Monitoring, Evaluation and Learning (MEL) is multi-center and multi-CRP online platform for integrated management, monitoring, and reporting of projects, from planning to budgeting, risks’ assessment, knowledge sharing and more. MEL creates synergy between research and development partners, bridging competences in a results-oriented platform. MEL allows to save resources and time, reducing paperwork, facilitating administrative steps, quickening project related communications and enabling near real-time data collecting to inform decision-making.

MEL holds a flexible structure that can be tuned with impact pathways and results frameworks used by CGIAR and donors. Its modular structure allows the implementer to customize the platform and re-shape it to meet their specific needs.

The platform comes with an integrated Open Access repository that boosts the projects outreach. Carved in the system is the Knowledge Sharing tool-set, which includes an internal discussion forum, a technical assistance chat, project dedicated web-pages, and a communication-friendly module to write and disseminate project related blog stories.

MEL safeguards intellectual property and provides full credit to the authors of knowledge reported, making use of international metadata standards such as Dublin Core. The platform has been aligned with HR management, internal finance and internal sharing systems (e.g. One Corporate System – OCS, SharePoint).

MEL is the result of the synergic efforts by CGIAR Research Program on Grain Legumes and Dryland Cereals (GLDC), CGIAR Research Program on Roots, Tubers and Bananas (RTB), CGIAR Research Program on Fish Agri-food Systems (FISH), The International Center for Agricultural Research in the Dry Areas (ICARDA), The International Potato Center (CIP), The World Agroforestry Center (ICRAF), The International Institute of Tropical Agriculture (IITA), ICARDA Geoinformatics Unit (GU), and is powered by iMMAP, Codeobia, D-Space and Amazon Web Services.

The Global Geo-informatics Context and Options (GeCO) is a new web-based GIS tool that enables its users to define, monitor, assess and co-create knowledge and learning on relevant Sustainable Land Management (SLM) options that match the social-ecological context at global, regional and national scales.

The GeOC tool aims to support the implementation of SLM practices by the local international communities by providing them with context-specific information that is required to make sound investment decisions for agricultural and rural development.

The GeOC is designed to provide land users, development projects or programs, and policy decision-makers with plausible, robust extrapolation domains for guiding decisions on the selection and use of SLM options, and an open platform for docking different disciplinary projects into integrative/holistic and converging actions for promoting SLM at scale.

GeOC is the result of the synergic efforts by CGIAR Research Program on Dryland Systems (CRP-DS), the International Center for Agricultural Research in the Dry Areas (ICARDA) and its Geoinformatics Unit (GU), and is powered by iMMAP, Codeobia, D-Space and Amazon Web Services.

ICARDA INTERNATIONAL NURSERIES

ICARDA has the global mandate for barley, lentil and faba bean and a regional mandate for chickpea, durum and bread wheat improvement within the Consultative Group of International Agricultural Research (CGIAR). ICARDA’s commodity improvement programs develop nurseries for a wide range of agricultural systems and distributes them worldwide upon request. All nurseries are developed, prepared and dispatched from the ICARDA’s Headquarters in Lebanon, except winter barley and wheat from ICARDA, Turkey.

The international nursery trialing system is an integral part of the commodity improvement programs of ICARDA and NARIs partners. It provides the cooperators with the opportunity to evaluate the genetically diverse germplasms generated through conventional and modern breading methodologies under their own agro-ecological conditions and socio-economic contexts. For this process to succeed, effective data collection and timely sharing is crucial.

The Monitoring, Evaluation and Learning Quality Assurance Processor (M-QAP) is a publications metadata extractor from Web of Science (https://clarivate.com/webofsciencegroup/solutions/xml-and-apis/), Scopus (https://dev.elsevier.com/) and unpaywall (https://unpaywall.org/). It was created to support the reporting of CGIAR institutions to its dashboard (https://www.cgiar.org/impact/results-dashboard/) and ensure that publications with a DOI are screened against the above mentioned sources. Additionally the tool matches institution names with CGIAR lists (https://clarisa.cgiar.org). CGIAR Users can submit a list of DOIs with own reference ID to export verified data. M-QAP provides a facility to submit a request for new institutions to be added to CLARISA List.

Institutions pairing is done as 100% text matching or allowing the user to confirm the pairing when the similarity test is less than 100%. The tool has also an AI feature to pair institutions based on previous matching. The AI will only pair when institutions are manually matched multiple times however the user should always confirm the AI matching when reaching 100% since the tool is in pilot phase.

It began as a proof of concept designed by the Monitoring, Evaluation and Learning (https://mel.cgiar.org/) team at the International Center for Agricultural Research in the Dry Areas (http://icarda.org/) with the financial support of the System Management Office (https://www.cgiar.org/how-we-work/governance/system-organization/system-management-office/). It has been developed by CodeObia (https://codeobia.com/). The code is available at: https://github.com/icarda-git/M-QAP.

Submission into interface will retrieve metadata according to standard SMO structure to feed https://www.cgiar.org/impact/results-dashboard/.