README.md

---
license: cc0-1.0
language:
- en
pretty_name: Character Similarity Dataset
description: "Collection of textual trait descriptions of fish along with the corresponding ontology based similarity measures between trait description pairs. The distance is estimated using the Phenoscape Knowledgebase as the ontology."
task_categories:
- feature-extraction
tags:
- biology
- organism
- animals
- fish
- traits
- ontology
- phenoscape
size_categories: 10K<n<100K
configs:
  - config_name: full_data
    data_files:
      - split: train
        path: all/*_TRAINING.tsv.gz
      - split: test
        path: all/*_ALL_NON_TRAIN.tsv.gz
    default: true
  - config_name: characiformes
    data_files:
      - split: train
        path: characiformes/*_TRAINING.tsv.gz
      - split: test
        path: characiformes/*_ALL_NON_TRAIN.tsv.gz
  - config_name: cypriniformes
    data_files:
      - split: train
        path: cypriniformes/*_TRAINING.tsv.gz
      - split: test
        path: cypriniformes/*_ALL_NON_TRAIN.tsv.gz
  - config_name: gymnotiformes
    data_files:
      - split: train
        path: gymnotiformes/*_TRAINING.tsv.gz
      - split: test
        path: gymnotiformes/*_ALL_NON_TRAIN.tsv.gz
  - config_name: siruliformes
    data_files:
      - split: train
        path: siruliformes/*_TRAINING.tsv.gz
      - split: test
        path: siruliformes/*_ALL_NON_TRAIN.tsv.gz
---

# Dataset Card for Character Similarity Dataset

<!-- Provide a quick summary of what the dataset is or can be used for. --> 

## Dataset Details
The Character Similarity Dataset is a collection of textual trait descriptions along with the corresponding ontology based similarity measures between trait description pairs. The distance is estimated using the [Phenoscape Knowledgebase](https://kb.phenoscape.org/) as the ontology.

### Dataset Description

- **Curated by:** Jim Balhoff, Soumyashree Kar, Juan Garcia, Hilmar Lapp
- **Language(s) (NLP):** English
- **Repository:** [Imageomics/char-sim](https://github.com/Imageomics/char-sim)
- **Paper:** Coming soon!

The Character Similarity Dataset is a collection of 19K textual trait descriptions of fish collected from the [Phenoscape Knowledgebase](https://kb.phenoscape.org/). The dataset also contains the corresponding pairwise similarity measures between trait descriptors (i.e., maxIC, Jaccard, SimGIC). These metrics estimate semantic similarity between the ontological representation of the traits descriptions per the Phenoscape Knowledgebase. The goal is to use this pairwise similarities to inform an embedding space that preserves the structure of the underlying ontology.

### Supported Tasks and Leaderboards
Task: Aligned feature extraction. Metric: Spearman's correlation coefficient. 

| Model              | Test set |
|:-------------------|:-----------|
| [**Trait2Vec**](https://huggingface.co/imageomics/trait2vec) | **0.7057** |

<!-- Provide benchmarking results -->


## Dataset Structure

```
raw-source/
    phenex-data-merged.ofn.gz
    phenoscape-kb-tbox-classified.ttl.gz
processed-data/
    all/
        data_{percentage}p_TRAINING.tsv.gz
        data_{percentage}p_ALL_NON_TRAIN.tsv.gz
        data_{percentage}p_NON_OVERLAP.tsv.gz
    characiformes/
        data_{percentage}p_TRAINING.tsv.gz
        data_{percentage}p_ALL_NON_TRAIN.tsv.gz
        data_{percentage}p_NON_OVERLAP.tsv.gz
    cypriniformes/
        data_{percentage}p_TRAINING.tsv.gz
        data_{percentage}p_ALL_NON_TRAIN.tsv.gz
        data_{percentage}p_NON_OVERLAP.tsv.gz
    gymnotiformes/
        data_{percentage}p_TRAINING.tsv.gz
        data_{percentage}p_ALL_NON_TRAIN.tsv.gz
        data_{percentage}p_NON_OVERLAP.tsv.gz
    siruliformes/
        data_{percentage}p_TRAINING.tsv.gz
        data_{percentage}p_ALL_NON_TRAIN.tsv.gz
        data_{percentage}p_NON_OVERLAP.tsv.gz

```

`phenex-data-merged.ofn.gz` and `phenoscape-kb-tbox-classified.ttl.gz` contain URLs to access the trait data from [Phenoscape Knowledgebase](https://kb.phenoscape.org/). Running the processing script creates the four subset folders (`characiformes/`, `cypriniformes/`, `gymnotiformes/`, and `siruliformes/`, each an order of fish), then combines their data into the `all/` directory to create the training and test datasets. 

Note: `percentage` is the parameter passed for the percentage of the data to use for training; in this case, `percentage = 80`.

### Data Instances
Percentage is the proportion of data that will be used for training (i.e. data_{percentage}p_TRAINING.tsv.gz). In case the percentage is smaller than 100, the remaining proportion of the dataset is stored in data{percentage}p_ALL_NON_TRAIN.tsv.gz and a subset of this in data_{percentage}p_NON_OVERLAP.tsv.gz. Each of this files corresponds to a 

<!--
Describe data files

Ex: All images are named <img_id>.png, each within a folder named for the species. They are 1024 x 1024, and the color has been standardized using <link to color standardization package>.
-->

### Data Fields

**data_{percentage}p_TRAINING.tsv.gz**: [ADD SUMMARY HERE + descriptions of columns below]
  - `id_1`:
  - `id_2`:
  - `maxIC`: Ontology based measure 
  - `jaccard`: Ontology based measure
  - `simGIC`: Ontology based measure
  - `order`: Pairwise score indices
  - `character_1`: 
  - `desc_1`: Textual trait description.
  - `character_2`: 
  - `desc_2`: Textual trait description.
[More Information Needed]
<!--
Describe the types of the data files or the columns in a CSV with metadata.

Ex: 
**metadata.csv**:
  - `img_id`: Unique identifier for the dataset. 
  - `specimen_id`: ID of specimen in the image, provided by museum data source. There are multiple images of a single specimen.
  - `species`: Species of the specimen in the image. There are N different species of <genus> of <animal>.
  - `view`: View of the specimen in the image (e.g., `ventral` or `dorsal` OR `top` or `bottom`, etc.; specify options where reasonable).
  - `file_name`: Relative path to image from the root of the directory (`<species>/<img_id>.png`); allows for image to be displayed in the dataset viewer alongside its associated metadata.
-->

### Data Splits

None. Split is determined by the user. [NEEDS UPDATING to reflect change to train/test split]

## Dataset Creation

### Curation Rationale
[More Information Needed]
<!-- 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. -->

### Source Data
Data was collected from the [Phenoscape Knowledgebase](https://kb.phenoscape.org/).
<!-- This section describes the source data (e.g., news text and headlines, social media posts, translated sentences, ...). As well as an original source it was created from (e.g., sampling from Zenodo records, compiling images from different aggregators, etc.) -->

#### 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.
-->

#### Who are the source data producers?
[More Information Needed]
<!-- This section describes the people or systems who originally created the data.

Ex: This dataset is a collection of images taken of the butterfly collection housed at the Ohio State University Museum of Biological Diversity. The associated labels and metadata are the information provided with the collection from biologists that study butterflies and supplied the specimens to the museum.
 -->


### Annotations
<!-- 
If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. 

Ex: We standardized the taxonomic labels provided by the various data sources to conform to a uniform 7-rank Linnean structure. (Then, under annotation process, describe how this was done: Our sources used different names for the same kingdom (both _Animalia_ and _Metazoa_), so we chose one for all (_Animalia_). -->

#### 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. -->

#### Who are the annotators?
[More Information Needed]
<!-- This section describes the people or systems who created the annotations. -->

### Personal and Sensitive Information

None 

## Considerations for Using the Data
The distribution of SimGIC scores is skewed towards smaller values. This imbalance may cause the similarity of embeddings to follow the same bias. Consider subsampling to ensure uniform representation of distances. 

### Bias, Risks, and Limitations
This dataset has the biases of the Phenoscape ontology. This means the estimated models embeddings will inherit the ontology's inductive biases, coverage gaps, and evolving definitions. Biological conclusions may differ under alternative metrics (e.g., [Resnik](ADD LINK)) or other phenotype ontologies.

## Licensing Information
This dataset is dedicated to the public domain for the benefit of scientific pursuits. We ask that you cite the dataset and original source data using the below citations if you make use of it in your research.

[CHECK THIS]

## Citation

We ask that you cite the dataset and original source data using the below citations if you make use of it in your research.

**Data**
```
@misc{char-sim-data-2025,
  author = {Jim Balhoff and Soumyashree Kar and Juan Garcia and Hilmar Lapp},
  title = {Character Similarity Dataset},
  year = {2025},
  url = {https://huggingface.co/datasets/imageomics/char-sim-data},
  doi = {<doi once generated>},
  publisher = {Hugging Face}
}
```
<!--
-for an associated paper:
**Paper**
```
@article{<ref_code>,
  title    = {<title>},
  author   = {<author1 and author2>},
  journal  = {<journal_name>},
  year     =  <year>,
  url      = {<DOI_URL>},
  doi      = {<DOI>}
}
```
-->

Please be sure to also cite the original data source:

```bibtext
ADD Phenoscape Knowledgebase citation HERE
```


## Acknowledgements

This work was supported by the [Imageomics Institute](https://imageomics.org), which 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). 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.

<!-- You may also want to credit the source of your data, i.e., if you went to a museum or nature preserve to collect it. -->

## Dataset Card Authors 

Juan Garcia, Jim Balhoff, and Elizabeth Campolongo

## Dataset Card Contact

Please open a [Discussion on the Community Tab](https://huggingface.co/datasets/imageomics/char-sim-data/discussions) with any questions on the dataset.