The WorldFAIR project, led by CODATA, the Committee on Data of the International Science Council (ISC), and partnered with Research Data Alliance(RDA), and others, focuses on advancing the FAIR principles across 11 disciplinary and cross-disciplinary case studies. It aims to enhance the interoperability and reusability of digital research objects, emphasizing the creation of interoperability frameworks for each case study and research domain.
This initiative seeks to provide recommendations, interoperability frameworks, and guidelines for assessing FAIR data. With CODATA and RDA leading the effort, the project collaborates with several authoritative international bodies and institutions with global reach, ensuring broad implementation and impactful outcomes.
Starting in June 2022, the project concentrates on case studies spanning various scientific fields and cultural heritage sectors. By tailoring FAIR Implementation Profiles to each discipline, it aims to develop comprehensive insights into best practices and emerging solutions for FAIR data within these domains.
This guide outlines projects, tools, and best practices for managing plant-pollinator interactions data, intending to create guidelines aligned with FAIR principles. Examining methods and platforms used for data sharing, it identifies opportunities for enhancing data mobilization and improving current practices. This work aims to enhance data interoperability for plant-pollinator interactions, aligning with broader efforts to develop a Cross-Domain Interoperability Framework in the WorldFAIR project.
We welcome and recognize all contributions.
- Debora Pignatari Drucker, Embrapa Agricultura Digital, Brazil
- Filipi Miranda Soares, Universidade de São Paulo, Brazil
- Jeff Ollerton, University of Northampton (UK) and Kunming Institute of Botany (China)
- Jorrit H. Poelen, Global Biotic Interactions, United States
- José Augusto Salim, University of Campinas, Brazil
- Rocío A. González-Vaquero, Facultad de Agronomía, Universidad de Buenos Aires, Argentina
This guide is created using the excellent open source Jupyter Book project and the executablebooks/cookiecutter-jupyter-book template.