Nowadays, knowledge management systems are confronted with a variety and unprecedented amount of data, resulting from big data sources. A new generation of knowledge management systems for exploring and exploiting big data becomes a major need for organizations. For this reason, the paper proposes a novel service-oriented architecture for big data-driven knowledge management systems. The purpose of this research is to support organizations to leverage their knowledge-based assets for improving decision-making and facilitating organizational learning. The proposed architecture is based on the principles of design science research, including a set of constructs, a model and a method. The design evaluation is presented based on the analytical evaluation method. By applying the architecture, an organization can manage and govern business and digital transformation, setting them apart from their competitors.
Tạp chí: Maintenance, Monitoring, Safety, Risk and Resilience of Bridges and Bridge Networks Proceedings of the 8th International Conference on Bridge Maintenance, Safety and Management, IABMAS 2016 (2016)
Tạp chí: the 6th International Conference on Recent Advances in Geotechnical Earthquake Engineering and Soil Dynamics, August 1-6, Greater Noida, India
Tạp chí: 32ème Conférence sur la Gestion de Données - Principes, Technologies et Applications (BDA 2016), Futuroscop - Poitiers - France, 15 au 18 Novembre, 2016
Tạp chí khoa học Trường Đại học Cần Thơ
Lầu 4, Nhà Điều Hành, Khu II, đường 3/2, P. Xuân Khánh, Q. Ninh Kiều, TP. Cần Thơ
Điện thoại: (0292) 3 872 157; Email: tapchidhct@ctu.edu.vn
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