Two procedures for analyzing the reliability of open government data

D. Ceolin, L. Moreau, K. O'Hara, W. Fokkink, W.R. van Hage, V. Maccatrozzo, A. Sackley, G. Schreiber, N. Shadbolt

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

4 Citations (Scopus)

Abstract

Open Government Data often contain information that, in more or less detail, regard private citizens. For this reason, before publishing them, public authorities manipulate data to remove any sensitive information while trying to preserve their reliability. This paper addresses the lack of tools aimed at measuring the reliability of these data. We present two procedures for the assessment of the Open Government Data reliability, one based on a comparison between open and closed data, and the other based on analysis of open data only. We evaluate the procedures over data from the data.police.uk website and from the Hampshire Police Constabulary in the United Kingdom. The procedures effectively allow estimating the reliability of open data and, actually, their reliability is high even though they are aggregated and smoothed.

Original languageEnglish
Title of host publicationInformation Processing and Management of Uncertainty in Knowledge-Based Systems - 15th International Conference, IPMU 2014, Proceedings
EditorsA. Laurent, O. Strauss, B. Bouchon-Meunier, R.R. Yager
Place of PublicationCham
PublisherSpringer
Pages15-24
Number of pages10
ISBN (Electronic)978-3-319-08795-5
ISBN (Print)978-3-319-08794-8
DOIs
Publication statusPublished - 2014
Externally publishedYes
Event15th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2014) - Montpellier, France
Duration: 15 Jul 201419 Jul 2014
http://www.ipmu2014.univ-montp2.fr/

Publication series

NameCommunications in Computer and Information Science
PublisherSpringer
Volume442
ISSN (Print)1865-0929

Conference

Conference15th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2014)
Abbreviated titleIPMU 2014
CountryFrance
CityMontpellier
Period15/07/1419/07/14
Internet address

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