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:https://doi.org/10.4204/EPTCS.209.2) (Full text available)

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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
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: Faculties > University wide - Teaching/Research Groups > Centre for Cyber Security Research
Faculties > Sciences > School of Computing > Security Group
Faculties > Sciences > School of Computing > Programming Languages and Systems Group
Depositing User: E.A. Boiten
Date Deposited: 10 Nov 2015 21:27 UTC
Last Modified: 30 Jan 2017 15:14 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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