Please use this identifier to cite or link to this item: https://ruomo.lib.uom.gr/handle/7000/348
Title: Linked Open Cube Analytics Systems: Potential and Challenges
Authors: Kalampokis, Evangelos
Tambouris, Efthimios
Tarabanis, Konstantinos
Type: Article
Subjects: FRASCATI::Natural sciences::Computer and information sciences
Issue Date: 2016
Publisher: IEEE
Source: IEEE Intelligent Systems
Volume: 31
Issue: 5
First Page: 89
Last Page: 92
Abstract: Linked Open Cube Analytics (LOCA) systems enable the performance of analytics on top of multiple open statistical data (OSD) that reside in disparate portals. We present OSD’s potential and highlight problems hampering its integration and reuse. To overcome these problems, we introduce an approach for OSD integration. The proposed approach capitalizes on the data cube model and linked data technologies to enable unified access to multiple OSD published in disparate portals. Finally, we present an online analytical processing (OLAP) browser for linked data cubes as a proof of concept of LOCA systems. Throughout this article, we also outline the challenges that need to be addressed for the wide adoption of LOCA systems.
URI: https://doi.org/10.1109/MIS.2016.82
https://ruomo.lib.uom.gr/handle/7000/348
ISSN: 1541-1672
1941-1294
Other Identifiers: 10.1109/MIS.2016.82
Appears in Collections:Department of Business Administration

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