Our Communities of Practice
As problems in society have become more complex and the nature of solutions more independent, extension systems have increased pressure to work across traditional expertise, as well as geographic and institutional boundaries to leverage maximum impact from resources. In response to this pressure, networks and communities need to emerge as the basis for solving problems rather than single institutions.
The Platform’s communities of practice (CoP’s), which are part of the Platform’s Module 2: Convene, aim to leverage technology and new data resources to create broader and deeper impact in programming, as well as to build capacity internally and externally on big data approaches in agriculture.
The Platform established these Communities of Practice (CoPs) across Centers to work towards defining data standards and interoperability protocols, dovetailed with the Open Access and Open Data initiatives of the System Management Office.
They foster collaboration spaces and opportunities, facilitate connectivity and sharing of methodologies, and support the organization of capacity-building workshops.
A community aimed at collectively strengthening the innovation of technology and big data to tackle an array of agricultural challenges – including the closing of yield gaps – to reduce hunger and poverty and transform global agriculture.
A community that encompasses a wide range of quantitative applications, based around the broad concept of parametrizing interactions within and among the main drivers of cropping system.
A community that facilitates CGIAR’s research using geospatial data and analysis, undertaking activities to bring spatial scientists together through a series of coordinated communications and activities.
A community that brings together livestock and data modellers with project implementers and decision makers from industry, the public sector and NGOs o drive informed livestock decision-making through the better use of existing data and analyses.
A community that focuses on the use and application of semantics for data harmonization at the levels of collection and storage, and for data interoperability and data discovery following the FAIR principles.
News from our communities
Interested in joining our community of practice?
Sign up to our mailing list for community news and updates.