TY - BOOK

T1 - Navigating uncertainty

T2 - understanding stakeholder decision-making in environmental data science

AU - Wright, Kate

PY - 2025

Y1 - 2025

N2 - Increasing amounts of environmental data and use of alternative analysis techniques from statistics and computing are creating a paradigm shift for environmental studies. Tackling environmental problems requires trustworthy decisions, based on cross-disciplinary, open, and transparent research, with recognition that uncertainties in research need to be considered in more detail. Post-normal science, a concept developed in the 1990’s, highlighted these features and recognised that single disciplinary applied science was no longer sufficient for the changes occurring in the natural environment, and that decisions required input from different stakeholders. More recently, the requirement of decision-makers for data-derived evidence to make decisions for alleviating environmental challenges has enabled environmental data science to emerge as a new research area. This cross-disciplinary study explores the production of scientific evidence for making decisions about environmental problems, particularly focussing on the different types of uncertainty along a data-to-decision pathway that could impact decision-making. Involving a multidisciplinary literature review, interviews and focus groups with environmental data scientists, and a historical case study looking at stratospheric ozone depletion, the study investigates the different types of uncertainties experienced by environmental data scientists and how these influence research used for making decisions. It also considers how scientists handle the challenges of conducting research at the boundary of science and policy, and finally considers the extent to which the concept of post-normal science provides a framework to guide environmental data science research. A new typology of uncertainty for environmental data science is presented which provides a summary of the uncertainties experienced by the different stakeholders at different points along the pathway. The study highlights the challenges of communication – particularly, how to communicate within cross-disciplinary research groups and communicating the research so that it is not misinterpreted. Building on these a generic communication framework is proposed to aid the environmental science community to communicate uncertainties to the different stakeholders involved with a particular environmental challenge.

AB - Increasing amounts of environmental data and use of alternative analysis techniques from statistics and computing are creating a paradigm shift for environmental studies. Tackling environmental problems requires trustworthy decisions, based on cross-disciplinary, open, and transparent research, with recognition that uncertainties in research need to be considered in more detail. Post-normal science, a concept developed in the 1990’s, highlighted these features and recognised that single disciplinary applied science was no longer sufficient for the changes occurring in the natural environment, and that decisions required input from different stakeholders. More recently, the requirement of decision-makers for data-derived evidence to make decisions for alleviating environmental challenges has enabled environmental data science to emerge as a new research area. This cross-disciplinary study explores the production of scientific evidence for making decisions about environmental problems, particularly focussing on the different types of uncertainty along a data-to-decision pathway that could impact decision-making. Involving a multidisciplinary literature review, interviews and focus groups with environmental data scientists, and a historical case study looking at stratospheric ozone depletion, the study investigates the different types of uncertainties experienced by environmental data scientists and how these influence research used for making decisions. It also considers how scientists handle the challenges of conducting research at the boundary of science and policy, and finally considers the extent to which the concept of post-normal science provides a framework to guide environmental data science research. A new typology of uncertainty for environmental data science is presented which provides a summary of the uncertainties experienced by the different stakeholders at different points along the pathway. The study highlights the challenges of communication – particularly, how to communicate within cross-disciplinary research groups and communicating the research so that it is not misinterpreted. Building on these a generic communication framework is proposed to aid the environmental science community to communicate uncertainties to the different stakeholders involved with a particular environmental challenge.

U2 - 10.17635/lancaster/thesis/2765

DO - 10.17635/lancaster/thesis/2765

M3 - Doctoral Thesis

PB - Lancaster University

ER -