Add to dataset card.

README.md

@@ -1,9 +1,9 @@
 ---
-license: cc0-1.0
+license: cc-by-3.0
 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."
+description: "Collection of textual trait descriptions of vertebrates (primarily 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:
@@ -41,12 +41,12 @@ configs:
         path: gymnotiformes/*_TRAINING.tsv.gz
       - split: test
         path: gymnotiformes/*_ALL_NON_TRAIN.tsv.gz
-  - config_name: siruliformes
+  - config_name: siluriformes
     data_files:
       - split: train
-        path: siruliformes/*_TRAINING.tsv.gz
+        path: siluriformes/*_TRAINING.tsv.gz
       - split: test
-        path: siruliformes/*_ALL_NON_TRAIN.tsv.gz
+        path: siluriformes/*_ALL_NON_TRAIN.tsv.gz
 ---
 
 # Dataset Card for Character Similarity Dataset
@@ -54,7 +54,7 @@ configs:
 <!-- 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.
+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. The Knowledgebase is built upon a number of OBO ontologies, most importantly the Uberon anatomy ontology.
 
 ### Dataset Description
 
@@ -63,7 +63,7 @@ The Character Similarity Dataset is a collection of textual trait descriptions a
 - **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.
+The Character Similarity Dataset is a collection of 19K textual trait descriptions of fish and other vertebrates 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. 
@@ -105,7 +105,7 @@ processed-data/
 
 ```
 
-`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. 
+`phenex-data-merged.ofn.gz` and `phenoscape-kb-tbox-classified.ttl.gz` are raw data files built as part of the [Phenoscape Knowledgebase](https://kb.phenoscape.org/) construction pipeline. 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`.
 
@@ -151,39 +151,16 @@ None. Split is determined by the user. [NEEDS UPDATING to reflect change to trai
 ## 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. -->
+The overall objective of the Phenoscape Project is to create a scalable infrastructure that enables linking descriptive phenotype observations across different fields of biology by the semantic similarity of their free-text descriptions. This linking is manual and labor intensive; see https://doi.org/10.1093/database/bav040. The dataset created by the Phenoscape project is used here to train a model which produces text embeddings aligned with ontology-derived similarity values.
 
 ### 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 was collected from the [Phenoscape Knowledgebase](https://kb.phenoscape.org/). `phenoscape-kb-tbox-classified.ttl.gz` contains the classified terminology composed of several OBO ontologies as well as generated class expressions materializing various axes of classification. `phenex-data-merged.ofn.gz` contains links from textual character trait descriptions to ontology class expressions.
 
 #### 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.
--->
+The raw data is directly generated by the [Phenoscape build pipeline](https://github.com/phenoscape/pipeline). Further processing to compute ontology-based similarity scores, and to create derived files for model training, is defined by the workflow at https://github.com/Imageomics/char-sim.
 
 #### 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. -->
+The source data was originally created by the curators of the [Phenoscape Project](https://phenoscape.org), a collaborative NSF-funded project.
 
 ### Personal and Sensitive Information
 
@@ -193,12 +170,10 @@ None
 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.
+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 similarity metrics 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]
+This dataset is licensed using a [Creative Commons Attribution 3.0 Unported license](http://creativecommons.org/licenses/by/3.0/) 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.
 
 ## Citation
 
@@ -233,7 +208,42 @@ We ask that you cite the dataset and original source data using the below citati
 Please be sure to also cite the original data source:
 
 ```bibtext
-ADD Phenoscape Knowledgebase citation HERE
+@ARTICLE{Balhoff2016-aw,
+  title    = "The Phenoscape Knowledgebase: tools and {APIs} for computing
+              across phenotypes from evolutionary diversity and model organisms",
+  author   = "Balhoff, James P and {Phenoscape project team}",
+  journal  = "bioRxiv",
+  pages    =  071951,
+  abstract = "The Phenoscape Knowledgebase (KB) is an ontology-driven database
+              that combines existing phenotype annotations from model organism
+              databases with new phenotype annotations from the evolutionary
+              literature. Phenoscape curators have created phenotype annotations
+              for more than 5,000 species and higher taxa, by defining
+              computable phenotype concepts for more than 20,000 character
+              states from over 160 published phylogenetic studies. These
+              phenotype concepts are in the form of Entity-Quality (EQ)
+              compositions which incorporate terms from the Uberon anatomy
+              ontology, the Biospatial Ontology (BSPO), and the Phenotype and
+              Trait Ontology (PATO). Taxonomic concepts are drawn from the
+              Vertebrate Taxonomy Ontology (VTO). This knowledge of comparative
+              biodiversity is linked to potentially relevant developmental
+              genetic mechanisms by importing associations of genes to
+              phenotypic effects and gene expression locations from zebrafish
+              (ZFIN), mouse (MGI), Xenopus (Xenbase), and human (Human Phenotype
+              Ontology project). Thus far, the Phenoscape KB has been used to
+              identify candidate genes for evolutionary phenotypes, to match
+              profiles of ancestral evolutionary variation with gene phenotype
+              profiles, and to combine data across many evolutionary studies by
+              inferring indirectly asserted values within synthetic
+              supermatrices. Here we describe the software architecture of the
+              Phenoscape KB, including data ingestion, integration of OWL
+              reasoning, web service interface, and application features.",
+  month    =  jan,
+  year     =  2016,
+  url      = "http://biorxiv.org/cgi/content/short/071951",
+  doi      = "10.1101/071951",
+  language = "en"
+}
 ```