This is the underlying dataset used for the country analysis regarding the percentage of papers in Dimensions and Web of Science (WoS), published between 2015 and 2019 that are open access (OA), regardless of mode of OA.A paper was assigned a country affiliation based on the affiliation of the first author of a paper, thus each paper is only counted once, regardless whether the paper had multiple coauthors.Each row represents the data for a country. A country only appears once (i.e., each row is unique).Column headings:iso_alpha_2 = the ISO alpha 2 country code of the countrycountry = the name of the country as stated either in Dimensions or WoS.world_bank_region_2021 = pub_wos = total number of papers (document type articles and reviews) indexed in WoS, published from 2015 to 2019oa_pers_wos = Percentage of pub_wos that are OApub_dim = total number of papers (document type journal articles) indexed in Dimensions, published from 2015 to 2019oa_pers_dim = Percentage of pub_dim that are OArelative_diff = the relative difference between oa_pers_dim and oa_pers_wos using the following equation: ((x-y))/((x+y) ), with x representing the percentage of papers for the country in the Dimensions dataset that are OA, and y representing the percentage of papers for the country in the WoS dataset that are OA. In cases of "N/A" in a cell, a division by 0 occurred.Data availabilityRestriction apply to both datasets used to generate the aggregate data. The Web of Science data is owned by Clarivate Analytics. To obtain the bibliometric data in the same manner as authors (i.e. by purchasing them), readers can contact Clarivate Analytics at the following URL: https://clarivate.com/webofsciencegroup/solutions/web-of-science/contact-us/. The Dimensions data is owned by Digital Science, which has a programme that provides no cost access to its data. It can be accessed at: https://dimensions.ai/data_access.

The global market for academic research databases is experiencing robust growth, projected to be valued at $259.3 million in 2025 and exhibiting a Compound Annual Growth Rate (CAGR) of 5.9% from 2025 to 2033. This expansion is driven by several key factors. The increasing digitization of scholarly publications and the growing reliance on online research resources across universities, research institutions, and corporations are significant contributors. Furthermore, the expanding availability of open-access journals and repositories, while presenting challenges to some established players, ultimately broadens the overall market by increasing accessibility and usage. The rising demand for advanced search functionalities, data analytics tools integrated within these databases, and robust citation management systems also fuels market growth. Different subscription models, including free and charge-based access, cater to diverse user needs – students, teachers, experts, and others – further driving market segmentation and overall growth. The North American market currently holds a significant share due to the presence of major research institutions and established database providers. However, increasing research activities in Asia-Pacific and other regions are poised to fuel future growth, with a potentially significant increase in the market share in these regions over the forecast period. Competition remains intense among established players like Scopus, Web of Science, and PubMed, alongside newer entrants. Differentiation through superior indexing, advanced search capabilities, and specialized content areas is vital for success in this competitive landscape. The market segmentation by application (Student, Teacher, Expert, Others) and type of access (Charge, Free) provides valuable insights into the diverse user base and revenue streams. The "charge" segment is expected to maintain a significant market share, driven by the demand for comprehensive and specialized research content requiring paid subscriptions. However, the "free" segment, fueled by the increasing availability of open-access resources, will also show considerable growth, broadening accessibility and market penetration. Regional growth patterns will likely reflect existing research infrastructure and investments in higher education and research across different geographic areas. Continued technological advancements and innovation in areas such as artificial intelligence-powered search and data analysis will further shape the market landscape, leading to more sophisticated and efficient research tools in the years to come.

Database compilation of global and regional data sources used in the three case studies. Some of the sources included in this database were identified in collaboration with the regional stakeholders. This inventory of Open Access databases is relevant to multi-objective, multi-realm and multi-time planning in Europe.

The data in this set was gathered to analyze the open access practices of library journals. The data 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. Starting with a batch of 377 journals, the researchers focused their 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 analysis, and 4) scoped to librarianship. The dataset presents an overview of the landscape of open access scholarly publishing in the LIS field during a very specific time period, spring and summer of 2023. Methods Data Collection The researchers gathered 377 scholarly journals whose content covered the work of librarians, archivists, and affiliated information professionals. This data encompassed 222 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 11 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

Publisher Type: the kind of publisher, whether association, traditional, university library, or independent

Country of publication: country where the journal is published

Region: geographical place of publication

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

Open Data Notes: descriptions of the open data policies Open ranking: details whether the journal is diamond, gold, and/or green

Open peer review: specifies if the journal does open peer review

Author retains copyright: explains copyright policy

APCs: Details whether there is an article processing charge

In DOAJ: details whether the journal is also published in the Directory of Open Access Journals

The second set includes similar as the previous set, but it also includes two additional columns:

Type of CC: lists the Creative Commons license applied to the journal articles

In LISA: details whether the journal is also published in the Library and Information Science Abstracts database

A third dataset includes eleven scholarly, peer reviewed journals focused on Library and Information Science that were not in DOAJ or LISA. This dataset is also labeled with the same fields as the first dataset. The fourth dataset is the complete list of 377 journals that we evaluated for inclusion in this dataset. Data Processing To explore the current state of OA scholarly publishing in librarianship, we developed the following criteria: Journals must be published at the time of analysis, peer reviewed, and scoped to librarianship and must have articles or abstracts in English so that we could determine the journal’s scope. After applying inclusion/exclusion criteria, 145 of 377 journals remained; however, the total number of journals analyzed is 133 because the DOAJ and LISA shared 12 journals. The researchers explored the open data policies, open access publication options, country of origin, publisher, and peer review process of each of the remaining 133 journals. The researchers also looked for article processing costs, type of Creative Commons licensing (open licenses that allow users to redistribute and sometimes remix intellectual property), and whether the journals were included in either the DOAJ and/or LISA index. References: Budapest Open Access Initiative. (2002) http://www.soros.org/openaccess/

Database providing access to quality controlled Open Access Journals. For a journal to be included it should exercise quality control on submitted papers through an editor, editorial board and/or a peer-review system. It is not be limited to particular languages or subject areas. Offering free online access to high quality full text content, plus excellent search tools, the portal enables researchers to find, use and re-use a vast range of materials with ease. The content of DOAJ will be even more visible and disseminated through this portal. The aim of the Directory is to increase the visibility and ease of use of open access scientific and scholarly journals thereby promoting their increased usage and impact. As of April 2014, DOAJ has 9,709 journals, 5,624 journals searchable at article level, 133 Countries and 1,600,991 articles. The database may be browsed by title or subject, or searched through the interface to for journals or articles.

The dataset shows the subjects of open access items (2012) indexed in the database of Open-Access-Netzwerk. The dataset is presented in csv.

The global academic research databases market is projected to grow from $439 million in 2025 to $739 million by 2033, at a CAGR of 6.1%. The market is driven by the increasing demand for access to academic content, the growing number of students and researchers, and the adoption of digital technologies in education and research. The major players in the market include Scopus, Web of Science, PubMed, ERIC, and ProQuest. The growth of the academic research databases market is also fueled by the increasing availability of open access content and the rising use of artificial intelligence (AI) in research. AI can be used to automate tasks such as literature search and data analysis, which can save researchers time and effort. Additionally, the development of new technologies such as virtual reality (VR) and augmented reality (AR) is creating new opportunities for researchers to access and interact with research content. These trends are expected to continue to drive the growth of the academic research databases market in the coming years.

ST - DHS Public Access Database: Consistent with the 2013 OSTP Memorandum and the 2022 update, “Increasing Access to the Results of Federally Funded Scientific Research,” directed all agencies with greater than $100 million in R&D expenditures each year to prepare a plan for improving the public’s access to the results of federally funded research, specifically peer-reviewed scholarly publications and digital data. In response to the memorandum, DHS developed a DHS Public Access Plan, and intends to make available to the public digitally formatted scientific data that support the conclusions in peer-reviewed scholarly publications that are the results of DHS R&D funding. This data repository site with a customized DHS Storefront allows DHS to post releasable scientific digital data from peer-reviewed publications resulting from DHS-funded research. The data repository is configured to allow DHS users (and publishers acting on behalf of these users) to deposit data sets into the repository, making them available to the general public.

United States agricultural researchers have many options for making their data available online. This dataset aggregates the primary sources of ag-related data and determines where researchers are likely to deposit their agricultural data. These data serve as both a current landscape analysis and also as a baseline for future studies of ag research data. Purpose As sources of agricultural data become more numerous and disparate, and collaboration and open data become more expected if not required, this research provides a landscape inventory of online sources of open agricultural data. An inventory of current agricultural data sharing options will help assess how the Ag Data Commons, a platform for USDA-funded data cataloging and publication, can best support data-intensive and multi-disciplinary research. It will also help agricultural librarians assist their researchers in data management and publication. The goals of this study were to

establish where agricultural researchers in the United States-- land grant and USDA researchers, primarily ARS, NRCS, USFS and other agencies -- currently publish their data, including general research data repositories, domain-specific databases, and the top journals compare how much data is in institutional vs. domain-specific vs. federal platforms determine which repositories are recommended by top journals that require or recommend the publication of supporting data ascertain where researchers not affiliated with funding or initiatives possessing a designated open data repository can publish data

Approach The National Agricultural Library team focused on Agricultural Research Service (ARS), Natural Resources Conservation Service (NRCS), and United States Forest Service (USFS) style research data, rather than ag economics, statistics, and social sciences data. To find domain-specific, general, institutional, and federal agency repositories and databases that are open to US research submissions and have some amount of ag data, resources including re3data, libguides, and ARS lists were analysed. Primarily environmental or public health databases were not included, but places where ag grantees would publish data were considered.
Search methods We first compiled a list of known domain specific USDA / ARS datasets / databases that are represented in the Ag Data Commons, including ARS Image Gallery, ARS Nutrition Databases (sub-components), SoyBase, PeanutBase, National Fungus Collection, i5K Workspace @ NAL, and GRIN. We then searched using search engines such as Bing and Google for non-USDA / federal ag databases, using Boolean variations of “agricultural data” /“ag data” / “scientific data” + NOT + USDA (to filter out the federal / USDA results). Most of these results were domain specific, though some contained a mix of data subjects. We then used search engines such as Bing and Google to find top agricultural university repositories using variations of “agriculture”, “ag data” and “university” to find schools with agriculture programs. Using that list of universities, we searched each university web site to see if their institution had a repository for their unique, independent research data if not apparent in the initial web browser search. We found both ag specific university repositories and general university repositories that housed a portion of agricultural data. Ag specific university repositories are included in the list of domain-specific repositories. Results included Columbia University – International Research Institute for Climate and Society, UC Davis – Cover Crops Database, etc. If a general university repository existed, we determined whether that repository could filter to include only data results after our chosen ag search terms were applied. General university databases that contain ag data included Colorado State University Digital Collections, University of Michigan ICPSR (Inter-university Consortium for Political and Social Research), and University of Minnesota DRUM (Digital Repository of the University of Minnesota). We then split out NCBI (National Center for Biotechnology Information) repositories. Next we searched the internet for open general data repositories using a variety of search engines, and repositories containing a mix of data, journals, books, and other types of records were tested to determine whether that repository could filter for data results after search terms were applied. General subject data repositories include Figshare, Open Science Framework, PANGEA, Protein Data Bank, and Zenodo. Finally, we compared scholarly journal suggestions for data repositories against our list to fill in any missing repositories that might contain agricultural data. Extensive lists of journals were compiled, in which USDA published in 2012 and 2016, combining search results in ARIS, Scopus, and the Forest Service's TreeSearch, plus the USDA web sites Economic Research Service (ERS), National Agricultural Statistics Service (NASS), Natural Resources and Conservation Service (NRCS), Food and Nutrition Service (FNS), Rural Development (RD), and Agricultural Marketing Service (AMS). The top 50 journals' author instructions were consulted to see if they (a) ask or require submitters to provide supplemental data, or (b) require submitters to submit data to open repositories. Data are provided for Journals based on a 2012 and 2016 study of where USDA employees publish their research studies, ranked by number of articles, including 2015/2016 Impact Factor, Author guidelines, Supplemental Data?, Supplemental Data reviewed?, Open Data (Supplemental or in Repository) Required? and Recommended data repositories, as provided in the online author guidelines for each the top 50 journals. Evaluation We ran a series of searches on all resulting general subject databases with the designated search terms. From the results, we noted the total number of datasets in the repository, type of resource searched (datasets, data, images, components, etc.), percentage of the total database that each term comprised, any dataset with a search term that comprised at least 1% and 5% of the total collection, and any search term that returned greater than 100 and greater than 500 results. We compared domain-specific databases and repositories based on parent organization, type of institution, and whether data submissions were dependent on conditions such as funding or affiliation of some kind. Results A summary of the major findings from our data review:

Over half of the top 50 ag-related journals from our profile require or encourage open data for their published authors. There are few general repositories that are both large AND contain a significant portion of ag data in their collection. GBIF (Global Biodiversity Information Facility), ICPSR, and ORNL DAAC were among those that had over 500 datasets returned with at least one ag search term and had that result comprise at least 5% of the total collection.
Not even one quarter of the domain-specific repositories and datasets reviewed allow open submission by any researcher regardless of funding or affiliation.

See included README file for descriptions of each individual data file in this dataset. Resources in this dataset:Resource Title: Journals. File Name: Journals.csvResource Title: Journals - Recommended repositories. File Name: Repos_from_journals.csvResource Title: TDWG presentation. File Name: TDWG_Presentation.pptxResource Title: Domain Specific ag data sources. File Name: domain_specific_ag_databases.csvResource Title: Data Dictionary for Ag Data Repository Inventory. File Name: Ag_Data_Repo_DD.csvResource Title: General repositories containing ag data. File Name: general_repos_1.csvResource Title: README and file inventory. File Name: README_InventoryPublicDBandREepAgData.txt

Context
From June 2020 to February 2021, a consortium of 10 organisations undertook a large-scale study on open access journals across the world that are free for readers and authors, usually referred to as “OA diamond journals”. This study was commissioned by cOAlition S in order to gain a better understanding of the OA diamond landscape.

Presentation
The study undertook a statistical analysis of several bibliographic databases, surveyed 1,619 journals, collected 7,019 free text submissions and other data from 94 questions, and organised three focus groups with 11 journals and 10 interviews with hosting platforms. It collected 163 references in the academic literature, and inventoried 1048 journals not listed in DOAJ.

The results of the study are available in the following outputs:

• Findings Report - DOI: 10.5281/zenodo.4558704
• Recommendations Report- DOI:10.5281/zenodo.4562790
• References Library - DOI: 10.5281/zenodo.4562816
• Journals Inventory - DOI: 10.5281/zenodo.4562828
• Dataset - DOI: 10.5281/zenodo.4553103

This dataset contains data used by and partly generated by the OA Diamond Journals Study on open access journals that do not charge authors. It contains the data files themselves as well as some readme texts with variable lists.

Available files:

• Survey questionnaire, English version (PDF)
• Survey data without identifying information and without free texts answers (as these might also include identifying information) (CSV). This includes, for some questions, data from DOAJ for journals present in that database.
• Readme text with the variable list for the survey data file (TXT)
• Stratified sample of 500 records from the ROAD database of open access journals downloaded 20201102 (CSV)
• Readme text with the variable list for the ROAD database sample (TXT)
• Directory of Open Access Journals (DOAJ) metadata downloaded 20200602 (CSV)
• Directory of Open Access Journals (DOAJ) metadata downloaded 20200918 (CSV)
• Added and Removed change log DOAJ, downloaded 20210121 (CSV)
• Readme text with variable list for the Added and Removed change log DOAJ (TXT)

All data are available for reuse under a CC0 license.

Additionally, an online version of the survey results (excluding DOAJ data and excluding free text answers) is available from SurveyMonkey

University of Sfax

The dataset contains all the data produced running the research software for the study:"Open Science for Social Sciences and Humanities: Open Access availability and distribution across disciplines and Countries in OpenCitations Meta".

Disclaimer: these results are not considered to be representative, because we have fount that Mega Journals skewed significantly some of the data. The result datasets without Mega Journals are published here.

Description of datasets:

SSH_Publications_in_OC_Meta_and_Open_Access_status.csv: containing information about OpenCitations Meta coverage of ERIH PLUS Journals as well as their Open Access availability. In this dataset, every row holds data for a Journal of ERIH PLUS also covered by OpenCitations Meta database. It is structured with the following columns: "EP_id", the internal ERIH PLUS identifier; "Publications_in_venue", the numbers of Publications counted in each venue; "OC_omid", the internal OpenCitations Meta identifier for the venue; "issn", numbers of publications in each venue; "Open Access", a value to represent if the journal is OA or not, either "True" or "Unknown".

SSH_Publications_by_Discipline.csv: containing information about number of publications per discipline (in addition, number of journals per discipline are also included). The dataset has three columns, the first, labeled "Discipline", contains single disciplines of the ERIH classificaton, the second and the third, labeled "Journal_count" and "Publication_count", respectively, the number of Journals and the number of Publications counted for each discipline.

SSH_Publications_and_Journals_by_Country: containing information about number of publications and journals per country. The dataset has three columns, the first, labeled "Country", contains single countries of the ERIH classificaton, the second and the third, labeled "Journal_count" and "Publication_count", respectively, the number of Journals and the number of Publications counted for each discipline.

result_disciplines.json: the dictionary containing all disciplines as key and a list of related ERIH PLUS venue identifiers as value.

result_countries.json: the dictionary containing all countries as key and a list of related ERIH PLUS venue identifiers as value.

duplicate_omids.csv: a dataset containing the duplicated Journal entries in OpenCitations Meta, structured with two columns: "OC_omid", the internal OC Meta identifier; "issn", the issn values associated to that identifier

eu_data.csv: contains the data specific for European countries' SSH Journals covered in OCMeta. It is structured with the following columns: "EP_id", the internal ERIH PLUS identifier; "Publications_in_venue", the numbers of Publications counted in each venue; "Original_Title", "Country_of_Publication","ERIH_PLUS_Disciplines", "disc_count", the number of disciplines per Journal.

eu_disciplines_count.csv: containing information about number of publications per discipline and number of journals per discipline of european countries. The dataset has three columns, the first, labeled "Discipline", contains single disciplines of the ERIH classificaton, the second and the third, labeled "Journal_count" and "Publication_count", respectively, the number of Journals and the number of Publications counted for each discipline.

meta_coverage_eu.csv: contains the data specific for European countries' SSH Journals covered in OCMeta. It is structured with the following columns: "EP_id", the internal ERIH PLUS identifier; "Publications_in_venue", the numbers of Publications counted in each venue; "OC_omid", the internal OpenCitations Meta identifier for the venue; "issn", numbers of publications in each venue; "Open Access", a value to represent if the journal is OA or not, either "True" or "Unknown".

us_data.csv: contains the data specific for the United States' SSH Journals covered in OCMeta. It is structured with the following columns: "EP_id", the internal ERIH PLUS identifier; "Publications_in_venue", the numbers of Publications counted in each venue; "Original_Title", "Country_of_Publication","ERIH_PLUS_Disciplines", "disc_count", the number of disciplines per Journal.

us_disciplines_count.csv: containing information about number of publications per discipline and number of journals per discipline of the United States. The dataset has three columns, the first, labeled "Discipline", contains single disciplines of the ERIH classificaton, the second and the third, labeled "Journal_count" and "Publication_count", respectively, the number of Journals and the number of Publications counted for each discipline.

meta_coverage_us.csv: contains the data specific for the United States' SSH Journals covered in OCMeta. It is structured with the following columns: "EP_id", the internal ERIH PLUS identifier; "Publications_in_venue", the numbers of Publications counted in each venue; "OC_omid", the internal OpenCitations Meta identifier for the venue; "issn", numbers of publications in each venue; "Open Access", a value to represent if the journal is OA or not, either "True" or "Unknown".

Abstract of the research:

Purpose: this study aims to investigate the representation and distribution of Social Science and Humanities (SSH) journals within the OpenCitations Meta database, with a particular emphasis on their Open Access (OA) status, as well as their spread across different disciplines and countries. The underlying premise is that open infrastructures play a pivotal role in promoting transparency, reproducibility, and trust in scientific research. Study Design and Methodology: the study is grounded on the premise that open infrastructures are crucial for ensuring transparency, reproducibility, and fostering trust in scientific research. The research methodology involved the use of secondary data sources, namely the OpenCitations Meta database, the ERIH PLUS bibliographic index, and the DOAJ index. A custom research software was developed in Python to facilitate the processing and analysis of the data. Findings: the results reveal that 78.1% of SSH journals listed in the European Reference Index for the Humanities (ERIH-PLUS) are included in the OpenCitations Meta database. The discipline of Psychology has the highest number of publications. The United States and the United Kingdom are the leading contributors in terms of the number of publications. However, the study also uncovers that only 38% of the SSH journals in the OpenCitations Meta database are OA. Originality: this research adds to the existing body of knowledge by providing insights into the representation of SSH in open bibliographic databases and the role of open access in this domain. The study highlights the necessity for advocating OA practices within SSH and the significance of open data for bibliometric studies. It further encourages additional research into the impact of OA on various facets of citation patterns and the factors leading to disparity across disciplinary representation.

Related resources:

Ghasempouri S., Ghiotto M., & Giacomini S. (2023). Open Science for Social Sciences and Humanities: Open Access availability and distribution across disciplines and Countries in OpenCitations Meta - RESEARCH ARTICLE. https://doi.org/10.5281/zenodo.8263908

Ghasempouri, S., Ghiotto, M., Giacomini, S., (2023). Open Science for Social Sciences and Humanities: Open Access availability and distribution across disciplines and Countries in OpenCitations Meta - DATA MANAGEMENT PLAN (Version 4). Zenodo. https://doi.org/10.5281/zenodo.8174644

Ghasempouri, S., Ghiotto, M., Giacomini, S. (2023e). Open Science for Social Sciences and Humanities: Open Access availability and distribution across disciplines and Countries in OpenCitations Meta - PROTOCOL. V.5. (https://dx.doi.org/10.17504/protocols.io.5jyl8jo1rg2w/v5)

Libraries have a long and storied history, dating back thousands of years to the legendary Library of Alexandria. Even in today's digital age, they act as vital public institutions that provide free access to costly information and resources, contributing significantly to community development and literacy. Since library benefits are distributed as externalities across the community, funding for libraries primarily comes from local government sources, such as property taxes. However, budgets are often under pressure due to shifting priorities. Libraries have sought alternative funding sources like grants, donations and partnerships with private entities. Despite diverse funding, libraries struggle with underutilization and competition from substitutes. Over the past five years, industry revenue growth has wavered, dipping at a CAGR of 2.1% to a total of $2.5 billion in 2024, with inflation burning any excess profit down to 3.4% and revenue falling 3.0% in the most recent twelve months. Libraries serve a diverse market, including students, researchers, entrepreneurs and the general public, disproportionately benefitting financially challenged communities. They offer services beyond book lending, like access to digital resources, educational programs and community events. The emergence and surge in popularity of digital technology have also expanded the library's role. It now provides access to e-books, online databases and physical technology like desktops and mobile hotspots. Cultural shifts toward rapid digital information consumption pose challenges and opportunities for libraries. Intellectual property laws affect how libraries can provide access to copyrighted materials. In response to this challenge, libraries have advocated for fair use policies and open access initiatives, particularly after COVID shut down access to physical book lending. Libraries are also adapting by investing in digital infrastructure and enhancing their online presence, often partnering with private companies to build online platforms and taking pages from entertainment competitors like Netflix and Audible. Some libraries are evolving into community hubs or maker (3d printing) spaces. Still, the high cost of these transitions is challenging, and revenue is poised to continue its downward trend, sliding at a CAGR of 2.1% to $2.2 billion through the end of 2029.

Database containing papers sourced from the XML result of a PubMed search for those entries where the grant number includes a reference to the Wellcome Trust. The db contains two tables; one contains the set of papers, including unique IDs, the second is the set of journals that the papers appear in. Article Table was Created via: CREATE TABLE articles (id INTEGER PRIMARY KEY,created_on DATE DEFAULT CURRENT_DATE,created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,article_title TEXT,pubyear INTEGER,pmid INTEGER,doi TEXT,journal INTEGER) and the Journal Table via: CREATE TABLE journals (id INTEGER PRIMARY KEY,created_on DATE DEFAULT CURRENT_DATE,created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,journal_title TEXT,nlm_unique_id INTEGER)

The National Pollutant Release Inventory (NPRI) is Canada's public inventory of pollutant releases (to air, water and land), disposals and transfers for recycling. This database contains the full NPRI dataset from 1993 to the current reporting year. To help you navigate, a Microsoft Word file provides information on the database’s structure and schema. The database is available in Microsoft Access format (accdb). The data are in normalized or “list” format and are optimized for pivot table analyses. The data are also available in a CSV format : https://open.canada.ca/data/en/dataset/40e01423-7728-429c-ac9d-2954385ccdfb. Please consult the following resources to enhance your analysis: - Guide on using and Interpreting NPRI Data: https://www.canada.ca/en/environment-climate-change/services/national-pollutant-release-inventory/using-interpreting-data.html - Access additional data from the NPRI, including datasets and mapping products: https://www.canada.ca/en/environment-climate-change/services/national-pollutant-release-inventory/tools-resources-data/exploredata.html Supplemental Information This data is also available in non-proprietary CSV format on the Bulk Data page. http://open.canada.ca/data/en/dataset/40e01423-7728-429c-ac9d-2954385ccdfb These files contain data from 1993 to the latest reporting year available. These datasets are in normalized or ‘list’ format and are optimized for pivot table analyses. Supporting Projects: National Pollutant Release Inventory (NPRI)

PigBiobank is one of the most ambitious and extensive biobank projects globally, aimed at improving our understanding of diverse and complex traits in pigs. It is a large-scale research database that collects and stores a comprehensive range of genetic data and biological samples from thousands of participants. The database is periodically replenished with new data and is freely accessible to researchers. It contributes to a deeper insight into pig biology, genetics, and health, as well as its broader implications for human health and agriculture.

Graph from 2012 preprint covering only years 2000 - 2010 (use newer version 2000-2015): The Citation Advantage of papers that links to data as a function of the year of publication as registered in ADS (defined as the ratio of the average number of citations per year to papers with links to data, and the average number of citations per year to papers without such links).

Sample Library Carpentry SQL lesson database created from the Directory of Open Access Journals (DOAJ) data. The sample SQL database contains tables: articles, journals, languages, licences, and publishers. Previous version of the sample SQL database: Staiger, Christine (2016): LC-articles. figshare. Dataset. https://doi.org/10.6084/m9.figshare.3409471.v3

Context
From June 2020 to February 2021, a consortium of 10 organisations undertook a large-scale study on open access journals across the world that are free for readers and authors, usually referred to as “OA diamond journals”. This study was commissioned by cOAlition S in order to gain a better understanding of the OA diamond landscape.

Presentation
The study undertook a statistical analysis of several bibliographic databases, surveyed 1,619 journals, collected 7,019 free text submissions and other data from 94 questions, and organised three focus groups with 11 journals and 10 interviews with hosting platforms. It collected 163 references in the academic literature, and inventoried 1048 journals not listed in DOAJ.

The results of the study are available in the following outputs:

• Findings Report - DOI: 10.5281/zenodo.4558704
• Recommendations Report- DOI:10.5281/zenodo.4562790
• References Library - DOI: 10.5281/zenodo.4562816
• Journals Inventory - DOI: 10.5281/zenodo.4562828
• Dataset - DOI: 10.5281/zenodo.4553103

Zotero Library

We conducted a literature search, which led us to collect 163 references, focusing more particularly on the open access business models. The literature review was used primarily to design the survey, prepare the focus groups, and analyse the answers collected. The references are stored in a Zotero library, available online.

The full text database market is projected to reach a value of USD XXX million by 2033, exhibiting a CAGR of XX% during the forecast period (2025-2033). The growth of the market is attributed to the increasing adoption of digital content, the need for efficient and comprehensive research tools, and the growing demand for customized and personalized content. The market is segmented on the basis of type (comprehensive database, special classification database), application (enterprise, government, school, others), and region (North America, South America, Europe, Middle East & Africa, Asia Pacific). Key drivers of the market include the rising demand for accurate and up-to-date information, the growing use of artificial intelligence and machine learning in data analysis, and the increasing popularity of cloud-based database solutions. However, factors such as data security concerns, privacy regulations, and competition from open access databases may hinder the market growth. Major players in the market include John Wiley & Sons, ICPSR, IEEE, EBSCO, UMI, Blackwell, Springer Link, Elsevier Science, Apache Solr, Elastic N.V., CNKI, China Science and Technology Journal Database, Wanfang Data Knowledge Service Platform, China Science Citation Database, Chinese, Western, Japanese and Russian Journals Joint Directory Database, among others.