Solving food problems using AI and Data Science

'Artificial Intelligence and Data Science offer opportunities and are controversial at the same time. It is up to us to develop responsible applications, because AI and Data Science can contribute to a sustainable and healthy world', advocates Anna Fensel. She has been appointed as a full professor of artificial intelligence and data science at Wageningen University & Research.

An impressive and international career has taken Anna Fensel from her native Russia to Austria, Ireland and the UK. She was recently appointed as a full professor of artificial intelligence and data sciences, strengthening the Consumption and Healthy Lifestyles group. 'The world is facing a major challenge: how can we feed the growing number of people in a healthy and sustainable way? Part of the solution can be found in AI and Data Science', states Fensel. 'Machines have the capacity to store huge amounts of data, and AI can combine data and make relationships and connections. Examples include datasets on the properties of food ingredients, their production and human health. Humans are naturally better at knowledge management and decision-making: by "merging" machines and humans, scientists, governments and organisations can make better decisions. This is what makes my job so fascinating'.

Anna Fensel thus specialises in semantic technology, which is technology that helps to represent and analyse the meaning and context of information. 'Our research helps scientists and organisations develop and share data in the right way by developing data infrastructures, linking data and applying the FAIR principles (findable, accessible, interoperable and reusable). For example, in our search for data-access solutions, we are working on managing user consent, licences and contracts'.

As a further example, Anna Fensel cites her work for the Horizon Europe project SoilWise, a freely accessible repository for knowledge and data on soil protection. 'Soil health is a major issue. According to recent assessments, 60-70% of all European soils could be considered unhealthy. The Soil Deal for Europe aims to ensure that 75% of all EU soils to be either healthy or significantly improved by 2030. Achieving this will require access to reliable data and knowledge collected at the local, national and EU level. With this information, politicians will be able to make informed decisions. We are working on that repository, using AI techniques to connect dispersed data and knowledge, derive new knowledge and increase FAIR-ness'.

Another important topic Fensel intends to continue focusing on is lifestyle. 'We are developing applications that encourage behavioural and lifestyle changes. The combination of AI and Data Science with research in the Food Valley (the Silicon Valley of food) makes it possible to build applications like digital assistants that communicate with users and make nutritional recommendations based on their knowledge about the users and related communications'.

According to Fensel, the greatest challenge for WUR is to unlock the potential of data-driven innovations and turn information into knowledge. 'To do this, we must develop both new technologies and new ways of working together. We need to bridge the gap between data scientists, AI experts and domain scientists, such as those specialising in climate and health. We will be working hard on this in the coming years. With AI and Data Science, we can make a big impact'.

Protein transition

Anna Fensel and her team are also using AI and Data Science to contribute to the protein transition. Proteins are the building blocks of life on earth, but the way in which we produce and consume them is depleting natural resources. Moreover, proteins are not distributed fairly around the world. 'So, for a sustainable and equitable food system, we need to distribute proteins better. It will also require a shift to more plant-based proteins and new protein sources', says Fensel. 'For this reason, WUR is working with the RIVM on an application and FAIR data-management solutions to optimise the transition. We are collecting and connecting data on how food is produced and consumed'.

Anna Fensel

With an educational background in computer science and mathematics, Anna Fensel has a global career, having worked in Russia, Ireland, England and Austria. In the Department of Computer Science at the University of Innsbruck in Austria, she worked as an associate professor and senior assistant professor for STI Innsbruck. Before that, she was a senior researcher at the FTW Telecommunications Research Center Vienna in Austria, and as a research fellow at the University of Surrey in the UK. She has been extensively involved in European and national projects related to semantic technologies. 'I make computers, the web and information systems more intelligent so that they are able to understand themselves and their users better, in addition to enabling better communication and collaboration'.

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