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On Modeling Linked Open Statistical Data

15 Pages Posted: 19 Nov 2018 First Look: Accepted

See all articles by Evangelos Kalampokis

Evangelos Kalampokis

University of Macedonia - Information Systems Lab

Dimitris Zeginis

University of Macedonia - Information Systems Lab

Konstantinos Tarabanis

University of Macedonia - Information Systems Lab

Abstract

A major part of Open Data concerns statistics such as economic and social indicators. Statistical data are structured in a multidimensional manner creating data cubes. Recently, National Statistical Institutes and public authorities adopted the Linked Data paradigm to publish their statistical data on the Web. Many vocabularies have been created to enable modeling data cubes as RDF graphs, and thus creating Linked Open Statistical Data (LOSD). However, the creation of LOSD remains a demanding task mainly because of modeling challenges related either to the conceptual definition of the cube, or to the way of modeling cubes as linked data. The aim of this paper is to identify and clarify (a) modeling challenges related to the creation of LOSD and (b) approaches to address them. Towards this end, nine LOSD experts were involved in an interactive feedback collection and consensus-building process that was based on Delphi method. We anticipate that the results of this paper will contribute towards the formulation of best practices for creating LOSD, and thus facilitate combining and analysing statistical data from diverse sources on the Web.

Keywords: Open Data, Linked Open Statistical Data, Modeling Challenges, Delphi Method

Suggested Citation

Kalampokis, Evangelos and Zeginis, Dimitris and Tarabanis, Konstantinos, On Modeling Linked Open Statistical Data (November 19, 2018). Available at SSRN: https://ssrn.com/abstract=3287147 or http://dx.doi.org/10.2139/ssrn.3287147

Evangelos Kalampokis (Contact Author)

University of Macedonia - Information Systems Lab

156 Egnatia St.
P.O. 1591
Thessaloniki, 54006
Greece

Dimitris Zeginis

University of Macedonia - Information Systems Lab

156 Egnatia St.
P.O. 1591
Thessaloniki, 54006
Greece

Konstantinos Tarabanis

University of Macedonia - Information Systems Lab ( email )

156 Egnatia St.
P.O. 1591
Thessaloniki, 54006
Greece

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