Building a Community-Based FAIR Metadata Schema for Brazilian Agriculture and Livestock Trading Data

Filipi Miranda Soares*, Fernando Elias Corrêa, Luis Ferreira Pires, Luiz Olavo Bonino da Silva Santos, Debora Pignatari Drucker, Kelly Rosa Braghetto, Dilvan de Abreu Moreira, Alexandre Cláudio Botazzo Delbem, Roberto Fray da Silva, Celso Oviedo da Silva Lopes, Antonio Mauro Saraiva

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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Abstract

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.

Original languageEnglish
Title of host publicationSEMPDW 2022
Publication statusPublished - 2022
Event18th International Conference on Semantic Systems, SEMANTiCS 2022 - Vienna, Austria
Duration: 12 Sept 202215 Sept 2022
Conference number: 18

Publication series

NameCEUR workshop proceedings
PublisherRheinisch Westfälische Technische Hochschule
Volume3235
ISSN (Print)1613-0073

Conference

Conference18th International Conference on Semantic Systems, SEMANTiCS 2022
Abbreviated titleSEMANTiCS 2022
Country/TerritoryAustria
CityVienna
Period12/09/2215/09/22

Keywords

  • Agriculture
  • FAIR data principles
  • livestock
  • metadata
  • trading data

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