Webinar – Target Population of Environments (TPE) & beyond: Helping make better crop improvement practice
Webinar organized by the Crop Modeling Community of Practice of the CGIAR Platform for Big Data in Agriculture.
by Hannah Craig | Jun 30, 2020 | Communities of Practice, Crop Modeling CoP, Webinar
Webinar organized by the Crop Modeling Community of Practice of the CGIAR Platform for Big Data in Agriculture.
by Hannah Craig | Feb 25, 2020 | Communities of Practice, News, Ontology CoP, Webinar
Webinar organized by the Ontologies Community of Practice of the CGIAR Platform for Big Data in Agriculture.
by Hannah Craig | Feb 25, 2020 | Communities of Practice, Ontology CoP
In this new webinar series, “All about our products and their uses,” the Ontologies Community of Practice presents and explores the use of current ontology products developed by the members of the CoP.
by Hannah Craig | Jan 27, 2020 | Communities of Practice, News, Ontology CoP
The Ontologies Community of Practice is engaged in the development of ontologies for agricultural research. In a series of blog posts, we’ll take a look at ongoing ontologies projects and developments.
by CGIAR-CSI | May 23, 2019 | Geospatial CoP
Matthew Reynolds and Zhonghu He from CIMMYT co-authored a paper, A rapid monitoring of NDVI across the wheat growth cycle for grain yield prediction using a multi-spectral unmanned aerial vehicle (UAV) platform, investigating the potential of using UAV-based NDVI measurement in the phenotyping of wheat varieties in the breeding program.
CGIAR Platform for Big Data in Agriculture advocates open data for agricultural research for development. It considers that opening up research data for scrutiny and reuse confers significant benefits to society.
However, the Platform appreciates that not all research data can be open and that a broad range of legitimate circumstances may require data to be restricted.
As an integral component of its advocacy for open data, the Platform promotes responsible data management through the entire research data lifecycle from planning, collecting, storing, disclosing or publishing, transferring, discovery and archiving.
These guidelines were created from information collected from: review on best and emerging practices across various sectors in the fast changing landscape of privacy and ethics (130 external resources); privacy and ethic materials sourced from seven CGIAR centers; first draft was circulated for input and feedback across CGIAR and incorporated into this edition. It’s important to note that this is an evolving document, the next stage is to consult externally for further input.
These Guidelines are intended to assist agricultural researchers handle privacy and personally identifiable information (PII) in the research project data lifecycle.
Ensure compatibility with the DMP-PII (as above) and also the purpose for which prior informed consent has been obtained
Ensure PII is stored securely to protect privacy, through organizational or project specific safeguards to prevent unauthorized access, accidental disclosure or breach of data (physical & technical)
Don’t store data in unsecured locations or on unsecured devices or servers
Don’t store encrypted data and encryption keys in locations where they can be easily accessed simultaneously
Don’t underestimate the importance and value of administrative safeguards to standardize practices (i.e. organizational policies, procedures and maintenance of security measures that are designed to protect private information, data and access)