A Semiotic Approach to Investigate Quality Issues of Open Big Data Ecosystems

Abstract

Part 2: Organisational Semiotics and ApplicationsInternational audienceThe quality of data models has been investigated since the mid-nineties. In another strand of research, data and information quality has been investigated even longer. Data can also be looked upon as a type of model (on the instance level), as illustrated e.g. in the product models in CAD-systems. We have earlier presented a specialization of the general SEQUAL-framework to be able to evaluate the combined quality of data models and data. In this paper we look in particular on the identified issues of ‘Big Data’. We find on the one hand that the characteristics of quality of big data can be looked upon in the light of the quality levels of the SEQUAL-framework as it is specialized for data quality, and that there are aspects in this framework that are not covered by the existing work on big data. On the other hand, the exercise has resulted in a useful deepening of the generic framework for data quality, and has in this way improved the practical applicability of the SEQUAL-framework when applied to discussing and assessing quality of big data

Smart sustainable cities of the future: An extensive interdisciplinary literature review

“…Al Nuaimi et al 2015;Batty et al 2012;Bertot and Choi 2013;Demchenko et al 2013;DeRen, JianJun and Yuan 2015;Fan and Bifet 2013; Khan, Uddin and Gupta 2014;Kitchin 2014;Krogstie and Gao 2015; Malilk 2013;Mann 2012;Solanas et al 2014;Townsend 2013), and modeling and management of contextual information in large-scale distributed pervasive applications and in open and dynamic pervasive environments (e.g. Bibri 2015a;Strimpakou et al 2006).…”