FAIRagro is aimed at everyone who deals with the challenges of modern agriculture either professionally or privately and at the same time is facing the tasks of digital transformation and research data management. FAIRagro promotes the willingness to integrate the idea of Open Science into one’s own work and thus strengthen the transparency and accessibility of research results.
Contents
Who we are
Within the National Research Data Infrastructure (Nationale Forschungsdateninfrastruktur -NFDI), 26 consortia and one base service (Basisdienst) have been systematically indexing, networking and making valuable data sets from various scientific disciplines available to the German science system in the long term since 2020.
FAIRagro has been representing the agrosystems research community in Germany with more than 30 partners since March 2023. We are building a FAIR (Findable, Accessible, Interoperable, Reusable) research data management (RDM) system for the agrosystems research community. We are developing the right tools and workflows to lay the foundations for sustainable crop production – now and in the future.
Findable
Accessible
Interoperable
ReusableAnd what does “agrosystems research” mean?
Agrosystems are agroculturally used landscapes and ecosystems which require an integrated systems perpective to develop sustainable crop production systems and interventions considering agri-environment interactions (plant, soil, microbiota, abiotic and biotic environment) and relationships across scales (spaces, time and organisations).
What we want to achieve
Agriculture is facing enormous challenges: Stagnating productivity, climate change, loss of biodiversity, supply shortages due to crises and wars as well as the degradation of natural resources are facing an ever-increasing demand.
To meet these challenges, we need sustainable solutions – made possible by integrated research approaches, networked research data infrastructures (RDI) and uniform standards for common research data management (RDM).
This is what we have been working on since March 2023.
Our 10 objectives
1. Cultural Change
Enabling researchers, students, and infrastructure providers to achieve an open and sustainable research data life cycle and foster a cultural change towards FAIR and collaborative RDM.
2. Solutions for the Community
Continuously identify RDM challenges in the agrosystem community and provide solutions via continuously agile developed RDM services to meet the needs of our community.
3. Portal as a central Hub
Developing the FAIRagro Portal as the central access point for RDM in the agrosystem sciences to enable knowledge exchange, technology transfer and participatory processes to promote dialogue with our community.
4. Findability and Exchange
Improving the findability of published research data as well as existing data repositories and providing discipline-specific interoperable infrastructures to enable standardised data exchange.
5. Orientation for Researchers
Developing and establishing a set of standards, guidelines and best-practices as guidance for researchers to promote and enable FAIR RDM and infrastructure.
6. Quality assurance
Ensuring research data quality via domain-specific measures of quality control and establish a quality feedback and curation system to facilitate the reuse of research data by agricultural scientists.
7. Legal Security
Providing legal certainty to infrastructure providers, data providers and users for the publication and reuse of sensitive data.
8. Reproducibility
Enabling reproducible research results, the deployment and publishing of models and data analysis workflows, and contributing to the reproducibility of research results.
9. Interoperability
Ensuring the interoperability of an agrosystem research data infrastructure within related domains in the agricultural sciences and within NFDI as well as with the overarching NFDI and international initiatives.
10. Internationalisation
Contributing to and leading European and international developments of RDI in agrosystem and agricultural research with the goal of and playing a lead role.
How we organize
Our Task Areas and our Measures
Our consortium currently consists of 11 co-applicant institutions and 21 participants from the relevant disciplines of plant, soil and agri-environmental sciences (see also below: Partners). Under Governance you can find the various bodies of FAIRagro and the respective contact persons.
The content-related areas of responsibility are divided into five Task Areas (TAs), which work closely together and coordinate their activities on an ongoing basis. Each Task Area is also divided into individual measures. What these are and who the contact person is in each case is shown below.
Task Area 1: Use Cases – Implementation
In TA 1 we address the challenges of agrosystems science, which are formulated in several specific Use Cases and Use Case Pilots. The concepts and services for data, metadata harmonization, standardization, data discoverability and data access developed in TAs 2-4 are based on the findings from these Use Cases. The results from TA1 continue to be an important component for training and further education, which are coordinated with TA2. The Use Cases in TA1 cover a broad spectrum of research questions on agricultural systems, taking into account different scales.
Task Area Lead: Senthold Asseng
Task Area Co Lead: Benjamin Leroy, Til Feike, Christoph Jochen Reif
The Team of Task Area 1 is meeting on the first thursday of each month on a regular basis.
Measure 1.1:
UC 1 – Exploiting Genotype x Location x Year x Management Interactions for Sustainable Crop Production
Lead: Jochen C. Reif (IPK)
Use Case 1 in Measure 1.1 addresses challenges in breeding of crops and will exploit possibilities to build up required data management processes that enable genotype × location × year × management interactions.
Measure 1.2:
UC 2 – Assessing Tradeoffs for Optimal Crop Nitrogen Management
Lead: Heidi Webber (ZALF)
Use Case 2 in Measure 1.2 addresses challenges for process-based crop model applications to optimize nitrogen use.
Measure 1.3:
UC 3 – Streamlining Pest and Disease Data to Advance Integrated Pest Management
Lead: Till Feike (JKI)
Use Case 3 in Measure 1.3 addresses challenges in pests and diseases management.
Measure 1.4:
UC 4 – Learning from Incomplete Data
Lead: Gunnar Lischeid (ZALF)
Use Case 4 in Measure 1.4 addresses the challenges of how to deal with incomplete data on the case of data from long-term experiments.
Measure 1.5:
UC 5 – Noninvasive Phenotyping with Autonomous Robots
Lead: Uwe Rascher (FZJ),
Co-Lead: Jan-Henrik Haunert (UBN)
Use Case 5 in Measure 1.5 showcases the potential of multimodal data analytics methods and machine-learning algorithms for in-field plant phenotyping.
Measure 1.6:
UC 6- Automated Data Flows for Crop Simulation Models
Lead: Senthold Asseng (TUM)
Co-Lead: Benjamin Leroy (TUM)
Use Case 6 in Measure 1.6 addresses data challenges with respect to the calibration and application of crop models.
Measure 1.7:
UC 7- Next-Generation Environmental and EXtended Tools for Extreme Events and Plant Resilience Assessment
Lead: Amit Kumar Srivastava (ZALF)
Use Case 7 in Measure 1.7 focuses on the development of automated tools for impact assessment of climate events.
Measure 1.8:
Erhöhung der FAIRness von FAIRagro-Daten durch KI-unterstützte Metadatenanreicherung
Lead: Juliane Fluck (ZB MED)
Co-Lead: Gabriel Schneider (ZB MED)
UC (Pilot) 8 in Measure 1.8 deals with the possibilities of AI-based methods to support the enrichment of metadata in order to improve the FAIRness of data in the context of agrosystems research.
Measure 1.9:
Systematische Ansätze zur effizienten Datensynchronisation in den Gartenbauwissenschaften (HortSEEDS)
Lead: Nicole van Dam (IGZ)
UC (Pilot) 9 in Measure 1.9 is finished and did focus on the development of a prototype for the harmonization of data and metadata for a standardized process of horticultural experiments.
Measure 1.10:
Eintauchen in Daten zu Unkraut im Ackerbau zur Verknüpfung von Biodiversität und Landwirtschaft (WeeDive)
Lead: Bärbel Gerowitt (Uni Rostock)
UC (Pilot) 10 In Measure 1.10 deals with strategically offering knowledge to join food security and biodiversity conservation goals in arable management and providing FAIR data therefor.
Measure 1.11:
BrAPI Integration on PSI Hardware
Lead: Marc C. Heuermann (IPK)
UC (Pilot) 11 in Measure 1.11 deals with the integration of an open, standardized interface (Breeding API) to make the proprietary data management systems available in the PhenoSphere system FAIR.
Measure 1.12:
Linking Agrosystem Data with Socio-Economic Information
Lead: Günther Filler (HU Berlin)
UC (Pilot) 12 in Measure 1.12 extends existing information on agricultural systems to include socio-economic information and establishes a link between these areas – with a focus on agricultural land markets.
Measure 1.13:
Agri-Gaia meets DataHUB: Connecting Technologies & Communities via a Potato Virus Dataset FAIRification
Lead: Heiko Tapken (HSOS)
Co-Lead: Timo Mühlhaus (RPTU)
Use Case 13 in Measure 1.13 deals with the conversion of data into FAIR digital objects using the ARC DataHub and the AI development platform Agri-Gaia.
Measure 1.14:
Unlocking Multifunctional Insights with Near‐Surface Geophysical Data Harmonization in Agriculture
Lead: Ulrike Werban (UFZ)
Use Case 14 in Measure 1.14 deals with the harmonization and usability of geophysical datasets and is part of an inter-consortial initiative with FAIRagro, NFDI4Objects and NFDI4Earth.
Task Area 2: Community Involvement and Networking
In TA2, we address the broadly diversified agrosystems community. A particular feature of this community is its distribution across many disciplines, institutions and organizations. Agrosystems research also includes many different stakeholders (such as advisors, breeders, farmers, policy makers…) and is linked to other fields such as plant, environmental, biodiversity and earth sciences. This makes it all the more important to pool ideas, needs, support requests and feedback and to provide appropriate training and assistance. TA2 provides the other TAs in FAIRagro with feedback on the insights gained – this is how FAIRagro’s products are developed specifically for the community.
Task Area Lead: Ulrike Stahl
Task Area Co Lead: Birte Lindstädt
The Team of Task Area 2 is meeting on the second monday of each month on a regular basis.
Measure 2.1:
Communication and Dissemination
Lead: Ulrike Stahl (JKI)
Measure 2.1 deals with communication and networking within the agrosystem community. Here we operate the FAIRagro portal, do public relations work and organize events.
Measure 2.2:
Community Participation
Lead: James M. Anderson (ATB)
Measure 2.2 deals with the management of feedback by the community and cooperation with the Community Advisory Board (CAB).
Measure 2.3:
Use Case Onboarding
Lead: James M. Anderson (ATB)
In Measure 2.3, we are developing and establishing a structured onboarding process for Use Cases to integrate new research areas and institutions.
Measure 2.4:
Training and Education
Lead: Birte Lindstädt (ZB MED)
Here we create customized training courses and training materials to further develop the skills of the agrosystems research community in a targeted manner.
Measure 2.5:
Data Steward Service Center (DSSC)
Lead: Nikolai Svoboda (ZALF)
The Data Steward Service Center (DSSC) is the competent central point of contact for all questions relating to data management, both for the Use Cases and for the wider community.
Task Area 3: Standardization, Interoperability and Quality
In TA3, we are working on easier reuse, quality checking and annotation of research data. We consolidate the FAIR data concepts of the participating research infrastructures and improve the interoperability of the participating vocabularies and ontologies. We create metadata models and publication guidelines for the different types of FAIRagro data to ensure findability and reusability. We are also working on extending schema.org, creating data quality metrics and developing a legal framework. Based on this, we are able to summarize all results of TA3 into actionable guidelines and legal metadata standards for improved reusability.
Task Area Lead: Daniel Martini
Task Area Co Lead: Claus Weiland, Jan-Henrik Haunert
The Team of Task Area 3 is meeting on the third monday of each month on a regular basis.
Measure 3.1:
Standardization, Interoperability and Quality
Lead: Daniel Martini (KTBL),
Co-Leads: Claus Weiland (SGN)
To promote awareness and compliance with FAIR principles within the agricultural systems community, we are creating and developing an inventory of established (meta-)data standards, vocabularies and ontologies in Measure 3.1.
Measure 3.2:
Standards for Data Management, FAIRness and Discoverability
Lead: Juliane Fluck (ZB MED),
Co-Lead: Daniel Martini (KTBL)
Here we are creating community standards to improve data management practices, FAIRness of data and visibility of data. We will create specific templates for data management plans (DMP) and develop extensions to schema.org.
Measure 3.3:
Measures and Application-Data-Matrix for Data Quality and Fitness-for-Use
Lead: Markus Möller (JKI),
Co-Lead: Carsten Hoffmann (ZALF)
To ensure the reusability of data, we develop standard criteria for data quality in agrosystem research based on representative agrosystem datasets.
Measure 3.4:
Data Quality Annotation, Curation and Feedback / Review
Lead: Jan Henrik Haunert (Uni Bonn),
Co-Lead: Uwe Rascher (FZJ)
Building on Measure 3.3, which focuses on the definition of data quality metrics, here we create the appropriate toolset (including algorithms, reference data and a verification system) to enable the evaluation and improvement of data content based on these quality metrics.
Measure 3.5:
FAIR Workflows and FAIR Digital Objects
Lead: Claus Weiland (SGN),
Co-Lead: Daniel Martini (KTBL)
In Measure 3.5, we develop digital FAIR objects (FDO) and provide services and frameworks for describing research data workflows. This enables the creation and use of specific FDOs.
Measure 3.6:
Legal Framework and Machine-Actionable Policies
Lead: Franziska Boehm (FIZ),
Co-Lead: Stephan Lesch (SGN)
Measure 3.6 focuses on creating a legally compliant framework for the sharing of agricultural system data within FAIRagro. This will improve the accessibility of data and facilitate compliance with regulations.
Task Area 4: Infrastructure Services
Based on the agrosystem domain, the requirements formulated by the Use Cases in TA 1 and the standards defined in TA 3, we implement the necessary components and infrastructure services of the federated RDM along a FAIR-enabled research data lifecycle in TA 4. Access for the community is provided by the FAIRagro portal. Here we provide and implement central FAIRagro services that link existing data repositories. We are also building a searchable directory of services and data to improve findability. In addition, a framework for reusable data integration workflows is being implemented to enable application-specific, cloud-enabled analysis workflows. Furthermore, TA 4 is responsible for ensuring the technical compatibility and potential application of the NFDI’s overarching infrastructure services.
Task Area Lead: Dr. Matthias Lange
Task Area Co Lead: Juliane Fluck, Björn Usadel
The Team of Task Area 4 is meeting on the second tuesday of each month on a regular basis.
Measure 4.1:
Central Services for the FAIRagro Community
Lead: Xenia Specka (ZALF)
The central services to support the activities of the FAIRagro consortium are provided here. First and foremost: the FAIRagro portal, a project management platform, a customer relationship management system (CRM) and research data management software (RDMO).
Measure 4.2:
Network of Federated Research Data Infrastructures (RDI)
Lead: Daniel Arend (IPK),
Co-Leads: Stephan Lesch (SGN), Xenia Specka (ZALF)
Measure 4.2 develops a network that connects the various research data sources in agricultural systems science and enables a smooth and user-friendly exchange of information and data access according to the FAIR principles.
Measure 4.3:
Searchable Inventory of Services and Data
Lead: Juliane Fluck (ZB MED),
Co-Lead: Björn Usadel (FZJ)
Measure 4.3 focuses on creating a user-friendly service to query the network of interlinked data infrastructures developed in Measure 4.2 to easily find relevant datasets and infrastructures.
Measure 4.4:
Scientific Workflow Infrastructure (SciWIn)
Lead: Harald von Waldow (Thünen)
Co-Lead: Antonia Leidel (IPK)
FAIR data management, analysis and integration often involves multiple services and platforms that are regularly updated and corrected. As a result, data integration and analysis processes can be complicated, inefficient and difficult to reproduce. Measure 4.4 addresses these challenges by providing a workflow infrastructure called SciWIn that makes it possible to streamline data processing.
Task Area 5: Management and Coordination
TA5 is responsible for the coordination and management of our FAIRagro consortium. This is where measures are initiated and coordinated to ensure the long-term success of FAIRagro. TA5 organizes the day-to-day business of FAIRagro, takes care of the consortium’s finances and ensures that the funding conditions are met. TA5 is responsible for organizing the regular reports and the FAIRagro plenary events. Through a variety of activities, TA5 will develop FAIRagro beyond the NFDI funding phase into a sustainable, permanent institution and coordinate communication and relations between FAIRagro, NFDI and relevant national and international RDM initiatives.
Task Area Lead: Prof. Dr. Frank A. Ewert
Task Area Co Lead: Xenia Specka
The Team of Task Area 5.
Measure 5.1:
Project Management, Governance and Financial Controlling
Lead: Xenia Specka (ZALF)
Co-Lead: Carsten Hoffmann (ZALF)
Measure 5.1 ensures the smooth operation of our consortium: it supports and monitors activities to support joint governance, day-to-day business, financial control and project progress.
Measure 5.2:
Sustainability and Business Model
Lead: Xenia Specka (ZALF)
Co-Lead: Carsten Hoffmann (ZALF)
In order to be able to establish FAIRagro sustainably beyond the funding period, a suitable business model is being developed and implemented here in order to maintain the developments of the funding period in the long term and to further advance the cultural change in RDM.
Measure 5.3:
Cross-NFDI and International Networking
Lead: Carsten Hoffmann (ZALF)
Co-Lead: Xenia Specka (ZALF)
Measure 5.3 coordinates communication and collaboration with other NFDI consortia, the NFDI and relevant international RDM initiatives. In this way, we contribute to a common vision and facilitate the interdisciplinary exchange of FAIR data.
Partner
The FAIRagro consortium comprises over 30 partner institutions from all over Germany, representing the relevant disciplines from the plant, soil and agri-environmental sciences.
Governance
In order to ensure the success of FAIRagro, our consortium has adopted a structure that is characterized by coordination and close integration of all those involved, while at the same time providing opportunities for the community to participate.
Steering Committee
Spokesperson
Prof. Dr. Frank A. Ewert
Elected Representatives:
Dr. Daniel Arend (IPK, Co-Applicant)
Dr. Anne Sennhenn (ATB, Participant)
Dr. Torsten Thalheim (DBFZ, Participant)
Gabriel Schneider (ZB MED, Young Scientist)
Permanent Representatives:
Prof. Dr. Senthold Asseng (TU München, TA1)
Dr. Ulrike Stahl (JKI, TA2)
Daniel Martini (KTBL, TA3)
Dr. Matthias Lange (IPK, TA4)
Prof. Dr. Frank A. Ewert (ZALF, TA5)
FAIRagro Secretariat
Dr. Xenia Specka (Projectcoordination)
Dr. Carsten Hoffmann (Projectmanagement)
Lena Schlüter (Projectadministration, Finance)
Laura Elena Ramallo Gago (Projectassistance)
Community Advisory Board (CAB)
Co-Spokespersons
Meet the Co-Spokespersons of FAIRagro. For the time being, the link leads to the German version of our website. English version coming soon.
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