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Valuing regional geoscientific data acquisition programmes: addressing issues of quantification,uncertainty and risk

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Abstract:

Geological surveys worldwide are involved with research in support of sustainable mineral resource development.The socio-economic benefits to be derived from these activities, however, continue to raise organisational and government sector questions. Fundamental questions include whether or not the resources committed are appropriate and in economic balance with the total benefits to be derived. Another question concerns the degree to which such services should be funded by the community at large. These questions in turn raise important issues regarding the role and cost of geological surveys, the impact of their services, and how they should maximise community benefit from their activities and expertise. To assess the value of geoscientific information,standard valuation processes need to be modified. This paper reports on a methodology designed to quantify the ‘worth’ of programmes upgrading regional geoscientific infrastructure. An interdisciplinary approach is used to measure the impact of geoscientific information using quantitative resource assessment, computer-based mineral potential modelling, statistical analysis and risk quantification to model decision-processes and assess the impact of additional data. These modelling stages are used to address problems of complexity,uncertainty and credibility in the valuation of geoscientific data. A case study demonstrates the application of the methodology to generate a dollar value for current regional data upgrade programmes in the Geological Survey of Queensland. The results obtained are used for strategic planning of future data acquisition programmes aimed at supporting mineral resource management and stimulating effective exploration activity.

Document Type: Research Article

DOI: https://doi.org/10.1111/1477-8947.00006

Affiliations: 1: WH Bryan Mining Geology Research Centre, University of Queensland, Brisbane, Australia, 2: School of Economics, University of Queensland, Brisbane, Australia

Publication date: 2002-02-01

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