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The usage of large amounts of data has an immense potential for global economic growth and the competitiveness of countries with high technological standards. Vast amounts of data from different sources are collected and analyzed in order to seek economic profit and competitive advantages for companies and society in general. To gain profit from such data, it needs to be analyzed, processed, and interpreted. Thus, knowledge can be created and such generation of knowledge within the analysis and interpretation process constitutes the difference between "Big" and "Smart" Data. In this paper we present a taxonomy to develop standards in the field of Smart Data. It consists of 8 challenges that need to be addressed by standards and 13 fields of standardization.
Lenk et al. (Thu,) studied this question.
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