The Research Data Alliance Interest Group for Agricultural Data (IGAD) developed this innovative initiative with the objective to help to create an ongoing dialogue and encourage the exchange of experiences on agricultural research and innovation within the IGAD community and beyond. The webinar series took place from 16 June 2021 to 27 October 2021.

16 June 2021 - "Aligning AGROVOC and Ontologies to connect semantics to improve Agrifood data annotation and interoperability"

Presented by: Pier Luigi Buttigieg, Helmholtz Metadata Collaboration/GEOMAR Helmholtz Centre for Ocean Research

Throughout the webinar, Pier Luigi Buttigie answers the question of whether it would be a good idea to semantically connect AGROVOC, the FAO agricultural multilingual thesaurus, with complementary ontologies.

“Is it worth it?” Pier Luigi said, “Yes, it is worth it, because thesauri and ontologies do different things, they have different jobs.”

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30 June 2021 - "Agricultural market dynamics based on data evidence"

Presented by: Luiza Petrosyan from the Universitat Politécnica de Valencia

Throughout the webinar, Luiza Petrosyan presents her research on the evolution of agricultural products and their commercial supply through existing data. Participants were also introduced to a systematic protocol for downloading data from several sources that generates a sufficient mass of information and automatically establishes analysis parameters.

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14 July 2021 - "Introduction to the Georgian Farmers' Association"

Presented by: Ketevan Gogotchuri from the Georgian Farmers’ Association (GFA)

The Georgian Farmers’ Association (GFA) was founded in 2012. Currently, the organization unites over 4,500 farmers in Georgia. During this webinar, Ketevan Gogotchuri introduces how GFA establishes its value to members by giving guidance on governmental programs; links to service providers and sources of funding, markets and technical support; provides consultation on policy issues and represents members’ interests; participates in policy making; and advocates fair access to markets and resources. Even more, she presents the current analysis and studies of the Analytical and Research Department in the agricultural field.

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8 September 2021 - "Supporting Open Data in agriculture with F1000Research"

Presented by: Guillaume Wright from F1000Research

F1000Research is an open research publishing platform with a mission to allow authors to publish fast, openly and without restrictions, while incorporating unique post-publication transparent peer reviews and open data as core principles for publication.

During this webinar, Guillaume introduces the innovative publishing model behind F1000Research and provided guidance and resources for authors on meeting F1000Research’s criteria for ensuring open data; and how their publishing model aligns with the FAIR data principles. He also introduced the Agriculture, Food and Nutrition Gateway; a dedicated space on F1000Research supporting Rapid and transparent dissemination of research, shaping key challenges in all areas of agriculture, food, and nutrition.

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22 September 2021 - "Data innovation and semantics are crucial to the future of animal health"

Presented by: Georgina Cherry, from the Veterinary Health Innovation Engine (vHive) team at the University of Surrey

The Veterinary Health Innovation Engine (vHive), a research centre dedicated to the development and adoption of new digital technologies, in collaboration with Zoetis, ATC and University of Exeter, have built a customized digital platform called The Data Innovation Hub for Animal Health (DIHAH). DIHAH is a unique, global repository for different data drawn from all sectors in animal health that will facilitate mutual data and knowledge sharing between industry partners in a secure environment.

During this webinar, Georgina introduces the DIHAH user community, more about the innovative platform, including its catalogue of open datasets and other data that can be used for research purposes under licence. Furthermore, the webinar explains how DIHAH is intended as a comprehensive “one-stop shop” for data in the sector. Data gathering is an ongoing process and the datasets added to the catalogue are being used to create a prototype livestock taxonomy to aid dataset discoverability on the platform.

Also, as an extension to this, how vHive is collaborating with Livestock Data for Decisions (LD4D) and the Global Burden of Animal Diseases (GBADs) to validate automated content tagging tools created by the Bayes Centre at the University of Edinburgh and to build a livestock taxonomy to submit to FAO's AGROVOC, the largest Linked open data set about agriculture available for public use.

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6 October 2021 - "Developing an information system to support agrobiodiversity conservation in Mexico"

Presented by: Dr. Alicia Mastretta Yanes and Irene Ramos, from the National Commission for the Knowledge and Use of Biodiversity (CONABIO)

CONABIO is a governmental agency which coordinates biodiversity data collection and analysis in support of the sustainable management of natural resources in Mexico. Agrobiodiversity Information System (SIAgroBD) is a comprehensive project that is part of the Mexican Agrobiodiversity GEF project, together with FAO. SIAgroBD’s objective is to produce and systematize data in order to generate knowledge that enables the conservation of traditional agricultural practices and native crops which have a large global importance.

SIAgroBD is in a late development stage, and is currently testing with users the publication of the first datasets. During this webinar, Dr. Alicia Mastretta Yanes and Irene Ramos discuss lessons learned while integrating pre-existing datasets on nutritional information, qualitative and quantitative agronomic data, and qualitative assessments of local use of agrobiodiversity. They also discuss how they are implementing a workflow that facilitates FAIRness across the data lifecycle, from collection to publication. This includes the adoption of field data collection tools, vocabulary standards, reproducible methods for data cleaning, open data training for participants, and the development of a custom data integration platform.

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20 October 2021 - "Growing Digital Agriculture from the Grassroots: designing just and sustainable agricultural data applications"

Presented by: Sarah-Louise Ruder, Dr. Hannah Wittman, and Kevin Cussen, from University of British Columbia (UBC) Farm

During this webinar, Sarah-Louise Ruder, Dr. Hannah Wittman, and Kevin Cussen present LiteFarm, a living case study for a tool that leverages digital technology for social and ecological justice. LiteFarm is a free, open-access, and open-source web-based application developed through farmer-led consultation by the (UBC) Farm, as well as through community-based research with farmers across North and South America.

As a community-driven, free and open-source application reporting on social, financial, and ecological indicators, LiteFarm is unlike other digital farming tools. It equips farmers with the data and tools to make informed decisions about the health of their farm, their livelihood, their community, and the planet. Though still in early development, hundreds of farmers on six continents have adopted the platform to run their farms.

Even further, the presenters will facilitate a conversation on data governance, justice, and transitions to more just and sustainable food systems with questions including:

1. In the age of big data and the Fourth Industrial Revolution, what governance and economic models support food & data sovereignty?
2. What are data commons? Who gets to define and enact data commons? Who is involved? Who can share what and with whom?
3. What governance and economic models could secure the longevity of non-profit innovations like LiteFarm, without charging for access or monetizing farmer data without their informed consent?

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27 October 2021 - "Analysis of time series of Sentinel 1 and Sentinel 2 data – the new quality of information for Agriculture"

Presented by: Karel Charvat, from Plan4all

Satellite Crop Detection technologies are focused on detection of different types of crops on the field in the early stage before harvesting. Their classification is one of the key themes of the common agricultural policy within the initiatives of the European Commission. Currently, data obtained from Remote Sensing (RS) are used to solve tasks related to the identification of the type of agricultural crops and modern technologies in the issue of post processing  this kind of data sources.

During this webinar, Karel Charvat discusses the importance of the common classification methods for crops including:

1. 1. Supervised classification, which is the technique most often used for the quantitative analysis of remote sensing image data. At its core is the concept of segmenting the spectral domain into regions that can be associated with the ground cover classes of interest to a particular application. In supervised classification the user or image analyst “supervises” the pixel classification process. The user specifies the various pixel values or spectral signatures that should be associated with each class.
2.  2. Image segmentation, which is defining object fields directly, can be considered as a more advanced method. Till now the method is working with Sentinel 2 and most of the solutions are working with data from one period.

Watch the full webinar here: