Datasets:
Add SSHRC to acknowledgement, description to yaml
Browse files
README.md
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@@ -14,9 +14,11 @@ tags:
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- image
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- animals
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- CV
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size_categories:
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- 10K<n<100K
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pretty_name: The Wilds Camera Trap Data
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---
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# Dataset Card for The Wilds Camera Trap Data
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@@ -229,20 +231,17 @@ This dataset is dedicated to the public domain under a [CC0 license](https://cre
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## Acknowledgements
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This project is supported by
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[Award # 2112606](https://www.nsf.gov/awardsearch/showAward?AWD_ID=2112606), Intelligent
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Cyberinfrastructure with Computational Learning in the Environment (ICICLE), and by the [Imageomics Institute](https://imageomics.org),
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which is funded by the US National Science Foundation's Harnessing the Data Revolution (HDR) program under
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[Award #2118240](https://www.nsf.gov/awardsearch/showAward?AWD_ID=2118240)
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(Imageomics: A New Frontier of Biological Information Powered by Knowledge-Guided Machine Learning).
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This work is also supported by the AI and Biodiversity Change (ABC) Global Center.
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The ABC Global Center is funded by the US National Science Foundation under Award No. 2330423
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and the Natural Sciences and Engineering Research Council of Canada under Award No. 585136.
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Any opinions, findings
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and do not necessarily reflect the views of the National Science Foundation or the Natural Sciences and
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Engineering Research Council of Canada.
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Special thanks to Dan Beetem and [The Wilds](https://www.thewilds.org/) in Ohio for providing access to deployment sites
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and supporting this wildlife monitoring research. We thank the Columbus Zoo Aquarium for their support in facilitating
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- image
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- animals
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- CV
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- video
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size_categories:
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- 10K<n<100K
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pretty_name: The Wilds Camera Trap Data
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description: "Images and video captured from camera traps deployed at The Wilds safari park in Ohio during Summer 2025. It supports ecological monitoring, animal behavior analysis, and biodiversity studies."
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---
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# Dataset Card for The Wilds Camera Trap Data
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## Acknowledgements
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This project is supported by the [AI Institute for Intelligent Cyberinfrastructure with Computational Learning in the Environment (ICICLE)](https://icicle.osu.edu/), which is funded by the US National Science Foundation under [Award #2112606](https://www.nsf.gov/awardsearch/showAward?AWD_ID=2112606), and by the [Imageomics Institute](https://imageomics.org),
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which is funded by the US National Science Foundation's Harnessing the Data Revolution (HDR) program under
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[Award #2118240](https://www.nsf.gov/awardsearch/showAward?AWD_ID=2118240)
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(Imageomics: A New Frontier of Biological Information Powered by Knowledge-Guided Machine Learning).
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This work is also supported by the AI and Biodiversity Change (ABC) Global Center.
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The ABC Global Center is funded by the US National Science Foundation under [Award No. 2330423](https://www.nsf.gov/awardsearch/showAward?AWD_ID=2330423&HistoricalAwards=false)
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and the Natural Sciences and Engineering Research Council of Canada under [Award No. 585136](https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=782440).
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This dataset draws on research supported by the Social Sciences and Humanities Research Council.
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Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation, Natural Sciences and Engineering Research Council of Canada, or Social Sciences and Humanities Research Council.
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Special thanks to Dan Beetem and [The Wilds](https://www.thewilds.org/) in Ohio for providing access to deployment sites
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and supporting this wildlife monitoring research. We thank the Columbus Zoo Aquarium for their support in facilitating
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