Quotation Neumaier, Sebastian, Umbrich, Jürgen, Polleres, Axel. 2016. Automated Quality Assessment of Metadata Across Open Data Portals. ACM Journal of Data and Information Quality, 8 (1),


RIS


BibTeX

Abstract

The Open Data movement has become a driver for publicly available data on the Web. More and more data - from governments, public institutions but also from the private sector - is made available online and is mainly published in so called Open Data portals. However, with the increasing number of published resources, there are a number of concerns with regards to the quality of the data sources and the corresponding metadata, which compromise the searchability, discoverability and usability of resources. In order to get a more complete picture of the severity of these issues, the present work aims at developing a generic metadata quality assessment framework for various Open Data portals: we treat data portals independently from the portal software frameworks by mapping the specific metadata of three widely used portal software frameworks (CKAN, Socrata, OpenDataSoft) to the standardized DCAT metadata schema. We subsequently define several quality metrics, which can be evaluated automatically and in a efficient manner. Finally, we report findings based on monitoring a set of over 260 Open Data portals with 1.1M datasets. This includes the discussion of general quality issues, e.g. the retrievability of data, and the analysis of our specific quality metrics.

Tags

Press 'enter' for creating the tag

Publication's profile

Status of publication Published
Affiliation WU
Type of publication Journal article
Journal ACM Journal of Data and Information Quality
Language English
Title Automated Quality Assessment of Metadata Across Open Data Portals
Volume 8
Number 1
Year 2016
DOI http://dx.doi.org/10.1145/2964909
Open Access N

Associations

People
Neumaier, Sebastian (Details)
Umbrich, Jürgen (Former researcher)
Polleres, Axel (Details)
Organization
Applied Information Technology (Details)
Information Business IN (Details)
Research areas (ÖSTAT Classification 'Statistik Austria')
1100 Mathematics, information technology (Details)
1109 Information and data processing (Details)
1122 Artificial intelligence (Details)
5367 Management information systems (Details)
5937 Information systems (Details)
Google Scholar: Search