The vision of the Semantic Web is that computers as well as humans will be able to leverage the information on the web. One important capability that would facilitate this goal is using Knowledge Graph and Ontology. An ontology can serve as a underlying schema of Knowledge Graphs to enable logical inference and reasoning. An ontology is a representation of the concepts in a domain and how they relate to one another. Creating an ontology involves a lot of design decisions, which tend to be influenced by the designers’ backgrounds and the application they are targeting. The result is that two ontologies that represent the same domain will not necessarily be the same. Ontology alignment is considered as a key interoperability enabler for the Semantic Web, as well as a useful technique in some classical data integration tasks dealing with the semantic heterogeneity problem. It takes ontologies as input and determines as output an alignment, that is, a set of correspondences between the semantically related entities of those ontologies. These correspondences can be used for various tasks, such as ontology merging, data interlinking, query answering or process mapping. Thus, matching ontologies enables the knowledge and data expressed with the matched ontologies to interoperate.
DaSe Lab has been working on Knowledge Graph Integration, including Ontology Alignment and Coreference Resolution for many years. Particularly, our expertise mostly includes 1) establishing and maintaining benchmarks for ontology alignment community for evaluating the performance of state of the art alignment algorithms, 2) generating and improving complex ontology alignment and coreference resolution systems, 3) reseaching and developing the evaulation matrixes to evaluate complex ontology alignment.
- KnowWhere Graph merges novel Artificial Intelligence-based geoenrichment technologies with a knowledge graph that brings together open, cross-domain, densely integrated data spanning the human-environment interface.
- Cross Project Demonstratior inventories the scope and overlap of the Track A Knowledge Graphs in the Convergence Accelerator Project.
- AROA Results of OAEI 2020
- GeoLink Cruises: A Non-Synthetic Benchmark for Co-Reference Resolution on Knowledge Graphs
- The Enslaved Dataset: A Real-world Complex Ontology Alignment Benchmark using Wikibase
- Towards Evaluating Complex Ontology Alignments
- Alignment of Surface Water Ontologies: A comparison of manual and automated approaches
- AROA Results of 2019 OAEI
- GeoLink Dataset: A Complex Alignment Benchmark from Real-world Ontology
- Towards Association Rule-Based Complex Ontology Alignment
- A Complex Alignment Benchmark: Geolink dataset
- The First Version of the OAEI Complex Alignment Benchmark
- A Journey From Simple to Complex Alignment on Real-World Ontologies
- A Replication Study: Understanding What Drives the Performance in WikiMatch
- KnowWhereGraph: Enriching and Linking Cross-Domain Knowledge Graphs using Spatially-Explicit AI Technologies
- Convergence Accelerator Phase I (RAISE): Spatially-Explicit Models, Methods, and Services for Open Knowledge Networks
- Ontology Modeling for the Slave Trade
- EarthCube Building Blocks: GeoLink - Leveraging Semantics and Linked Data for Data Sharing and Discovery in the Geosciences
- Lu Zhou: luzhou[at]ksu[dot]edu
- Pascal Hitzler: hitzler[at]ksu[dot]edu