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Problem

Problem. Raw imagery -> Quantitative information. Various organisations (Commonwealth and State Govt, universities, Private industry etc. Fragmented approach formats storage locations methodology analysis classification hence limited collaboration and reuse. Courtesy of UWA.

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Problem

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  1. Problem Raw imagery -> Quantitative information Various organisations (Commonwealth and State Govt, universities, Private industry etc. • Fragmented approach • formats • storage locations • methodology • analysis • classification • hence limited collaboration and reuse Courtesy of UWA Courtesy of SeaGIS Courtesy of IMOS Exponential growth in data and time intensive to annotate

  2. Draft: Tony Rees (CSIRO) Standardised classification

  3. Draft Workflow • Benefits: • Cost saving through less time spent manually annotating • Increased collaboration • Better science tools Friedman, A.L., 2013, 'Automated interpretation of benthic stereo imagery', PhD thesis, Australian Centre for Field Robotics, University of Sydney

  4. Acknowledgement / Further information The many collaborators on the project and the Technical Working Group (TWG) who without their support this project would not be possible This project includes development funded by the Australian National Data Service (ANDS, http://ands.org.au) and the National eResearch Collaboration Tools and Resources (NeCTAR, http://nectar.org.au). ANDS is supported by the Australian Government through the National Collaborative Research Infrastructure Strategy Program and the Education Investment Fund (EIF) Super Science Initiative. NeCTAR is an Australian Government project conducted as part of the Super Science initiative and financed by the Education Investment Fund. The University of Melbourne has been appointed the lead agent by the Commonwealth of Australia, Department of Industry, Innovation, Science, Research and Tertiary Education. http://catami-australia.blogspot.com.au/ http://catami.github.com

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