TY - JOUR
T1 - Geolink data set
T2 - A complex alignment benchmark from real-world ontology
AU - Zhou, Lu
AU - Cheatham, Michelle
AU - Krisnadhi, Adila
AU - Hitzler, Pascal
N1 - Funding Information:
The project that this benchmark arose from is called GeoLink [16] and was funded under the US National Science Foundation’s EarthCube initiative. This planned decade-long endeavor is a recognition that oftentimes the most innovative and useful discoveries come at the intersection of traditional fields of research. This is particularly true in the geosciences, which often bring together disparate groups of researchers such as geologists, meteorologists, climatologists, ecologists, archaeologists, and so on. For its part, GeoLink employs semantic Web technologies to support data representation, sharing, integration, and discovery [17]. In particular, seven diverse geoscience data sets have been brought together into a single data repository.
Publisher Copyright:
© 2019 Chinese Academy of Sciences Published under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
PY - 2020/7/1
Y1 - 2020/7/1
N2 - 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 data set from the GeoLink project as a potential complex ontology alignment benchmark. The data set 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. The benchmark has been expanded from its original version to contain real-world instance data from seven geoscience data providers that has been published according to both ontologies. This allows it to be used by extensional alignment systems or those that require training data. This benchmark has been incorporated into the Ontology Alignment Evaluation Initiative (OAEI) complex track to help researchers test their automated alignment systems and algorithms. This paper also analyzes the challenges inherent in effectively generating, detecting, and evaluating complex ontology alignments and provides a road map for future work on this topic.
AB - 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 data set from the GeoLink project as a potential complex ontology alignment benchmark. The data set 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. The benchmark has been expanded from its original version to contain real-world instance data from seven geoscience data providers that has been published according to both ontologies. This allows it to be used by extensional alignment systems or those that require training data. This benchmark has been incorporated into the Ontology Alignment Evaluation Initiative (OAEI) complex track to help researchers test their automated alignment systems and algorithms. This paper also analyzes the challenges inherent in effectively generating, detecting, and evaluating complex ontology alignments and provides a road map for future work on this topic.
KW - Complex ontology alignment
KW - Complex ontology alignment benchmark
KW - Ontology matching
KW - Ontology population
KW - Real-world ontology
UR - http://www.scopus.com/inward/record.url?scp=85117829187&partnerID=8YFLogxK
U2 - 10.1162/dint_a_00054
DO - 10.1162/dint_a_00054
M3 - Article
AN - SCOPUS:85117829187
VL - 2
SP - 353
EP - 378
JO - Data Intelligence
JF - Data Intelligence
SN - 2096-7004
IS - 3
ER -