Solving food problems using AI and Data Science

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’.