1887
2nd Australasian Exploration Geoscience Conference: Data to Discovery
  • ISSN: 2202-0586
  • E-ISSN:

Abstract

Summary

We report on the results and lessons learned from Australia’s largest minerals exploration crowdsourcing challenge - the OZ Minerals Explorer Challenge. We discuss some of the challenges in running an international competition with a large amount of technical data at scale, and the methods used to engage innovators from outside the traditional geoscience community. We discuss specific examples of innovative approaches which have been submitted. We also examine the ways in which open innovation and crowdsourcing can provide a novel approach to rapidly evaluating tenement prospectivity and to unlock value from companies’ data assets.

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/content/journals/10.1080/22020586.2019.12072988
2019-12-01
2026-01-19
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References

  1. Betts, P.G., Valenta, R.K. and Findlay, J., 2003. Evolution of the Mt Woods Inlier, northern Gawler Craton: an integrated structural and aeromagnetic analysis. Tectonophysics, 366:83-111
  2. Cathers, G., 2010, A combined geological and geochemical approach to determine the petrogenesis and geochronology of the Mount Hawker and Pluto packages, Gawler Craton, South Australia. Macquarie University, unpublished Honours thesis.
  3. Department for Energy and Mining, Government of South Australia, 2019, Geology of South Australia - Gawler Craton. http://www.energymining.sa.gov.au/minerals/geoscience/geol ogy/gawler_craton, accessed 15 March 2019
  4. Freeman, H., Tomkinson, M., 2010, Geological setting of iron oxide related mineralisation in the southern Mount Woods domain, South Australia: in Porter, T. M. (Ed) Hydrothermal Iron Oxide Copper-Gold and Related Deposits: A Global Perspective. v.3 pp. 171-190, PGC Publishing, Adelaide
  5. Robertson, J. (2019) explore_australia - Access to Australiawide public exploration data (Python package - v0.1). Source code: https://github.com/unearthed/explore_australia. doi: 10.5281/zenodo.2600654
/content/journals/10.1080/22020586.2019.12072988
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  • Article Type: Research Article
Keyword(s): crowdsourcing; data science; exploration; open data; open innovation
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