Knowledge Governance for building and sharing public Covid-19 global knowledge
Knowledge about the various aspects of the Covid19 must be public so that their sharing should be facilitated and accelerated. Knowledge creation and knowledge transfer need a collaboration work in order to translate into action and promptly inform decision-makers.
The role of evidence is crucial for taking wise decision on coronavirus challenge, by diverse stakeholders (Moresi e Pinho, 2020). Several communities (scientific, political, social and economic) need relevant data and information to build knowledge on several fronts: a) search for vaccine and treatment; b) to avoid infection and manage the spread Covid19 disease; c) to manage the impact on work, on education, on travel, on trade, on economic and social conditions; d) on government response to Covid19; e) to manage fake news, among other challenges.
Ackoff offers some definitions of data, information, knowledge and wisdom, and their associated transformation processes: Data are defined as symbols that represent properties of objects, events and their environment. They are the products of observation. But are of no use until they are in a useable form. The difference between data and information is functional, not structural; Information is contained in descriptions, answers to questions that begin with such words as who, what, when and how many; Information systems generate, store, retrieve and process data. Information is inferred from data; Knowledge is know-how, and is what makes possible the transformation of information into instructions. Knowledge can be obtained either by transmission from another who has it, by instruction, or by extracting it from experience; Wisdom is the ability to increase effectiveness. Wisdom adds value, which requires the mental function that we call judgment. The ethical and aesthetic values that this implies are inherent to the actor and are unique and personal (Ackoff, 1989). These concepts can be considered in a hierarchical view, articulating the different levels (Rowley, 2007) as in figure 1.
Figure 1- The Data, Information, Knowledge, Wisdom hierarchy
Knowing how to select the relevant information in a sea of excess information can help to navigate in the cov19 era. Identify what is the level that the information is located and the context the stakeholders belongs is crucial to organize data and information. Taking a knowledge governance (Pinho et al., 2019a; Pinho et al., 2019b) can be a useful approach to deal with the complexity of integrate diverse sources of information and knowledge, along network, macro, meso and micro levels. Those diverse levels are the social spaces where the interaction of several consumers and providers of information happens. This conceptual model can be useful to map global and local knowledge (see Figure2). Knowledge governance refers to choosing the structures and mechanisms that can influence the processes of knowledge looking the interrelation between network, macro, meso and micro levels, with a strategic focus (Foss, 2009; Foss, 2007; Pinho e Pinho, 2016). At each level and between levels the growing trend is to work in a network and to use and create knowledge through the evidence available in databases and vast knowledge networks (Leite et al., 2014; Leite et al., 2018).
Figure 2- Knowledge Governance Levels of Analysis
Source: Pinho et al. (2019a)
Additionally efforts to provide updated information are being made worldwide.Some relevant sources on Covid-19 can be examples of quality information, such as:
Some supranational institutions collect and organize information (data and texts) about COVID_19, and share it, like OECD (https://www.oecd.org/coronavirus/en/).
A Portal brings together the activities promoted within OpenAire and the European Commission to support researchers in the field of research development on COVID-19 (https://www.openaire.eu/openaire-activities-for-covid-19).
World Health Organization update research activities and others health issues (https://www.who.int/blueprint/priority-diseases/key-action/novel-coronav...).
European Centre for Disease Prevention and Control is also a good example (https://www.ecdc.europa.eu/en/covid-19-pandemic)
So, there are a lot of information but we need critical thinking to build relevant knowledge and wisdom to use them to take action for the welfare of all humanity.
Ackoff, R. L. (1989). From data to wisdom. Journal of applied systems analysis, 16(1), 3-9.
Foss, N. (2009). Alternative research strategies in the knowledge movement: From macro bias to micro-foundations and multi-level explanation. Eur Manage Rev, 6(1), 16-28.
Foss, N. J. (2007). The Emerging Knowledge Governance Approach: Challenges and Characteristics. Organization, 14(1), 29-52.
Leite, D., Caregnato, C. E., Lima, E. G. d. S., Pinho, I., Miorando, B. S. e Bier da Silveira, P. (2014). Avaliação de redes de pesquisa e colaboração. Avaliação: Revista da Avaliação da Educação Superior, 19(1), 291-312.
Leite, D., Pinho, I., Caregnato, C. E. e Miorando, B. S. (2018). Methodological Tracks to Study Research Collaboration Networks in higher Education. In J. Huisman & M. Tight (Eds.), Theory and Method in Higher Education Research (Vol. 4, pp. 125-143). United Kingdom: Emerald.
Moresi, E. A. D. e Pinho, I. (2020). Coronavírus: explorando o tema através da bibliometria. Ciaiq2020-9º CONGRESSO IBERO-AMERICANO EM INVESTIGAÇÃO QUALITATIVA, Corunha, Espanha.
Pinho, I., Costa, A. P. e Pinho, C. (2019a). What is Knowledge Governance? IFKAD-International Forum on Knowledge Asset Dynamics, Matera, Italy.
Pinho, I. e Pinho, C. (2016). Aligning Knowledge Management with Research Knowledge Governance. In J. T. Martins & A. Molnar (Eds.), Handbook of Research on Innovations in Information Retrieval, Analysis, and Management (pp. 489-504). Pennsylvania: IGI Global.
Pinho, I., Pinho, C. e Costa, A. P. (2019b). Knowledge Governance: Building a Conceptual Framework. Fronteiras: Journal of Social, Technological and Environmental Science 8(1), 72-92.
Rowley, J. (2007). The wisdom hierarchy: representations of the DIKW hierarchy. Journal of Information Science, 33(2), 163-180.