by Stefanie Neno | Sep 26, 2018 | Uncategorized
CIFOR started monitoring water levels and quality in the Sondu Basin of South-West Mau in 2014 using automatic sensors. These generated the first ever precise data set of water flow and water quality information, available continuously over two years. But now, locals...by Stefanie Neno | Sep 26, 2018 | Uncategorized
Intrigued by the unique relationship our food crops have to their geographical environment, Lorena Gonzalez dedicated her passion for geomatic technology to collect site-specific farm data that is revolutionizing the way researchers and farmers tackle hunger.by Stefanie Neno | Sep 26, 2018 | Uncategorized
As part of its worldwide AI for Earth program, Microsoft has recently announced grants to provide artificial intelligence (AI) technology to organizations engaged in solving environmental challenges. ICRISAT is one of the grantees and will now be able to use Microsoft...by Stefanie Neno | Sep 10, 2018 | Uncategorized
This App developed by ICRAF shows the distribution of indigenous tree species and information on the products and services that they can provide. It arms local community members, government agencies, private sector owners, and other land managers with the information...by Stefanie Neno | Sep 10, 2018 | Uncategorized
A new mapping procedure developed by scientists at ILRI uses Demographic Health Surveys (DHS) data to bring out spatial patterns of socio-economic factors among livestock herders and systems. The map creation procedure incorporates three innovations: how the DHS data...
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)