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Valuing local knowledge as a source of expert data: farmer engagement and the design of decision support systems.

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Valuing local knowledge as a source of expert data : farmer engagement and the design of decision support systems. / Oliver, David; Fish, Robert; Winter, Michael; Hodgson, C. J.; Heathwaite, A. Louise; Chadwick, D. R.

In: Environmental Modelling and Software, Vol. 36, 10.2012, p. 76-85.

Research output: Contribution to journalJournal article

Harvard

Oliver, D, Fish, R, Winter, M, Hodgson, CJ, Heathwaite, AL & Chadwick, DR 2012, 'Valuing local knowledge as a source of expert data: farmer engagement and the design of decision support systems.', Environmental Modelling and Software, vol. 36, pp. 76-85. https://doi.org/10.1016/j.envsoft.2011.09.013

APA

Oliver, D., Fish, R., Winter, M., Hodgson, C. J., Heathwaite, A. L., & Chadwick, D. R. (2012). Valuing local knowledge as a source of expert data: farmer engagement and the design of decision support systems. Environmental Modelling and Software, 36, 76-85. https://doi.org/10.1016/j.envsoft.2011.09.013

Vancouver

Author

Oliver, David ; Fish, Robert ; Winter, Michael ; Hodgson, C. J. ; Heathwaite, A. Louise ; Chadwick, D. R. / Valuing local knowledge as a source of expert data : farmer engagement and the design of decision support systems. In: Environmental Modelling and Software. 2012 ; Vol. 36. pp. 76-85.

Bibtex

@article{72523eb5a31144fdaf5412e3cb5466a2,
title = "Valuing local knowledge as a source of expert data: farmer engagement and the design of decision support systems.",
abstract = "Engagement with farmers and landowners is often undertaken by the research community to obtain information relating to typical land, livestock and enterprise management and generally centres on responses to questionnaire surveys. Farmers and land managers are constituted as expert observers of ground-level processes and provide diverse information on farming practices, enterprise economics and underpinning attitudes towards risk. Research projects designed to inform policy and practice may rely on such data to understand better on-the-ground decisions that can impact on environmental quality and the rural economy. Such approaches to eliciting local-level expert knowledge can generate large quantities of data from which to formulate rules relating to farm enterprise types. In turn, this can help to inform the structure of Decision Support Systems (DSS) and risk-based tools to determine farming practices likely to impact on environmental quality. However, in this paper we advocate the need for integrated farmer participation throughout the whole research process – from project inception through to community qualitative validation and legitimation - and thus not just for the elicitation of questionnaire responses. With farm questionnaire surveys being adopted widely by the research community, it is an opportune time to highlight a recent case study of the Taw catchment, Devon, UK. This serves as an example of co-construction of a DSS via a co-ordinated and integrated approach to expert elicitation with a farmer questionnaire survey as a central methodology. The aim of the paper is to detail the core aspects of an iterative cycle of participatory environmental management and DSS development for water quality protection and consider the multiple benefits of co-ordinated programmes of engagement with the farming community in this process. ",
keywords = "Decision support, Expert, Farmer, Local knowledge, Questionaire survey, Stakeholder participation, Uncertainty, Water quality",
author = "David Oliver and Robert Fish and Michael Winter and Hodgson, {C. J.} and Heathwaite, {A. Louise} and Chadwick, {D. R.}",
year = "2012",
month = oct
doi = "10.1016/j.envsoft.2011.09.013",
language = "English",
volume = "36",
pages = "76--85",
journal = "Environmental Modelling and Software",
issn = "1364-8152",
publisher = "Elsevier BV",

}

RIS

TY - JOUR

T1 - Valuing local knowledge as a source of expert data

T2 - farmer engagement and the design of decision support systems.

AU - Oliver, David

AU - Fish, Robert

AU - Winter, Michael

AU - Hodgson, C. J.

AU - Heathwaite, A. Louise

AU - Chadwick, D. R.

PY - 2012/10

Y1 - 2012/10

N2 - Engagement with farmers and landowners is often undertaken by the research community to obtain information relating to typical land, livestock and enterprise management and generally centres on responses to questionnaire surveys. Farmers and land managers are constituted as expert observers of ground-level processes and provide diverse information on farming practices, enterprise economics and underpinning attitudes towards risk. Research projects designed to inform policy and practice may rely on such data to understand better on-the-ground decisions that can impact on environmental quality and the rural economy. Such approaches to eliciting local-level expert knowledge can generate large quantities of data from which to formulate rules relating to farm enterprise types. In turn, this can help to inform the structure of Decision Support Systems (DSS) and risk-based tools to determine farming practices likely to impact on environmental quality. However, in this paper we advocate the need for integrated farmer participation throughout the whole research process – from project inception through to community qualitative validation and legitimation - and thus not just for the elicitation of questionnaire responses. With farm questionnaire surveys being adopted widely by the research community, it is an opportune time to highlight a recent case study of the Taw catchment, Devon, UK. This serves as an example of co-construction of a DSS via a co-ordinated and integrated approach to expert elicitation with a farmer questionnaire survey as a central methodology. The aim of the paper is to detail the core aspects of an iterative cycle of participatory environmental management and DSS development for water quality protection and consider the multiple benefits of co-ordinated programmes of engagement with the farming community in this process.

AB - Engagement with farmers and landowners is often undertaken by the research community to obtain information relating to typical land, livestock and enterprise management and generally centres on responses to questionnaire surveys. Farmers and land managers are constituted as expert observers of ground-level processes and provide diverse information on farming practices, enterprise economics and underpinning attitudes towards risk. Research projects designed to inform policy and practice may rely on such data to understand better on-the-ground decisions that can impact on environmental quality and the rural economy. Such approaches to eliciting local-level expert knowledge can generate large quantities of data from which to formulate rules relating to farm enterprise types. In turn, this can help to inform the structure of Decision Support Systems (DSS) and risk-based tools to determine farming practices likely to impact on environmental quality. However, in this paper we advocate the need for integrated farmer participation throughout the whole research process – from project inception through to community qualitative validation and legitimation - and thus not just for the elicitation of questionnaire responses. With farm questionnaire surveys being adopted widely by the research community, it is an opportune time to highlight a recent case study of the Taw catchment, Devon, UK. This serves as an example of co-construction of a DSS via a co-ordinated and integrated approach to expert elicitation with a farmer questionnaire survey as a central methodology. The aim of the paper is to detail the core aspects of an iterative cycle of participatory environmental management and DSS development for water quality protection and consider the multiple benefits of co-ordinated programmes of engagement with the farming community in this process.

KW - Decision support

KW - Expert

KW - Farmer

KW - Local knowledge

KW - Questionaire survey

KW - Stakeholder participation

KW - Uncertainty

KW - Water quality

U2 - 10.1016/j.envsoft.2011.09.013

DO - 10.1016/j.envsoft.2011.09.013

M3 - Journal article

VL - 36

SP - 76

EP - 85

JO - Environmental Modelling and Software

JF - Environmental Modelling and Software

SN - 1364-8152

ER -