Research Knowledge production is the result from knowledge processes that happen at diverse networks spaces. Those spaces are supported by a cascade of systems (Data Management Systems, Information Management Systems, Knowledge Management Systems, Evaluation Systems and Monitoring Systems) that must be aligned to avoid formation of silos and barriers to the flows of information and knowledge. The energy that powers consists of the people and their connections; so there is crucial to understand and govern formal and informal networks. By take a holistic approach, we propose to join benefits of an efficient knowledge management with the implementation of knowledge governance mechanisms in order to improve Research Knowledge production and its impacts.
Top1. Introduction
Research knowledge production and knowledge use in the context of research-oriented Higher Education Institutions can be improved. Research and knowledge production deals with great complexity. It is therefore necessary to align knowledge management and research knowledge governance to enlarge and enhance capabilities by connecting multiple research networks and knowledge networks.
Although universities are knowledge intensive environments, there seems to be a lack of alignment between organizational knowledge management and the governance of scientific knowledge at institutional, national and supranational levels.
Knowledge creation is the result of collaborations across institutional and organizational boundaries. The facilitation of access to distributed knowledge and the establishment of networks spaces are tasks that appeal to new forms of management and governance. By taking a holistic approach, we can understand such networking spaces of knowledge co-creation and identify potential benefits of aligning knowledge management and research knowledge governance.
At all levels of governance, it is crucial that institutions, agencies and organizations seek out for solutions to value knowledge, through adequate data, information and knowledge management.
Our starting point is the fact that the production of knowledge is a social process that must be managed. Adopting this knowledge–based perspective, we build a conceptual model that structures this chapter and that can serve as a content navigation guide (Figure 1).
By taking this approach we have chosen three key concepts that are interconnected, namely: knowledge, networks and management.
Knowledge is the main resource (input) and the most value product (output) of research processes. Networks are the context, virtual spaces and shared mental spaces that give energy to those research processes. Management should focus on this resource and also in the environment on which those processes develop.
Research networks are special spaces where tacit knowledge - existing within individuals’ heads - can be shared and increased via interpersonal interaction and social relationships. Thus, beyond information technology to support digital capture, storage, retrieval and distribution of an organization’s documented, it is necessary to cultivate knowledge management practices that look at hard and soft factors pertaining to knowledge processes (Pinho et al., 2012). This kind of knowledge management can be perceived as a service that can improve scientific knowledge production and also can add value to this new knowledge.
In order to deal with the complexity of knowledge production at micro, meso and macro levels, we can integrate the knowledge management definition advanced by Carla O'Dell & Jackson Grayson (1998, p.6) - “the conscious strategy of getting the right knowledge to the right people at the right time and helping people share and put information into action in ways that strive to improve organizational performance” – with a knowledge governance approach. Finally, we argue that there should be an alignment between knowledge management and the research knowledge governance, in order to match common efforts to achieve the scientific objectives and desired societal impacts.
In terms of its organization the chapter begins with structural concepts and later focuses on research networks. From those multifaceted theoretical bases we propose a reflection on research knowledge governance.