Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2017 Dec 4;8(1):56.
doi: 10.1186/s13326-017-0166-5.

Experiences from the anatomy track in the ontology alignment evaluation initiative

Zlatan Dragisic  1 , Valentina Ivanova  1 , Huanyu Li  1 , Patrick Lambrix  2
Affiliations
Review

Experiences from the anatomy track in the ontology alignment evaluation initiative

Zlatan Dragisic et al. J Biomed Semantics. .

Abstract

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 as well as the challenges it poses for ontology alignment systems. 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.

Keywords: Biomedical ontologies; Ontology alignment; Ontology alignment evaluation initiative.

PubMed Disclaimer

Conflict of interest statement

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
Ontology alignment framework (e.g., [95])
Fig. 2
Fig. 2
Evolution of precision of the participating systems 2007–2016
Fig. 3
Fig. 3
Evolution of recall of the participating systems 2007–2016
Fig. 4
Fig. 4
Evolution of F-measure of the participating systems 2007–2016
Fig. 5
Fig. 5
Evolution of recall+ of the participating systems 2007–2016
Fig. 6
Fig. 6
Number of the participating systems that produce a coherent alignment (red bar) w.r.t. to the total number of participants (blue bar)
Fig. 7
Fig. 7
Evolution of run-times (medians) in the period 2011–2016
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

References

    1. Achichi M, Cheatham M, Dragisic Z, Euzenat J, Faria D, Ferrara A, Flouris G, Fundulaki I, Harrow I, Ivanova V, Jiménez-Ruiz E, Kuss E, Lambrix P, Leopold H, Li H, Meilicke C, Montanelli S, Pesquita C, Saveta T, Shvaiko P, Splendiani A, Stuckenschmidt H, Todorov K, Trojahn C, Zamazal O. Results of the ontology alignment evaluation initiative 2016 In: Shvaiko P, Euzenat J, Jiménez-Ruiz E, Cheatham M, Hassanzadeh O, Ichise R, editors. Proceedings of the 11th International Workshop on Ontology Matching, volume 1766 of CEUR Workshop Proceedings: 2016. p. 73–129.
    1. Aguirre JL, Eckert K, Euzenat J, Ferrara A, van Hage WR, Hollink L, Meilicke C, Nikolov A, Ritze D, Scharffe F, Shvaiko P, Sváb-Zamazal O, Trojahn C, Jiménez-Ruiz E, Cuenca Grau B, Zapilko B. Results of the ontology alignment evaluation initiative 2012. In: Shvaiko P, Euzenat J, Kementsietsidis A, Mao M, Noy N, Stuckenschmidt H, editors. Proceedings of the 7th International Workshop on Ontology Matching, volume 946 of CEUR Workshop Proceedings: 2012. p. 73–115.
    1. Aitken S, Korf R, Webber B, Bard J. Cobra: a bio-ontology editor. Bioinformatics. 2005;21(6):825–6. doi: 10.1093/bioinformatics/bti097. - DOI - PubMed
    1. Ba M, Diallo G. Servomap and servomap-lt results for oaei 2012. In: Shvaiko P, Euzenat J, Kementsietsidis A, Mao M, Noy N, Stuckenschmidt H, editors. Proceedings of the 7th International Workshop on Ontology Matching, volume 946 of CEUR Workshop Proceedings: 2012. p. 197–204.
    1. Beisswanger E, Hahn U. Towards valid and reusable reference alignments - ten basic quality checks for ontology alignments and their application to three different reference data sets. J Biomed Semant. 2012;3(Suppl 1):S4:1–S4:14. doi: 10.1186/2041-1480-3-S1-S4. - DOI - PMC - PubMed