Open Science and Innovation in Agrifood: A Conversation with Eleni Toli
As data becomes a cornerstone of innovation across sectors, the agrifood domain is increasingly engaging with the principles of open science to build transparent, accessible, and efficient food systems.
To explore this shift, we spoke with Eleni Toli, Research Associate at the Athena Research Centre, whose work focuses on ICT, data infrastructures, and open access. With a background in structural history and a passion for knowledge systems, Eleni shares her journey, the challenges in managing agrifood data, and her perspectives on the evolving culture of data sharing in the sector.
Exploring Our Guest’s Motivation and Background
Could you tell us about your professional path and how you became involved in the field of ICT, research data infrastructures, and open science? Was there a specific project, challenge, or experience that drew you into this field?
A defining moment for me was probably the choice of direction in my postgraduate studies, where, after studying history with an emphasis on structural history, I decided to work on how knowledge is structured and shared within an organisation, and what the role of quality management in this process can be.
This quickly led me to understand the intrinsic value of data and the essential conditions that accompany it, such as the necessity of research data infrastructures and favourable conditions for data use and exploitation, as provided by open science.
What aspects of working with data infrastructures and open access continue to challenge or motivate you today? In your current role at the Athena Research Centre, what are your main areas of focus, particularly regarding your work with European projects?
It continues to amaze me, and I think that will never stop, the power that lies in data: the ability it provides us to see beyond the surface, to shape new perceptions, and even to revisit and change the way we conduct research. Data science has permeated every scientific discipline and offers new possibilities for discovery, analysis, and synthesis.
This momentum could not have happened without the support of the necessary infrastructures, but also without the open science movement. Open access and open science are both a necessity for successfully using research results to address the grand challenges of our time, but also the “right way” to conduct science.
Of course, we must distinguish between reliable, trustworthy data and the vast amount of so-called “data” that circulates without proper review or even scientific responsibility and integrity. These are exactly among the issues we work on across a range of research projects at Athena RC.
From Infrastructure to Impact: Open Science in the Agrifood Sector
You’ve been involved in many projects around data infrastructures, open data, and cloud tools. What are the biggest challenges in building and maintaining these systems - especially when it comes to making agrifood data easy to access and use?
I think I’ll pick up where I left off in the previous answer: the use of data offers us new possibilities across all sectors – possibilities we couldn’t have imagined just a few years ago. However, this doesn’t happen automatically. Especially in sectors like agrifood, which, until recently, wouldn’t have been the first to come to mind when discussing data, the landscape has changed significantly. That said, challenges remain. I would consider the challenges related to technology as the “minor” ones.
Fragmented agrifood data sources (satellite, sensors, on-farm data collection, official and statistical data, and so on) certainly pose a higher level of complexity in building and maintaining infrastructures because of different formats, vocabularies, and standards. But this isn’t a challenge we cannot overcome. Agile technical architectures and profound domain expertise help address the technical issues.
In my opinion, things become more complicated when considering the human factor, as is always the case: how to balance openness with data sensitivity and privacy? How to talk with farmers about data ownership? How to build trust among the various actors in the data chain? How to regulate data sovereignty across countries?
And of course – data accessibility. Just making data available isn’t enough; tools and platforms need to be designed with the end user in mind, whether that’s a policymaker, farmer, or data scientist. This involves not just user interface design, but also documentation, training, support, and thoughtful functionalities. Many users in the agrifood space don’t have a technical background, so reducing barriers to entry is critical to real-world impact.
Collaborating for Change: STELAR, FAIR Principles, and Responsible Sharing
The STELAR project aims to make agrifood data easier to find, connect, and use. Where do you see the strongest overlaps between your work and the goals of STELAR? Could you share an example of how your experience contributes to that mission?
First of all, I would like to congratulate you on the innovative and ambitious approach you’ve taken in your project. I’m sure it hasn’t been easy to create meaningful connections between diverse data sources and make them truly usable across the agrifood ecosystem.
This challenge lies at the heart of our work as well. In several of our research projects, we focus on how to make data more FAIR (Findable, Accessible, Interoperable, and Reusable) in such a complex and multidisciplinary domain as agrifood systems. We aim to support better decision-making and generate outcomes that are not only impactful but also inclusive and sustainable.
Having worked directly with farmers on co-developing data-driven, community-led solutions, I fully understand the difficulties involved. But at the same time, I’ve seen firsthand the potential of data when it is well explained, responsibly shared, and properly structured. It can profoundly shift the way farmers, consumers, and researchers understand food systems, sustainability, and resilience. But this potential can only be realised with the right infrastructures and an open science mindset.
How do you think attitudes towards data sharing and openness might change in the coming years, especially within the agrifood sector?
I am not sure we can expect attitude changes in agrifood in a linear way. Actually, I am convinced that we can’t. There are certainly general trends that are expected to become more prominent, such as the growing demand for transparency across the food system, from farm to fork, linked with a more conscious consumer behaviour.
The discussion around cultivation and logistics in relation to environmental impact is very vibrant. We now know that food systems generate approximately one-third of global GHG emissions, and we value the importance of sustainable soil management. Farmers also now understand that they are data producers and owners, and this can redefine their role in the value chain.
All of the above places data quality even more at the centre of development and increases the demand for transparency. Consumers, regulators, and supply chain actors increasingly expect access to reliable, verifiable information, which creates pressure for data availability, open sharing, and standardisation.
However, due to the heterogeneity of the agrifood sector, we cannot expect a unified approach from farmers. Smallholders and family farmers still face valid concerns around data misuse, privacy, and unequal benefit-sharing. They also face technological hurdles and have limited access to digital infrastructures compared to large-scale, industrial producers.
That said, technology can also offer solutions. Emerging approaches such as data trusts, federated learning, and blockchain may help create more secure and transparent environments for data sharing. They may also provide the evidence needed that sharing data leads to tangible benefits, even for small-scale farmers: better market access, improved productivity, and stronger resilience.
This is how we can build trust and collectively move towards a more open, ethical, and inclusive data culture.
Conclusion
Eleni Toli’s insights offer a clear view of what is at stake and what is possible when we apply open science principles to the agrifood sector. With the right infrastructures, inclusive design, and a commitment to open access, projects like STELAR are laying the groundwork for a data ecosystem that serves everyone: from researchers and policymakers to farmers and consumers.
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