Data Governance Model For Nation-Wide Non-Profit Organization
DOI:
https://doi.org/10.37385/jaets.v5i1.2415Keywords:
non-profit, data, governance, information systems, modelAbstract
According to Connolly's (2017) research, the context of nonprofit organizations exhibits variations when compared to commercial organizations or businesses, as supported by Zhang's (2010) study. Hence, it is imperative for both theoretical and empirical studies to contribute towards enhancing our comprehension of the strategy, implementation, and utilization of information systems in the specific context of nonprofit organizations. The investigation of information systems within the context of non-profit organizations offers a promising avenue for advancing the field of information systems research. This study focuses on the development of an information systems framework using the soft systems methodology, which has already been established. One opportunity for the advancement of information systems in non-profit organizations lies in the establishment of a comprehensive framework that facilitates adoption and is accompanied by robust data governance. This framework enables the analysis of data and the generation of valuable insights, thereby contributing to the development of information systems in the non-profit sector. The choice of data governance was informed by Zhang's (2010) research, which demonstrated that non-profit organizations face significant obstacles in the form of privacy and data security concerns. Furthermore, it is apparent that the preservation of data privacy plays a crucial role in the acceptance and utilization of information systems within non-profit entities. This research aims to contribute to the resolution of the issue by establishing a governance framework for information systems that effectively communicates to users the absence of data privacy risks associated with the systems employed by organizations. The objective of this study is to create a data governance model that will fill the research gap mentioned earlier and make a valuable contribution to the field of information systems research. The formation of the data governance model will involve the integration of soft systems methodology and the DAMA framework. The outcome of this study will be a data governance model specifically designed for a nationwide non-profit organization that utilizes microservices as its cutting-edge technology.
Downloads
References
Aisyah, M., & Ruldeviyani, Y. (2019). Designing data governance structure based on data management body of knowledge (DMBOK) Framework: A case study on Indonesia deposit insurance corporation (IDIC). 2018 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018, 307–312. https://doi.org/10.1109/ICACSIS.2018.8618151
Augustsson, H., Churruca, K., & Braithwaite, J. (2020). Change and improvement 50 years in the making: a scoping review of the use of soft systems methodology in healthcare. BMC Health Services Research, 20(1), 1–13. https://doi.org/10.1186/s12913-020-05929-5
Connolly, A. J., & Connolly, A. J. (2017). Data Analytics as a Conduit for Progressing Information Systems Research in Nonprofit Organizations. Southern Association for Information Systems (SAIS) Proceeding.
DAMA International. (2014). DAMA-DMBOK2 Framework. The Data Mangement Association, 1–27. https://dama.org/sites/default/files/download/DAMA-DMBOK2-Framework-V2-20140317-FINAL.pdf
Falahah, & Santoso, A. F. (2022). Design of Data Interchange Regulation for Regional ICT Office. International Journal on Informatics Visualization, 6(2), 335–342. https://doi.org/10.30630/joiv.6.1.546
Febiryani, W., Kusumasari, T. F., & Fauzi, R. (2021). Analysis and Design of Implementation Guidelines Data Security Management Assessment Techniques Based on DAMA-DMBOKv2. Proceedings - 2021 IEEE 5th International Conference on Information Technology, Information Systems and Electrical Engineering: Applying Data Science and Artificial Intelligence Technologies for Global Challenges During Pandemic Era, ICITISEE 2021, 371–375. https://doi.org/10.1109/ICITISEE53823.2021.9655782
Georgiou, I. (2015). Unravelling soft systems methodology. International Journal of Economics and Business Research, 9(4), 415–436. https://doi.org/10.1504/IJEBR.2015.069680
Gustriansyah, R., Sensuse, D. I., & Ramadhan, A. (2017). A sales prediction model adopted the recency-frequency-monetary concept. Indonesian Journal of Electrical Engineering and Computer Science, 6(3), 711–720. https://doi.org/10.11591/ijeecs.v6.i3.pp711-720
Harrison, T., Canestraro, D., Pardo, T., Avila-Maravilla, M., Soto, N., Sutherland, M., Burke, G. B., & Gasco, M. (2019). Applying an Enterprise Data Model in Government: Transitioning to a Data-Centric Information System for Child Welfare in the US. 20th Annual International Conference on Digital Government Research on - Dg.o 2019, 265–271. http://dl.acm.org/citation.cfm?doid=3325112.3325219
Hennink, M., & Kaiser, B. N. (2022). Sample sizes for saturation in qualitative research: A systematic review of empirical tests. Social Science and Medicine, 292, 114523. https://doi.org/10.1016/j.socscimed.2021.114523
Jackson, M. C. (2004). Systems Thinking – Creative Holism for Managers. John Wiley & Sons. https://doi.org/10.1108/k.2004.06733hae.001
Karkošková, S. (2022). Data Governance Model To Enhance Data Quality In Financial Institutions. Information Systems Management, 00(00), 1–21. https://doi.org/10.1080/10580530.2022.2042628
Krämer, M., Frese, S., & Kuijper, A. (2019). Implementing secure applications in smart city clouds using microservices. Future Generation Computer Systems, 99, 308–320. https://doi.org/10.1016/j.future.2019.04.042
Lin, Y. (2019). Government management model of non-profit organizations based on E-government. ACM International Conference Proceeding Series, 164–168. https://doi.org/10.1145/3348445.3348464
Marshall, B., Cardon, P., Poddar, A., & Fontenot, R. (2013). Does sample size matter in qualitative research?: A review of qualitative interviews in is research. Journal of Computer Information Systems, 54(1), 11–22. https://doi.org/10.1080/08874417.2013.11645667
Otto, B. (2011). Data governance. Business and Information Systems Engineering, 3(4), 241–244. https://doi.org/10.1007/s12599-011-0162-8
Paramita, A. S., Gaol, F. L., Ranti, B., & Supangkat, S. H. (2022). Microservices Architecture As a Data Governance Tools in Decentralized E-Government. 2022 International Conference on Science and Technology, ICOSTECH 2022. https://doi.org/10.1109/ICOSTECH54296.2022.9829098
Pinheiro, C., Vasconcelos, A., & Guerreiro, S. (2019). Microservice Architecture from Enterprise Architecture Management Perspective. Lecture Notes in Business Information Processing, 356, 236–245. https://doi.org/10.1007/978-3-030-24854-3_17
Prof. Dr. Frederik Ahlemann Prof. Dr. Reinhard Schütte, P. D. S. S. (2021). Innovation Through Information Systems. In Lecture Notes in Information Systems and Organisation: Vol. III. http://link.springer.com/book/10.1007/978-3-030-86800-0
Ramadhan, A., Arymurthy, A. M., Sensuse, D. I., & Muladno. (2021). Modeling e-Livestock Indonesia. Heliyon, 7(8), e07754. https://doi.org/10.1016/j.heliyon.2021.e07754
Ramadhan, A., Muladno, Sensuse, D. I., & Arymurthy, A. M. (2012). e-Livestock in Indonesia: Definition adjustment, expected benefits, and challenges. 2012 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2012 - Proceedings, 131–136.
Ramadhan, A., Sensuse, D. I., Muladno, & Arymurthy, A. M. (2013). Synthesizing success factors for e-government initiative. Research Journal of Applied Sciences, Engineering and Technology, 6(9), 1685–1702. https://doi.org/10.19026/rjaset.6.3891
Ramírez-Gutiérrez, A. G., Cardoso-Castro, P. P., & Tejeida-Padilla, R. (2021). A Methodological Proposal for the Complementarity of the SSM and the VSM for the Analysis of Viability in Organizations. Systemic Practice and Action Research, 34(3), 331–357. https://doi.org/10.1007/s11213-020-09536-7
Ruijer, E. (2021). Designing and implementing data collaboratives: A governance perspective. Government Information Quarterly, 38(4), 101612. https://doi.org/10.1016/j.giq.2021.101612
Setyawan, R., Nizar Hidayanto, A., Indra Sensuse, D., Suryono, R. R., & Kautsarina. (2022). Software Architecture Refactoring Based on Data Integration and Interoperability Issues in PeduliLindungi. Proceedings - 2022 2nd International Conference on Information Technology and Education, ICIT and E 2022, 221–226. https://doi.org/10.1109/ICITE54466.2022.9759897
Sunardi, Ramadhan, A., Abdurachman, E., Trisetyarso, A., & Zarlis, M. (2022). Acceptance of augmented reality in video conference based learning during COVID-19 pandemic in higher education. Bulletin of Electrical Engineering and Informatics, 11(6), 3598–3608. https://doi.org/10.11591/eei.v11i6.4035
Susha, I., Rukanova, B., Zuiderwijk, A., Gil-Garcia, J. R., & Gasco Hernandez, M. (2023). Achieving voluntary data sharing in cross sector partnerships: Three partnership models. Information and Organization, 33(1), 100448. https://doi.org/10.1016/j.infoandorg.2023.100448
Ulrich, W., & Reynolds, M. (2020). Critical Systems Heuristics: The Idea and Practice of Boundary Critique. In Systems Approaches to Making Change: A Practical Guide. https://doi.org/10.1007/978-1-4471-7472-1_6
Van Donge, W., Bharosa, N., & Janssen, M. F. W. H. A. (2020). Future government data strategies: Data-driven enterprise or data steward?: Exploring definitions and challenges for the government as data enterprise. ACM International Conference Proceeding Series, 196–204. https://doi.org/10.1145/3396956.3396975
Wheeler, F. P., & Checkland, P. (2000). Systems Thinking, Systems Practice: Includes a 30-Year Retrospective. The Journal of the Operational Research Society, 51(5), 647. https://doi.org/10.2307/254200
Yebenes, J., & Zorrilla, M. (2019). Towards a data governance framework for third generation platforms. Procedia Computer Science, 151, 614–621. https://doi.org/10.1016/j.procs.2019.04.082
Zhang, Q., Sun, X., & Zhang, M. (2022). Data Matters: A Strategic Action Framework for Data Governance. Information and Management, 59(4), 103642. https://doi.org/10.1016/j.im.2022.103642
Zhang, W., Gutierrez, O., & Mathieson, K. (2010). Information systems research in the nonprofit context: Challenges and opportunities. Communications of the Association for Information Systems, 27(1), 1–12. https://doi.org/10.17705/1cais.02701
Zorrilla, M., & Yebenes, J. (2022). A reference framework for the implementation of data governance systems for industry 4.0. Computer Standards & Interfaces, 81(October 2021), 103595. https://doi.org/10.1016/j.csi.2021.103595