%0 Conference Proceedings
%T An Evaluation Framework for Linked Open Statistical Data in Government
%+ Delft University of Technology (TU Delft)
%A Matheus, Ricardo
%A Janssen, Marijn
%Z Part 5: Big and Open Linked Data
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 16th International Conference on Electronic Government (EGOV)
%C St. Petersburg, Russia
%Y Marijn Janssen
%Y Karin Axelsson
%Y Olivier Glassey
%Y Bram Klievink
%Y Robert Krimmer
%Y Ida Lindgren
%Y Peter Parycek
%Y Hans J. Scholl
%Y Dmitrii Trutnev
%I Springer International Publishing
%3 Electronic Government
%V LNCS-10428
%P 255-263
%8 2017-09-04
%D 2017
%R 10.1007/978-3-319-64677-0_21
%K Linked open statistical data
%K LOSD
%K Open data
%K Big data
%K Open government
%K Data cube
%K Evaluation
%K Parameters
%K Requirements
%K Agile development
%Z Computer Science [cs]
%Z Humanities and Social Sciences/Library and information sciencesConference papers
%X 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.
%G English
%Z TC 8
%Z WG 8.5
%2 https://inria.hal.science/hal-01703001/document
%2 https://inria.hal.science/hal-01703001/file/453552_1_En_21_Chapter.pdf
%L hal-01703001
%U https://inria.hal.science/hal-01703001
%~ SHS
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-WG
%~ IFIP-TC8
%~ IFIP-EGOV
%~ IFIP-WG8-5
%~ IFIP-LNCS-10428