Artigo 2020 LAS ANS Symposium - inglês (original) (raw)

One of the main goals of Knowledge Management is to make institutional knowledge, that is, all explicit and tacit knowledge of their collaborators, a dynamic asset, capable of leveraging the company's growth. In a research institution, data is one the many types of explicit knowledge, produced as a result of research projects, processes and other related activities, such as laboratory experiments, computer simulations, and so on. Manage this explicit knowledge form so that it can be a dynamic asset, a propeller of institution growth, is one of the main functions of Data Governance. In this work we present Data Governance as a effective tool of explicit knowledge management for two analytic techniques currently used in the Research Reactor Center -CERPq of the Nuclear and Energy Research Institute (IPEN), namely Instrumental Neutron Activation Analysis (INAA) and Atomic Absorption Spectroscopy (AAS). A methodology was adapted from the Data Governance literature for conventional companies, and, in order to identify essential research data that should be preserved under the scope of Data Governance, several researchers, experts on the subject, were interviewed, to select for each technique, a subset of all research data regarded as essential to warrant the reproducibility of the experiment, as well as a subset of these data essential to evaluate the quality of those experiments. Identifying these data sets and the underlying processes allowed us to identify key aspects of data management that must be observed on INAA and AAS techniques experiments. The methodology presented can be applied to other laboratories, helping the adoption and deployment of Data Governance as an important tool for Knowledge Management within a Nuclear Institution.