Create README.md

README.md

@@ -0,0 +1,152 @@
+---
+task_categories:
+- summarization
+language:
+- en
+tags:
+- chemistry
+- biology
+- medical
+pretty_name: Generating Abstracts of Academic Chemistry Papers
+size_categories:
+- 100K<n<1M
+---
+# Dataset Card for ChemSum
+
+## ChemSum Description
+
+<!---- **Homepage:** 
+- **Leaderboard:** 
+----->
+- **Paper:** [What are the Desired Characteristics of Calibration Sets? Identifying Correlates on Long Form Scientific Summarization ](https://openreview.net/forum?id=bIC0BfWzCs)
+- **Journal:** ACL 2023
+- **Point of Contact:** [email protected]
+- **Repository:** https://github.com/griff4692/calibrating-summaries
+
+### ChemSum Summary
+
+We introduce a dataset with a pure chemistry focus by compiling a list of chemistry academic journals with Open-Access articles. For each journal, we downloaded full-text article PDFs from the Open-Access portion of the journal using available APIs, or scraping this content using [Selenium Chrome WebDriver](https://www.selenium.dev/documentation/webdriver/). 
+Each PDF was processed with Grobid via a locally installed [client](https://pypi.org/project/grobid-client-python/) to extract free-text paragraphs with sections. 
+
+The table below shows the journals from which Open Access articles were sourced, as well as the number of papers processed.
+
+For all journals, we filtered for papers with the provided topic of Chemistry when papers from other disciplines were also available (e.g. PubMed).
+
+
+| Source | # of Articles |
+| ----------- | ----------- |
+| Beilstein | 1,829 |
+| Chem Cell | 546 |
+| ChemRxiv | 12,231 |
+| Chemistry Open | 398 |
+| Nature Communications Chemistry | 572 |
+| PubMed Author Manuscript | 57,680 |
+| PubMed Open Access | 29,540 |
+| Royal Society of Chemistry (RSC) | 9,334 |
+| Scientific Reports - Nature | 6,826 |
+
+<!---
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+--->
+
+### Languages
+
+English
+
+## Dataset Structure
+
+<!--- ### Data Instances --->
+
+### Data Fields
+
+
+| Column | Description |
+| ----------- | ----------- |
+| `uuid` | Unique Identifier for the Example |
+| `title` | Title of the Article |
+| `article_source` | Open Source Journal (see above for list) |
+| `abstract` | Abstract (summary reference) |
+| `sections` | Full-text sections from the main body of paper (<!> indicates section boundaries)|
+| `headers` | Corresponding section headers for `sections` field (<!> delimited) |
+| `source_toks` | Aggregate number of tokens across `sections` |
+| `target_toks` | Number of tokens in the `abstract` |
+| `compression` | Ratio of `source_toks` to `target_toks` |
+
+Please refer to `load_chemistry()` in https://github.com/griff4692/calibrating-summaries/blob/master/preprocess/preprocess.py for pre-processing as a summarization dataset. The inputs are `sections` and `headers` and the targets is the `abstract`.
+
+
+### Data Splits
+
+| Split | Count |
+| ----------- | ----------- |
+| `train` | 115,956 |
+| `validation` | 1,000 |
+| `test` | 2,000 |
+
+
+### Citation Information
+
+[More Information Needed]
+
+<!---
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed]
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+### Annotations
+
+#### Annotation process
+
+[More Information Needed]
+
+#### Who are the annotators?
+
+[More Information Needed]
+
+### Personal and Sensitive Information
+
+[More Information Needed]
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More Information Needed]
+
+### Discussion of Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed]
+
+### Licensing Information
+
+[More Information Needed]
+
+### Contributions
+
+[More Information Needed]
+--->