Please use this identifier to cite or link to this item: https://ruomo.lib.uom.gr/handle/7000/1285
Title: Interoperability Conflicts in Linked Open Statistical Data
Authors: Kalampokis, Evangelos
Karamanou, Areti
Tarabanis, Konstantinos
Type: Article
Subjects: FRASCATI::Engineering and technology::Electrical engineering, Electronic engineering, Information engineering
Keywords: Open Data
Linked Data
Open Government
Issue Date: 2019
Source: Information
Volume: 10
Issue: 8
First Page: 249
Abstract: An important part of Open Data is of a statistical nature and describes economic and social indicators monitoring population size, inflation, trade, and employment. Combining and analyzing Open Data from multiple datasets and sources enable the performance of advanced data analytics scenarios that could result in valuable services and data products. However, it is still difficult to discover and combine Open Statistical Data that reside in different data portals. Although Linked Open Statistical Data (LOSD) provide standards and approaches to facilitate combining statistics on the Web, various interoperability challenges still exist. In this paper, we propose an Interoperability Framework for LOSD, comprising definitions of LOSD interoperability conflicts as well as modelling practices currently used by six official open government data portals. Towards this end, we combine a top-down approach that studies interoperability conflicts in the literature with a bottom-up approach that studies the modelling practices of data portals. We define two types of LOSD schema-level conflicts, namely naming conflicts and structural conflicts. Naming conflicts result from using different URIs. Structural conflicts result from different practices of modelling the structure of data cubes. Only two out of the 19 conflicts are currently resolved and 11 can be resolved according to literature.
URI: https://doi.org/10.3390/info10080249
https://ruomo.lib.uom.gr/handle/7000/1285
ISSN: 2078-2489
Other Identifiers: 10.3390/info10080249
Appears in Collections:Department of Business Administration

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