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An argumentation reasoning approach for data processing
journal contribution
posted on 2017-09-21, 10:30 authored by E. Karafili, Konstantina Spanaki, Emil LupuData-intensive environments enable us to capture information and knowledge about the physical surroundings, to optimise our resources, enjoy personalised services and gain unprecedented insights into our lives. However, to obtain these endeavours extracted from the data, this data should be generated, collected and the insight should be exploited. Following an argumentation reasoning approach for data
processing and building on the theoretical background of data management, we highlight the importance of data sharing agreements (DSAs) and quality attributes for the proposed data processing mechanism. The proposed approach is taking into account the DSAs and usage policies as well as the quality attributes of the data, which were previously neglected compared to existing methods in the data processing and management field. Previous research provided techniques towards this direction; however, a more intensive research approach for processing techniques should be introduced for the future to enhance the value creation from the data and new strategies should be formed around this data generated daily from various devices and sources.
Funding
This is an Open Access Article. It is published by Elsevier under the Creative Commons Attribution 4.0 International Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/
History
School
- Business and Economics
Department
- Business
Published in
Computers in IndustryVolume
94Pages
52-61Citation
KARAFILI, E., SPANAKI, K. and LUPU, E., 2018. An argumentation reasoning approach for data processing. Computers in Industry, 94, pp. 52-61.Publisher
Elsevier © The AuthorsVersion
- VoR (Version of Record)
Publisher statement
This work is made available according to the conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/Acceptance date
2017-09-08Publication date
2017-11-05Copyright date
2018Notes
Supported by FP7 EU-funded project Coco Cloud grant no.: 610853, and EPSRC Project CIPART grant no. EP/L022729/1.ISSN
0166-3615Publisher version
Language
- en