The Enslaved Dataset: A Real-world Complex Ontology Alignment Benchmark using Wikibase (Q22): Difference between revisions
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Varvantakis (talk | contribs) (Created claim: Publication title (P8): The Enslaved Dataset: A Real-world Complex Ontology Alignment Benchmark using Wikibase) |
Varvantakis (talk | contribs) (Created claim: Abstract (P6): Ontology alignment has taken a critical place for helping heterogeneous resources to interoperate. It has been studied for over a decade, and over that time many alignment systems and methods have been developed by researchers to find simple 1:1 equivalence matches between two ontologies. However, very few alignment systems focus on finding complex correspondences. Even if the complex alignment systems are developed, the performance of finding com...) |
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| Property / Abstract | |||
Ontology alignment has taken a critical place for helping heterogeneous resources to interoperate. It has been studied for over a decade, and over that time many alignment systems and methods have been developed by researchers to find simple 1:1 equivalence matches between two ontologies. However, very few alignment systems focus on finding complex correspondences. Even if the complex alignment systems are developed, the performance of finding complex relations still has a lot of room for improvement. One reason for this limitation may be that there are still few applicable alignment benchmarks that contain such complex relationships that can raise researchers' interests. In this paper, we propose a real-world dataset from the Enslaved project as a potential complex alignment benchmark. The benchmark consists of two resources, the Enslaved Ontology along with a Wikibase repository holding a large number of instance data from the Enslaved project, as well as a manually created reference alignment between them. The alignment was developed in consultation with domain experts in the digital humanities. The alignment not only includes simple 1:1 equivalence correspondences, but also more complex m:n equivalence and subsumption correspondences and are provided in both Expressive and Declarative Ontology Alignment Language (EDOAL) format and rule syntax. The Enslaved benchmark has been incorporated into the Ontology Alignment Evaluation Initiative (OAEI) 2020 and is completely free for public use to assist the researchers in developing and evaluating their complex alignment algorithms. (English) | |||
| Property / Abstract: Ontology alignment has taken a critical place for helping heterogeneous resources to interoperate. It has been studied for over a decade, and over that time many alignment systems and methods have been developed by researchers to find simple 1:1 equivalence matches between two ontologies. However, very few alignment systems focus on finding complex correspondences. Even if the complex alignment systems are developed, the performance of finding complex relations still has a lot of room for improvement. One reason for this limitation may be that there are still few applicable alignment benchmarks that contain such complex relationships that can raise researchers' interests. In this paper, we propose a real-world dataset from the Enslaved project as a potential complex alignment benchmark. The benchmark consists of two resources, the Enslaved Ontology along with a Wikibase repository holding a large number of instance data from the Enslaved project, as well as a manually created reference alignment between them. The alignment was developed in consultation with domain experts in the digital humanities. The alignment not only includes simple 1:1 equivalence correspondences, but also more complex m:n equivalence and subsumption correspondences and are provided in both Expressive and Declarative Ontology Alignment Language (EDOAL) format and rule syntax. The Enslaved benchmark has been incorporated into the Ontology Alignment Evaluation Initiative (OAEI) 2020 and is completely free for public use to assist the researchers in developing and evaluating their complex alignment algorithms. (English) / rank | |||
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Revision as of 08:49, 28 September 2023
Zhou et al 2020
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | The Enslaved Dataset: A Real-world Complex Ontology Alignment Benchmark using Wikibase |
Zhou et al 2020 |
Statements
Lu Zhou, Cogan Shimizu, Pascal Hitzler, Alicia M. Sheill, Seila Gonzalez Estrecha, Catherine Foley, Duncan Tarr, Dean Rehberger (English)
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2020
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The Enslaved Dataset: A Real-world Complex Ontology Alignment Benchmark using Wikibase (English)
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Ontology alignment has taken a critical place for helping heterogeneous resources to interoperate. It has been studied for over a decade, and over that time many alignment systems and methods have been developed by researchers to find simple 1:1 equivalence matches between two ontologies. However, very few alignment systems focus on finding complex correspondences. Even if the complex alignment systems are developed, the performance of finding complex relations still has a lot of room for improvement. One reason for this limitation may be that there are still few applicable alignment benchmarks that contain such complex relationships that can raise researchers' interests. In this paper, we propose a real-world dataset from the Enslaved project as a potential complex alignment benchmark. The benchmark consists of two resources, the Enslaved Ontology along with a Wikibase repository holding a large number of instance data from the Enslaved project, as well as a manually created reference alignment between them. The alignment was developed in consultation with domain experts in the digital humanities. The alignment not only includes simple 1:1 equivalence correspondences, but also more complex m:n equivalence and subsumption correspondences and are provided in both Expressive and Declarative Ontology Alignment Language (EDOAL) format and rule syntax. The Enslaved benchmark has been incorporated into the Ontology Alignment Evaluation Initiative (OAEI) 2020 and is completely free for public use to assist the researchers in developing and evaluating their complex alignment algorithms. (English)
0 references