This document describes a dataset that aggregates information about 135 data journals.
Data journals focus on the publication of data papers -- a specialized publication type describing datasets, their collection and reuse potential that is peer-reviewed, citable and indexed.
This dataset includes a comprehensive list of data journals that was compiled by aggregating existing sources, as well as an overview of these sources.

The list is continually updated on GitHub, where additional information on data journals (URLs of data journal homepages) is provided: https://github.com/MaxiKi/data-journals

Version: 5

Authors: Carlota Balsa-Sánchez, Vanesa Loureiro

Date of data collection: 2023/09/05

General description: The publication of datasets according to the FAIR principles, could be reached publishing a data paper (or software paper) in data journals or in academic standard journals. The excel and CSV file contains a list of academic journals that publish data papers and software papers. File list:

• data_articles_journal_list_v5.xlsx: full list of 140 academic journals in which data papers or/and software papers could be published
• data_articles_journal_list_v5.csv: full list of 140 academic journals in which data papers or/and software papers could be published

Relationship between files: both files have the same information. Two different formats are offered to improve reuse

Type of version of the dataset: final processed version

Versions of the files: 5th version - Information updated: number of journals, URL, document types associated to a specific journal.

Version: 4

Authors: Carlota Balsa-Sánchez, Vanesa Loureiro

Date of data collection: 2022/12/15

General description: The publication of datasets according to the FAIR principles, could be reached publishing a data paper (or software paper) in data journals or in academic standard journals. The excel and CSV file contains a list of academic journals that publish data papers and software papers. File list:

• data_articles_journal_list_v4.xlsx: full list of 140 academic journals in which data papers or/and software papers could be published
• data_articles_journal_list_v4.csv: full list of 140 academic journals in which data papers or/and software papers could be published

Relationship between files: both files have the same information. Two different formats are offered to improve reuse

Type of version of the dataset: final processed version

Versions of the files: 4th version - Information updated: number of journals, URL, document types associated to a specific journal, publishers normalization and simplification of document types - Information added : listed in the Directory of Open Access Journals (DOAJ), indexed in Web of Science (WOS) and quartile in Journal Citation Reports (JCR) and/or Scimago Journal and Country Rank (SJR), Scopus and Web of Science (WOS), Journal Master List.

Version: 3

Authors: Carlota Balsa-Sánchez, Vanesa Loureiro

Date of data collection: 2022/10/28

General description: The publication of datasets according to the FAIR principles, could be reached publishing a data paper (or software paper) in data journals or in academic standard journals. The excel and CSV file contains a list of academic journals that publish data papers and software papers. File list:

• data_articles_journal_list_v3.xlsx: full list of 124 academic journals in which data papers or/and software papers could be published
• data_articles_journal_list_3.csv: full list of 124 academic journals in which data papers or/and software papers could be published

Relationship between files: both files have the same information. Two different formats are offered to improve reuse

Type of version of the dataset: final processed version

Versions of the files: 3rd version - Information updated: number of journals, URL, document types associated to a specific journal, publishers normalization and simplification of document types - Information added : listed in the Directory of Open Access Journals (DOAJ), indexed in Web of Science (WOS) and quartile in Journal Citation Reports (JCR) and/or Scimago Journal and Country Rank (SJR).

Erratum - Data articles in journals Version 3:

Botanical Studies -- ISSN 1999-3110 -- JCR (JIF) Q2 Data -- ISSN 2306-5729 -- JCR (JIF) n/a Data in Brief -- ISSN 2352-3409 -- JCR (JIF) n/a

Version: 2

Author: Francisco Rubio, Universitat Politècnia de València.

Date of data collection: 2020/06/23

General description: The publication of datasets according to the FAIR principles, could be reached publishing a data paper (or software paper) in data journals or in academic standard journals. The excel and CSV file contains a list of academic journals that publish data papers and software papers. File list:

• data_articles_journal_list_v2.xlsx: full list of 56 academic journals in which data papers or/and software papers could be published
• data_articles_journal_list_v2.csv: full list of 56 academic journals in which data papers or/and software papers could be published

Relationship between files: both files have the same information. Two different formats are offered to improve reuse

Type of version of the dataset: final processed version

Versions of the files: 2nd version - Information updated: number of journals, URL, document types associated to a specific journal, publishers normalization and simplification of document types - Information added : listed in the Directory of Open Access Journals (DOAJ), indexed in Web of Science (WOS) and quartile in Scimago Journal and Country Rank (SJR)

Total size: 32 KB

Version 1: Description

This dataset contains a list of journals that publish data articles, code, software articles and database articles.

The search strategy in DOAJ and Ulrichsweb was the search for the word data in the title of the journals. Acknowledgements: Xaquín Lores Torres for his invaluable help in preparing this dataset.

General descriptionThis dataset contains some markers of Open Science in the publications of the Chemical Biology Consortium Sweden (CBCS) between 2010 and July 2023. The sample of CBCS publications during this period consists of 188 articles. Every publication was visited manually at its DOI URL to answer the following questions.1. Is the research article an Open Access publication?2. Does the research article have a Creative Common license or a similar license?3. Does the research article contain a data availability statement?4. Did the authors submit data of their study to a repository such as EMBL, Genbank, Protein Data Bank PDB, Cambridge Crystallographic Data Centre CCDC, Dryad or a similar repository?5. Does the research article contain supplementary data?6. Do the supplementary data have a persistent identifier that makes them citable as a defined research output?VariablesThe data were compiled in a Microsoft Excel 365 document that includes the following variables.1. DOI URL of research article2. Year of publication3. Research article published with Open Access4. License for research article5. Data availability statement in article6. Supplementary data added to article7. Persistent identifier for supplementary data8. Authors submitted data to NCBI or EMBL or PDB or Dryad or CCDCVisualizationParts of the data were visualized in two figures as bar diagrams using Microsoft Excel 365. The first figure displays the number of publications during a year, the number of publications that is published with open access and the number of publications that contain a data availability statement (Figure 1). The second figure shows the number of publication sper year and how many publications contain supplementary data. This figure also shows how many of the supplementary datasets have a persistent identifier (Figure 2).File formats and softwareThe file formats used in this dataset are:.csv (Text file).docx (Microsoft Word 365 file).jpg (JPEG image file).pdf/A (Portable Document Format for archiving).png (Portable Network Graphics image file).pptx (Microsoft Power Point 365 file).txt (Text file).xlsx (Microsoft Excel 365 file)All files can be opened with Microsoft Office 365 and work likely also with the older versions Office 2019 and 2016. MD5 checksumsHere is a list of all files of this dataset and of their MD5 checksums.1. Readme.txt (MD5: 795f171be340c13d78ba8608dafb3e76)2. Manifest.txt (MD5: 46787888019a87bb9d897effdf719b71)3. Materials_and_methods.docx (MD5: 0eedaebf5c88982896bd1e0fe57849c2),4. Materials_and_methods.pdf (MD5: d314bf2bdff866f827741d7a746f063b),5. Materials_and_methods.txt (MD5: 26e7319de89285fc5c1a503d0b01d08a),6. CBCS_publications_until_date_2023_07_05.xlsx (MD5: 532fec0bd177844ac0410b98de13ca7c),7. CBCS_publications_until_date_2023_07_05.csv (MD5: 2580410623f79959c488fdfefe8b4c7b),8. Data_from_CBCS_publications_until_date_2023_07_05_obtained_by_manual_collection.xlsx (MD5: 9c67dd84a6b56a45e1f50a28419930e5),9. Data_from_CBCS_publications_until_date_2023_07_05_obtained_by_manual_collection.csv (MD5: fb3ac69476bfc57a8adc734b4d48ea2b),10. Aggregated_data_from_CBCS_publications_until_2023_07_05.xlsx (MD5: 6b6cbf3b9617fa8960ff15834869f793),11. Aggregated_data_from_CBCS_publications_until_2023_07_05.csv (MD5: b2b8dd36ba86629ed455ae5ad2489d6e),12. Figure_1_CBCS_publications_until_2023_07_05_Open_Access_and_data_availablitiy_statement.xlsx (MD5: 9c0422cf1bbd63ac0709324cb128410e),13. Figure_1.pptx (MD5: 55a1d12b2a9a81dca4bb7f333002f7fe),14. Image_of_figure_1.jpg (MD5: 5179f69297fbbf2eaaf7b641784617d7),15. Image_of_figure_1.png (MD5: 8ec94efc07417d69115200529b359698),16. Figure_2_CBCS_publications_until_2023_07_05_supplementary_data_and_PID_for_supplementary_data.xlsx (MD5: f5f0d6e4218e390169c7409870227a0a),17. Figure_2.pptx (MD5: 0fd4c622dc0474549df88cf37d0e9d72),18. Image_of_figure_2.jpg (MD5: c6c68b63b7320597b239316a1c15e00d),19. Image_of_figure_2.png (MD5: 24413cc7d292f468bec0ac60cbaa7809)

This chart shows the annual number of papers published in Scientific Data and the percentile among journals.

This dataset contains information from scientific publications written by authors who have published papers in the RecSys conference. It contains four files which have information extracted from scientific publications. The details of each file are explained below:i) all_authors.tsv: This file contains the details of authors who published research papers in the RecSys conference. The details include authors' identifier in various forms, such as number, orcid id, dblp url, dblp key and google scholar url, authors' first name, last name and their affiliation (where they work)ii) all_publications.tsv: This file contains the details of publications authored by the authors mentioned in the all_authors.tsv file (Please note the list of publications does not contain all the authored publications of the authors, refer to the publication for further details).The details include publications' identifier in different forms (such as number, dblp key, dblp url, dblp key, google scholar url), title, filtered title, published date, published conference and paper abstract.iii) selected_author_publications-information.tsv: This file consists of identifiers of authors and their publications. Here, we provide the information of selected authors and their publications used for our experiment.iv) selected_publication_citations-information.tsv: This file contains the information of the selected publications which consists of both citing and cited papers’ information used in our experiment. It consists of identifier of citing paper, identifier of cited paper, citation title, citation filtered title, the sentence before the citation is mentioned, citing sentence, the sentence after the citation is mentioned, citation position (section).Please note, it does not contain information of all the citations cited in the publications. For more detail, please refer to the paper.This dataset is for the use of research purposes only and if you use this dataset, please cite our paper "Capturing and exploiting citation knowledge for recommending recently published papers" due to be published in Web2Touch track 2020 (not yet published).

This report presents findings from the 2018 National Mental Health Services Survey (N-MHSS), an annual census of all known facilities in the United States, both public and private, that provide mental health treatment services to people with mental illness. Planned and directed by the Center for Behavioral Health Statistics and Quality (CBHSQ) of the Substance Abuse and Mental Health Services Administration (SAMHSA), U.S. Department of Health and Human Services, the N-MHSS is designed to collect data on the location, characteristics, and utilization of organized mental health treatment services for facilities within the scope of the survey throughout the 50 states, the District of Columbia, Puerto Rico, and other jurisdictions.

This chart compares annual publications with citations to papers published in the same year for ACM Transactions on Knowledge Discovery From Data. These citations refer to papers published in year X, not total citations received by the journal in year X.

This dataset contains background data for a small study about how the recommendations for how to increase the FAIRness of research data are being adopted in scientific/scholarly communities. To get a rough indication of how large the group of Early Adopters of the FAIR Data Principles might be in Norway, I compared the number of unique authors of datasets published in 2019 with the number of unique authors of publications of research results in anthology chapters, articles and monographies (books) in the same year. As a use case, I chose my own university, UiT The Arctic University of Norway (UiT).

Data enclosed in a single zipped folder:

A) DASH-V2 : Data files for final published analysis (J. Informetrics, 2019)

File A1: PubData_DOI_141986_Nc_0_2019.dta

File A2: PubData_DOI_141986_Nc_0_2019_DOFILE

B) DASH-V1 : Data files for preprint version (https://ssrn.com/abstract=2901272)

File B1: PubData_Obs_102741_Nc_10_No2015_CitationsAnalysis.dta

File B2: PubData_Obs_128734_Nc_10_AcceptanceTimeAnalysis.dta

File B3: STATA13_DOFILE

C) Data description common to all .dta files, which contain parsed and merged PLOS ONE and Web of Science metadata:

File A3: UC-DASH_DataDescription_Petersen_V2.pdf

File B4: UC-DASH_DataDescription_Petersen_V1.pdf

Background The geographical distribution of publications as an indicator of the research productivity of individual countries, regions or institutions has become a field of interest. We investigated the geographical distribution of contributions to the two leading journals in the field of medical education, Academic Medicine and Medical Education.

   Methods
   PubMed was used to search Medline. For both journals all journal articles in each year from 1995 to 2000 were included into the study. Then the affiliation was retrieved from the affiliation field of the MEDLINE format. If this was not possible, it was obtained from the paper version of the journal.


   Results
   Academic Medicine published contributions from 25 countries between 1995 and 2000. Authors from 50 countries contributed to Medical Education in the same period of time. Authors from the USA and Canada wrote ca. 95% off all articles in Academic Medicine, whereas authors from the UK, Australia, the USA, Canada and the Netherlands were responsible for ca. 74% of all articles in Medical Education in the investigated period of time.


   Conclusions
   While many countries contributed to both journals, only a few of them were responsible for the majority of all articles.

The data in this set was culled from the Directory of Open Access Journals (DOAJ), the Proquest database Library and Information Science Abstracts (LISA), and a sample of peer reviewed scholarly journals in the field of Library Science. The data include journals that are open access, which was first defined by the Budapest Open Access Initiative: By ‘open access’ to [scholarly] literature, we mean its free availability on the public internet, permitting any users to read, download, copy, distribute, print, search, or link to the full texts of these articles, crawl them for indexing, pass them as data to software, or use them for any other lawful purpose, without financial, legal, or technical barriers other than those inseparable from gaining access to the internet itself. Starting with a batch of 377 journals, we focused our dataset to include journals that met the following criteria: 1) peer-reviewed 2) written in English or abstracted in English, 3) actively published at the time of..., Data Collection In the spring of 2023, researchers gathered 377 scholarly journals whose content covered the work of librarians, archivists, and affiliated information professionals. This data encompassed 221 journals from the Proquest database Library and Information Science Abstracts (LISA), widely regarded as an authoritative database in the field of librarianship. From the Directory of Open Access Journals, we included 144 LIS journals. We also included 12 other journals not indexed in DOAJ or LISA, based on the researchers’ knowledge of existing OA library journals. The data is separated into several different sets representing the different indices and journals we searched. The first set includes journals from the database LISA. The following fields are in this dataset:

Journal: title of the journal

Publisher: title of the publishing company

Open Data Policy: lists whether an open data exists and what the policy is

Country of publication: country where the journal is publ..., , # Open access practices of selected library science journals

The data in this set was culled from the Directory of Open Access Journals (DOAJ), the Proquest database Library and Information Science Abstracts (LISA), and a sample of peer reviewed scholarly journals in the field of Library Science.

The data include journals that are open access, which was first defined by the Budapest Open Access Initiative:Â

By ‘open access’ to [scholarly] literature, we mean its free availability on the public internet, permitting any users to read, download, copy, distribute, print, search, or link to the full texts of these articles, crawl them for indexing, pass them as data to software, or use them for any other lawful purpose, without financial, legal, or technical barriers other than those inseparable from gaining access to the internet itself.

Starting with a batch of 377 journals, we focused our dataset to include journals that met the following criteria: 1) peer-reviewed 2) written in Engli...

Data supporting the Master thesis "Monitoring von Open Data Praktiken - Herausforderungen beim Auffinden von Datenpublikationen am Beispiel der Publikationen von Forschenden der TU Dresden" (Monitoring open data practices - challenges in finding data publications using the example of publications by researchers at TU Dresden) - Katharina Zinke, Institut für Bibliotheks- und Informationswissenschaften, Humboldt-Universität Berlin, 2023

This ZIP-File contains the data the thesis is based on, interim exports of the results and the R script with all pre-processing, data merging and analyses carried out. The documentation of the additional, explorative analysis is also available. The actual PDFs and text files of the scientific papers used are not included as they are published open access.

The folder structure is shown below with the file names and a brief description of the contents of each file. For details concerning the analyses approach, please refer to the master's thesis (publication following soon).

## Data sources

Folder 01_SourceData/

- PLOS-Dataset_v2_Mar23.csv (PLOS-OSI dataset)

- ScopusSearch_ExportResults.csv (export of Scopus search results from Scopus)

- ScopusSearch_ExportResults.ris (export of Scopus search results from Scopus)

- Zotero_Export_ScopusSearch.csv (export of the file names and DOIs of the Scopus search results from Zotero)

## Automatic classification

Folder 02_AutomaticClassification/

- (NOT INCLUDED) PDFs folder (Folder for PDFs of all publications identified by the Scopus search, named AuthorLastName_Year_PublicationTitle_Title)

- (NOT INCLUDED) PDFs_to_text folder (Folder for all texts extracted from the PDFs by ODDPub, named AuthorLastName_Year_PublicationTitle_Title)

- PLOS_ScopusSearch_matched.csv (merge of the Scopus search results with the PLOS_OSI dataset for the files contained in both)

- oddpub_results_wDOIs.csv (results file of the ODDPub classification)

- PLOS_ODDPub.csv (merge of the results file of the ODDPub classification with the PLOS-OSI dataset for the publications contained in both)

## Manual coding

Folder 03_ManualCheck/

- CodeSheet_ManualCheck.txt (Code sheet with descriptions of the variables for manual coding)

- ManualCheck_2023-06-08.csv (Manual coding results file)

- PLOS_ODDPub_Manual.csv (Merge of the results file of the ODDPub and PLOS-OSI classification with the results file of the manual coding)

## Explorative analysis for the discoverability of open data

Folder04_FurtherAnalyses

Proof_of_of_Concept_Open_Data_Monitoring.pdf (Description of the explorative analysis of the discoverability of open data publications using the example of a researcher) - in German

## R-Script

Analyses_MA_OpenDataMonitoring.R (R-Script for preparing, merging and analyzing the data and for performing the ODDPub algorithm)

Supplemental Data of Academic Papers

How many of them are broken links?

About this dataset

This dataset was collected as part of an effort to catalog and analyze supplementary data from publications in the CaltechAUTHORS repository. The dataset includes information on the digital object identifiers (DOIs) for each publication, as well as the URL, title, and description of each linked supplemental data file. This dataset can be used to better understand the types of data that are often included in research publications, as well as how this data is accessed and used over time

How to use the dataset

This dataset contains a wealth of information on supplementary data from publications in the CaltechAUTHORS repository. In particular, it includes:

• A list of all the publications in the CaltechAUTHORS repository and the corresponding doi (digital object identifier) for each publication
• A list of all the URLs related to supplementary data for publications in the CaltechAUTHORS repository
• Data on the number of links that are broken or no longer working over time
• A list of all the years for which supplementary data is available in the CaltechAUTHORS repository
• Data on the number of supplementary data files associated with each publication

This dataset is a valuable resource for anyone interested in collecting and analyzing supplementary data from scientific publications

Research Ideas

1. Finding new supplementary data for publications in the CaltechAUTHORS repository
2. Analyzing trends in the types of supplementary data being published
3. Examining how supplemental data changes over time

Acknowledgements

This data was collected as part of an effort to collect, catalog, and analyze supplementary data from publications in the CaltechAUTHORS repository. We would like to thank the California Institute of Technology for their support of this project

Columns

File: CaltechDATA_URLs.csv | Column name | Description | |:----------------|:--------------------------------------------| | record_doi | The DOI of the publication record. (String) | | related_url | The URL of the related data. (String) | | description | A description of the data. (String) | | type | The type of data. (String) |

File: URLsToCheck.csv | Column name | Description | |:--------------|:------------------------------------------------------------------------| | testLink | A test link to a publication in the CaltechAUTHORS repository. (String) | | rowNum | The row number of the dataset. (Integer) |

File: doi-owners.csv | Column name | Description | |:--------------|:------------------------------------------------------------| | doi | The digital object identifier for the publication. (String) | | doi_name | The name of the publication. (String) |

File: link404s.csv | Column name | Description | |:----------------|:------------------------------------------------------------------------| | record_doi | The DOI of the publication record. (String) | | related_url | The URL of the related data. (String) | | description | A description of the data. (String) | | type | The type of data. (String) | | doi_name | The name of the publication. (String) | | testLink | A test link to a publication in the CaltechAUTHORS repository. (String) | | rowNum | The row number of the dataset. (Integer) |

File: linkDecay.csv | Column name | Description | |:----------------|:------------------------------------------------------------------------| | record_doi | The DOI of the publication record. (String) | | related_url | The URL of the related data. (String) | | description | A description of the data. (String) | | type | The type of data. (String) | | doi_name | The name of the publication. (String) | | testLink | A test link to a publication in the CaltechAUTHORS repository. (String) | | rowNum | The row number of the dataset. (Integer) |

**File: linkTitles.cs...

Publication Types (Publication Characteristics) are Descriptors that indicate what an indexed item is, (i.e., its genre, rather than what it is about - for example, Historical Article). They may include Publication Components, such as Charts; Publication Formats, such as Editorial; and Study Characteristics, such as Clinical Trial. They function as metadata, rather than being about the content. These records are searchable in PubMed as Publication Type [PT], and the terms in MEDLINE records are labeled as "PT" or rather than "MH" or . They are listed in category V of the MeSH Tree Structures.

This is a metadata record for a continuously updated dataset of preprints and journal articles on SARS-CoV-2 and COVID-19 where at least one author has an affiliation with a Swedish university or research institute. The dataset is created as part of the Swedish COVID-19 Data Portal (https://covid19dataportal.se). The dataset is manually curated.The most recent version can be browsed using the following link: https://covid19dataportal.se/publications/. The most recent version can be downloaded as a .JSON file using the following link: https://publications-covid19.scilifelab.se/publications.json.For each entry, the dataset contains information automatically imported from Crossref or PubMed such as: publication title, author list, abstract text, journal/preprint server name and other bibliographic information. In addition, each entry is manually assigned categories corresponding scientific field, publication type, acknowledged funder, associated data description and links/accession numbers. Please see the README.txt file for more information about available variables.Researchers are welcome to use the data contained in the dataset for any projects. Please cite this metadata record upon use. We encourage reuse using the same CC BY 4.0 License.The dataset is maintained using the Publications web-based reference database system, https://github.com/pekrau/Publications, built by Per Kraulis (https://github.com/pekrau) at the SciLifeLab Data Centre.

This article describes the novel open source tools for open data publication in open access journal workflows. This comprises a plugin for Open Journal Systems that supports a data submission, citation, review, and publication workflow; and an extension to the Dataverse system that provides a standard deposit API. We describe the function and design of these tools, provide examples of their use, and summarize their initial reception. We conclude by discussing future plans and potential impact.

Yearly citation totals from each year of the MEDLINE/PubMed Baseline referencing citations back to year 1781. These totals may increase over time for a particular year as new citations are added. For example, 25 citations were listed for the year 1800 in the 2018 MEDLINE/PubMed Baseline, while the 2019 Baseline includes 387 citations for that year.

Much prior research finds women earn fewer citations than men for their publications and offers various reasons why that is the case. We offer new evidence on such citation differences from two data sets on career citations earned by male and female political scientists. Our findings extend and elaborate those in earlier research. Most notably, we find that older cohorts of women demonstrate substantial progress toward citation equity with their male peers.

Complementary materials contain the annexes to the article, the raw data, and the data that resulted from the analysis

The BGS Publications Database contains metadata relating to documents created by the British Geological Survey (BGS). These documents include published works (commercially published, formally printed, listed for sale and available for general distribution to the public), as well as informally published technical reports and current report RR, OR, CR and IR series. The database contains documents which are released for general distribution, as well as confidential documents and documents which are available only to BGS staff. The database contains series of publications which have been used throughout the existence of the Geological Survey, including sheet memoirs, district memoirs, summaries of work and regional geological guides which date from the beginning of Geological Survey activity in the early 19th century to the present day. The database also contains RR (research), OR (open), CR (commissioned) and IR (internal) reports from the current BGS report series, as well as a large (over 25 000) number of technical reports created by various units within BGS from the 1940s through to the year 2000. Basic metadata about a publication are held, including its unique ID, reference number, year of publication, full title, author(s), series and publisher. Many publications are held in digital formats, either as scans of hard-copy documents or as born-digital files. Publications stored within the database are available to view, but are not available for download. Non-confidential technical reports are available to download in PDF format. The database can be browsed and reports accessed through the BGS Publications Viewer: https://webapps.bgs.ac.uk/data/publications/. The current series of open reports from BGS are available on the NERC Open Research Archive (NORA): https://nora.nerc.ac.uk/.