880 members

CGIAR Consortium for Spatial Information (CGIAR-CSI) is the Platform’s geospatial science Community of Practice (CoP) that facilitates CGIAR’s research using geospatial data and analysis. CGIAR-CSI coordinates community-wide activities to bring CGIAR’s spatial scientists together through collaborative research, capacity building, communications, developing geospatial datasets and publications and convening of various events to share learning and represent CGIAR in the geospatial domain of expertise.

Building on capacity building activities initiated in the earlier years, this CoP continued to focus on the community-wide training and facilitation of using R for analyzing geospatial datasets. Two on-site training workshops were organized, and the materials were made public. Three technical sessions were organized during the 2019 Big Data Convention, attracting more than 250 attendees.

Through their mini-grant programs, the Geospatial CoP contributed — in collaboration with the University of Twente — on “A suite of global accessibility indicators,” which was published in the Nature journal Scientific Data.

The Geospatial CoP continued to play a key coordinating role in the identification, provision, and management of key geospatial shared services. A position paper about the community’s view on the role of geospatial big data for supporting agro-ecosystems was published as a book chapter. A new recipient for the 2019 mini-grant was decided to support the development of key climate projection data layers, and this will be completed in 2020.

Activities and products from the CoP were communicated through the community website, which was visited 140K times by 54K visitors in 2019.

1126 members

The Data-Driven Agronomy CoP works to collectively strengthen 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.

In 2019, this CoP developed and shared a variety of content with the wider global community, building capacity for knowledge transfer and to build novel connections and partnerships. The content included webinars, newsletters, papers, blogs and videos on and around topics such as agri-businesses in the developing world, artificial intelligence, and digital extension with particular focus on increasing understanding of the digital landscape of developing nations.

In early 2019, they shared a report and a video on key constraints agri-businesses have in the developing world and published a peer-reviewed paper, in collaboration with the Colombian government, on “A scalable scheme to implement data-driven agriculture for small-scale farmers”. It demonstrated how machine learning can help make farming more efficient and productive even amid climate uncertainty.

In collaboration with the World Bank, FAO, and the African Development Bank, the Community began work to create several Digital Agriculture Country Profiles (DAPs). The profiles aim to enable a better understanding of the digital agricultural landscape at a global level, painting a data-driven picture of what technologies are in use, the benefits they are providing and where the greatest digital needs exist. In 2019, profiles were completed on Turkey, Argentina, Grenada, Vietnam, Kenya, Rwanda, Ivory Coast and South-Africa, and are expected to be launched in 2020.

931 members

During 2019, the Crop Modeling CoP continued promoting capacity building activities related to identified needs within the community. In their webinar series, they covered useful platforms for crop modeling purposes such as GARDIAN and GEMS, strategies to bridge the gap between modelers and researchers regarding the data required for reliable simulations, and have helped the community answer pressing questions about the world’s most widely used crop modeling software (DSSAT). These webinars reached over 500 live participants, and the recordings have been viewed 1,500 times, collectively.

Two technical sessions were organized during the 2019 Big Data Convention, attracting more than 50 participants. A full-day writing workshop on digital extension within CGIAR was organized, in collaboration with the Data Driven Agronomy CoP, and attracted more than 20 experts to attend.

The Crop Modeling CoP continued to play an important coordinating role in identifying the gaps and needs in crop modeling activities within CGIAR. As a result of their mini-grant program, the Community awarded one project, done in collaboration with CIMMYT and the University of Florida, that works to identify the minimum data requirements researchers should collect in order to perform different crop modeling and other analytical activities.

The CoP participated in two peer-reviewed papers, one on “Different uncertainty distribution between high and low latitudes in modeling warming impacts on wheat,” which was published in Nature Food, and a second one on “Adapting irrigated and rainfed wheat to climate change in semi-arid environments: Management, breeding options and land use change”. Activities and products from the CoP were communicated through regular newsletters, and the CoP’s website.

885 members

The Socio-Economic Data CoP is dedicated to improving the landscape of livestock data by encouraging better use of existing data and analysis, and supporting collaboration on new and innovative data solutions.

In 2019, CoP grew to over 650 CGIAR and non-CGIAR members, attracting interest from disciplines in academia, business and government, all committed to improving data interoperability. The members convened during several virtual meetings throughout the year.

The CoP addressed the issue of data standardization and harmonization through the publication of the 100Q report to boost household survey data usability with 100 core questions. In a bid to improve gender awareness within agricultural research, the community collaborated with the CGIAR Platform for Gender Research to publish a report on the findability of gendered datasets. The CoP presented preliminary findings regarding an ontology-agnostic, flexible, extensible, machine-readable and human-intelligible metadata schema at several events.

During the 2019 Big Data in Agriculture Convention, the SED-CoP organized a workshop to build capacity on blockchain technologies to improve transparency in agriculture. It also published a report on the use of blockchain technology in agri-food systems focusing on the use case of biofortified maize.

In 2019, key representatives involved in research ethics across CGIAR formed an informal Community of Practice, aptly named: ´Informal group of CGIAR IRB folks’. The with close ties to the Community of practice on socio-economic data as the majority of ethics concerns in CGIAR research are related to human subjects research and the related data.

In 2019, LD4D authored the Livestock Fact Check journal paper, an exploration of the data behind popular livestock figures. The Livestock Fact Check project aims to help inform discussions about livestock production through a balanced examination of some commonly referenced livestock ‘facts.’ The project’s key findings are useful to anyone engaged in discussions about livestock and society.

The CoP formed a new working group, Livestock Ontologies. The group is open to anyone with an interest in exploring and building livestock vocabularies and ontologies with the aim to answer the question: “How do we present livestock and fish data in a consistent manner that enhances interoperability and re-use?” This is a collective effort aimed at cataloguing initiatives to develop standards and ontologies, map expertise and interests of community members, and share tools and best practices for ontologies, vocabularies, terminologies, thesauri, and similar tools and methods.

Additionally, the CoP engaged in monitoring, learning, and evaluation of livestock initiatives; a number of livestock development projects are developing key performance indicators for their activities with the aim of providing more clarity to the sector.

563 members

The Ontologies CoP made significant advancements in the development and adoption of quality ontologies for agrifood research data across CGIAR Research Programs, allied research organizations and private partners. Through dedicated Working Groups (WG), significant progress was made in the development of the agrifood ontology framework:

• As of 2019, Crop Ontology (CO) comprised 4,125 traits and 5,556 variables for 29 plant species to describe plant phenotypes in databases, and, with support of Planteome, a US National Science Foundation project, enables comparative genotypic and phenotypic studies as well as gene-discovery experiments. CO counts the University of British Columbia, Cornell University, PEPSICO Inc and the NIAB, a UK research organization,  as new contributors.
• Agronomy Ontology (AgrO), which compiles field management practices, was extended to address the feedback of users like Rothamsted Research and the University of Florida.
• The draft version of the Socio Economy Ontology (SEOnt) was developed with scientists from the Socio Economic CoP using the ‘100Q’ and through Machine Learning techniques with the University of Sheffield, UK.
• The  Fish Ontology WG, in collaboration with Worldfish, and the Livestock Ontology WG led by the Livestock Data for Decisions CoP were created.

The CoP stimulated knowledge sharing and capacity building through webinars, blog articles and members contributed to a peer-reviewed paper. Webinars explored ontology selection criteria for data annotation, the use of ontologies in machine learning techniques, as well as  knowledge graphs, and reached approximately 1400 viewers. Blog articles were published on the Crop Ontology, the GEMS platform and the Breeding API.