published journal article. This dataset is associated with the following publication: Schumacher, B., J. Zimmerman, J. Elliot, and G. Swanson. The Effect of Equilibration Time and Tubing Material on Soil Gas Measurements. SOIL AND SEDIMENT CONTAMINATION: AN INTERNATIONAL JOURNAL. CRC Press LLC, Boca Raton, FL, USA, 25(2): 151-163, (2016).

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.

Files associated with the manuscript: Proteome profiling of rat brain cortical changes during early postnatal brain development. This dataset is associated with the following publication: Winnik, W., W. Padgett, E. Pitzer, and D. Herr. Proteome profiling of rat brain cortical changes during early postnatal brain development. Journal of Proteome Research. American Chemical Society, Washington, DC, USA, 22(7): 2460-2476, (2023).

The journals’ author guidelines and/or editorial policies were examined on whether they take a stance with regard to the availability of the underlying data of the submitted article. The mere explicated possibility of providing supplementary material along with the submitted article was not considered as a research data policy in the present study. Furthermore, the present article excluded source codes or algorithms from the scope of the paper and thus policies related to them are not included in the analysis of the present article.

For selection of journals within the field of neurosciences, Clarivate Analytics’ InCites Journal Citation Reports database was searched using categories of neurosciences and neuroimaging. From the results, journals with the 40 highest Impact Factor (for the year 2017) indicators were extracted for scrutiny of research data policies. Respectively, the selection journals within the field of physics was created by performing a similar search with the categories of physics, applied; physics, atomic, molecular & chemical; physics, condensed matter; physics, fluids & plasmas; physics, mathematical; physics, multidisciplinary; physics, nuclear and physics, particles & fields. From the results, journals with the 40 highest Impact Factor indicators were again extracted for scrutiny. Similarly, the 40 journals representing the field of operations research were extracted by using the search category of operations research and management.

Journal-specific data policies were sought from journal specific websites providing journal specific author guidelines or editorial policies. Within the present study, the examination of journal data policies was done in May 2019. The primary data source was journal-specific author guidelines. If journal guidelines explicitly linked to the publisher’s general policy with regard to research data, these were used in the analyses of the present article. If journal-specific research data policy, or lack of, was inconsistent with the publisher’s general policies, the journal-specific policies and guidelines were prioritized and used in the present article’s data. If journals’ author guidelines were not openly available online due to, e.g., accepting submissions on an invite-only basis, the journal was not included in the data of the present article. Also journals that exclusively publish review articles were excluded and replaced with the journal having the next highest Impact Factor indicator so that each set representing the three field of sciences consisted of 40 journals. The final data thus consisted of 120 journals in total.

‘Public deposition’ refers to a scenario where researcher deposits data to a public repository and thus gives the administrative role of the data to the receiving repository. ‘Scientific sharing’ refers to a scenario where researcher administers his or her data locally and by request provides it to interested reader. Note that none of the journals examined in the present article required that all data types underlying a submitted work should be deposited into a public data repositories. However, some journals required public deposition of data of specific types. Within the journal research data policies examined in the present article, these data types are well presented by the Springer Nature policy on “Availability of data, materials, code and protocols” (Springer Nature, 2018), that is, DNA and RNA data; protein sequences and DNA and RNA sequencing data; genetic polymorphisms data; linked phenotype and genotype data; gene expression microarray data; proteomics data; macromolecular structures and crystallographic data for small molecules. Furthermore, the registration of clinical trials in a public repository was also considered as a data type in this study. The term specific data types used in the custom coding framework of the present study thus refers to both life sciences data and public registration of clinical trials. These data types have community-endorsed public repositories where deposition was most often mandated within the journals’ research data policies.

The term ‘location’ refers to whether the journal’s data policy provides suggestions or requirements for the repositories or services used to share the underlying data of the submitted works. A mere general reference to ‘public repositories’ was not considered a location suggestion, but only references to individual repositories and services. The category of ‘immediate release of data’ examines whether the journals’ research data policy addresses the timing of publication of the underlying data of submitted works. Note that even though the journals may only encourage public deposition of the data, the editorial processes could be set up so that it leads to either publication of the research data or the research data metadata in conjunction to publishing of the submitted work.

1The totals in this column equal the number of articles reporting a particular type of funding, minus instances of duplicate classification by type of company within funding category. These instances were: There was no information on funding for the article classified as both manufacturing and mining, and non-profit, non-governmental funding was used by the articles classified as both tobacco and transportation and both tobacco and alcohol. The overall column total is greater than the total number of included articles (N = 361) because some articles reported multiple types of funding.2Other funding sources include Blue Cross Blue Shield (4 tobacco articles), the World Health Organization (2 tobacco articles), and funding from a law firm (1 manufacturing article).3The totals in this row equal the total number of articles reporting funding for each type of company, minus instances where articles reported multiple types of funding, of which there are too many to list. The totals for the columns are therefore not equal to the sum of the classifications within the columns. The overall row total is greater than the total number of included articles (N = 361) because three articles were classified with two types of companies.

This is a CSV file containing a listing of the top 60 articles published in the Journal of Digital Scholarship in the Humanities (JDSH, preciously LLC), as exported from the Altmetric Explorer tool on11 April 2017. The sheet has been manually annotated adding columns to indicate each article entry's corresponding License (column E) and Access Type (column F). License and Access Type data was crosschecked manually by accessing each article online individually. The file also contains data obtained from the Open Access Button API. The article DOIs as obtained from the Altmetric Explorer were run through the Open Access Button API on 15 May 2017 in order to discover if any of the published articles had open versions available. Any resulting links when available, were added to column O. Columns O and P also include additional information, when available, about the type of content available via the Open Access Button. Joe McArthur from the Open Access Button ran the first initial search for open surrogates of this dataset through the Open Access Button API. Ernesto Priego then manually crosschecked each entry and limited the final dataset to the top 60 articles (of 82). Please note that the Altmetric data for the JDSH is likely to have changed by now, though not too significantly. Altmetric scores have not been included in this file but the order of the entries correspond to the order in the data initially exported from the Altmetric Explorer (from most mentions to fiewer mentions, with a minimum of 1 mention). This dataset is part of the author and collaborator's ongoing research on open access and institutional repository uptake in the digital humanities. The data included in this file allows users to quickly quantify the number of JDSH articles published with open licenses, number of currently 'free', paywalled or open access articles. The data shared here also allows users to see which of the articles and/or their metadata (according to the Open Access Button API) have been deposited in institutional repositories. The data presented is the result of the specific methods employed to obtain the data. In this sense this data represents as much a testing of the technologies employed as of the actual articles' licensing and open availability. This means that data in columns L-P reflect the data available through the Open Access Button API at the moment of collection. It is perfectly possible that 'open surrogates' of the articles listed are available elsewhere through other methods. As indicated above data in columns E-F was obtained and added manually. Article DOI's were accessed manually from a computer browser outside/without access to university library networks, as the intention was to verify if any of the articles were available to the general public without university library network/subscription credentials.This deposit is part of a work in progress and is shared openly to document ongoing work and to encourage further discussion and analyses.

Uzbekistan UZ: Scientific and Technical Journal Articles data was reported at 357.400 Unit in 2016. This records an increase from the previous number of 287.800 Unit for 2015. Uzbekistan UZ: Scientific and Technical Journal Articles data is updated yearly, averaging 334.250 Unit from Dec 2003 (Median) to 2016, with 14 observations. The data reached an all-time high of 388.900 Unit in 2010 and a record low of 277.700 Unit in 2003. Uzbekistan UZ: Scientific and Technical Journal Articles data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Uzbekistan – Table UZ.World Bank: Technology. Scientific and technical journal articles refer to the number of scientific and engineering articles published in the following fields: physics, biology, chemistry, mathematics, clinical medicine, biomedical research, engineering and technology, and earth and space sciences.; ; National Science Foundation, Science and Engineering Indicators.; Gap-filled total;

Journal Article Tag Suite (JATS) is an application of NISO Z39.96.2019, which defines a set of XML elements and attributes for describing the textual and graphical content of journal articles and describes three article models.

Scientific and technical journal articles in India was reported at 207390 in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. India - Scientific and technical journal articles - actual values, historical data, forecasts and projections were sourced from the World Bank on October of 2025.

This article describes a systematic analysis of the relationship between empirical data and theoretical conclusions for a set of experimental psychology articles published in the journal Science between 2005–2012. When the success rate of a set of empirical studies is much higher than would be expected relative to the experiments' reported effects and sample sizes, it suggests that null findings have been suppressed, that the experiments or analyses were inappropriate, or that the theory does not properly follow from the data. The analyses herein indicate such excess success for 83% (15 out of 18) of the articles in Science that report four or more studies and contain sufficient information for the analysis. This result suggests a systematic pattern of excess success among psychology articles in the journal Science.

The dataset contains the list of 213 journal articles and book chapters that deal with media empirical evidence on femicide, available in Scopus, Web of Science (WoS), and EBSCOhost. The dataset includes three sheets in one file, the first contains a list of the 213 documents available in the three databases including their bibliographic information, general description, and keywords describing the main results. The second sheet contains the codes for variables, and the third sheet contains the list of a subgroup of articles available in Scopus and Web of Science (WoS).

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)

Dataset

This dataset was created by Hikmet Gumus

Released under Other (specified in description)

Contents

This graph shows the proportion of articles by discipline with original data generated by the research described in the article, along with associated confidence intervals. See Tables 9 and 11 for numeric values.

README

COVID-19 Research Papers Dataset

Introduction

This dataset includes papers containing published research results on COVID-19. Each paper has its PubMed ID, DOI number, journal title, journal country, article title, authors, abstract, date of publication, and the number of citations until the date of update. It contains more than 150,000 articles in total. Newly added paper and citation numbers are updated monthly.

Data Collection

All articles with the word "COVID-19" published before September 2021 were included in the dataset. All data were collected using the PubMed API. Using multiple APIs, the data related to the articles were combined and made into a data set. The data set will be updated by adding new articles every month.

Dataset

All data is in papers.csv file.

Columns

• PubMed ID
• DOI
• Journal Name
• Journal Country
• Paper Title
• Authors
• Abstract
• Publication Date
• Citation Count

Update History

• 25.05.2021: Articles before May 2021 have been added.
• 23.08.2021: Articles before August 2021 have been added.
• 07.10.2021: Articles before September 2021 have been added.

Licence

See LICENSE for details.

WhenArthritis Researchwas launched in 1999 the publishers and ourselves took the innovative decision to make all primary research articles available to everyone for free through the journal's own websitehttp://arthritis-research.comas well as through PubMed Centralhttp://www.pubmedcentral.nih.gov/, the National Institute of Health's repository for biomedical research articles, and through the BioMed Central (BMC) websitehttp://biomedcentral.com. We now feel that it is time to lead the way forward again by only publishing research articles in full online beginning with volume 4 number 4 ofArthritis Research.

ERS supports a broad spectrum of food and nutrition assistance research and has compiled an electronic database of over 900 peer-reviewed reports and articles based on ERS-supported research. The database is searchable by title, lead author, topic, year of publication, and data set analyzed.

This research aims to reveal the effects of risk perceptions and economic crisis on holiday intention in the COVID-19 process in the context of Planned Behavior Theory. Data were collected online from 576 people from Turkey.

Lebanon LB: Scientific and Technical Journal Articles data was reported at 1,397.900 Unit in 2016. This records an increase from the previous number of 1,278.100 Unit for 2015. Lebanon LB: Scientific and Technical Journal Articles data is updated yearly, averaging 776.500 Unit from Dec 2003 (Median) to 2016, with 14 observations. The data reached an all-time high of 1,397.900 Unit in 2016 and a record low of 459.900 Unit in 2003. Lebanon LB: Scientific and Technical Journal Articles data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Lebanon – Table LB.World Bank: Technology. Scientific and technical journal articles refer to the number of scientific and engineering articles published in the following fields: physics, biology, chemistry, mathematics, clinical medicine, biomedical research, engineering and technology, and earth and space sciences.; ; National Science Foundation, Science and Engineering Indicators.; Gap-filled total;

Turkey TR: Scientific and Technical Journal Articles data was reported at 33,902.200 Unit in 2016. This records an increase from the previous number of 33,113.000 Unit for 2015. Turkey TR: Scientific and Technical Journal Articles data is updated yearly, averaging 25,015.500 Unit from Dec 2003 (Median) to 2016, with 14 observations. The data reached an all-time high of 33,902.200 Unit in 2016 and a record low of 13,353.600 Unit in 2003. Turkey TR: Scientific and Technical Journal Articles data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Turkey – Table TR.World Bank: Technology. Scientific and technical journal articles refer to the number of scientific and engineering articles published in the following fields: physics, biology, chemistry, mathematics, clinical medicine, biomedical research, engineering and technology, and earth and space sciences.; ; National Science Foundation, Science and Engineering Indicators.; Gap-filled total;