Linked data quality of DBpedia, Freebase, OpenCyc, Wikidata, and YAGO

By Michael Färber, Frederic Bartscherer, Carsten Menne, Achim Rettinger. Semantic Web, 2017

368 citations recorded by the source corpus.

In recent years, several noteworthy large, cross-domain and openly available knowledge graphs (KGs) have been created. These include DBpedia, Freebase, OpenCyc, Wikidata, and YAGO. Although extensively in use, these KGs have not been subject to an in-depth comparison so far. In this survey, we provide data quality criteria according to which KGs can be analyzed and analyze and compare the above mentioned KGs. Furthermore, we propose a framework for finding the most suitable KG for a given setting.

Subfields: Artificial Intelligence, Management Science and Operations Research, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/a531fb4d4e91c79adf6d81928e1ca5e64dcab3e8

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Ciyuan Peng
2. Francesco Osborne
3. Feng Xia
4. Mehdi Naseriparsa

In Molecular Biology

1. Ciyuan Peng
2. Francesco Osborne
3. Feng Xia
4. Mehdi Naseriparsa

Citations in the corpus

• Knowledge Graphs (2020, neutral): “[153] of DBpedia, Freebase, OpenCyc, and YAGO for further details.”
• Knowledge Graphs: Opportunities and Challenges (2023, background): “Resource Description Framework (RDF) and Labeled Property Graphs (LPGs) are two typical ways to represent and manage knowledge graphs (Färber et al. 2018; Baken 2020).”