cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10651965
title: BIP! NDR (NoDoiRefs): a dataset of citations from papers without DOIs in computer science conferences and workshops

description: In the field of Computer Science, conference and workshop papers serve as important contributions, carrying substantial weight in research assessment processes, compared to other disciplines. However, a considerable number of these papers are not assigned a Digital Object Identifier (DOI), hence their citations are not reported in widely used citation datasets like OpenCitations and Crossref, raising limitations to citation analysis. While the Microsoft Academic Graph (MAG) previously addressed this issue by providing substantial coverage, its discontinuation  has created a void in available data.

    BIP! NDR aims to alleviate this issue and enhance the research assessment processes within the field of Computer Science. To accomplish this, it leverages a workflow that identifies and retrieves Open Science papers lacking DOIs from the DBLP Corpus, and by performing text analysis, it extracts citation information directly from their full text. The current version of the dataset contains ~2.9M citations made by approximately 171K open access Computer Science conference or workshop papers that, according to DBLP, do not have a DOI.

File Structure:

The dataset is formatted as a JSON Lines (JSONL) file (one JSON Object per line) to facilitate file splitting and streaming. 

Each JSON object has three main fields:





“_id”: a unique identifier,




“citing_paper”, the “dblp_id” of the citing paper,




“cited_papers”: array containing the objects that correspond to each reference found in the text of the “citing_paper”; each object may contain the following fields:





“dblp_id”: the “dblp_id” of the cited paper. Optional - this field is required if a “doi” is not present.




“doi”: the doi of the cited paper. Optional - this field is required if a “dblp_id” is not present.




“bibliographic_reference”: the raw citation string as it appears in the citing paper.





Changes from previous version:



Added more papers from DBLP.
DOI: 10.5281/zenodo.10888704
title: BIP! NDR (NoDoiRefs): a dataset of citations from papers without DOIs in computer science conferences and workshops

description: In the field of Computer Science, conference and workshop papers serve as important contributions, carrying substantial weight in research assessment processes, compared to other disciplines. However, a considerable number of these papers are not assigned a Digital Object Identifier (DOI), hence their citations are not reported in widely used citation datasets like OpenCitations and Crossref, raising limitations to citation analysis. While the Microsoft Academic Graph (MAG) previously addressed this issue by providing substantial coverage, its discontinuation  has created a void in available data.

  BIP! NDR aims to alleviate this issue and enhance the research assessment processes within the field of Computer Science. To accomplish this, it leverages a workflow that identifies and retrieves Open Science papers lacking DOIs from the DBLP Corpus, and by performing text analysis, it extracts citation information directly from their full text. The current version of the dataset contains ~3.1M citations made by approximately 176K open access Computer Science conference or workshop papers that, according to DBLP, do not have a DOI.

File Structure:

The dataset is formatted as a JSON Lines (JSONL) file (one JSON Object per line) to facilitate file splitting and streaming. 

Each JSON object has three main fields:





“_id”: a unique identifier,




“citing_paper”, the “dblp_id” of the citing paper,




“cited_papers”: array containing the objects that correspond to each reference found in the text of the “citing_paper”; each object may contain the following fields:





“dblp_id”: the “dblp_id” of the cited paper. Optional - this field is required if a “doi” is not present.




“doi”: the doi of the cited paper. Optional - this field is required if a “dblp_id” is not present.




“bibliographic_reference”: the raw citation string as it appears in the citing paper.





Changes from previous version:



Added more papers from DBLP.
DOI: 10.5281/zenodo.11238289
title: BIP! NDR (NoDoiRefs): a dataset of citations from papers without DOIs in computer science conferences and workshops

description: In the field of Computer Science, conference and workshop papers serve as important contributions, carrying substantial weight in research assessment processes, compared to other disciplines. However, a considerable number of these papers are not assigned a Digital Object Identifier (DOI), hence their citations are not reported in widely used citation datasets like OpenCitations and Crossref, raising limitations to citation analysis. While the Microsoft Academic Graph (MAG) previously addressed this issue by providing substantial coverage, its discontinuation  has created a void in available data.

  BIP! NDR aims to alleviate this issue and enhance the research assessment processes within the field of Computer Science. To accomplish this, it leverages a workflow that identifies and retrieves Open Science papers lacking DOIs from the DBLP Corpus, and by performing text analysis, it extracts citation information directly from their full text. The current version of the dataset contains ~3.2M citations made by approximately 180K open access Computer Science conference or workshop papers that, according to DBLP, do not have a DOI.

File Structure:

The dataset is formatted as a JSON Lines (JSONL) file (one JSON Object per line) to facilitate file splitting and streaming. 

Each JSON object has three main fields:





“_id”: a unique identifier,




“citing_paper”, the “dblp_id” of the citing paper,




“cited_papers”: array containing the objects that correspond to each reference found in the text of the “citing_paper”; each object may contain the following fields:





“dblp_id”: the “dblp_id” of the cited paper. Optional - this field is required if a “doi” is not present.




“doi”: the doi of the cited paper. Optional - this field is required if a “dblp_id” is not present.




“bibliographic_reference”: the raw citation string as it appears in the citing paper.





Changes from previous version:



Added more papers from DBLP.
DOI: 10.5281/zenodo.13693321
title: BIP! NDR (NoDoiRefs): a dataset of citations from papers without DOIs in computer science conferences and workshops

description: In the field of Computer Science, conference and workshop papers serve as important contributions, carrying substantial weight in research assessment processes, compared to other disciplines. However, a considerable number of these papers are not assigned a Digital Object Identifier (DOI), hence their citations are not reported in widely used citation datasets like OpenCitations and Crossref, raising limitations to citation analysis. While the Microsoft Academic Graph (MAG) previously addressed this issue by providing substantial coverage, its discontinuation  has created a void in available data.

BIP! NDR aims to alleviate this issue and enhance the research assessment processes within the field of Computer Science. To accomplish this, it leverages a workflow that identifies and retrieves Open Science papers lacking DOIs from the DBLP Corpus, and by performing text analysis, it extracts citation information directly from their full text. The current version of the dataset contains ~3.3M citations made by approximately 183K open access Computer Science conference or workshop papers that, according to DBLP, do not have a DOI.

File Structure:

The dataset is formatted as a JSON Lines (JSONL) file (one JSON Object per line) to facilitate file splitting and streaming. 

Each JSON object has three main fields:





“_id”: a unique identifier,




“citing_paper”, the “dblp_id” of the citing paper,




“cited_papers”: array containing the objects that correspond to each reference found in the text of the “citing_paper”; each object may contain the following fields:





“dblp_id”: the “dblp_id” of the cited paper. Optional - this field is required if a “doi” is not present.




“doi”: the doi of the cited paper. Optional - this field is required if a “dblp_id” is not present.




“bibliographic_reference”: the raw citation string as it appears in the citing paper.





Changes from previous version:



Added more papers from DBLP.
DOI: 10.5281/zenodo.13757999
title: BIP! NDR (NoDoiRefs): a dataset of citations from papers without DOIs in computer science conferences and workshops

description: In the field of Computer Science, conference and workshop papers serve as important contributions, carrying substantial weight in research assessment processes, compared to other disciplines. However, a considerable number of these papers are not assigned a Digital Object Identifier (DOI), hence their citations are not reported in widely used citation datasets like OpenCitations and Crossref, raising limitations to citation analysis. While the Microsoft Academic Graph (MAG) previously addressed this issue by providing substantial coverage, its discontinuation  has created a void in available data.

BIP! NDR aims to alleviate this issue and enhance the research assessment processes within the field of Computer Science. To accomplish this, it leverages a workflow that identifies and retrieves Open Science papers lacking DOIs from the DBLP Corpus, and by performing text analysis, it extracts citation information directly from their full text. The current version of the dataset contains ~3.5M citations made by approximately 188K open access Computer Science conference or workshop papers that, according to DBLP, do not have a DOI.

File Structure:

The dataset is formatted as a JSON Lines (JSONL) file (one JSON Object per line) to facilitate file splitting and streaming. 

Each JSON object has three main fields:





“_id”: a unique identifier,




“citing_paper”, the “dblp_id” of the citing paper,




“cited_papers”: array containing the objects that correspond to each reference found in the text of the “citing_paper”; each object may contain the following fields:





“dblp_id”: the “dblp_id” of the cited paper. Optional - this field is required if a “doi” is not present.




“doi”: the doi of the cited paper. Optional - this field is required if a “dblp_id” is not present.




“bibliographic_reference”: the raw citation string as it appears in the citing paper.





Changes from previous version:



Added more papers from DBLP.
DOI: 10.5281/zenodo.14196266
title: BIP! NDR (NoDoiRefs): a dataset of citations from papers without DOIs in computer science conferences and workshops

description: In the field of Computer Science, conference and workshop papers serve as important contributions, carrying substantial weight in research assessment processes, compared to other disciplines. However, a considerable number of these papers are not assigned a Digital Object Identifier (DOI), hence their citations are not reported in widely used citation datasets like OpenCitations and Crossref, raising limitations to citation analysis. While the Microsoft Academic Graph (MAG) previously addressed this issue by providing substantial coverage, its discontinuation  has created a void in available data.

BIP! NDR aims to alleviate this issue and enhance the research assessment processes within the field of Computer Science. To accomplish this, it leverages a workflow that identifies and retrieves Open Science papers lacking DOIs from the DBLP Corpus, and by performing text analysis, it extracts citation information directly from their full text. The current version of the dataset contains ~3.6M citations made by approximately 192.6K open access Computer Science conference or workshop papers that, according to DBLP, do not have a DOI. The DBLP snapshot used for this version was the one released on November 2024. 

File Structure:

The dataset is formatted as a JSON Lines (JSONL) file (one JSON Object per line) to facilitate file splitting and streaming. 

Each JSON object has three main fields:





“_id”: a unique identifier,




“citing_paper”, the “dblp_id” of the citing paper,




“cited_papers”: array containing the objects that correspond to each reference found in the text of the “citing_paper”; each object may contain the following fields:





“dblp_id”: the “dblp_id” of the cited paper. Optional - this field is required if a “doi” is not present.




“doi”: the doi of the cited paper. Optional - this field is required if a “dblp_id” is not present.




“bibliographic_reference”: the raw citation string as it appears in the citing paper.





Changes from previous version:



Added more papers from DBLP.
DOI: 10.5281/zenodo.7962020
title: BIP! NDR (NoDoiRefs): a dataset of citations from papers without DOIs in computer science conferences and workshops

description: In the field of Computer Science, conference and workshop papers serve as important contributions, carrying substantial weight in research assessment processes, compared to other disciplines. However, a considerable number of these papers are not assigned a Digital Object Identifier (DOI), hence their citations are not reported in widely used citation datasets like OpenCitations and Crossref, raising limitations to citation analysis. While the Microsoft Academic Graph (MAG) previously addressed this issue by providing substantial coverage, its discontinuation in December 2021 has created a void in available data. BIP! NDR aims to alleviate this issue and enhance the research assessment processes within the field of Computer Science. To accomplish this, it leverages a workflow that identifies and retrieves Open Science papers lacking DOIs from the DBLP database, and by performing automated text analysis, it extracts citation information directly from their full text. The current version of the dataset contains more than 500K citations made by approximately 60K Computer Science conference or workshop papers that, according to DBLP, do not have a DOI. <strong>File Structure:</strong> The dataset is formatted as a JSON Lines (JSONL) file (one JSON Object per line) to facilitate file splitting and streaming. Each JSON object has three main fields: “_id”: a unique identifier, “citing_paper”, the “dblp_id” of the citing paper, “cited_papers”: array containing the objects that correspond to each reference found in the text of the “citing_paper”; each object may contain the following fields: “dblp_id”: the “dblp_id” of the cited paper. Optional - this field is required if a “doi” is not present. “doi”: the doi of the cited paper. Optional - this field is required if a “dblp_id” is not present. “doi_url”: a link through doi.org. Optional - if available. “bibliographic_reference”: the raw citation string as it appears in the citing paper.
DOI: 10.5281/zenodo.8163673
title: BIP! NDR (NoDoiRefs): a dataset of citations from papers without DOIs in computer science conferences and workshops

description: In the field of Computer Science, conference and workshop papers serve as important contributions, carrying substantial weight in research assessment processes, compared to other disciplines. However, a considerable number of these papers are not assigned a Digital Object Identifier (DOI), hence their citations are not reported in widely used citation datasets like OpenCitations and Crossref, raising limitations to citation analysis. While the Microsoft Academic Graph (MAG) previously addressed this issue by providing substantial coverage, its discontinuation has created a void in available data. BIP! NDR aims to alleviate this issue and enhance the research assessment processes within the field of Computer Science. To accomplish this, it leverages a workflow that identifies and retrieves Open Science papers lacking DOIs from the DBLP Corpus, and by performing text analysis, it extracts citation information directly from their full text. The current version of the dataset contains more than 510K citations made by approximately 60K open access Computer Science conference or workshop papers that, according to DBLP, do not have a DOI. <strong>File Structure:</strong> The dataset is formatted as a JSON Lines (JSONL) file (one JSON Object per line) to facilitate file splitting and streaming. Each JSON object has three main fields: “_id”: a unique identifier, “citing_paper”, the “dblp_id” of the citing paper, “cited_papers”: array containing the objects that correspond to each reference found in the text of the “citing_paper”; each object may contain the following fields: “dblp_id”: the “dblp_id” of the cited paper. Optional - this field is required if a “doi” is not present. “doi”: the doi of the cited paper. Optional - this field is required if a “dblp_id” is not present. “bibliographic_reference”: the raw citation string as it appears in the citing paper. Changes from previous version: Removed "doi_url" from the dataset (to be more space-efficient, given the existence of the "doi" field.
DOI: 10.5281/zenodo.8356790
title: BIP! NDR (NoDoiRefs): a dataset of citations from papers without DOIs in computer science conferences and workshops

description: In the field of Computer Science, conference and workshop papers serve as important contributions, carrying substantial weight in research assessment processes, compared to other disciplines. However, a considerable number of these papers are not assigned a Digital Object Identifier (DOI), hence their citations are not reported in widely used citation datasets like OpenCitations and Crossref, raising limitations to citation analysis. While the Microsoft Academic Graph (MAG) previously addressed this issue by providing substantial coverage, its discontinuation has created a void in available data. BIP! NDR aims to alleviate this issue and enhance the research assessment processes within the field of Computer Science. To accomplish this, it leverages a workflow that identifies and retrieves Open Science papers lacking DOIs from the DBLP Corpus, and by performing text analysis, it extracts citation information directly from their full text. The current version of the dataset contains more than 2.1M citations made by approximately 147K open access Computer Science conference or workshop papers that, according to DBLP, do not have a DOI. <strong>File Structure:</strong> The dataset is formatted as a JSON Lines (JSONL) file (one JSON Object per line) to facilitate file splitting and streaming. Each JSON object has three main fields: “_id”: a unique identifier, “citing_paper”, the “dblp_id” of the citing paper, “cited_papers”: array containing the objects that correspond to each reference found in the text of the “citing_paper”; each object may contain the following fields: “dblp_id”: the “dblp_id” of the cited paper. Optional - this field is required if a “doi” is not present. “doi”: the doi of the cited paper. Optional - this field is required if a “dblp_id” is not present. “bibliographic_reference”: the raw citation string as it appears in the citing paper. Changes from previous version: Replaced the PDF Downloader module with PublicationsRetriever (https://github.com/LSmyrnaios/PublicationsRetriever) to cover the full range of available URLs Fixed a bug that affected how the DBLP IDs were allocated to the downloaded PDF files (this bug affected records in the previous versions of the dataset).
DOI: 10.5281/zenodo.8378087
title: BIP! NDR (NoDoiRefs): a dataset of citations from papers without DOIs in computer science conferences and workshops

description: In the field of Computer Science, conference and workshop papers serve as important contributions, carrying substantial weight in research assessment processes, compared to other disciplines. However, a considerable number of these papers are not assigned a Digital Object Identifier (DOI), hence their citations are not reported in widely used citation datasets like OpenCitations and Crossref, raising limitations to citation analysis. While the Microsoft Academic Graph (MAG) previously addressed this issue by providing substantial coverage, its discontinuation has created a void in available data. BIP! NDR aims to alleviate this issue and enhance the research assessment processes within the field of Computer Science. To accomplish this, it leverages a workflow that identifies and retrieves Open Science papers lacking DOIs from the DBLP Corpus, and by performing text analysis, it extracts citation information directly from their full text. The current version of the dataset contains more than 2.4M citations made by approximately 156K open access Computer Science conference or workshop papers that, according to DBLP, do not have a DOI. <strong>File Structure:</strong> The dataset is formatted as a JSON Lines (JSONL) file (one JSON Object per line) to facilitate file splitting and streaming. Each JSON object has three main fields: “_id”: a unique identifier, “citing_paper”, the “dblp_id” of the citing paper, “cited_papers”: array containing the objects that correspond to each reference found in the text of the “citing_paper”; each object may contain the following fields: “dblp_id”: the “dblp_id” of the cited paper. Optional - this field is required if a “doi” is not present. “doi”: the doi of the cited paper. Optional - this field is required if a “dblp_id” is not present. “bibliographic_reference”: the raw citation string as it appears in the citing paper. Changes from previous version: Processed additional papers from a more recent version of DBLP.
DOI: 10.5281/zenodo.8413221
title: BIP! NDR (NoDoiRefs): a dataset of citations from papers without DOIs in computer science conferences and workshops

description: In the field of Computer Science, conference and workshop papers serve as important contributions, carrying substantial weight in research assessment processes, compared to other disciplines. However, a considerable number of these papers are not assigned a Digital Object Identifier (DOI), hence their citations are not reported in widely used citation datasets like OpenCitations and Crossref, raising limitations to citation analysis. While the Microsoft Academic Graph (MAG) previously addressed this issue by providing substantial coverage, its discontinuation has created a void in available data. BIP! NDR aims to alleviate this issue and enhance the research assessment processes within the field of Computer Science. To accomplish this, it leverages a workflow that identifies and retrieves Open Science papers lacking DOIs from the DBLP Corpus, and by performing text analysis, it extracts citation information directly from their full text. The current version of the dataset contains ~2.7M citations made by approximately 164K open access Computer Science conference or workshop papers that, according to DBLP, do not have a DOI. <strong>File Structure:</strong> The dataset is formatted as a JSON Lines (JSONL) file (one JSON Object per line) to facilitate file splitting and streaming. Each JSON object has three main fields: “_id”: a unique identifier, “citing_paper”, the “dblp_id” of the citing paper, “cited_papers”: array containing the objects that correspond to each reference found in the text of the “citing_paper”; each object may contain the following fields: “dblp_id”: the “dblp_id” of the cited paper. Optional - this field is required if a “doi” is not present. “doi”: the doi of the cited paper. Optional - this field is required if a “dblp_id” is not present. “bibliographic_reference”: the raw citation string as it appears in the citing paper. Changes from previous version: Added more papers from DBLP.
DOI: 10.15468/dl.bbaesz
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Camellia viridicalyx Hung T.Chang & S.Y.Liang"
 ]
}

 The dataset includes 8 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027104-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.