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Big Data Refinement

Boiten, Eerke Albert (2016) Big Data Refinement. Electronic Proceedings in Theoretical Computer Science, 209 . pp. 17-23. ISSN 2075-2180. E-ISSN 2075-2180. (doi:10.4204/EPTCS.209.2) (KAR id:51635)

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http://dx.doi.org/10.4204/EPTCS.209.2

Abstract

"Big data" has become a major area of research and associated funding, as well as a focus of utopian thinking. In the still growing research community, one of the favourite optimistic analogies for data processing is that of the oil refinery, extracting the essence out of the raw data. Pessimists look for their imagery to the other end of the petrol cycle, and talk about the "data exhausts" of our society.

Obviously, the refinement community knows how to do "refining". This paper explores the extent to which notions of refinement and data in the formal methods community relate to the core concepts in "big data". In particular, can the data refinement paradigm can be used to explain aspects of big data processing?

Item Type: Article
DOI/Identification number: 10.4204/EPTCS.209.2
Additional information: Full text upload compliant with proceedings regulations
Uncontrolled keywords: refinement, big data
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming, > QA76.76 Computer software
Divisions: University wide Teaching/Research Centres > Kent Interdisciplinary Research Centre in Cyber Security
Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Eerke Boiten
Date Deposited: 10 Nov 2015 21:27 UTC
Last Modified: 16 Feb 2021 13:29 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/51635 (The current URI for this page, for reference purposes)
Boiten, Eerke Albert: https://orcid.org/0000-0002-9184-8968
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