Critical Raw Materials (CRMs) require a deep understanding of their societal metabolism, for which robust data and information are needed. However, despite the efforts to build reliable data, some CRMs such as cobalt, are still characterised by lack of data harmonization, lack of connection between datasets, and significant data unavailability. Together with data gaps filling, data quality is a crucial aspect to improve Material Flow Analysis (MFA) and Criticality Assessment (CA). Nevertheless, most of the methodologies for Data Quality Assessment (DQA) are not designed for these tools, but for others, e.g. life cycle assessment. The current research addresses the following challenges; a better understanding of the societal metabolism of CRMs; the development and implementation of DQA in MFA and CA; and a better understanding of the available data related to current cobalt flows in the EU technosphere. The underlying life cycle phases of CRMs within the technosphere were identified, together with 15 key parameters. A new DQA matrix was developed, which was subsequently applied to the full dataset collected for cobalt. The dataset was built considering seven high-end applications of cobalt. More than 300 values were gathered, which were analysed in function of different aspects, such as the country/region, and year. Through the data analysis and the application of the DQA framework, data gaps were identified due to low availability and/or low quality. It was concluded that the main deficiency of cobalt data is its reliability, due to lack of information regarding its generation method, and the incomplete stakeholder coverage.