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Adapting to Climate Change - An Open Data Platform for Cumulative Environmental Analysis and Management

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Book cover Computational Science and Its Applications -- ICCSA 2015 (ICCSA 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9155))

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Abstract

The frequency of extreme weather events has accelerated, an apparent outcome of progressive climate change. Excess water is a significant consequence of these events and is now the leading cause of insurance claims for infrastructure and property damage.

Governments recognize that plans for growth must reflect communities’ needs, strengths and opportunities while balancing the cumulative effects of economic growth with environmental concerns. Legislation must incorporate the cumulative effects of economic growth with adaptation to weather events to protect the environment and citizens, while ensuring that products of growth such as buildings and infrastructure are resilient. For such a process to be effective it will be necessary for the private sector to develop and operate cumulative effect decision support software (CEDSS) tools and to work closely with all levels of government including watershed management authorities (WMAs) that supply environmental data. Such cooperation and sharing will require a new Open Data information-sharing platform managed by the private sector. This paper outlines that platform, its operation and possible governance model.

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References

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Correspondence to Donald Cowan .

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© 2015 Springer International Publishing Switzerland

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Cowan, D., Alencar, P., McGarry, F., Palmer, R.M. (2015). Adapting to Climate Change - An Open Data Platform for Cumulative Environmental Analysis and Management. In: Gervasi, O., et al. Computational Science and Its Applications -- ICCSA 2015. ICCSA 2015. Lecture Notes in Computer Science(), vol 9155. Springer, Cham. https://doi.org/10.1007/978-3-319-21404-7_1

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  • DOI: https://doi.org/10.1007/978-3-319-21404-7_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-21403-0

  • Online ISBN: 978-3-319-21404-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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