Harnessing data flow and modelling potentials for sustainable development

MWITONDI, Kassim and BUGRIEN, Jamal (2012). Harnessing data flow and modelling potentials for sustainable development. CODATA Data Science Journal, 11, 140-152.

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Official URL: http://dx.doi.org/10.2481/dsj.009-027
Link to published version:: https://doi.org/10.2481/dsj.009-027


Tackling some of the global challenges relating to health, poverty, business and the environment is known to be heavily dependent on the flow and utilisation of data. However, while enhancements in data generation, storage, modelling, dissemination and the related integration of global economies and societies are fast transforming the way we live and interact, the resulting dynamic, globalised and information society remains digitally divided. On the African continent, in particular, the division has resulted into a gap between knowledge generation and its transformation into tangible products and services which Kirsop and Chan (2005) attribute to a broken information flow. This paper proposes some fundamental approaches for a sustainable transformation of data into knowledge for the purpose of improving the peoples' quality of life. Its main strategy is based on a generic data sharing model providing access to data utilising and generating entities in a multi disciplinary environment. It highlights the great potentials in using unsupervised and supervised modelling in tackling the typically predictive-in-nature challenges we face. Using both simulated and real data, the paper demonstrates how some of the key parameters may be generated and embedded in models to enhance their predictive power and reliability. Its main outcomes include a proposed implementation framework setting the scene for the creation of decision support systems capable of addressing the key issues in society. It is expected that a sustainable data flow will forge synergies between the private sector, academic and research institutions within and between countries. It is also expected that the paper's findings will help in the design and development of knowledge extraction from data in the wake of cloud computing and, hence, contribute towards the improvement in the peoples' overall quality of life. To void running high implementation costs, selected open source tools are recommended for developing and sustaining the system. Key words: Cloud Computing, Data Mining, Digital Divide, Globalisation, Grid Computing, Information Society, KTP, Predictive Modelling and STI.

Item Type: Article
Additional Information: Originally presented at CODATA2010 - Cape Town, South Africa
Research Institute, Centre or Group - Does NOT include content added after October 2018: Cultural Communication and Computing Research Institute > Communication and Computing Research Centre
Departments - Does NOT include content added after October 2018: Faculty of Science, Technology and Arts > Department of Computing
Identification Number: https://doi.org/10.2481/dsj.009-027
Page Range: 140-152
Depositing User: Kassim Mwitondi
Date Deposited: 24 Sep 2012 16:20
Last Modified: 18 Mar 2021 04:46
URI: https://shura.shu.ac.uk/id/eprint/5267

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