A study on several organizations in one of the districts of Kelantan that was severely affected by the massive floods in 2014 highlights a number of problems in managing data, notably critical data, owing to the lack of a standard operating procedure (SOP) that could be used as guidelines for data storage, data loss, and data inconsistency between organizations. Admittedly, there are several data management frameworks available, but in general, they are less effective for the management of data in times of crisis due to natural disasters. In view of this predicament, a critical data management framework was developed to serve as guidelines in dealing with the above prevailing issues. More specifically, the aim of this study is to identify and validate the components and elements of an appropriate assessment instrument using the Delphi technique to help formulate such a framework in dealing with the management of critical data in situations facing disasters. In this study, the validation of several selected components and elements through the Delphi technique was carried out in two rounds involving a panel of experts, consisting of three data managers, three ICT administrators from the public sector, and three academicians. The findings of the validation process showed that all the experts unanimously accepted and validated 10 components that were deemed vital for the formulation of the proposed critical data management framework. In fact, the formulation of the proposed framework was more compressive and holistic by focusing not only on the general aspects of data management but also on the critical aspects of disaster management, of which the latter could help organizations to handle important data in times when disasters occur unpredictably. Equipped with such a comprehensive framework, the researchers would be able to develop a critical data management system prototype to help organizations, with which organizations could use to help manage their important, valuable data in critical, precarious situations.
Armstrong, J. S. (1985). Long range forecasting: from crystal ball to computer (2nd ed.). New York: John Wiley & Sons Inc.
Australian National Data Service. (2017). Creating a data mangement framework. Retrieved January 10 2017, from https://www.ands.org.au/guides/creating-a-data-management-framework.
Beaujardière, J. D. (n.d.). NOAA environmental data management framework (1.0st ed.). Retrieved from https://nosc.noaa.gov/EDMC/documents/NOAA_EDM_Framework_v1.0.pdf.
Brockhoff, K. (1975). The performance of forecasting groups in computer dialogue and face- to-face discussion. In Linstone, H. & Turoff, M. (Eds.), The Delphi methods: technique and applications. London: Addison-Wesley.
Cagle, K. (2015). Understanding the big data life-cycle. Retrieved October 15 2017, from https://www.linkedin.com/pulse/four-keys-big-data-life-cycle-kurt-cagle.
Cantrill, J. A., Sibbald, B. & Beutow, S. (1996). The Delphi and minimal group technique in health service research. International Journal of Pharmacy Practice, 4, 67-74.
Chu, H. C. & Hwang, G. J. (2007). A Delphi-based approach to developing experts system with the cooperation of multiple experts. Experts System with Application, 1-15.
Cochran, S. W. (1983). The Delphi method: formulation and refining group judgments. Journal of Human Sciences, 2(2), 111-117.
Cuhls, K. (2014). Delphi method, Fraunhofer Institute for Systems and Innovation Research. Retrieved from http://www.unido.org/fileadmin/import/16959_DelphiMethod.pdf
Douglas, C. (2014). Technology & information services: architecture principles (data principles). Retrieved from https://www.plymouth.ac.uk/uploads/production/document/path/4/4225/Architecture_Principles_v2.pdf
Egan, A. F. & Jones, S. B. (1997). Determining forest harvest impact assessment criteria using expert opinion: A Delphi study. Northern Journal of Applied Forestry, 14(1), 20-25.
Erl, T., Buhler, P., & Khattak, W. (2016). Big data fundamentals: concepts, drivers & techniques. Retrieved October 15 2017, from http://www.informit.com/articles/article.aspx?p=2473128&seqNum=11.
Gary, S. (2011). Can your district survive a data disaster? Retrieved July 27 2018, from http://www.asbointi.com.
GEO Data Management Principles Task Force. (2015). Data management principles implementation guidelines. Retrieved from https://www.earthobservations.org/documents/geo_xii/GEO-XII_10_Data Management Principles Implementation Guidelines.pdf.
Gidey, A. (2012). Reviewing the values of a standard operating procedure. Ethiop Journal Health Science, 22(3), 205-208.
Hai, L. T., Hai, P. H., Thai, C. L., Hugé, J., Ahenkan, A., Quynh, L. X., & Van Hieu, V. (2011). Software for sustainability assessment: a case study in Quang Tri province, Vietnam. Environmental Modeling & Assessment, 16(6), 541–550.
Haraguchi, M., & Lall, U. (2015). Flood risks and impacts: A case study of Thailand’s floods in 2011 and research questions for supply chain decision making. International Journal of Disaster Risk Reduction, 14, 256-272. http://doi.org/10.1016/j.ijdrr.2014.09.005i.
Mohamed, R. H. A. (2014). A proposed model for IT disaster recovery plan. International Journal of Modern Education and Computer Science, 4, 57-67. DOI:10.5815/ijmecs2014.04.08.
Hsu, C. C., & Sandford, B. A. (2007). The Delphi technique: making sense of consensus. Practical Assessment Research & Evaluation, 12(10). Retrieved January 22 2014, from http://pareonline.net/getvn.asp?v=12&n=10.
Kaur, M., & Shah, A. (2017). A novel framework for big data security infrastructure components. International Journal on Recent and Innovation Trends in Computing and Communication, 5(6). Retrieved October 10 2017, from http://www.ijritcc.org/download/browse/Volume_5_Issues/June_17_Volume_5_Issue_6/1498730590_29-06-2017.pdf&p=DevEx.LB.1,5067.1
Ketchum, A. M. (2016). Guiding principles for data management: is your data FAIR? HSLS Update. Retrieved September 26 2017, from http://info.hsls.pitt.edu/updatereport/?p=9493.
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In-Text Citation: (Ubaidullah et al., 2018)
To Cite this Article: Ubaidullah, N. H., Saad, A., Hamid, J., Rashid, N. A., Mohamed, Z., & Hashim, M. (2018). The Formulation of a Critical Data Management Framework for Situations Facing Disasters through the Delphi Technique. International Journal of Academic Research in Business and Social Sciences, 8(9), 1193–1210.
Copyright: © 2018 The Author(s)
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