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Dataset Card for S2ORC: The Semantic Scholar Open Research Corpus
Dataset Summary
A large corpus of 81.1M English-language academic papers spanning many academic disciplines. Rich metadata, paper abstracts, resolved bibliographic references, as well as structured full text for 8.1M open access papers. Full text annotated with automatically-detected inline mentions of citations, figures, and tables, each linked to their corresponding paper objects. Aggregated papers from hundreds of academic publishers and digital archives into a unified source, and create the largest publicly-available collection of machine-readable academic text to date.
Supported Tasks and Leaderboards
[More Information Needed]
Languages
The text in the dataset is in English.
Dataset Structure
Data Instances
Example Paper Record:
{
"id":"4cd223df721b722b1c40689caa52932a41fcc223",
"title":"Knowledge-rich, computer-assisted composition of Chinese couplets",
"paperAbstract":"Recent research effort in poem composition has focused on the use of automatic language generation...",
"entities":[
],
"fieldsOfStudy":[
"Computer Science"
],
"s2Url":"https://semanticscholar.org/paper/4cd223df721b722b1c40689caa52932a41fcc223",
"pdfUrls":[
"https://doi.org/10.1093/llc/fqu052"
],
"s2PdfUrl":"",
"authors":[
{
"name":"John Lee",
"ids":[
"3362353"
]
},
"..."
],
"inCitations":[
"c789e333fdbb963883a0b5c96c648bf36b8cd242"
],
"outCitations":[
"abe213ed63c426a089bdf4329597137751dbb3a0",
"..."
],
"year":2016,
"venue":"DSH",
"journalName":"DSH",
"journalVolume":"31",
"journalPages":"152-163",
"sources":[
"DBLP"
],
"doi":"10.1093/llc/fqu052",
"doiUrl":"https://doi.org/10.1093/llc/fqu052",
"pmid":"",
"magId":"2050850752"
}
Data Fields
Identifier fields
paper_id
: astr
-valued field that is a unique identifier for each S2ORC paper.arxiv_id
: astr
-valued field for papers on arXiv.org.acl_id
: astr
-valued field for papers on the ACL Anthology.pmc_id
: astr
-valued field for papers on PubMed Central.pubmed_id
: astr
-valued field for papers on PubMed, which includes MEDLINE. Also known aspmid
on PubMed.mag_id
: astr
-valued field for papers on Microsoft Academic.doi
: astr
-valued field for the DOI.
Notably:
- Resolved citation links are represented by the cited paper's
paper_id
. - The
paper_id
resolves to a Semantic Scholar paper page, which can be verified using thes2_url
field. - We don't always have a value for every identifier field. When missing, they take
null
value.
Metadata fields
title
: astr
-valued field for the paper title. Every S2ORC paper must have one, though the source can be from publishers or parsed from PDFs. We prioritize publisher-provided values over parsed values.authors
: aList[Dict]
-valued field for the paper authors. Authors are listed in order. Each dictionary has the keysfirst
,middle
,last
, andsuffix
for the author name, which are allstr
-valued with exception ofmiddle
, which is aList[str]
-valued field. Every S2ORC paper must have at least one author.venue
andjournal
:str
-valued fields for the published venue/journal. Please note that there is not often agreement as to what constitutes a "venue" versus a "journal". Consolidating these fields is being considered for future releases.year
: anint
-valued field for the published year. If a paper is preprinted in 2019 but published in 2020, we try to ensure thevenue/journal
andyear
fields agree & prefer non-preprint published info. Missing years are replaced by -1. We know this decision prohibits certain types of analysis like comparing preprint & published versions of a paper. We're looking into it for future releases.abstract
: astr
-valued field for the abstract. These are provided directly from gold sources (not parsed from PDFs). We preserve newline breaks in structured abstracts, which are common in medical papers, by denoting breaks with':::'
.inbound_citations
: aList[str]
-valued field containingpaper_id
of other S2ORC papers that cite the current paper. Currently derived from PDF-parsed bibliographies, but may have gold sources in the future.outbound_citations
: aList[str]
-valued field containingpaper_id
of other S2ORC papers that the current paper cites. Same note as above.has_inbound_citations
: abool
-valued field that istrue
ifinbound_citations
has at least one entry, andfalse
otherwise.has_outbound_citations
abool
-valued field that istrue
ifoutbound_citations
has at least one entry, andfalse
otherwise.
We don't always have a value for every metadata field. When missing, str
fields take null
value, while List
fields are empty lists.
Data Splits
There is no train/dev/test split given in the dataset
Dataset Creation
Curation Rationale
Academic papers are an increasingly important textual domain for natural language processing (NLP) research. Aside from capturing valuable knowledge from humankind’s collective research efforts, academic papers exhibit many interesting characteristics – thousands of words organized into sections, objects such as tables, figures and equations, frequent inline references to these objects, footnotes, other papers, and more
Source Data
Initial Data Collection and Normalization
To construct S2ORC, we must overcome challenges in (i) paper metadata aggregation, (ii) identifying open access publications, and (iii) clustering papers, in addition to identifying, extracting, and cleaning the full text and bibliometric annotations associated with each paper. The pipeline for creating S2ORC is:
- Process PDFs and LATEX sources to derive metadata, clean full text, inline citations and references, and bibliography entries,
- Select the best metadata and full text parses for each paper cluster,
- Filter paper clusters with insufficient metadata or content, and
- Resolve bibliography links between paper clusters in the corpus.
Who are the source language producers?
S2ORC is constructed using data from the Semantic Scholar literature corpus (Ammar et al., 2018). Papers in Semantic Scholar are derived from numerous sources: obtained directly from publishers, from resources such as MAG, from various archives such as arXiv or PubMed, or crawled from the open Internet. Semantic Scholar clusters these papers based on title similarity and DOI overlap, resulting in an initial set of approximately 200M paper clusters.
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
Semantic Scholar Open Research Corpus is licensed under ODC-BY.
Citation Information
@misc{lo2020s2orc,
title={S2ORC: The Semantic Scholar Open Research Corpus},
author={Kyle Lo and Lucy Lu Wang and Mark Neumann and Rodney Kinney and Dan S. Weld},
year={2020},
eprint={1911.02782},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
Contributions
Thanks to @bhavitvyamalik for adding this dataset.
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