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In a global and interconnected economy, decision makers often need to consider information from various domains. A tourism destination manager, for example, has to correlate tourist behavior with financial and environmental indicators to allocate funds for strategic long-term investments. Statistical data underpins a broad range of such cross-domain decision tasks. A variety of statistical datasets are available as Linked Open Data, often incorporated into visual analytics solutions to support decision making. What are the principles, architectures, workflows and implementation design patterns that should be followed for building such visual cross-domain decision support systems. This article introduces a methodology to integrate and visualize cross-domain statistical data sources by applying selected RDF Data Cube (QB) principles. A visual dashboard built according to this methodology is presented and evaluated in the context of two use cases in the tourism and telecommunications domains.

Author(s): Adrian Brasoveanu, Marta Sabou, Arno Scharl, Alexander Hubmann-Haidvogel, Daniel Fischl

Publication date: 2017

Volume: 8

Issue number: 1

Pages: 113-137

Electronic version(s), related files and links: http://dx.doi.org/10.3233/SW-160225

Author(s): Lyndon Nixon, Arno Scharl, Adrian Brasoveanu, Albert Weichselbraun

Publication date: 1. 5. 2016

The complexity of the social, political and economical settings in which tourism enterprises operate, increasingly require them to perform data analytics tasks that rely on data from various domains (e.g., economy, environmental sustainability). A survey of tourism practitioners performed in this study showed that although such cross-domain analytics are important, they are primarily performed by relying on manual data collection and aggregation, which is both time-consuming and error-prone. This paper investigates the suitability of Linked Data technologies to support data aggregation tasks needed for establishing such complex analytics systems. To that end, a prototypical implementation is developed that relies on Linked Data as a technological platform for integrating data from three major tourism data sources: TourMIS, World Bank and Eurostat. Enabled by this integrated data, the ETIHQ Dashboard for data analytics was implemented, the first visual data analytics system that supports cross-domain analytics over tourism, economic and sustainability indicators. An exploratory evaluation performed with practitioners shows that this Linked Data enabled system could potentially bring important improvements in terms of execution times and answer quality when compared to current manual approaches typically used by tourism practitioners in daily practice.

Author(s): Marta Sabou, Irem Önder, Adrian Brasoveanu, Arno Scharl

Publication date: 3. 2016

Volume: 16

Issue number: 1

Pages: 71-101

Electronic version(s), related files and links: http://dx.doi.org/10.1007/s40558-015-0049-5

The complexity of the socio-, political- and economical settings in which tourism enterprises operate, increasingly require them to make decisions that take into account data from various domains (e.g., economy, environmental sustainability). Based on a practitioners' survey that we performed, we conclude that although such cross-domain decisions are important, they are primarily performed by relying on manual data collection and aggregation, which is both time-consuming and error-prone. We propose a solution that relies on Linked Data as a technological platform for integrating data from three major tourism data sources: TourMIS, World Bank and Eurostat. Enabled by this integrated data, we developed the ETIHQ Dashboard, the first visual decision support system that supports cross-domain decisions over tourism, economic and sustainability indicators. An evaluation performed with practitioners shows that this Linked Data enabled systems brings important improvements in terms of execution times (28% faster) and answer quality when compared to current manual approaches.

Author(s): Arno Scharl, Irem Önder, Adrian Brasoveanu, Marta Sabou

Publication date: 11. 3. 2015

Series information: Modul University Working Paper Series

Place of Publication Volume: Vienna

Publisher: Modul University Vienna GmbH

Electronic version(s), related files and links: http://dx.doi.org/10.2139/ssrn.2580242

Author(s): Marta Sabou, Adrian Brasoveanu, Irem Önder

Publication date: 2015