Datasets:
Update Dataset descriptors: NEON links, highlight trait annotations
Browse filesEdited accoring to this discussion: https://huggingface.co/datasets/imageomics/Hawaii-beetles/discussions/1
Dataset description should include that these beetles are all from the Hawaii NEON site, a link to NEON at first mention (in description) and in the acknowledgements section. >> DONE! ✅
Also should highlight that these images include trait annotations/measurements! >> DONE! ✅
Citation section should be included too. >> DONE! ✅
README.md
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@@ -43,9 +43,16 @@ size_categories: 1K<n<10K # ex: n<1K, 1K<n<10K, 10K<n<100K, 100K<n<1M, ...
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### Key Uses
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* species-level classification or retrieval
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* automated extraction of morphological traits (elytra length)
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* ecological modelling via linkage to NEON environmental streams
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## Dataset Structure
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```
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For instance, if your data includes people or endangered species. -->
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Our data does not contain any personal and sensitive Information.
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## Licensing Information
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Images and associated metadata: [Creative Commons BY 4.0](https://creativecommons.org/licenses/by/4.0/).
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## Acknowledgements
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This work was supported by both the [Imageomics Institute](https://imageomics.org) and the [AI and Biodiversity Change (ABC) Global Center](https://www.biodiversityai.org/). The Imageomics Institute is funded by the US National Science Foundation's Harnessing the Data Revolution (HDR) program under [Award #2118240](https://www.nsf.gov/awardsearch/showAward?AWD_ID=2118240) (Imageomics: A New Frontier of Biological Information Powered by Knowledge-Guided Machine Learning).
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S. Record and A. East were additionally supported by the US National Science Foundation's [Award No. 242918](https://www.nsf.gov/awardsearch/showAward?AWD_ID=2429418&HistoricalAwards=false) and by Hatch project Award #MEO-022425 from the US Department of Agriculture’s National Institute of Food and Agriculture.
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This material is based in part upon work supported by the National Ecological Observatory Network (NEON), a program sponsored by the U.S. National Science Foundation (NSF) and operated under cooperative agreement by Battelle.
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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 US National Science Foundation, the US Department of Agriculture, or Natural Sciences and Engineering Research Council of Canada.
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```bibtex
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@dataset{
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title = {
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author = {S M Rayeed and Mridul Khurana and Alyson East and Samuel Stevens and Iuliia Zarubiieva and Jiaman (Lisa) Wu and Isadora E. Fluck and Scott C. Lowe and Elizabeth G.
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Campolongo and Evan D. Donoso and Tanya Berger-Wolf and Hilmar Lapp and Charles V Stewart and Graham W. Taylor and Sydne Record},
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year = {2025},
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url = {https://huggingface.co/datasets/imageomics/
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note = {Version 1.0, CC-BY-4.0
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}
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-->
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## Dataset Description
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This dataset comprises 1,614 high-resolution PNG images of individual ground-beetle
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specimens (Coleoptera: Carabidae) representing 14 distinct species.
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All specimens were collected by the [U.S. National Ecological Observatory Network (NEON)](https://www.neonscience.org/)
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at the Pu'u Maka'ala Natural Area Reserve [](https://www.neonscience.org/field-sites/puum)
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on the Island of Hawai'i (the Big Island).
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Each image is accompanied by trait annotations and measurements,
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providing valuable data for morphological and ecological analyses of these ground-beetle species from the Hawaii NEON site.
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### Key Uses
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* species-level classification or retrieval
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* automated extraction of morphological traits (elytra length)
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* ecological modelling via linkage to NEON environmental streams
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## Dataset Structure
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```
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For instance, if your data includes people or endangered species. -->
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Our data does not contain any personal and sensitive Information.
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## Licensing Information
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Images and associated metadata: [Creative Commons BY 4.0](https://creativecommons.org/licenses/by/4.0/).
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## Acknowledgements
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This work was supported by both the [Imageomics Institute](https://imageomics.org) and the [AI and Biodiversity Change (ABC) Global Center](https://www.biodiversityai.org/). The Imageomics Institute is funded by the US National Science Foundation's Harnessing the Data Revolution (HDR) program under [Award #2118240](https://www.nsf.gov/awardsearch/showAward?AWD_ID=2118240) (Imageomics: A New Frontier of Biological Information Powered by Knowledge-Guided Machine Learning).
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S. Record and A. East were additionally supported by the US National Science Foundation's [Award No. 242918](https://www.nsf.gov/awardsearch/showAward?AWD_ID=2429418&HistoricalAwards=false) and by Hatch project Award #MEO-022425 from the US Department of Agriculture’s National Institute of Food and Agriculture.
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This material is based in part upon work supported by the [U.S. National Ecological Observatory Network (NEON)](https://www.neonscience.org/), a program sponsored by the [U.S. National Science Foundation (NSF)](https://www.nsf.gov/) and operated under cooperative agreement by [Battelle](https://www.battelle.org/).
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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 US National Science Foundation, the US Department of Agriculture, or Natural Sciences and Engineering Research Council of Canada.
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## Citation
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```bibtex
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@dataset{rayeed2025HawaiiBeetles,
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title = {Hawaii Beetles},
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author = {S M Rayeed and Mridul Khurana and Alyson East and Samuel Stevens and Iuliia Zarubiieva and Jiaman (Lisa) Wu and Isadora E. Fluck and Scott C. Lowe and Elizabeth G.
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Campolongo and Evan D. Donoso and Tanya Berger-Wolf and Hilmar Lapp and Charles V Stewart and Graham W. Taylor and Sydne Record},
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year = {2025},
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url = {https://huggingface.co/datasets/imageomics/Hawaii-beetles},
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note = {Version 1.0, CC-BY-4.0}
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}
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