A Complex Alignment Benchmark: GeoLink Dataset
Ontology alignment has been studied for over a decade, and over that time many alignment systems and methods have been developed by researchers in order to find simple 1-to-1 equivalence matches between two ontologies. However, very few alignment systems focus on finding complex correspondences. One reason for this limitation may be that there are no widely accepted alignment benchmarks that contain such complex relationships. In this paper, we propose a real-world dataset from the GeoLink project as a potential complex alignment benchmark. The dataset consists of two ontologies, the GeoLink Base Ontology (GBO) and the GeoLink Modular Ontology (GMO), as well as a manually created reference alignment, that was developed in consultation with domain experts from different institutions. The alignment includes 1:1, 1:n, and m:n equivalence and subsumption correspondences, and is available in both Expressive and Declarative Ontology Alignment Language (EDOAL) and rule syntax.
We would like to thank the geosciences data providers for sharing the data, and the domain experts for helping understand the concepts to create the ontologies and evaluate the reference alignment. In addition, we would also like to show our gratitude to Jerome Euzenat for providing advice regarding the conversion of rules to EDOAL.
- 1.Cheatham, M., Hitzler, P.: The properties of property alignment. In: Proceedings of the 9th International Workshop on Ontology Matching collocated with the 13th International Semantic Web Conference (ISWC 2014), Riva del Garda, Trentino, Italy, October 20, 2014, pp. 13–24 (2014)Google Scholar
- 2.David, J.: AROMA results for OAEI 2009. In: Proceedings of the 4th International Workshop on Ontology Matching (OM-2009) Collocated with the 8th International Semantic Web Conference (ISWC-2009) Chantilly, USA, October 25 (2009)Google Scholar
- 4.Hitzler, P., Gangemi, A., Janowicz, K., Krisnadhi, A., Presutti, V. (eds.): Ontology Engineering with Ontology Design Patterns - Foundations and Applications, Studies on the Semantic Web, vol. 25. IOS Press, Netherlands (2016)Google Scholar
- 6.Krisnadhi, A.: Ontology Pattern-Based Data Integration. Ph.D. thesis, Wright State University (2015)Google Scholar
- 8.Krisnadhi, A.A., Hitzler, P., Janowicz, K.: On the capabilities and limitations of OWL regarding typecasting and ontology design pattern views. In: Tamma, V., Dragoni, M., Gonçalves, R., Ławrynowicz, A. (eds.) OWLED 2015. LNCS, vol. 9557, pp. 105–116. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-33245-1_11CrossRefGoogle Scholar
- 9.Krisnadhi, A.A., et al.: The geolink framework for pattern-based linked data integration. In: Proceedings of the ISWC 2015 Posters & Demonstrations Track co-located with the 14th International Semantic Web Conference (ISWC-2015), Bethlehem, PA, USA, October 11, 2015 (2015)Google Scholar
- 10.Pesquita, C., Cheatham, M., Faria, D., Barros, J., Santos, E., Couto, F.M.: Building reference alignments for compound matching of multiple ontologies using OBO cross-products. In: Proceedings of the 9th International Workshop on Ontology Matching collocated with the 13th International Semantic Web Conference (ISWC 2014), Riva del Garda, Trentino, Italy, October 20, 2014, pp. 172–173 (2014)Google Scholar
- 11.Ritze, D., Meilicke, C., Sváb-Zamazal, O., Stuckenschmidt, H.: A pattern-based ontology matching approach for detecting complex correspondences. In: Proceedings of the 4th International Workshop on Ontology Matching (OM-2009) collocated with the 8th International Semantic Web Conference (ISWC-2009) Chantilly, USA, October 25, 2009 (2009)Google Scholar
- 13.Suchanek, F.M., Abiteboul, S., Senellart, P.: PARIS: probabilistic alignment of relations, instances, and schema. PVLDB 5(3), 157–168 (2011)Google Scholar
- 14.Thiéblin, É., Haemmerlé, O., Hernandez, N., dos Santos, C.T.: Towards a complex alignment evaluation dataset. In: Proceedings of the 12th International Workshop on Ontology Matching co-located with the 16th International Semantic Web Conference (ISWC 2017), Vienna, Austria, October 21, 2017, pp. 217–218 (2017)Google Scholar