From Field Data to Global Indicators: A Framework for intelligent Plant Data Linkage
1 May 2019 - 1 June 2022
PI/s in Exeter: Professor Sabina Leonelli
Funding awarded: (total funding of £ 196,491)
Sponsor(s): The Alan Turing Institute
About the research
A key task for data science is to develop systems through which diverse types of data can be aligned to provide common ground for discovery. These systems determine how data is incorporated into machine learning algorithms and whose perspective is incorporated or excluded from data-driven knowledge systems. Through sustained engagement with stakeholders involved in the development and use of plant data infrastructures, the project investigates current models and future prospects for managing environmental and biological data collected from experiments and field trials around the world.
The project aims to provide the building blocks towards investigating the conditions under which plant data can be efficiently and reliably linked across data platforms and infrastructures around the world, in ways that could serve the development of global indicators for the United Nations’ Sustainable Development Goals (particularly SDG 2: Zero Hunger, SDG 3: Good Health and Wellbeing; SDG 10: Reduce Inequalities and SDG 15: Life on Land).