Methodology for Assessment of Linked Data Quality

@inproceedings{Rula2014MethodologyFA,
  title={Methodology for Assessment of Linked Data Quality},
  author={Anisa Rula and Amrapali Zaveri},
  booktitle={LDQ@SEMANTICS},
  year={2014}
}
With the expansion in the amount of data being produced as Linked Data (LD), the opportunity to build use cases has also increased. However, a crippling problem to the reliability of these use cases is the underlying poor data quality. Moreover, the ability to assess the quality of the consumed LD, based on the satisfaction of the consumers’ quality requirements, significantly influences usability of such data for a given use case. In this paper, we propose a data quality assessment methodology… CONTINUE READING
Highly Cited
This paper has 38 citations. REVIEW CITATIONS

From This Paper

Figures, tables, and topics from this paper.

Explore Further: Topics Discussed in This Paper

References

Publications referenced by this paper.
Showing 1-10 of 12 references

Linked Data: Evolving the Web into a Global Data Space

Synthesis Lectures on the Semantic Web • 2011
View 1 Excerpt

ORE - A Tool for Repairing and Enriching Knowledge Bases

International Semantic Web Conference • 2010
View 1 Excerpt

Quality characteristics of linked data publishing datasources

A. Flemming
Master’s thesis, Humboldt-Universität zu Berlin, • 2010
View 1 Excerpt

: Learning Concepts in Description Logics

J. Lehmann. DL-Learner
Journal of Machine Learning Research • 2009

DL-Learner: Learning Concepts in Description Logics

Journal of Machine Learning Research • 2009
View 3 Excerpts