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WorldCist'17 - 5th World Conference on Information Systems and Technologies

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A Knowledge Management and Engineering Approach to Capture Organizational Learning Networks

Effective knowledge management practices in organizations are focused on knowledge creation and knowledge transfer activities, and this is why intelligence and competencies matters at the organizational workplace, and drive the workplaces more intelligent, productive, and innovative. For most knowledge intensive organizations is fundamental the continuous availability and development of domain expertise. This paper describes an ongoing research project to develop an organizational knowledge architecture that is being specified and developed to support collaboration tasks as well as design and model predictive data analysis and insights for organizational development. The primary goal of this research is to create an architecture suitable for use, initially, in intranet (corporate portal) collaborative procedures, but also scalable for later use in more generic forms of ontology-driven knowledge management systems. The designed architecture and functionalities aim to create coherent web data layers for intranet learning and predictive analysis, defining the vocabulary and semantics for knowledge sharing and reuse projects. This research argues that effective knowledge management are based on the dynamic nature of the organizational knowledge, and predictive data analysis and insights identification can transform and add value to an organization. This paper presents a knowledge management and engineering perspective (ontology based) for the application of predictive analysis and insights at the organizational (corporate) workplace towards the development of the organizational learning network.


Alexandre Barão    
Universidade Atlântica

José Braga Vasconcelos    
Universidade Atlântica

Álvaro Rocha    
Universidade de Coimbra


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