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--- |
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annotations_creators: |
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- expert-generated |
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language_creators: |
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- expert-generated |
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languages: |
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- en |
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licenses: |
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- cc-by-4.0 |
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multilinguality: |
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- monolingual |
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pretty_name: Elsevier OA CC-By Corpus |
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paperswithcode_id: elsevier-oa-cc-by-corpus |
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size_categories: |
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- 10K<n<100K |
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source_datasets: |
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- original |
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task_categories: |
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- fill-mask |
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- summarization |
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- text-classification |
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task_ids: |
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- masked-language-modeling |
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- news-articles-summarization |
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- news-articles-headline-generation |
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--- |
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# Dataset Card for [Dataset Name] |
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|
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## Table of Contents |
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- [Dataset Card for [Dataset Name]](#dataset-card-for-dataset-name) |
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- [Table of Contents](#table-of-contents) |
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- [Dataset Description](#dataset-description) |
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- [Dataset Summary](#dataset-summary) |
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- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) |
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- [Languages](#languages) |
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- [Dataset Structure](#dataset-structure) |
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- [Data Instances](#data-instances) |
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- [Data Fields](#data-fields) |
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- [Data Splits](#data-splits) |
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- [Dataset Creation](#dataset-creation) |
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- [Curation Rationale](#curation-rationale) |
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- [Source Data](#source-data) |
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- [Initial Data Collection and Normalization](#initial-data-collection-and-normalization) |
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- [Who are the source language producers?](#who-are-the-source-language-producers) |
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- [Annotations](#annotations) |
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- [Annotation process](#annotation-process) |
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- [Who are the annotators?](#who-are-the-annotators) |
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- [Personal and Sensitive Information](#personal-and-sensitive-information) |
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- [Considerations for Using the Data](#considerations-for-using-the-data) |
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- [Social Impact of Dataset](#social-impact-of-dataset) |
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- [Discussion of Biases](#discussion-of-biases) |
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- [Other Known Limitations](#other-known-limitations) |
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- [Additional Information](#additional-information) |
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- [Dataset Curators](#dataset-curators) |
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- [Licensing Information](#licensing-information) |
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- [Citation Information](#citation-information) |
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- [Contributions](#contributions) |
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## Dataset Description |
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- **Homepage:** https://elsevier.digitalcommonsdata.com/datasets/zm33cdndxs |
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- **Repository:** https://elsevier.digitalcommonsdata.com/datasets/zm33cdndxs |
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- **Paper:** https://arxiv.org/abs/2008.00774 |
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- **Leaderboard:** |
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- **Point of Contact:** [@orieg](https://huggingface.co/orieg) |
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### Dataset Summary |
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Elsevier OA CC-By Corpus: This is a corpus of 40k (40, 091) open access (OA) CC-BY articles from across Elsevier’s journals |
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representing a large scale, cross-discipline set of research data to support NLP and ML research. |
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***docId*** The docID is the identifier of the document. This is unique to the document, and can be resolved into a URL |
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for the document through the addition of https//www.sciencedirect.com/science/pii/<docId> |
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***abstract*** This is the author provided abstract for the document |
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body_text The full text for the document. The text has been split on sentence boundaries, thus making it easier to |
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use across research projects. Each sentence has the title (and ID) of the section which it is from, along with titles (and |
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IDs) of the parent section. The highest-level section takes index 0 in the parents array. If the array is empty then the |
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title of the section for the sentence is the highest level section title. This will allow for the reconstruction of the article |
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structure. References have been extracted from the sentences. The IDs of the extracted reference and their respective |
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offset within the sentence can be found in the “refoffsets” field. The complete list of references are can be found in |
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the “bib_entry” field along with the references’ respective metadata. Some will be missing as we only keep ‘clean’ |
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sentences, |
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***bib_entities*** All the references from within the document can be found in this section. If the meta data for the |
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reference is available, it has been added against the key for the reference. Where possible information such as the |
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document titles, authors, and relevant identifiers (DOI and PMID) are included. The keys for each reference can be |
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found in the sentence where the reference is used with the start and end offset of where in the sentence that reference |
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was used. |
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***metadata*** Meta data includes additional information about the article, such as list of authors, relevant IDs (DOI and |
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PMID). Along with a number of classification schemes such as ASJC and Subject Classification. |
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***Author_highlights*** Author highlights were included in the corpus where the author(s) have provided them. The |
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coverage is 61% of all articles. The author highlights, consisting of 4 to 6 sentences, is provided by the author with |
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the aim of summarising the core findings and results in the article. |
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### Supported Tasks and Leaderboards |
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[More Information Needed] |
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### Languages |
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English (`en`). |
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## Dataset Structure |
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* ***title***:This is the author provided title for the document. 100% coverage. |
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* ***abstract***: This is the author provided abstract for the document. 99.25% coverage. |
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* ***keywords***: This is the author and publisher provided keywords for the document. 100% coverage. |
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* ***asjc***: This is the disciplines for the document as represented by 334 ASJC (All Science Journal Classification) codes. 100% coverage. |
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* ***subjareas***: This is the Subject Classification for the document as represented by 27 ASJC top-level subject classifications. 100% coverage. |
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* ***body_text***: The full text for the document. 100% coverage. |
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* ***author_highlights***: This is the author provided highlights for the document. 61.31% coverage. |
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### Data Instances |
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The original dataset was published with the following json structure: |
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``` |
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{ |
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"docId": <str>, |
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"metadata":{ |
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"title": <str>, |
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"authors": [ |
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{ |
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"first": <str>, |
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"initial": <str>, |
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"last": <str>, |
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"email": <str> |
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}, |
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... |
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], |
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"issn": <str>, |
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"volume": <str>, |
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"firstpage": <str>, |
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"lastpage": <str>, |
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"pub_year": <int>, |
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"doi": <str>, |
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"pmid": <str>, |
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"openaccess": "Full", |
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"subjareas": [<str>], |
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"keywords": [<str>], |
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"asjc": [<int>], |
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}, |
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"abstract":[ |
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{ |
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"sentence": <str>, |
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"startOffset": <int>, |
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"endOffset": <int> |
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}, |
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... |
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], |
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"bib_entries":{ |
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"BIBREF0":{ |
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"title":<str>, |
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"authors":[ |
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{ |
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"last":<str>, |
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"initial":<str>, |
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"first":<str> |
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}, |
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... |
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], |
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"issn": <str>, |
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"volume": <str>, |
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"firstpage": <str>, |
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"lastpage": <str>, |
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"pub_year": <int>, |
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"doi": <str>, |
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"pmid": <str> |
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}, |
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... |
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}, |
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"body_text":[ |
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{ |
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"sentence": <str>, |
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"secId": <str>, |
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"startOffset": <int>, |
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"endOffset": <int>, |
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"title": <str>, |
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"refoffsets": { |
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<str>:{ |
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"endOffset":<int>, |
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"startOffset":<int> |
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} |
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}, |
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"parents": [ |
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{ |
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"id": <str>, |
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"title": <str> |
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}, |
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... |
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] |
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}, |
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... |
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] |
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} |
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``` |
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|
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### Data Fields |
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|
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[More Information Needed] |
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### Data Splits |
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|
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[More Information Needed] |
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|
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## Dataset Creation |
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|
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### Curation Rationale |
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|
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See `3.1 Data Sampling` in the [original paper](https://doi.org/10.48550/arXiv.2008.00774). |
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[More Information Needed] |
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|
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### Source Data |
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#### Initial Data Collection and Normalization |
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Date the data was collected: 2020-06-25T11:00:00.000Z |
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[More Information Needed] |
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#### Who are the source language producers? |
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[More Information Needed] |
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### Annotations |
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|
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#### Annotation process |
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[More Information Needed] |
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|
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#### Who are the annotators? |
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|
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[More Information Needed] |
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|
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### Personal and Sensitive Information |
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|
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[More Information Needed] |
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|
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## Considerations for Using the Data |
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|
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### Social Impact of Dataset |
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|
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[More Information Needed] |
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|
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### Discussion of Biases |
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|
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[More Information Needed] |
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|
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### Other Known Limitations |
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|
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[More Information Needed] |
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## Additional Information |
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### Dataset Curators |
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|
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[More Information Needed] |
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### Licensing Information |
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[CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) |
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### Citation Information |
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``` |
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@article{Kershaw2020ElsevierOC, |
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title = {Elsevier OA CC-By Corpus}, |
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author = {Daniel James Kershaw and R. Koeling}, |
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journal = {ArXiv}, |
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year = {2020}, |
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volume = {abs/2008.00774}, |
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doi = {https://doi.org/10.48550/arXiv.2008.00774}, |
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url = {https://elsevier.digitalcommonsdata.com/datasets/zm33cdndxs}, |
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keywords = {Science, Natural Language Processing, Machine Learning, Open Dataset}, |
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abstract = {We introduce the Elsevier OA CC-BY corpus. This is the first open |
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corpus of Scientific Research papers which has a representative sample |
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from across scientific disciplines. This corpus not only includes the |
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full text of the article, but also the metadata of the documents, |
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along with the bibliographic information for each reference.} |
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} |
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``` |
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|
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``` |
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@dataset{https://10.17632/zm33cdndxs.3, |
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doi = {10.17632/zm33cdndxs.2}, |
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url = {https://data.mendeley.com/datasets/zm33cdndxs/3}, |
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author = "Daniel Kershaw and Rob Koeling", |
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keywords = {Science, Natural Language Processing, Machine Learning, Open Dataset}, |
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title = {Elsevier OA CC-BY Corpus}, |
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publisher = {Mendeley}, |
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year = {2020}, |
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month = {sep} |
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} |
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``` |
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### Contributions |
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|
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Thanks to [@orieg](https://github.com/orieg) for adding this dataset. |
