Quality Assessment Methodologies for Linked Open Data

@inproceedings{Zaveri2012QualityAM,
  title={Quality Assessment Methodologies for Linked Open Data},
  author={Amrapali Zaveri and Anisa Rula and Andrea Maurino and Ricardo Pietrobon and Jens Lehmann and S{\"o}ren Auer},
  year={2012}
}
The development and standardization of semantic web technologies have resulted in an unprecedented volume of data being published on the Web as Linked Open Data (LOD). However, we observe widely varying data quality ranging from extensively curated datasets to crowd-sourced and extracted data of relatively low quality. Data quality is commonly conceived as fitness of use. Consequently, a key challenge is to determine the data quality wrt. a particular use case. In this article, we present the… CONTINUE READING
Highly Cited
This paper has 70 citations. REVIEW CITATIONS

Citations

Publications citing this paper.

71 Citations

0102030'13'14'15'16'17'18
Citations per Year
Semantic Scholar estimates that this publication has 71 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 58 references

Quality characteristics of linked data publishing datasources

  • A. FLEMMING
  • Master’s thesis, Humboldt-Universität zu Berlin,
  • 2010
Highly Influential
11 Excerpts

Similar Papers

Loading similar papers…