An Evaluation Framework for Linked Open Statistical Data in Government

Conference Paper (2017)
Author(s)

Ricardo Matheus (TU Delft - Information and Communication Technology)

Marijn Marijn (TU Delft - Information and Communication Technology)

Research Group
Information and Communication Technology
Copyright
© 2017 R. Matheus, M.F.W.H.A. Janssen
DOI related publication
https://doi.org/10.1007/978-3-319-64677-0_21
More Info
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Publication Year
2017
Language
English
Copyright
© 2017 R. Matheus, M.F.W.H.A. Janssen
Research Group
Information and Communication Technology
Volume number
10428
Pages (from-to)
255-263
ISBN (print)
978-3-319-64676-3
ISBN (electronic)
978-3-319-64677-0
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Demographic, economic, social and other datasets are often used in policy-making processes. These types of statistical data are opened more and more by governments, which enables the use of these datasets by the public. However, statistical data needs often to combine different datasets. Data cubes can be used to combine datasets and are a multi-dimensional array of values typically used to describe time series of geographical areas. While Linked Open Statistical Data (LOSD) cube software is still in an initial stage of maturity, there is a need for evaluation the software platforms used to process this open data. Yet there is a lack of evaluation methods. The objective of this ongoing research paper is to identify functional requirements for open data cubes infrastructures. Eight main processes are identified and a list of 23 functional requirements are used to evaluate the OpenCube platform. The evaluation results of a LOSD platform show that many functions are not automated and need to be manually executed. We recommend the further integration of the building blocks in the platform to reduce the barriers for the use of datasets by the public.

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