Building a community-based FAIR metadata schema for Brazilian agriculture and livestock trading data.
2022
SOARES, F. M. | CORRÊA, F. E. | PIRES, L. F. | SANTOS, L. O. B. da S. | DRUCKER, D. P. | BRAGHETTO, K. L. | MOREIRA, D. de A. | DELBEM, A. C. B. | SILVA, R. F. da | LOPES, C. O. da S. | SARAIVA, A. M.
anglais. Edition of the 18th International Conference on Semantic Systems, Vienna, Austria. SEMANTiCS 2022.
Afficher plus [+] Moins [-]anglais. In this paper, we discuss how we are using metadata schemas and controlled vocabularies to improve interoperability between Brazilian agriculture and livestock trading data providers. A new metadata schema is being created based on a community-based approach. This method relies on knowledge from specialists to define a list of relevant metadata properties for a given domain. In the first step of the research, we extracted metadata from three datasets maintained by three Brazilian public institutions: the Center for Advanced Studies in Applied Economics (Cepea), the Institute of Applied Economic Research (Ipea), and The National Supply Company (Conab). The extracted metadata were the input to the definition of a list of 15 potential metadata properties that specialists are validating.
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