FAIR Diagnostic assessment model as an instrument for analyzing scientific information sources

Abstract

This article proposes a diagnostic evaluation model based on the Findable, Accessible, Interoperable, Reusable principles to assess information sources on the internet, focusing on the qualification of collections in open and aggregated digital libraries. The applied research adopts a qualitative-quantitative, exploratory, and descriptive approach, analyzing scientific journals in the field of Museology. The model is based on six analytical dimensions: (i) Data Standards, (ii) Indexing from Metadata, (iii) Usage License, (iv) Infrastructure and Access Protocols, (v) Documentation and Provenance, and (vi) Integration and Connectivity. Adherence to the principles was measured using a formula that evaluates the criteria within these dimensions, using a scoring scale from 0 to 3. The results reveal that 20% of the analyzed journals achieved maximum adherence. It was highlighted that the adoption of simple procedures, such as the use of persistent identifiers, could significantly increase the conformity of the remaining journals. Furthermore, journals that use standards such as Dublin Core and interoperable protocols showed better indexing and accessibility. The study concludes that the proposed model is an efficient tool for evaluating the quality of information sources and supporting the selection, extraction, and organization of collections in digital libraries. The findings offer support for managers and researchers in the areas of Open Science, Digital Humanities, and Information Science, assisting in decision-making and the implementation of best practices for improving the interoperability and reuse of scientific data on the Web.