broadly speaking, while ontologies provide formal representations and thus the basis, ontology alignment supplies integration techniques and thus the means to turn the data kept in distributed, heterogeneous repositories into valuable knowledge.

While many automatic approaches for creating alignments have already been developed, user input is still required for obtaining the highest-quality alignments. This thesis focuses on supporting users during the cognitively intensive alignment process and makes several contributions.

We have identified front- and back-end system features that foster user involvement during the alignment process and have investigated their support in existing systems by user interface evaluations and literature studies. We have further narrowed down our investigation to features in connection to the, arguably, most cognitively demanding task from the users’ perspective—manual validation—and have also considered the level of user expertise by assessing the impact of user errors on alignments’ quality. As developing and aligning ontologies is an error-prone task, we have focused on the benefits of the integration of ontology alignment and debugging.

We have enabled interactive comparative exploration and evaluation of multiple alignments at different levels of detail by developing a dedicated visual environment—Alignment Cubes—which allows for alignments’ evaluation even in the absence of reference alignments.

Inspired by the latest technological advances we have investigated and identified three promising directions for the application of large, high-resolution displays in the field: improving the navigation in the ontologies and their alignments, supporting reasoning and collaboration between users.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2017. p. 73
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1891
Keywords
Knowledge representation, ontology, ontology engineering, ontology debugging, ontology matching, ontology matching evaluation, user interfaces, human-computer interaction, large and high-resolution displays
National Category
Computer Sciences
Identifiers
urn:nbn:se:liu:diva-143034 (URN)10.3384/diss.diva-143034 (DOI)9789176854037 (ISBN)
Public defence
2018-01-26, Planck, Hus F, Campus Valla, Linköping, 13:15 (English)
Opponent
Supervisors
Funder
Swedish Research Council, 2010-4759CUGS (National Graduate School in Computer Science)Swedish e‐Science Research CenterEU, FP7, Seventh Framework Programme, FP7-IP-608142
Available from: 2018-01-04 Created: 2017-11-16 Last updated: 2018-01-13Bibliographically approved

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