Agroclim: FAIR Workflows for the Crop Wild Relatives Digital Twin
Providing a FAIR-enabled digital twin for crop wild relatives, the project empowers researchers to identify resilient plant traits, addressing climate challenges and advancing sustainable agriculture.
In a nutshell
- Climate change disrupts global agriculture, threatening food security and requiring innovative solutions to improve crop resilience.
- The Biodiversity Digital Twin leverages FAIR workflows, earth observations, and genetic data to map habitats for resilient crop wild relatives.
- This system supports sustainable agriculture by enabling targeted use of resilient crops, fostering food security, and advancing the SDG “Zero Hunger” goal.
Technical Overview
Challenge
Human-induced global heating is imposing an increasing threat on global agriculture through extreme weather events, changing pest dynamics, and soil degradation. These challenges negatively affect crop yields and threaten food security, thus hindering the United Nations Sustainable Development Goal (SDG) to end hunger, achieve food security, improve nutrition, and promote sustainable agriculture.
Underutilized crops and crop wild relatives (CWR) offer a promising approach to mitigate such impacts of climate change, as their greater genetic diversity and resilience make them better suited to face these emerging challenges compared to traditional crops. However, identifying populations of CWRs with desirable traits is challenging and requires integration of data from diverse sources such as earth observation, biodiversity monitoring and gene/seed banks.
DestinE Solution
In the context of the Biodiversity Digital Twin project (biodt.eu), we are developing a digital twin for crop genetic resource modeling. This digital twin combines known species occurrences from the Global Biodiversity Information Facility (GBIF.org) with climate data from earth observations (ERA5/ERA5-Land) for advanced species distribution modeling. It generates habitat suitability maps which can be used to identify areas where populations of CWRs with interesting genotypes might be found.
Figure 1: Predicted habitat suitability map of Lathyrus latifolius (everlasting pea) generated by the CWR digital twin.
The Crop Wild Relative Prototype Digital Twin is incorporated into the Destination Earth platform, leveraging the resources of the Destination Earth Data Lake (DEDL). Through a workflow platform deployed to DEDL ISLET, researchers gain access to a user interface that allows exploration of existing CWR datasets and submission of custom workflows. These workflows are executed via the Argo workflow engine (similar to DEDL Hooks) and can access data from the Harmonized Data Access (HDA) API or from external repositories.
By using FAIR Digital Objects (FDOs) as fundamental data model, the project standardizes workflow execution in a FAIR (Findable, Accessible, Interoperable, and Reusable) manner: Workflows can be submitted as Workflow Run RO-Crates (ROCs), which describe an executable workflow in a machine-actionable way. After execution, data produced by the digital twin—along with provenance information—are stored as FAIR Digital Objects in a digital object repository based on CNRI’s Cordra middleware backed by the DEDL ISLET Storage Service. Outputs are provided in both human- and machine-interpretable format, i.e. as resubmittable RO-Crates which allow reusability of research data and workflows across data spaces. Additionally, by employing FAIR Signposting throughout our platform, a layer of machine-interpretable links is added to present the web topology of involved resources and computed results. This enables the mobilization of resources across other Common European Data Spaces and enhances discoverability and interoperability across a broader scientific community.
Figure 2: Architecture and data flow for the data space integration platform for crop wild relatives using FAIR workflows.
Impact
The project advances the potential to adopt global food production to emerging challenges posed by climate change. By making data from the Crop Wild Relatives Digital Twin accessible in a FAIR manner, our platform enables researchers and plant breeders to map habitats where CWR populations with desirable traits are likely to be found. This facilitates the targeted collection and use of these plants for research and breeding. By this, our use case supports the transition to a more sustainable agricultural system and contributes to achieving the sustainable development goal to create a world free of hunger by 2030 (SDG 2: ”Zero Hunger Goal”).
A second important objective of the use case is to utilise the Webby FAIR Digital Objects approach to foster seamless data sharing of the CWR Digital Twin’s output between Common European Data Spaces including in particular Green Deal Data Space projects such as B-Cubed and Biodiversity Meets Data/BMD.
Contributions
Providers
