Results of the Ontology Alignment Evaluation Initiative 2015

cheatham2016aInternational audienceOntology matching consists of finding correspondences between semantically related entities of two ontologies. OAEI campaigns aim at comparing ontology matching systems on precisely defined test cases. These test cases can use ontologies of different nature (from simple thesauri to expressive OWL ontologies) and use different modalities, e.g., blind evaluation, open evaluation and consensus. OAEI 2015 offered 8 tracks with 15 test cases followed by 22 participants. Since 2011, the campaign has been using a new evaluation modality which provides more automation to the evaluation. This paper is an overall presentation of the OAEI 2015 campaign

Results of the ontology alignment evaluation initiative 2020

The Ontology Alignment Evaluation Initiative (OAEI) aims at comparing ontology matching systems on precisely defined test cases. These test cases can be based on ontologies of different levels of complexity and use different evaluation modalities (e.g., blind evaluation, open evaluation, or consensus). The OAEI 2020 campaign offered 12 tracks with 36 test cases, and was attended by 19 participants. This paper is an overall presentation of that campaign

Results of the Ontology Alignment Evaluation Initiative 2021

The Ontology Alignment Evaluation Initiative (OAEI) aims at comparing ontology matching systems on precisely defined test cases. These test cases can be based on ontologies of different levels of complexity and use different evaluation modalities (e.g., blind evaluation, open evaluation, or consensus). The OAEI 2021 campaign offered 13 tracks and was attended by 21 participants. This paper is an overall presentation of that campaig

Pushing the Limits of Instance Matching Systems: A Semantics-Aware Benchmark for Linked Data

ABSTRACT The architectural choices behind the Data Web have led to the publication of large interrelated data sets that contain different descriptions for the same real-world objects. Due to the mere size of current online datasets, such duplicate instances are most commonly detected (semi-)automatically using instance matching frameworks. Choosing the right framework for this purpose remains tedious, as current instance matching benchmarks fail to provide end users and developers with the necessary insights pertaining to how current frameworks behave when dealing with real data. In this poster, we present the Semantic Publishing Instance Matching Benchmark (SPIMBENCH) which allows the benchmarking of instance matching systems against not only structure-based and value-based test cases, but also against semantics-aware test cases based on OWL axioms. SPIMBENCH features a scalable data generator and a weighted gold standard that can be used for debugging instance matching systems and for reporting how well they perform in various matching tasks

Results of the Ontology Alignment Evaluation Initiative 2016

Ontology matching consists of finding correspondences between se- mantically related entities of two ontologies. OAEI campaigns aim at comparing ontology matching systems on precisely defined test cases. These test cases can use ontologies of different nature (from simple thesauri to expressive OWL on- tologies) and use different modalities, e.g., blind evaluation, open evaluation, or consensus. OAEI 2016 offered 9 tracks with 22 test cases, and was attended by 21 participants. This paper is an overall presentation of the OAEI 2016 campaign

Introducing the HOBBIT platform into the ontology alignment evaluation campaign

OM is co-located with the 17th International Semantic Web Conference (ISWC)International audienceThis paper describes the Ontology Alignment Evaluation Initiative 2017.5 pre-campaign. Like in 2012, when we transitioned the evaluation to the SEALS platform, we have also conducted a pre-campaign to assess the feasibility of moving to the HOBBIT platform. We report the experiences of this pre-campaign and discuss the future steps for the OAEI

Toward an integrated profile of depression: evidence from the brain resource international database

The Ontology Alignment Evaluation Initiative (OAEI) aims at comparing ontology matching systems on precisely defined test cases. These test cases can be based on ontologies of different levels of complexity (from simple thesauri to expressive OWL ontologies) and use different evaluation modalities (e.g., blind evaluation, open evaluation, or consensus). The OAEI 2018 campaign offered 12 tracks with 23 test cases, and was attended by 19 participants. This paper is an overall presentation of that campaign

Results of the Ontology Alignment Evaluation Initiative 2023

collocated with the 22nd International Semantic Web Conference ISWC-2023 November 7th, 2023, Athens, GreeceInternational audienceThe Ontology Alignment Evaluation Initiative (OAEI) aims at comparing ontology matching systems on precisely defined test cases. These test cases can be based on ontologies of different levels of complexity and use different evaluation modalities. The OAEI 2023 campaign offered 15 tracks and was attended by 16 participants. This paper is an overall presentation of that campaign