Periodic Reporting for period 1 - Entrust (Next Generation of Trustworthy Agri-Data Management)
Reporting period: 2023-01-01 to 2024-12-31
EnTrust is a doctoral network funded by Marie Skłodowska-Curie Actions (MSCA) which is a part of Horizon Europe. MSCA is the European Union’s flagship funding programme for doctoral education and the postdoctoral training of researchers. The aim of EnTrust is to enable farmers to become equal partners in the agri-data value chain, enabling our Doctoral Candidates to excel in their future career prospects and to obtain a PhD at the intersection of computing, information systems and social science. The programme hopes to create a significant impact in science, the economy and wider society. EnTrust is investigating how agri-data coming from farmers can be made available, governed, and exploited, with the benefits shared in a fair way.
We are training a cohort of 11 Doctoral Candidates (DCs) in an intersectoral, international and interdisciplinary setting with the aim to establish a new generation of Data Executives who will be able to advance the state of the art in data sharing in a fair, transparent, and trusted environment. Data Executives represent the future leaders in data management with an interdisciplinary skillset covering technical, legal, managerial, and entrepreneurial skills.
We are training a cohort of 11 Doctoral Candidates (DCs) in an intersectoral, international and interdisciplinary setting with the aim to establish a new generation of Data Executives who will be able to advance the state of the art in data sharing in a fair, transparent, and trusted environment. Data Executives represent the future leaders in data management with an interdisciplinary skillset covering technical, legal, managerial, and entrepreneurial skills.
10 of the 11 Doctoral Candidates have been recruited and have started their PhD journeys. Progress has been made on the scientific work-packages and all deliverables have been met.
Work Package(WP) 1 has made significant strides in advancing secure, equitable, and user-centric agricultural data-sharing frameworks tailored for small-to-medium farms.
WP2 has made progress in advancing data governance practices for Agriculture 4.0 driven by the interdisciplinary research of doctoral candidates (DCs) and the development of actionable frameworks. By addressing the interrelated pillars of cybersecurity and cyber-risk assessment, data sovereignty and rights sharing, data quality & trustworthiness, WP2 has established a robust foundation for secure, ethical, and sustainable agri-data ecosystems.
The work on this WP3 has been progressing steadily throughout the project period. The individual research projects of the involved doctoral candidates (DCs) are significantly contributing to the scientific objective 3 of the project.
5 of the planned training weeks have taken place to date, with an additional optional training event taking place in June 2024 in Maynooth, Ireland.
Work Package(WP) 1 has made significant strides in advancing secure, equitable, and user-centric agricultural data-sharing frameworks tailored for small-to-medium farms.
WP2 has made progress in advancing data governance practices for Agriculture 4.0 driven by the interdisciplinary research of doctoral candidates (DCs) and the development of actionable frameworks. By addressing the interrelated pillars of cybersecurity and cyber-risk assessment, data sovereignty and rights sharing, data quality & trustworthiness, WP2 has established a robust foundation for secure, ethical, and sustainable agri-data ecosystems.
The work on this WP3 has been progressing steadily throughout the project period. The individual research projects of the involved doctoral candidates (DCs) are significantly contributing to the scientific objective 3 of the project.
5 of the planned training weeks have taken place to date, with an additional optional training event taking place in June 2024 in Maynooth, Ireland.
The EnTrust project has made significant strides in advancing secure, equitable, and user-centric agricultural data-sharing frameworks and made significant contributions beyond the state of the art along the three key pillars of the project.
We have tested some aspects of suitability of digital technologies in a farming context, particularly focussing on smaller farmers assistance in the adoption of innovative and affordable digital technologies. We have started the development of a modular data exchange protocol, integrating Large Language Models (LLMs) and advanced Retrieval-Augmented Generation (RAG) techniques. We also conducted pivotal stakeholder research, which revealed that practical barriers (e.g. time constraints, fragmented fields) outweighed privacy concerns as primary obstacles to data sharing. These insights informed the design of a toolbox Framework, emphasizing simplified interfaces, offline capabilities, and "living labs" to demonstrate tangible benefits. We also developed a GDPR-compliant metadata protocols and secure aggregation techniques, ensuring data sovereignty and trust through federated learning and role-based access controls.
We have enhance the understanding of trust in agri-data governance and sharing by addressing socio-technical and organizational challenges. The work focused on developing governance frameworks to ensure data quality, sovereignty, security, and trustworthiness, aligning with the EU’s vision for trustworthy data spaces. By addressing the interrelated pillars of cybersecurity and cyber-risk assessment, data sovereignty and rights sharing, data quality & trustworthiness, we have established a robust foundation for secure, ethical, and sustainable agri-data ecosystems.
This accomplishment underscores the project’s impact in advancing cybersecurity and data governance practices for Agriculture 4.0 while validating the relevance of its frameworks to both academic and practitioner communities.
The research on Business Model innovation provides valuable insights into fostering innovation and driving positive change, while identifying several challenges and opportunities for farmers and forest owners, particularly focusing on small farms and SMEs. In this aspect the key challenges identified that farmers and forest owners need to be pay attention including Data Ownership and Trust, Data Standardisation, Farmer and forest owner engagement, Ethical Considerations and Privacy and Business Model Development.
Furthermore, the deliverables produced so far have laid a strong foundation for the EnTrust project. One aim is to disseminate the findings to both the scientific community and practitioners through a comprehensive book. This book will integrate findings from all deliverables, including a dedicated section from WP3 on methodologies, frameworks, and best practices for innovative business models that drive value creation and sustainability in agricultural ecosystems. Targeted at practitioners, researchers, and policymakers, the book will serve as both an academic resource and a practical guide, advancing the discourse on business model innovation and supporting stakeholders in navigating the complexities of data-driven ecosystems.
We have tested some aspects of suitability of digital technologies in a farming context, particularly focussing on smaller farmers assistance in the adoption of innovative and affordable digital technologies. We have started the development of a modular data exchange protocol, integrating Large Language Models (LLMs) and advanced Retrieval-Augmented Generation (RAG) techniques. We also conducted pivotal stakeholder research, which revealed that practical barriers (e.g. time constraints, fragmented fields) outweighed privacy concerns as primary obstacles to data sharing. These insights informed the design of a toolbox Framework, emphasizing simplified interfaces, offline capabilities, and "living labs" to demonstrate tangible benefits. We also developed a GDPR-compliant metadata protocols and secure aggregation techniques, ensuring data sovereignty and trust through federated learning and role-based access controls.
We have enhance the understanding of trust in agri-data governance and sharing by addressing socio-technical and organizational challenges. The work focused on developing governance frameworks to ensure data quality, sovereignty, security, and trustworthiness, aligning with the EU’s vision for trustworthy data spaces. By addressing the interrelated pillars of cybersecurity and cyber-risk assessment, data sovereignty and rights sharing, data quality & trustworthiness, we have established a robust foundation for secure, ethical, and sustainable agri-data ecosystems.
This accomplishment underscores the project’s impact in advancing cybersecurity and data governance practices for Agriculture 4.0 while validating the relevance of its frameworks to both academic and practitioner communities.
The research on Business Model innovation provides valuable insights into fostering innovation and driving positive change, while identifying several challenges and opportunities for farmers and forest owners, particularly focusing on small farms and SMEs. In this aspect the key challenges identified that farmers and forest owners need to be pay attention including Data Ownership and Trust, Data Standardisation, Farmer and forest owner engagement, Ethical Considerations and Privacy and Business Model Development.
Furthermore, the deliverables produced so far have laid a strong foundation for the EnTrust project. One aim is to disseminate the findings to both the scientific community and practitioners through a comprehensive book. This book will integrate findings from all deliverables, including a dedicated section from WP3 on methodologies, frameworks, and best practices for innovative business models that drive value creation and sustainability in agricultural ecosystems. Targeted at practitioners, researchers, and policymakers, the book will serve as both an academic resource and a practical guide, advancing the discourse on business model innovation and supporting stakeholders in navigating the complexities of data-driven ecosystems.