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What is the Impact of Mobility Data Integration on Decision Support Systems' Modelling and Evolution?

What is the Impact of Mobility Data Integration on Decision Support Systems' Modelling and Evolution?

Noura Azaiez, Jalel Akaichi
Copyright: © 2016 |Volume: 8 |Issue: 1 |Pages: 12
ISSN: 1935-5688|EISSN: 1935-5696|EISBN13: 9781466689787|DOI: 10.4018/IJISSS.2016010101
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MLA

Azaiez, Noura, and Jalel Akaichi. "What is the Impact of Mobility Data Integration on Decision Support Systems' Modelling and Evolution?." IJISSS vol.8, no.1 2016: pp.1-12. http://doi.org/10.4018/IJISSS.2016010101

APA

Azaiez, N. & Akaichi, J. (2016). What is the Impact of Mobility Data Integration on Decision Support Systems' Modelling and Evolution?. International Journal of Information Systems in the Service Sector (IJISSS), 8(1), 1-12. http://doi.org/10.4018/IJISSS.2016010101

Chicago

Azaiez, Noura, and Jalel Akaichi. "What is the Impact of Mobility Data Integration on Decision Support Systems' Modelling and Evolution?," International Journal of Information Systems in the Service Sector (IJISSS) 8, no.1: 1-12. http://doi.org/10.4018/IJISSS.2016010101

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Abstract

Classic data seems unable to keep pace with the technology era. In fact, the incredible progress related to geographic information systems, pervasive computing, and positioning technologies have motivated classic data to evolve towards new data kind called mobility data. For decisional purposes, these later have to be analysed; therefore, their integration into a decision support system becomes a must. However, the data warehouse used to store classical data seems to be inadequate for mobility data storage and analysis. This gave the birth of a new central repository type called trajectory data warehouse which is able to support mobility data extraction, transformation, loading, and analysis and/or mining. As classic data warehouses, the trajectory one often changes its content as well as its structure for various reasons such as the organizational business processes progressing over time, the evolving needs of decision makers that lead to DW structure enrichment with additional analyses axes, or even the incompleteness of needs initially captured during the design phase of the DW . This work proposes a survey that gathers the research works that deal with the issue of trajectory data warehouse modelling and evolution; then the authors present comparative study of the proposed solutions.

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