This collection contains five sets of datasets: 1) Publication counts from two multidisciplinary humanities data journals: the Journal of Open Humanities Data and Research Data in the Humanities and Social Sciences (RDJ_JOHD_Publications.csv); 2) A large dataset about the performance of research articles in HSS exported from dimensions.ai (allhumss_dims_res_papers_PUB_ID.csv); 3) A large dataset about the performance of datasets in HSS harvested from the Zenodo REST API (Zenodo.zip); 4) Impact and usage metrics from the papers published in the two journals above (final_outputs.zip); 5) Data from Twitter analytics on tweets from the @up_johd account, with paper DOI and engagement rate (twitter-data.zip).

Please note that, as requested by the Dimensions team, for 2 and 4, we only included the Publication IDs from Dimensions rather than the full data. Interested parties only need the Dimensions publications IDs to retrieve the data; even if they have no Dimensions subscription, they can easily get a no-cost agreement with Dimensions, for research purposes, in order to retrieve the data.

This database is an addendum to the article "Privacy Perceptions in Digital Games: A Study with Information Technology (IT) Undergraduates" to provide information regarding the anonymously collected data. Abstract of the article This study explores the perceptions and practices of undergraduates in Information Technology (IT) regarding privacy issues in digital games. This topic becomes relevant in the current scenario where artificial intelligence (AI) is increasingly integrated into digital games, providing an enhanced experience for players. However, this integration poses security and privacy challenges, the understanding of which is crucial for both players and developers.The primary objective of this research is to comprehend the participants' perceptions and understandings of privacy in digital games. We employed a qualitative and quantitative methodology to address our research inquiries. Through an online form of data collection, we obtained 61 responses. Among the obtained information, we observed that 40\% of the students are interested in pursuing a career in game development, and 49.18% would consider this possibility. Noteworthy among the identified issues is the necessity for companies to devise more effective means of communicating their privacy policies to players/users, adapting the language to their target audience. Participants reported attacks related to online multiplayer games and expressed concerns about the security of personal data.

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.

This data set accompanies the text at doi 10.5281/zenodo.3732273. // Correspondence: JH: info@africarxiv.org, SK: sk111@soas.ac.uk

Visual Map: https://kumu.io/access2perspectives/african-digital-research-repositories Dataset: https://tinyurl.com/African-Research-Repositories Archived at https://info.africarxiv.org/african-digital-research-repositories/ Submission form: https://forms.gle/CnyGPmBxN59nWVB38

Licensing: Text and Visual Map – CC-BY-SA 4.0 // Dataset – CC0 (Public Domain) // The licensing of each database is determined by the database itself

Preprint doi: 10.5281/zenodo.3732273.
Data set doi: 10.5281/zenodo.3732172 // available in different formats (pdf, xls, ods, csv)

AfricarXiv in collaboration with the International African Institute (IAI) presents an interactive map of African digital research literature repositories. This drew from IAI’s earlier work from 2016 onwards to identify and list Africa-based institutional repositories that focused on identifying repositories based in African university libraries. Our earlier resources are available at https://www.internationalafricaninstitute.org/repositories.

The interactive map extends the work of the IAI to include organizational, governmental, and international repositories. It also maps the interactions between research repositories. In this dataset, we focus on institutional repositories for scholarly works, as defined by Wikipedia contributors (March 2020).

Objective

The map of African digital repositories was created as a resource to be used in activities addressing the following aims:

Improving the discoverability of African research and publications

Enhance the interoperability of existing and emerging African repositories

Identify ways through which digital scholarly search engines can enhance the discoverability of African research

We promote the dissemination of research-based knowledge from African repositories as part of a bigger landscape that also includes online journals, research data repositories, and scholarly publishers to enhance the interconnectivity and accessibility of such repositories across and beyond the African continent and to contribute to a more granular understanding of the continent’s scholarly resources.

Data archiving and maintenance

The map and corresponding dataset are hosted on the AfricArXiv website under ‘Resources’ at https://info.africarxiv.org/african-digital-research-repositories/. The listing is not exhaustive and therefore we encourage any repositories relevant for the African continent not listed here to the submission form at https://forms.gle/CnyGPmBxN59nWVB38, or to notify the International African Institute (email sk111@soas.ac.uk). Both AfricArXiv and IAI will continue to maintain the list of repositories as a resource for African researchers and other stakeholders including international African studies communities.

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/

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

Objective: Routinely collected health data, collected for administrative and clinical purposes, without specific a priori research questions, are increasingly used for observational, comparative effectiveness, health services research, and clinical trials. The rapid evolution and availability of routinely collected data for research has brought to light specific issues not addressed by existing reporting guidelines. The aim of the present project was to determine the priorities of stakeholders in order to guide the development of the REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) statement. Methods: Two modified electronic Delphi surveys were sent to stakeholders. The first determined themes deemed important to include in the RECORD statement, and was analyzed using qualitative methods. The second determined quantitative prioritization of the themes based on categorization of manuscript headings. The surveys were followed by a meeting of RECO...

Big Data and Society Abstract & Indexing - ResearchHelpDesk - Big Data & Society (BD&S) is open access, peer-reviewed scholarly journal that publishes interdisciplinary work principally in the social sciences, humanities and computing and their intersections with the arts and natural sciences about the implications of Big Data for societies. The Journal's key purpose is to provide a space for connecting debates about the emerging field of Big Data practices and how they are reconfiguring academic, social, industry, business, and government relations, expertise, methods, concepts, and knowledge. BD&S moves beyond usual notions of Big Data and treats it as an emerging field of practice that is not defined by but generative of (sometimes) novel data qualities such as high volume and granularity and complex analytics such as data linking and mining. It thus attends to digital content generated through online and offline practices in social, commercial, scientific, and government domains. This includes, for instance, the content generated on the Internet through social media and search engines but also that which is generated in closed networks (commercial or government transactions) and open networks such as digital archives, open government, and crowdsourced data. Critically, rather than settling on a definition the Journal makes this an object of interdisciplinary inquiries and debates explored through studies of a variety of topics and themes. BD&S seeks contributions that analyze Big Data practices and/or involve empirical engagements and experiments with innovative methods while also reflecting on the consequences for how societies are represented (epistemologies), realized (ontologies) and governed (politics). Article processing charge (APC) The article processing charge (APC) for this journal is currently 1500 USD. Authors who do not have funding for open access publishing can request a waiver from the publisher, SAGE, once their Original Research Article is accepted after peer review. For all other content (Commentaries, Editorials, Demos) and Original Research Articles commissioned by the Editor, the APC will be waived. Abstract & Indexing Clarivate Analytics: Social Sciences Citation Index (SSCI) Directory of Open Access Journals (DOAJ) Google Scholar Scopus

Graphs and data for ten journals sharing data in the Dryad digital repository.

Dataset of African Journals Online publications and journals (last update: February 2024). The dataset contains metadata for articles and journals indexed in African Journals Online (AJOL). It provides the information contained in AJOL in a structured format that can be downloaded and used easily. It also contains a unique identifier matching AJOL articles with their OpenAlex records in order to facilitate the use, comparison, and combination of both data sources.

Details about the download, methods, and findings are reported in the following preprint:

Alonso-Álvarez, P. (2025). A small step towards the epistemic decentralization of science: a dataset of journals and publications indexed in African Journals Online. Zenodo. 10.5281/zenodo.14900054

Detailed information on the database construction process is reported in the following file:

ajol_database_report.pdf

Data files:

ajol_journals.csv: contains metadata from journals, including title, eISSN, ISSN print, country, JPPS category, and open access status (binary for diamond journals).

ajol_journals_area.csv: related journals to their AJOL research area categories. Journals can belong up to three categories.

ajol_pub.csv: contains articles’ metadata, including journal identifiers, article URL, doi, issue, volume, date, year, title, first page, and last page.

ajol_pub_author.csv: relates articles to their authors.

ajol_pub_keyword.csv: includes article keywords.

ajol_pub_openalex.csv: relates AJOL articles to their OpenAlex records using the unique identifiers of each data source.

readme.csv: contains the description of the variables in all data files.

ajol_database_report.pdf: detailed information on the database construction process.

This description is part of the blog post "Systematic Literature Review of teaching Open Science" https://sozmethode.hypotheses.org/839

According to my opinion, we do not pay enough attention to teaching Open Science in higher education. Therefore, I designed a seminar to teach students the practices of Open Science by doing qualitative research.About this seminar, I wrote the article ”Teaching Open Science and qualitative methods“. For the article ”Teaching Open Science and qualitative methods“, I started to review the literature on ”Teaching Open Science“. The result of my literature review is that certain aspects of Open Science are used for teaching. However, Open Science with all its aspects (Open Access, Open Data, Open Methodology, Open Science Evaluation and Open Science Tools) is not an issue in publications about teaching.

Based on this insight, I have started a systematic literature review. I realized quickly that I need help to analyse and interpret the articles and to evaluate my preliminary findings. Especially different disciplinary cultures of teaching different aspects of Open Science are challenging, as I myself, as a social scientist, do not have enough insight to be able to interpret the results correctly. Therefore, I would like to invite you to participate in this research project!

I am now looking for people who would like to join a collaborative process to further explore and write the systematic literature review on “Teaching Open Science“. Because I want to turn this project into a Massive Open Online Paper (MOOP). According to the 10 rules of Tennant et al (2019) on MOOPs, it is crucial to find a core group that is enthusiastic about the topic. Therefore, I am looking for people who are interested in creating the structure of the paper and writing the paper together with me. I am also looking for people who want to search for and review literature or evaluate the literature I have already found. Together with the interested persons I would then define, the rules for the project (cf. Tennant et al. 2019). So if you are interested to contribute to the further search for articles and / or to enhance the interpretation and writing of results, please get in touch. For everyone interested to contribute, the list of articles collected so far is freely accessible at Zotero: https://www.zotero.org/groups/2359061/teaching_open_science. The figure shown below provides a first overview of my ongoing work. I created the figure with the free software yEd and uploaded the file to zenodo, so everyone can download and work with it:

To make transparent what I have done so far, I will first introduce what a systematic literature review is. Secondly, I describe the decisions I made to start with the systematic literature review. Third, I present the preliminary results.

Systematic literature review – an Introduction

Systematic literature reviews “are a method of mapping out areas of uncertainty, and identifying where little or no relevant research has been done.” (Petticrew/Roberts 2008: 2). Fink defines the systematic literature review as a “systemic, explicit, and reproducible method for identifying, evaluating, and synthesizing the existing body of completed and recorded work produced by researchers, scholars, and practitioners.” (Fink 2019: 6). The aim of a systematic literature reviews is to surpass the subjectivity of a researchers’ search for literature. However, there can never be an objective selection of articles. This is because the researcher has for example already made a preselection by deciding about search strings, for example “Teaching Open Science”. In this respect, transparency is the core criteria for a high-quality review.

In order to achieve high quality and transparency, Fink (2019: 6-7) proposes the following seven steps:

1. Selecting a research question.
2. Selecting the bibliographic database.
3. Choosing the search terms.
4. Applying practical screening criteria.
5. Applying methodological screening criteria.
6. Doing the review.
7. Synthesizing the results.

I have adapted these steps for the “Teaching Open Science” systematic literature review. In the following, I will present the decisions I have made.

Systematic literature review – decisions I made

1. Research question: I am interested in the following research questions: How is Open Science taught in higher education? Is Open Science taught in its full range with all aspects like Open Access, Open Data, Open Methodology, Open Science Evaluation and Open Science Tools? Which aspects are taught? Are there disciplinary differences as to which aspects are taught and, if so, why are there such differences?
2. Databases: I started my search at the Directory of Open Science (DOAJ). “DOAJ is a community-curated online directory that indexes and provides access to high quality, open access, peer-reviewed journals.” (https://doaj.org/) Secondly, I used the Bielefeld Academic Search Engine (base). Base is operated by Bielefeld University Library and “one of the world’s most voluminous search engines especially for academic web resources” (base-search.net). Both platforms are non-commercial and focus on Open Access publications and thus differ from the commercial publication databases, such as Web of Science and Scopus. For this project, I deliberately decided against commercial providers and the restriction of search in indexed journals. Thus, because my explicit aim was to find articles that are open in the context of Open Science.
3. Search terms: To identify articles about teaching Open Science I used the following search strings: “teaching open science” OR teaching “open science” OR teach „open science“. The topic search looked for the search strings in title, abstract and keywords of articles. Since these are very narrow search terms, I decided to broaden the method. I searched in the reference lists of all articles that appear from this search for further relevant literature. Using Google Scholar I checked which other authors cited the articles in the sample. If the so checked articles met my methodological criteria, I included them in the sample and looked through the reference lists and citations at Google Scholar. This process has not yet been completed.
4. Practical screening criteria: I have included English and German articles in the sample, as I speak these languages (articles in other languages are very welcome, if there are people who can interpret them!). In the sample only journal articles, articles in edited volumes, working papers and conference papers from proceedings were included. I checked whether the journals were predatory journals – such articles were not included. I did not include blogposts, books or articles from newspapers. I only included articles that fulltexts are accessible via my institution (University of Kassel). As a result, recently published articles at Elsevier could not be included because of the special situation in Germany regarding the Project DEAL (https://www.projekt-deal.de/about-deal/). For articles that are not freely accessible, I have checked whether there is an accessible version in a repository or whether preprint is available. If this was not the case, the article was not included. I started the analysis in May 2019.
5. Methodological criteria: The method described above to check the reference lists has the problem of subjectivity. Therefore, I hope that other people will be interested in this project and evaluate my decisions. I have used the following criteria as the basis for my decisions: First, the articles must focus on teaching. For example, this means that articles must describe how a course was designed and carried out. Second, at least one aspect of Open Science has to be addressed. The aspects can be very diverse (FOSS, repositories, wiki, data management, etc.) but have to comply with the principles of openness. This means, for example, I included an article when it deals with the use of FOSS in class and addresses the aspects of openness of FOSS. I did not include articles when the authors describe the use of a particular free and open source software for teaching but did not address the principles of openness or re-use.
6. Doing the review: Due to the methodical approach of going through the reference lists, it is possible to create a map of how the articles relate to each other. This results in thematic clusters and connections between clusters. The starting point for the map were four articles (Cook et al. 2018; Marsden, Thompson, and Plonsky 2017; Petras et al. 2015; Toelch and Ostwald 2018) that I found using the databases and criteria described above. I used yEd to generate the network. „yEd is a powerful desktop application that can be used to quickly and effectively generate high-quality diagrams.” (https://www.yworks.com/products/yed) In the network, arrows show, which articles are cited in an article and which articles are cited by others as well. In addition, I made an initial rough classification of the content using colours. This classification is based on the contents mentioned in the articles’ title and abstract. This rough content classification requires a more exact, i.e., content-based subdivision and

Dataset used in the paper "PredCheck: Detecting Predatory Behaviour in Scholarly World" accepted at JCDL 2020 as a poster.

Abstract: High solicitation for publishing a paper in scientific journals has led to the emergence of a large number of open-access predatory publishers. They fail to provide a rigorous peer-review process, thereby diluting the quality of research work and charge high article processing fees. Identification of such publishers has remained a challenge due to the vast diversity of the scholarly publishing ecosystem. Earlier works utilises only the objective features such as metadata. In this work, we aim to explore the possibility of identifying predatory behaviour through text-based features. We propose PredCheck, a four-step classificaton pipeline. The first classifier identifies the subject of the paper using TF-IDF vectors. Based on the subject of the paper, the Doc2Vec embeddings of the text are found. These embeddings are then fed into a Naive Bayes classifier that identifies the text to be predatory or non-predatory. Our pipeline gives a macro accuracy of 95% and an F1-score of 0.89.

Big Data and Society CiteScore 2024-2025 - ResearchHelpDesk - Big Data & Society (BD&S) is open access, peer-reviewed scholarly journal that publishes interdisciplinary work principally in the social sciences, humanities and computing and their intersections with the arts and natural sciences about the implications of Big Data for societies. The Journal's key purpose is to provide a space for connecting debates about the emerging field of Big Data practices and how they are reconfiguring academic, social, industry, business, and government relations, expertise, methods, concepts, and knowledge. BD&S moves beyond usual notions of Big Data and treats it as an emerging field of practice that is not defined by but generative of (sometimes) novel data qualities such as high volume and granularity and complex analytics such as data linking and mining. It thus attends to digital content generated through online and offline practices in social, commercial, scientific, and government domains. This includes, for instance, the content generated on the Internet through social media and search engines but also that which is generated in closed networks (commercial or government transactions) and open networks such as digital archives, open government, and crowdsourced data. Critically, rather than settling on a definition the Journal makes this an object of interdisciplinary inquiries and debates explored through studies of a variety of topics and themes. BD&S seeks contributions that analyze Big Data practices and/or involve empirical engagements and experiments with innovative methods while also reflecting on the consequences for how societies are represented (epistemologies), realized (ontologies) and governed (politics). Article processing charge (APC) The article processing charge (APC) for this journal is currently 1500 USD. Authors who do not have funding for open access publishing can request a waiver from the publisher, SAGE, once their Original Research Article is accepted after peer review. For all other content (Commentaries, Editorials, Demos) and Original Research Articles commissioned by the Editor, the APC will be waived. Abstract & Indexing Clarivate Analytics: Social Sciences Citation Index (SSCI) Directory of Open Access Journals (DOAJ) Google Scholar Scopus

Dataset available as supplementary material from article "Editorial quality and quantitative indicators in Peruvian electronic journals" that analyzes 121 Peruvian scholarly journals published in electronic format and from five journal selection resources: SciELO Peru, Latindex, Dialnet, DOAJ and REDIB.

Academic Research Databases Market Outlook

The global academic research databases market size was valued at approximately USD 3.5 billion in 2023 and is projected to reach around USD 6.2 billion by 2032, growing at a CAGR of 6.5% during the forecast period. The increasing demand for digital resources in academic and research institutions, along with the growing emphasis on online learning and resource accessibility, are key factors driving market growth.

One significant growth factor for the academic research databases market is the exponential increase in academic research activity worldwide. With the surge in the number of higher education institutions and research facilities, the demand for comprehensive and easily accessible databases has skyrocketed. These databases provide a centralized platform for researchers to access a wide array of scholarly articles, data sets, and other pertinent information, streamlining the research process and enhancing the quality of scholarly work.

Another driving force behind the market's expansion is the continuous technological advancements in database management and search functionalities. Modern academic research databases are equipped with sophisticated search algorithms, artificial intelligence, and machine learning capabilities that enable users to efficiently locate relevant information. These advancements not only improve user experience but also significantly reduce the time and effort required to conduct comprehensive literature reviews and gather data.

The increasing prevalence of interdisciplinary research is also contributing to the growth of the academic research databases market. Researchers today often work at the intersection of multiple disciplines, necessitating access to a diverse range of subject-specific databases. The availability of comprehensive databases that cover various fields such as science, technology, medicine, social sciences, and humanities supports this trend by providing researchers with the resources they need to explore and integrate knowledge from different domains.

From a regional perspective, North America holds the largest share of the academic research databases market, driven by the high concentration of leading academic and research institutions and substantial investments in research and development. Europe follows closely, with significant contributions from countries like the UK, Germany, and France. The Asia Pacific region is expected to witness the highest growth rate during the forecast period, fueled by the rapid expansion of higher education infrastructure and increasing government support for research activities. Latin America and the Middle East & Africa, though smaller in market size, are also projected to experience steady growth due to rising academic and research initiatives in these regions.

Database Type Analysis

The academic research databases market is segmented by database type into bibliographic, full-text, numeric, multimedia, and others. Bibliographic databases, which include indexes and abstracts of research articles, play a crucial role in helping researchers locate relevant literature. These databases have been foundational in academic research, providing essential references and citation tracking that are pivotal for scholarly work. Their significance remains high due to the increasing volume of academic publications and the need for comprehensive literature searches.

Full-text databases provide complete access to research articles, journals, and other scholarly materials, making them indispensable for researchers who require in-depth study materials. The convenience of accessing entire articles, rather than just abstracts or summaries, significantly enhances the research process. Full-text databases are particularly valuable in fields such as medicine, where access to full clinical study reports, reviews, and case studies is critical for evidence-based practice.

Numeric databases, which offer access to statistical and numerical data, are essential for researchers in fields like economics, social sciences, and the natural sciences. These databases provide valuable data sets that can be used for quantitative analysis, modeling, and empirical research. The increasing emphasis on data-driven research and the availability of large data sets are propelling the demand for numeric databases.

Multimedia databases, which include audio, video, and other multimedia content, are gaining traction in academic research. These databases are particularly useful in disciplines such a

The dataset consists of the text content of the journals published between 1898 through to 1959 in the the collections AHiRA. Archivo Histórico de Revistas Argentinas (https://ahira.com.ar/) at the Instituto de Historia Argentina y Americana "Dr. Emilio Ravignani” (Buenos Aires) and Cultural Magazines of Latin America (CMoLA) (https://digital.iai.spk-berlin.de/viewer/collections/lateinamerikanische-kulturzeitschriften/) of the Ibero-American Institute (Berlin) . The former consists of 898 files and the latter 4698, each file representing a journal issue. The research studied these archives and collections to estimate the representation of women writers in literary databases by leveraging Named Entity Recognition (NER) to extract names and map them to resources like Wikidata, which provide details on gender and occupation. By doing so, we tracked the representation of women writers, comparing their presence with that of male writers. In addition, the analysis was enriched with information on the countries of residence and the languages in which these women wrote, allowing for an estimation of how many were featured in translation or cited as foreign authors. The data was further visualized as bipartite graphs, linking writers to journals and quantifying the frequency of their contributions or citations, with a particular focus on the gender disparity and its evolution over time. Lastly, we examined the occurrence of terms related to translation and versioning, estimating the role of literary translation across various corpora, archives, and collections, highlighting its significance in the dissemination of works by women writers.

Note: this dataset is replication data for the paper: Kampen, A., Pearson, M., & Smit, M. (2016). Digital Tools and Techniques in Scholarship and Pedagogy in the Social Sciences and Humanities. Technical Report, Dalhousie University. This data is about the adoption, diffusion and use of digital tools and techniques within the social sciences and humanities research communities (Kampen, Pearson & Smit, 2016). The dataset includes a weighted random sampling of 1001 articles (500 from the Social Sciences subject area; 501 from the Arts and Humanities subject area) from original research articles published in academic journals in 2014. These articles were assessed individually for the presence, and nature, of digital tools and techniques used in the research process, particularly collection, analysis, and/or visualization. Each article was also assessed to determine if it belonged to one of the three focus areas identified by the funding agency: Diversity/Inequality/Differences, Environmental studies, and Resilient and innovative societies. Tabular data was recorded based on these assessments; a complete key is included in the Readme file. The tabular data and the bibliography for the sampled articles are included. Data consists of: 1) One tabular data file (CSV) containing, for each citation: - Numeric citation identifier - Metadata (e.g., title, subject areas, granting information) - Digital tools analysis (e.g., Type of digital tool used, name of digital tool, source of digital tool) - Research notes 2) One BibTeX file containing citations for the 1001 articles analyzed (citation identifier matched to CSV id) 3) One PDF file containing the output of the BibTeX file 4) One Readme file containing data description, cleaning techniques, and known remaining issues

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.

description: FUNCTION: NRL's Ruth H. Hooker Research Library offers a full range of traditional and digital library services to enhance and support the research program of the Naval Research Laboratory. Traditional library services include a physical facility for study and research, staffed with subject specialists and information professionals to assist researchers in locating and retrieving published information. A rich and extensive journal, technical report, and book collection has been created and maintained over the80+-year history of the library. To enhance traditional services, the library isactively expanding the NRLDigital Library (http://library.nrl.navy.mil), which provides access to thousands of journals, books, and reference sources at desktops at NRL-DC, NRL-Stennis, NRL-Monterey, and the Office of Naval Research.DESCRIPTION: The Library collections focus on physics, chemistry, electronics, and space sciences. They include 150,000 books and journal volumes, 4,000 current journal subscriptions, and over 2 million technical reports in paper, microfiche, or electronic format. The collections are regularly analyzed, organized, and updated to provide quick and easy retrieval of the most appropriate items. Services include the following: reference assistance in using the collections and locating information from external sources; mediated literature searches of several hundred online databases, including classified databases, to produce on-demand subject bibliographies; circulation of materials from the collection including classified literature up to the SECRET level; interlibrary loan and document delivery to obtain needed items from other scientific and research libraries or from commercial document providers; ordering all journals for office retention; and user education and outreach to help researchers improve productivity through effective use of both the physical library and the Digital Library resources available through TORPEDO Ultra and the World Wide Web.TheTORPEDO Ultra digital repository providesdesktop access to more than 8 million full content items; thousands of research journals; hundreds of technical databases; and reference tools including Web of Science, SCOPUS, and INSPEC. EEQUIPMENT: Public access computers, photocopiers, color printer, microform reader/printers, and self-service digital sender.; abstract: FUNCTION: NRL's Ruth H. Hooker Research Library offers a full range of traditional and digital library services to enhance and support the research program of the Naval Research Laboratory. Traditional library services include a physical facility for study and research, staffed with subject specialists and information professionals to assist researchers in locating and retrieving published information. A rich and extensive journal, technical report, and book collection has been created and maintained over the80+-year history of the library. To enhance traditional services, the library isactively expanding the NRLDigital Library (http://library.nrl.navy.mil), which provides access to thousands of journals, books, and reference sources at desktops at NRL-DC, NRL-Stennis, NRL-Monterey, and the Office of Naval Research.DESCRIPTION: The Library collections focus on physics, chemistry, electronics, and space sciences. They include 150,000 books and journal volumes, 4,000 current journal subscriptions, and over 2 million technical reports in paper, microfiche, or electronic format. The collections are regularly analyzed, organized, and updated to provide quick and easy retrieval of the most appropriate items. Services include the following: reference assistance in using the collections and locating information from external sources; mediated literature searches of several hundred online databases, including classified databases, to produce on-demand subject bibliographies; circulation of materials from the collection including classified literature up to the SECRET level; interlibrary loan and document delivery to obtain needed items from other scientific and research libraries or from commercial document providers; ordering all journals for office retention; and user education and outreach to help researchers improve productivity through effective use of both the physical library and the Digital Library resources available through TORPEDO Ultra and the World Wide Web.TheTORPEDO Ultra digital repository providesdesktop access to more than 8 million full content items; thousands of research journals; hundreds of technical databases; and reference tools including Web of Science, SCOPUS, and INSPEC. EEQUIPMENT: Public access computers, photocopiers, color printer, microform reader/printers, and self-service digital sender.

Swets Subscription Service Companies and Blackwell's Information Services has created a new company in the United Kingdom called Swets and Blackwell's Information Services, an agency of highly influential magazine subscriptions in the new era of electronic information. Until recently, these agencies "only" intermediate between libraries and publishers, centralizing the demands of the first to channel them towards the latter. A task rather "administrative" which provided little value to information flows. But the landscape has changed since the agencies have improved information services through the digitization of summary, the production of databases and electronic journal publishing. Contrary to other intermediaries, the agencies have increased their membership role.