| |
|
| | --- |
| | language: |
| | - en |
| | license: cc-by-4.0 |
| | size_categories: |
| | - 10K<n<100K |
| | tasks: |
| | - named-entity-recognition |
| | - token-classification |
| | pretty_name: COPIOUS |
| | tags: |
| | - named-entity-recognition |
| | - biodiversity |
| | - species-occurrence |
| | configs: |
| | - config_name: default |
| | data_files: |
| | - split: train |
| | path: train.jsonl |
| | - split: validation |
| | path: dev.jsonl |
| | - split: test |
| | path: test.jsonl |
| | --- |
| | |
| | # Dataset Card for COPIOUS |
| |
|
| | ## Table of Contents |
| | - [Dataset Description](#dataset-description) |
| | - [Dataset Summary](#dataset-summary) |
| | - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) |
| | - [Languages](#languages) |
| | - [Dataset Structure](#dataset-structure) |
| | - [Data Instances](#data-instances) |
| | - [Data Fields](#data-fields) |
| | - [Data Splits](#data-splits) |
| | - [Dataset Creation](#dataset-creation) |
| | - [Curation Rationale](#curation-rationale) |
| | - [Source Data](#source-data) |
| | - [Annotations](#annotations) |
| | - [Format Conversion](#format-conversion) |
| | - [Considerations for Using the Data](#considerations-for-using-the-data) |
| | - [Social Impact of Dataset](#social-impact-of-dataset) |
| | - [Other Known Limitations](#other-known-limitations) |
| | - [Additional Information](#additional-information) |
| | - [Dataset Curators](#dataset-curators) |
| | - [Licensing Information](#licensing-information) |
| | - [Citation Information](#citation-information) |
| |
|
| | ## Dataset Description |
| |
|
| | - **Homepage:** [COPIOUS: A gold standard corpus of named entities... (Biodiversity Data Journal)](https://doi.org/10.3897/BDJ.7.e29626) |
| | - **Paper:** [COPIOUS: A gold standard corpus of named entities towards extracting species occurrence from biodiversity literature](https://doi.org/10.3897/BDJ.7.e29626) |
| | - **Point of Contact:** [Sophia Ananiadou](mailto:sophia.ananiadou@manchester.ac.uk) |
| |
|
| | ### Dataset Summary |
| |
|
| | Species occurrence records are critical in the biodiversity domain. However, a key challenge has been the lack of a single, consolidated corpus that includes all the entity types needed to extract this information from scientific literature. To address this gap, the **COPIOUS corpus** (Corpus of named entities towards extracting Species Occurrence) was created. |
| |
|
| | This dataset serves as a gold standard, annotated with a wide range of entities relevant to biodiversity science. It was developed as part of the broader COPIOUS project, which aims to build a knowledge repository of Philippine biodiversity by applying text mining to scientific texts. The corpus is manually annotated with five key entity categories: **Taxon**, **Geographical Location**, **Habitat**, **Temporal Expression**, and **Person** names. |
| |
|
| | ### Supported Tasks and Leaderboards |
| |
|
| | - **Tasks:** Named Entity Recognition, Token Classification |
| | - **Leaderboards:** N/A |
| |
|
| | ### Languages |
| |
|
| | The text in the dataset is in English. |
| |
|
| | ## Dataset Structure |
| |
|
| | ### Data Instances |
| |
|
| | An example from the `train` split: |
| |
|
| | ```json |
| | { |
| | "id": "100785_English_120409_32367238_1954", |
| | "tokens": ["FAMILY", "SERRANIDAE", "—", "SCHULTZ", "..."], |
| | "ner_tags": [0, 1, 0, 0, ...] |
| | } |
| | ``` |
| |
|
| | ### Data Fields |
| |
|
| | - `id`: A unique identifier for the example (string). |
| | - `tokens`: A list of tokens (list of strings). |
| | - `ner_tags`: A list of integer IDs corresponding to the NER tags. The mapping is: |
| |
|
| | ```json |
| | { |
| | "0": "O", |
| | "1": "B-Taxon", |
| | "2": "I-Taxon", |
| | "3": "B-Geographical_Location", |
| | "4": "I-Geographical_Location", |
| | "5": "B-Habitat", |
| | "6": "I-Habitat", |
| | "7": "B-Temporal_Expression", |
| | "8": "I-Temporal_Expression", |
| | "9": "B-Person", |
| | "10": "I-Person" |
| | } |
| | ``` |
| |
|
| | ### Data Splits |
| |
|
| | The corpus consists of 668 documents split as follows: |
| |
|
| | | Split | Documents | |
| | |-----------|-----------| |
| | | train | 534 | |
| | | validation| 67 | |
| | | test | 67 | |
| |
|
| | ## Dataset Creation |
| |
|
| | ### Curation Rationale |
| |
|
| | The corpus was created to be a sufficiently reliable and sizeable resource for training and evaluating Named Entity Recognition (NER) tools in the biodiversity domain, specifically for the task of species occurrence extraction. |
| |
|
| | ### Source Data |
| |
|
| | The data consists of 668 documents randomly selected from over 169,000 English-language pages downloaded from the Biodiversity Heritage Library (BHL). |
| |
|
| | ### Annotations |
| |
|
| | The dataset was manually annotated by two experts in biology using the Argo workbench. 200 documents were double-annotated to ensure quality, achieving an overall Inter-Annotator Agreement (IAA) of 81.86% F-score. |
| |
|
| | ### Format Conversion |
| |
|
| | For this Hugging Face Hub version, the dataset was prepared as follows: |
| | - **Local Sourcing:** The data was sourced from a local copy because the original download link on the NaCTeM website was inactive. |
| | - **Conversion to JSONL:** The original data was annotated in the Brat Standoff Format (.txt + .ann files). It has been converted to the standard JSON Lines (.jsonl) format to align with Hugging Face Hub standards. |
| |
|
| | ## Considerations for Using the Data |
| |
|
| | ### Social Impact of Dataset |
| |
|
| | This corpus can be used to develop text mining tools that automatically locate species occurrences in literature, which is useful for monitoring species distribution and preserving biodiversity. |
| |
|
| | ### Other Known Limitations |
| |
|
| | - **Annotation Complexity:** The IAA for the Habitat entity type was the lowest (47.07% F-score), indicating this category is complex and challenging for both human annotators and automated systems. |
| | - **Source Text Quality:** The source documents from BHL contain a large number of OCR errors, which may adversely affect the performance of NER models trained on this data. |
| |
|
| | ## Additional Information |
| |
|
| | ### Dataset Curators |
| |
|
| | Nhung T.H. Nguyen, Roselyn S. Gabud, and Sophia Ananiadou. |
| |
|
| | ### Licensing Information |
| |
|
| | The dataset is distributed under the Creative Commons Attribution License (CC BY 4.0). |
| |
|
| | ### Citation Information |
| |
|
| | ```bibtex |
| | @article{nguyen2019copious, |
| | author = {Nguyen, Nhung T.H. and Gabud, Roselyn S. and Ananiadou, Sophia}, |
| | title = {{COPIOUS: A gold standard corpus of named entities towards extracting species occurrence from biodiversity literature}}, |
| | journal = {Biodiversity Data Journal}, |
| | volume = {7}, |
| | pages = {e29626}, |
| | year = {2019}, |
| | doi = {10.3897/BDJ.7.e29626} |
| | } |
| | ``` |
