General Dataset Curation Guide (GDCG) 3.0
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Pietro Bartolini, Asma Jeitani, Enrico Bonaiuti, Valentina De Col, Valerio Graziano, Sara Jani. (31/7/2023). General Dataset Curation Guide (GDCG) 3. 0.
Data collection and organization is one of the main tasks during research activities. In fact, most of the project's results depend on the good management of data. However, “the long-term value of data can be affected, for better or worse, by how well those data are curated. Unfortunately, many valuable datasets are poorly curated, which contributes to errors, redundant effort, and obstacles to replication and use” (Ruggles, 2018). It is common to organize data in spreadsheets in a way which makes them easily understandable for the dataset author at that time, without following the machine-readable standards or considering any next research use. Unfortunately, not-curated data can quickly become unusable if nobody report all relevant information and stores it in a stable format. “Data curation activities enable data discovery and retrieval, maintain data quality, add value, and provide for re-use over time” (Munoz, 2017). The present guide is targeted at the members of the DM sub-team and all ICARDA scientists interested in improving their data quality. It will be important for anyone to have basic knowledge of this subject to be able, during research activities, to create well curated datasets, and to ensure data are as open as possible, always FAIR (Findable, Accessible, Interoperable, and Reusable) and managed responsibly in compliance with the OFDA Policy.
- Agricultural Research Knowledge 
De Col, Valentinahttps://orcid.org/0000-0003-0895-969X