Quality assessment for Linked Data: A Survey
Leipzig University · University of Milano-Bicocca · +2 more institutions
Abstract
The development and standardization of Semantic Web technologies has resulted in an unprecedented volume of data being published on the Web as Linked Data (LD). However, we observe widely varying data quality ranging from extensively curated datasets to crowdsourced and extracted data of relatively low quality. In this article, we present the results of a systematic review of approaches for assessing the quality of LD. We gather existing approaches and analyze them qualitatively. In particular, we unify and formalize commonly used terminologies across papers related to data quality and provide a comprehensive list of 18 quality dimensions and 69 metrics. Additionally, we qualitatively analyze the 30 core…
Citation impact
- FWCI
- 93.06
- Percentile
- 100%
- References
- 62
Authors
6Topics & keywords
- Computer science
- Data quality
- Data science
- Standardization
- Quality (philosophy)
- Set (abstract data type)
- Semantic Web
- Data mining
- Industry, innovation and infrastructure