Add additional points of clarification, resolve mis-described column value

README.md

@@ -3,7 +3,7 @@ license: cc-by-4.0
 language:
 - en
 - la
-pretty_name: Hawaii_Beetles
+pretty_name: Hawaii Beetles
 tags: 
 - ecology
 - animals
@@ -21,44 +21,37 @@ task_categories:
 - image-classification
 - image-segmentation
 - object-detection
-
-size_categories: 1K<n<10K # ex: n<1K, 1K<n<10K, 10K<n<100K, 100K<n<1M, ...
+size_categories: 1K<n<10K
+description: "Collection of individual ground-beetle (Coleoptera: Carabidae) specimen images with corresponding trait annotations and measurements for all 14 distinct species. All specimens were collected by the U.S. National Ecological Observatory Network (NEON) at the Pu'u Maka'ala Natural Area Reserve on the Island of Hawai'i (the Big Island)."
 ---
 
-<div align="justify">
-
-# Dataset Card for Hawaii_Beetles
+# Dataset Card for Hawaii Beetles
 
-<!-- Provide a quick summary of what the dataset is or can be used for. --> 
+Collection of ground beetle specimen images; specimens collected by the [U.S. National Ecological Observatory Network (NEON)](https://www.neonscience.org/) at the [Pu'u Maka'ala Natural Area Reserve](https://www.neonscience.org/field-sites/puum) on the Island of Hawai'i (the Big Island). This collection includes both group images (by-tray) and the individual segmented individuals.
 
 ## Dataset Details
 
 ### Dataset Description
 <!--
 - **Curated by:** Lisa Wu, S M Rayeed, Mridul Khurana, Alyson East, Samuel Stevens, Iuliia Eyriay, Scott Lowe, Graham Taylor, Sydne Record
-- **Language(s):** English; Latin <!-- Provide the basic links for the dataset. These will show up on the sidebar to the right of your dataset card ("Curated by" too).
-- **Homepage:** https://huggingface.co/datasets/imageomics/beetle-intake/tree/main
-- **Repository:** https://github.com/Imageomics/beetle-intake
-- **Paper:** [[Paper Link]](https://github.com/Imageomics-ABC-edu/final-project-beetles/blob/main/Beetle-Intake-report.pdf)
-
+- **Language(s):** English; Latin
+- **Homepage:**
+- **Repository:**
 --> 
+- **Paper:** [Coming Soon!]() <!-- Add arXiv link once up -->
 
 ## Dataset Description
 
-This dataset comprises 1,614 high-resolution PNG images of individual ground-beetle 
-specimens (Coleoptera: Carabidae) representing 14 distinct species. 
-All specimens were collected by the [U.S. National Ecological Observatory Network (NEON)](https://www.neonscience.org/) 
-at the Pu'u Maka'ala Natural Area Reserve [](https://www.neonscience.org/field-sites/puum) 
-on the Island of Hawai'i (the Big Island). 
-Each image is accompanied by trait annotations and measurements, 
-providing valuable data for morphological and ecological analyses of these ground-beetle species from the Hawaii NEON site.
+This dataset comprises 1,614 high-resolution PNG images of individual ground-beetle specimens (Coleoptera: Carabidae) representing 14 distinct species. The group images from which the individuals were segmented are also included.
+All specimens were collected by [NEON](https://www.neonscience.org/) at the [Pu'u Maka'ala Natural Area Reserve (PUUM)](https://www.neonscience.org/field-sites/puum) on the Island of Hawai'i (the Big Island). 
+Each image is accompanied by trait annotations and measurements, providing valuable data for morphological and ecological analyses of these ground-beetle species from the Hawaii NEON site.
 
 
 ### Key Uses
 * species-level classification or retrieval  
 * object detection / instance segmentation on natural-history collections  
 * automated extraction of morphological traits (elytra length)  
-* ecological modelling via linkage to NEON environmental streams  
+* ecological modeling via linkage to NEON environmental streams  
 
 
 ## Dataset Structure
@@ -70,7 +63,6 @@ providing valuable data for morphological and ecological analyses of these groun
 /individual_specimens
     IMG_<id>_specimen_<number>_<taxonID>_<individualID>.png
     ...
-
 images_metadata.csv
 trait_annotations.csv
 
@@ -78,30 +70,31 @@ README.md
 ```
 
 ### Data Fields
+
 **images_metadata.csv**:
-- `groupImageFilePath`: Path to grouped beetle images. e.g., `group_images/IMG_<id>.png` where `IMG_<id>` is the image name assigned by the camera roll.
-- `individualImageFilePath`: Path to the individually cropped beetle image, e.g., `individual_specimens/IMG_<id>_specimen_<number>_<taxonID>_<individualID>.png`, where `<id>` matches the group image and `<number>` indicates the beetle's position within that group image.
-- `individualID`: Unique identification number assigned to each individual beetle. This begins with NEON_BET.D20 to show that the unique ID corresponds to a beetle from the National Ecological Observatory Network's Domain 20, followed by six digits.
-- `taxonID`: All pinned beetles in this dataset have been identified to genus and species. Here a six-letter code is given specifiying the first three letters of the genus followed by the first three letters of the specific epithet.
-- `ScientificName`: Binomial scientific name of the specimen.
-- `plotID`: A code that corresponds to the NEON plot in which the individual beetle was collected.
-- `trapID`: The cardinal direction (E - east, S - south, W - west) indicating which side of the plot the beetle was collected from.
-- `plotTrapID`: A three letter code that corresponds to the NEON plot in which the individual beetle was collected along with direction.
-- `collectDate`: The date of field collection of the pitfall trap from which NEON staff collected the beetle specimen. It follows the `YYYYMMDD` format.
-- `ownerInstitutionCode`: NEON owner code
-- `catalogNumber`: NEON catalog number
+- `individualImageFilePath`: Path to the individually cropped beetle image, e.g., `individual_specimens/IMG_<id>_specimen_<number>_<taxonID>_<individualID>.png`, where `<id>` matches the group image and `<number>` indicates the beetle's position within that group image. Ex: `individual_specimens/IMG_0093_specimen_1_MECKON_NEON.BET.D20.000001.png`.
+- `groupImageFilePath`: Path to grouped beetle images. e.g., `group_images/IMG_<id>.png` where `IMG_<id>` is the image name assigned by the camera roll. Ex: `group_images/IMG_0093.png`.
+- `individualID`: Unique identification number assigned by NEON to each individual beetle. This begins with NEON_BET.D20 to show that the unique ID corresponds to a beetle from the National Ecological Observatory Network's Domain 20, followed by six digits. Ex: `NEON.BET.D20.000001`.
+- `taxonID`: All pinned beetles in this dataset have been identified to genus and species. Here a six-letter code is given specifying the first three letters of the genus followed by the first three letters of the specific epithet. Ex: `MECKON`.
+- `ScientificName`: Binomial scientific name of the specimen (`<Genus specific epithet>`, ex: `Mecyclothorax konanus`).
+- `plotID`: A numeric code that corresponds to the NEON plot in which the individual beetle was collected (numbers, up to 18).
+- `trapID`: The cardinal direction (`E` - east, `S` - south, `W` - west) indicating which side of the plot the beetle was collected from.
+- `plotTrapID`: A three letter code that corresponds to the NEON plot from which the individual beetle was collected along with direction (ex: `006W` for `plotID` 6 and `trapID` W).
+- `collectDate`: The date NEON staff collected the beetle specimen from the pitfall trap. It follows the `YYYYMMDD` format.
+- `ownerInstitutionCode`: NEON owner code (`NEON`).
+- `catalogNumber`: NEON catalog number (ex: `DP1.10022.001`).
 
 <br>
 
 **trait_annotations.csv**:
 - `groupImageFilePath`: File path to grouped beetle specimen images. Format: `group_images/IMG_<id>.png`, where `IMG_<id>` corresponds to the unique image identifier assigned by the camera system.
 - `BeetlePosition`: Ordinal position of the individual beetle specimen within the group image (dorsal view). Specimens are numbered sequentially from top to bottom: topmost specimen = 1, subsequent specimens = 2, 3, 4, etc.
-- `individualID`: Unique identifier for each individual beetle specimen, derived from the combination of `ImageFilePath` and `BeetlePosition` values.
-- `coords_scalebar`: X and Y coordinate pairs defining the endpoints of the 1 cm reference scalebar, positioned in the upper or upper-left portion of each image.
-- `coords_elytra_max_length`: X and Y coordinate pairs defining the endpoints of the maximum elytral length measurement. Measured from the midpoint of the elytro-pronotal suture (junction between pronotum and elytra) to the midpoint of the elytral apex (posterior terminus of the elytra).
-- `coords_basal_pronotum_width`: X and Y coordinate pairs defining the endpoints of the basal pronotal width measurement at the elytro-pronotal junction.
-- `coords_elytra_max_width`: X and Y coordinate pairs defining the endpoints of the maximum elytral width measurement. Represents the greatest transverse distance across both elytra, measured orthogonal to the elytral length axis.
-- `px_scalebar`: Euclidean distance between coordinate endpoints of the reference scalebar (`coords_scalebar`) expressed in pixels.
+- `individualID`: Unique identifier assigned by NEON to each individual beetle specimen. This begins with NEON_BET.D20 to show that the unique ID corresponds to a beetle from the National Ecological Observatory Network's Domain 20, followed by six digits. Ex: `NEON.BET.D20.000001`. This allows for linking to the `images_metadata.csv` and additional metadata provided through the [NEON data portal](https://www.neonscience.org/data).
+- `coords_scalebar`: X and Y coordinate pairs defining the endpoints of the 1 cm reference scalebar, positioned in the upper or upper-left portion of each image. Ex: `"[[5713.91, 3045.68, 5701.21, 2265.92]]"`.
+- `coords_elytra_max_length`: X and Y coordinate pairs defining the endpoints of the maximum elytral length measurement. Measured from the midpoint of the elytro-pronotal suture (junction between pronotum and elytra) to the midpoint of the elytral apex (posterior terminus of the elytra). Ex: `"[[3865.5, 1245.87, 3881.25, 1045.81]]"`.
+- `coords_basal_pronotum_width`: X and Y coordinate pairs defining the endpoints of the basal pronotal width measurement at the elytro-pronotal junction. Ex: `"[[3922.92, 1046.2, 3872.53, 1035.06]]"`.
+- `coords_elytra_max_width`: X and Y coordinate pairs defining the endpoints of the maximum elytral width measurement. Represents the greatest transverse distance across both elytra, measured orthogonal to the elytral length axis. Ex: `"[[3960.08, 1145.79, 3814.38, 1123.85]]"`.
+- `px_scalebar`: Euclidean distance between coordinate endpoints of the reference scalebar (`coords_scalebar`) expressed in pixels, measured to ____ precision.
 - `px_elytra_max_length`: Euclidean distance between coordinate endpoints of the maximum elytral length (`coords_elytra_max_length`) expressed in pixels.
 - `px_basal_pronotum_width`: Euclidean distance between coordinate endpoints of the basal pronotal width (`coords_basal_pronotum_width`) expressed in pixels.
 - `px_elytra_max_width`: Euclidean distance between coordinate endpoints of the maximum elytral width (`coords_elytra_max_width`) expressed in pixels.
@@ -111,13 +104,12 @@ README.md
 - `cm_elytra_max_width`: Calibrated maximum elytral width in centimeters, representing the greatest transverse dimension across the fused elytra, calculated by converting pixel measurements using the scalebar calibration factor.
 
 
-
 ## Dataset Creation
 
-This dataset was compiled as part of the field component of the Experiential Introduction to AI and Ecology Course run by the Imageomics Institute and the AI and Biodiversity Change (ABC) Global Climate Center. This field work was done on the island of Hawai'i January 15-29, 2025.
+This dataset was compiled as part of the field component of the Experiential Introduction to AI and Ecology Course run by the Imageomics Institute and the AI and Biodiversity Change (ABC) Global Center. This field work was done on the island of Hawai'i January 15-29, 2025.
 
 ### Curation Rationale
-<!-- Motivation for the creation of this dataset. For instance, what you intended to study and why that required curation of a new dataset (or if it's newly collected data and why the data was collected (intended use)), etc. -->
+
 Ground beetles (Coleoptera: Carabidae) serve as critical bioindicators for ecosystem health, providing valuable insights into biodiversity shifts driven by environmental changes. Understanding their distribution, morphological traits, and responses to environmental conditions is essential for ecological research and conservation efforts. While the National Ecological Observatory Network (NEON) maintains an extensive collection of carabid specimens, these primarily exist as physical collections, restricting widespread research access and large-scale analysis. Despite the ecological significance of invertebrates, global trait databases remain heavily biased toward vertebrates and plants, leaving a critical “invertebrate gap” that hinders comprehensive ecological analyses, particularly for hyper-diverse groups like carabids. Existing beetle datasets lack standardized, high-resolution trait measurements like those provided here, limiting trait-based ecological studies. Morphological traits, such as elytra length and width, are paramount because they directly link to ecological processes like dispersal, niche partitioning, and responses to environmental stressors, enabling predictive modeling of biodiversity under global change.
 
 ### Source Data
@@ -127,39 +119,60 @@ The specimens come from the PUUM [NEON site](https://www.neonscience.org/field-s
 Our team photographed the beetles in 2025, using Canon EOS DSLR (model 7D).
 
 #### Data Collection and Processing
-<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, re-sizing of images, tools and libraries used, etc. 
-This is what _you_ did to it following collection from the original source; it will be overall processing if you collected the data initially.
--->
+
 Beetles were collected by PUUM NEON field technicians from 2018 through 2024.
 
-Specimens and identification are provided by [NEON Ground beetles sampled from pitfall traps](https://data.neonscience.org/data-products/DP1.10022.001)
+Specimens and identification are provided by [NEON Ground beetles sampled from pitfall traps](https://data.neonscience.org/data-products/DP1.10022.001).
 
+#### Who are the source data producers?
 
-### Personal and Sensitive Information
-<!-- 
-For instance, if your data includes people or endangered species. -->
-Our data does not contain any personal and sensitive Information.
+This dataset is a collection of images taken of the ground beetle collection at the PUUM NEON field site, collected by their technicians from 2018 through 2024. The associated labels and metadata are provided by the NEON team and were recorded based on the labels associated to each pinned specimen.
 
 
-## Licensing Information
+### Annotations
 
-Images and associated metadata: [Creative Commons Attribution 4.0](https://creativecommons.org/licenses/by/4.0/).
+After imaging all the specimens, the data curation team segmented the individuals and measured the elytra length and width for each.
 
+#### Annotation process
+[More Information Needed]
+<!-- This section describes the annotation process such as annotation tools used, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
 
-## Acknowledgements
+#### Who are the annotators?
+[More Information Needed]
+<!-- This section describes the people or systems who created the annotations. -->
 
-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). 
-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) and 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).
-This dataset draws on research supported by the Social Sciences and Humanities Research Council.
 
-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) (EPSCOR Research Fellows: NSF: Advancing National Ecological Observatory Network-Enabled Science and Workforce Development at the University of Maine with Artificial Intelligence) and by Hatch project Award #MEO-022425 from the US Department of Agriculture’s National Institute of Food and Agriculture. 
+### Personal and Sensitive Information
 
-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/).
+Our data does not contain any personal or sensitive Information.
 
-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, Natural Sciences and Engineering Research Council of Canada, Social Sciences and Humanities Research Council, or the US Department of Agriculture.
+## Considerations for Using the Data
+[More Information Needed]
+<!--
+Things to consider while working with the dataset. For instance, maybe there are hybrids and they are labeled in the `hybrid_stat` column, so to get a subset without hybrids, subset to all instances in the metadata file such that `hybrid_stat` is _not_ "hybrid".
+-->
+
+### Bias, Risks, and Limitations
+[More Information Needed]
+<!-- This section is meant to convey both technical and sociotechnical limitations. Could also address misuse, malicious use, and uses that the dataset will not work well for.-->
+
+<!-- For instance, if your data exhibits a long-tailed distribution (and why). -->
 
+### Recommendations
+[More Information Needed]
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+
+## Licensing Information
+
+Images and associated metadata: [Creative Commons Attribution 4.0](https://creativecommons.org/licenses/by/4.0/).
 
 ## Citation
+
+If you use this dataset in your research, please cite both the dataset and our paper.
+
+**Dataset:**
+
 ```bibtex
 @dataset{rayeed2025HawaiiBeetles,
   title  = {Hawaii Beetles},
@@ -170,3 +183,26 @@ Campolongo and Evan D. Donoso and Tanya Berger-Wolf and Hilmar Lapp and Charles
   note   = {Version 1.0, CC-BY-4.0},
   doi    = {}
 }
+
+
+**Paper:** Coming Soon!
+
+<!-- 
+
+```bibtex
+
+```
+-->
+
+
+## Acknowledgements
+
+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). 
+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) and 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).
+This dataset draws on research supported by the Social Sciences and Humanities Research Council.
+
+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) (EPSCOR Research Fellows: NSF: Advancing National Ecological Observatory Network-Enabled Science and Workforce Development at the University of Maine with Artificial Intelligence) and by Hatch project Award #MEO-022425 from the US Department of Agriculture’s National Institute of Food and Agriculture. 
+
+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/). Furthermore, this material uses specimens and/or samples collected as part of the NEON Program.
+
+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, the Natural Sciences and Engineering Research Council of Canada, or the Social Sciences and Humanities Research Council.