Journals & Ranking

An academic journal or research journal is a periodical publication in which research articles relating to a particular academic discipline is published, according to Wikipedia. Currently, there are more than 25,000 peer-reviewed journals that are indexed in citation index databases such as Scopus and Web of Science. These indexes are ranked on the basis of various metrics such as CiteScore, H-index, etc. The metrics are calculated from yearly citation data of the journal. A lot of efforts are given to make a metric that reflects the journal's quality.

Journal Ranking Dataset

This is a comprehensive dataset on the academic journals coving their metadata information as well as citation, metrics, and ranking information. Detailed data on their subject area is also given in this dataset. The dataset is collected from the following indexing databases: - Scimago Journal Ranking - Scopus - Web of Science Master Journal List

The data is collected by scraping and then it was cleaned, details of which can be found in HERE.

Key Features

• Rank: Overall rank of journal (derived from sorted SJR index).
• Title: Name or title of journal.
• OA: Open Access or not.
• Country: Country of origin.
• SJR-index: A citation index calculated by Scimago.
• CiteScore: A citation index calculated by Scopus.
• H-index: Hirsh index, the largest number h such that at least h articles in that journal were cited at least h times each.
• Best Quartile: Top Q-index or quartile a journal has in any subject area.
• Best Categories: Subject areas with top quartile.
• Best Subject Area: Highest ranking subject area.
• Best Subject Rank: Rank of the highest ranking subject area.
• Total Docs.: Total number of documents of the journal.
• Total Docs. 3y: Total number of documents in the past 3 years.
• Total Refs.: Total number of references of the journal.
• Total Cites 3y: Total number of citations in the past 3 years.
• Citable Docs. 3y: Total number of citable documents in the past 3 years.
• Cites/Doc. 2y: Total number of citations divided by the total number of documents in the past 2 years.
• Refs./Doc.: Total number of references divided by the total number of documents.
• Publisher: Name of the publisher company of the journal.
• Core Collection: Web of Science core collection name.
• Coverage: Starting year of coverage.
• Active: Active or inactive.
• In-Press: Articles in press or not.
• ISO Language Code: Three-letter ISO 639 code for language.
• ASJC Codes: All Science Journal Classification codes for the journal.

Rest of the features provide further details on the journal's subject area or category: - Life Sciences: Top level subject area. - Social Sciences: Top level subject area. - Physical Sciences: Top level subject area. - Health Sciences: Top level subject area. - 1000 General: ASJC main category. - 1100 Agricultural and Biological Sciences: ASJC main category. - 1200 Arts and Humanities: ASJC main category. - 1300 Biochemistry, Genetics and Molecular Biology: ASJC main category. - 1400 Business, Management and Accounting: ASJC main category. - 1500 Chemical Engineering: ASJC main category. - 1600 Chemistry: ASJC main category. - 1700 Computer Science: ASJC main category. - 1800 Decision Sciences: ASJC main category. - 1900 Earth and Planetary Sciences: ASJC main category. - 2000 Economics, Econometrics and Finance: ASJC main category. - 2100 Energy: ASJC main category. - 2200 Engineering: ASJC main category. - 2300 Environmental Science: ASJC main category. - 2400 Immunology and Microbiology: ASJC main category. - 2500 Materials Science: ASJC main category. - 2600 Mathematics: ASJC main category. - 2700 Medicine: ASJC main category. - 2800 Neuroscience: ASJC main category. - 2900 Nursing: ASJC main category. - 3000 Pharmacology, Toxicology and Pharmaceutics: ASJC main category. - 3100 Physics and Astronomy: ASJC main category. - 3200 Psychology: ASJC main category. - 3300 Social Sciences: ASJC main category. - 3400 Veterinary: ASJC main category. - 3500 Dentistry: ASJC main category. - 3600 Health Professions: ASJC main category.

This is dataset about Serbian papers published in journals indexed in Web of Science collections in the period 2003-2021
We used as "serbian" countries: Serbia, Serbia and Montenegro, Yugoslavia

The terms Serbian researcher and Serbian paper used in this dataset are defined as follows:
Serbian researcher is a researcher affiliated with a Serbian institution,
Serbian paper is a paper with at least one Serbian researcher in the list of authors.
This means that a paper published by a researcher with non-Serbian nationality (i.e. German) working at a Serbian institution is taken into account in the analysis of Serbian papers described in this paper.

Thomson Reuters’ Web of Science (WoS) database was used for data acquisition. We searched Serbian papers in two WoS collections - Science Citation Index Expanded (SCIE) and the Social Science Citation Index (SSCI). The search query executed over those collections on 18th of January, 2022.
CU=(%Serbia% OR %Serbia and Montenegro% OR %Yugoslavia%) AND PY=[2003-2021]

We also analyzed the number of articles of Serbian researchers published in journals with an unstable impact factor (IF), i.e. journals which didn’t have an IF before 2008, and had one in some subperiod of 2008-2015, i.e. lost their IF until 2015. The majority of those journals stopped being indexed in Web of Science as a ban for losing the quality or having predatory journal behavior. We found 143 such journals and their ISSNs by using the JCR (Journal citation reports in the period 2007 - 2015).

Version: 5

Authors: Carlota Balsa-Sánchez, Vanesa Loureiro

Date of data collection: 2023/09/05

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

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

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

Type of version of the dataset: final processed version

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

Version: 4

Authors: Carlota Balsa-Sánchez, Vanesa Loureiro

Date of data collection: 2022/12/15

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

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

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

Type of version of the dataset: final processed version

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

Version: 3

Authors: Carlota Balsa-Sánchez, Vanesa Loureiro

Date of data collection: 2022/10/28

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

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

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

Type of version of the dataset: final processed version

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

Erratum - Data articles in journals Version 3:

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

Version: 2

Author: Francisco Rubio, Universitat Politècnia de València.

Date of data collection: 2020/06/23

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

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

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

Type of version of the dataset: final processed version

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

Total size: 32 KB

Version 1: Description

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

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

Journal of Mind and Medical Sciences Impact Factor 2025-2026 - ResearchHelpDesk - Journal of Mind and Medical Sciences (JMMS, J Mind Med Sci) pays special attention to papers related to mental and medical topics, focusing primarily on interdisciplinary and integrative perspectives. It is an online and open-access journal, no charges being received for submission, review, and publication of articles. The journal adheres to the philosophy that high quality and original ideas and information should be freely shared within and amongst the scientific community, with the stipulation that the authors be acknowledged for their knowledge and contribution. J Mind Med Sci. is licensed under a CC BY-NC-ND 4.0 License. The journal is conducted by international norms of academic publishing, being listed by the International Committee of Medical Journal Editors (ICMJE), adhere to the most important and comprehensive ethical guidelines of COPE, it is a member of CrossRef and indexed by several International Databases. Authors are encouraged to supply the names of two potential referees, and/or of referees that they do not wish to review their paper. The decision regarding the selection process of the reviewers belongs to Editor(s). Our referees have the opportunity to be recognized as reviewers for their contributions, due to the fact that the Journal of Mind and Medical Sciences is a member of Publons (part of Clarivate Analytics). Journal of Mind and Medical Sciences is currently indexed in the following international databases: Web of Science WorldWideScience World Health Organization (Hinari/ Health Inter-Network Access to Research Initiative) Microsoft Academic Search EBSCO DOAJ Index Copernicus Cabell`s Whitelist Ulrich's Periodicals Directory SHERPA/ RoMEO OAJI J-Gate DRJI SCIPIO OpenAIRE (Horizon 2020) ClavisBCT Gale/ Cengage Learning Medicine and Health Sciences Commons Google Scholar WorldCat J Mind Med Sci. can also be accessed via prestigious medical universities, like: Harvard Library Yale University Library Oxford University Libraries Stanford University Libraries Boston University Libraries The British Library COPAC (Cambridge, Glasgow, Imperial College, Liverpool, Manchester, Sheffield, York, Southampton Universities) Berlin Social Science Center The Saskatoon Public Library BASE (Bielefeld Academic Search Engine) Nelson Mandela Metropolitan University Social Services Knowledge Scotland elibrary, etc.

The data is comprised of search results of journal articles from Scopus and Web of Science databases using three Boolean search strings. The search strings are:(“certification” AND “meat”) OR (“certification” AND “dairy”)], (ii) [(“credence” AND meat) OR (“experience” AND meat)], and (iii) [(“meat” AND “intrinsic”) OR (“meat” AND “extrinsic”) OR (“meat” AND “quality cue”)]

Journal lists of all the 46 Sub-Saharan African countries were retrieved manually from Ulrich periodical database using the "country of publication" field in the advanced search interface. Delimiters were used to limit the retrieved results to periodicals in the journal categories and with active status. Ulrich's database usually multiple records for the different formats (eg. online and print), or languages in which a single journal is published. Duplicates were removed from the retrieved results.

Master journal lists for Web of Science indexes comprising of the Science Citation Index Expanded (SCIE), the Social Science Citation Index (SSCI) and the Arts and Humanities Citation Index (A&HCI) and Emerging Sources Citation Index ESCI. Master journal lists for Scopus, EMBASE and MEDLINE databases were downloaded from their respective publishers' websites. Master journal lists for AJOL was not available on the publishers' website. Therefore, the master journal list from AJOL was created manually by extracting journal information from the publishers' websites. Only active journals were included in the study, where active journals were defined as journals that have published at least an issue in 2021 or 2020. The master journal list for AIM was not available as well. The whole database comprising of 18,949 articles were downloaded with the source (journal names). Journals were sorted to identify unique journal names, where only 15,279 articles had identifiable journal names. Five hundred twenty-four unique journals were identified, with only 74 active journals. Journals that were not indexed in the AIM database in 2020 or 2021 were deemed inactive and were not included in the study. This study was not considered for ethics review because data used was collected from publicly available records.

This is a list of all the journal abbreviations from Web of Science. It is not a perfect list, not least because of the numerous errors in the Web of Science list. However, it was quite a fast way of getting most of the nearly 90 000 journal titles and abbreviations into jabref, and could be useful for other bibliographic systems and/or doing it manually. This was created using R (the only "programming language" i know), extracting the abbreviations from the web of science lists (https://images.webofknowledge.com/WOKRS520B4.1/help/WOS/A_abrvjt.html). Feel free to help with improvements!Files:wos_abbrev_table.csv - Table with full names and abbreviations, with and without dots in abbreviations.jabref_wos_abbrev.txt - Abbreviation table in Jabref formatjabref_wos_abbrev_dots.txt - Abbreviation table in Jabref format, with dots.wos_abbrev_code.R - R code used to create the list. Thanks to Daniel Graeber (dgr@bios.au.dk) for inspiration and guidance regarding the addition of dots to abbreviated journal names.

Self-citation analysis data based on PubMed Central subset (2002-2005) ---------------------------------------------------------------------- Created by Shubhanshu Mishra, Brent D. Fegley, Jana Diesner, and Vetle Torvik on April 5th, 2018 ## Introduction This is a dataset created as part of the publication titled: Mishra S, Fegley BD, Diesner J, Torvik VI (2018) Self-Citation is the Hallmark of Productive Authors, of Any Gender. PLOS ONE. It contains files for running the self citation analysis on articles published in PubMed Central between 2002 and 2005, collected in 2015. The dataset is distributed in the form of the following tab separated text files: * Training_data_2002_2005_pmc_pair_First.txt (1.2G) - Data for first authors * Training_data_2002_2005_pmc_pair_Last.txt (1.2G) - Data for last authors * Training_data_2002_2005_pmc_pair_Middle_2nd.txt (964M) - Data for middle 2nd authors * Training_data_2002_2005_pmc_pair_txt.header.txt - Header for the data * COLUMNS_DESC.txt file - Descriptions of all columns * model_text_files.tar.gz - Text files containing model coefficients and scores for model selection. * results_all_model.tar.gz - Model coefficient and result files in numpy format used for plotting purposes. v4.reviewer contains models for analysis done after reviewer comments. * README.txt file ## Dataset creation Our experiments relied on data from multiple sources including properitery data from Thompson Rueter's (now Clarivate Analytics) Web of Science collection of MEDLINE citations. Author's interested in reproducing our experiments should personally request from Clarivate Analytics for this data. However, we do make a similar but open dataset based on citations from PubMed Central which can be utilized to get similar results to those reported in our analysis. Furthermore, we have also freely shared our datasets which can be used along with the citation datasets from Clarivate Analytics, to re-create the datased used in our experiments. These datasets are listed below. If you wish to use any of those datasets please make sure you cite both the dataset as well as the paper introducing the dataset. * MEDLINE 2015 baseline: https://www.nlm.nih.gov/bsd/licensee/2015_stats/baseline_doc.html * Citation data from PubMed Central (original paper includes additional citations from Web of Science) * Author-ity 2009 dataset: - Dataset citation: Torvik, Vetle I.; Smalheiser, Neil R. (2018): Author-ity 2009 - PubMed author name disambiguated dataset. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-4222651_V1 - Paper citation: Torvik, V. I., & Smalheiser, N. R. (2009). Author name disambiguation in MEDLINE. ACM Transactions on Knowledge Discovery from Data, 3(3), 1–29. https://doi.org/10.1145/1552303.1552304 - Paper citation: Torvik, V. I., Weeber, M., Swanson, D. R., & Smalheiser, N. R. (2004). A probabilistic similarity metric for Medline records: A model for author name disambiguation. Journal of the American Society for Information Science and Technology, 56(2), 140–158. https://doi.org/10.1002/asi.20105 * Genni 2.0 + Ethnea for identifying author gender and ethnicity: - Dataset citation: Torvik, Vetle (2018): Genni + Ethnea for the Author-ity 2009 dataset. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-9087546_V1 - Paper citation: Smith, B. N., Singh, M., & Torvik, V. I. (2013). A search engine approach to estimating temporal changes in gender orientation of first names. In Proceedings of the 13th ACM/IEEE-CS joint conference on Digital libraries - JCDL ’13. ACM Press. https://doi.org/10.1145/2467696.2467720 - Paper citation: Torvik VI, Agarwal S. Ethnea -- an instance-based ethnicity classifier based on geo-coded author names in a large-scale bibliographic database. International Symposium on Science of Science March 22-23, 2016 - Library of Congress, Washington DC, USA. http://hdl.handle.net/2142/88927 * MapAffil for identifying article country of affiliation: - Dataset citation: Torvik, Vetle I. (2018): MapAffil 2016 dataset -- PubMed author affiliations mapped to cities and their geocodes worldwide. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-4354331_V1 - Paper citation: Torvik VI. MapAffil: A Bibliographic Tool for Mapping Author Affiliation Strings to Cities and Their Geocodes Worldwide. D-Lib magazine : the magazine of the Digital Library Forum. 2015;21(11-12):10.1045/november2015-torvik * IMPLICIT journal similarity: - Dataset citation: Torvik, Vetle (2018): Author-implicit journal, MeSH, title-word, and affiliation-word pairs based on Author-ity 2009. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-4742014_V1 * Novelty dataset for identify article level novelty: - Dataset citation: Mishra, Shubhanshu; Torvik, Vetle I. (2018): Conceptual novelty scores for PubMed articles. University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-5060298_V1 - Paper citation: Mishra S, Torvik VI. Quantifying Conceptual Novelty in the Biomedical Literature. D-Lib magazine : The Magazine of the Digital Library Forum. 2016;22(9-10):10.1045/september2016-mishra - Code: https://github.com/napsternxg/Novelty * Expertise dataset for identifying author expertise on articles: * Source code provided at: https://github.com/napsternxg/PubMed_SelfCitationAnalysis Note: The dataset is based on a snapshot of PubMed (which includes Medline and PubMed-not-Medline records) taken in the first week of October, 2016. Check here for information to get PubMed/MEDLINE, and NLMs data Terms and Conditions Additional data related updates can be found at Torvik Research Group ## Acknowledgments This work was made possible in part with funding to VIT from NIH grant P01AG039347 and NSF grant 1348742. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. ## License Self-citation analysis data based on PubMed Central subset (2002-2005) by Shubhanshu Mishra, Brent D. Fegley, Jana Diesner, and Vetle Torvik is licensed under a Creative Commons Attribution 4.0 International License. Permissions beyond the scope of this license may be available at https://github.com/napsternxg/PubMed_SelfCitationAnalysis.

Introduction

This note describes the data sets used for all analyses contained in the manuscript 'Oxytocin - a social peptide?’[1] that is currently under review.

Data Collection

The data sets described here were originally retrieved from Web of Science (WoS) Core Collection via the University of Edinburgh’s library subscription [2]. The aim of the original study for which these data were gathered was to survey peer-reviewed primary studies on oxytocin and social behaviour. To capture relevant papers, we used the following query:

TI = (“oxytocin” OR “pitocin” OR “syntocinon”) AND TS = (“social*” OR “pro$social” OR “anti$social”)

The final search was performed on the 13 September 2021. This returned a total of 2,747 records, of which 2,049 were classified by WoS as ‘articles’. Given our interest in primary studies only – articles reporting original data – we excluded all other document types. We further excluded all articles sub-classified as ‘book chapters’ or as ‘proceeding papers’ in order to limit our analysis to primary studies published in peer-reviewed academic journals. This reduced the set to 1,977 articles. All of these were published in the English language, and no further language refinements were unnecessary.

All available metadata on these 1,977 articles was exported as plain text ‘flat’ format files in four batches, which we later merged together via Notepad++. Upon manually examination, we discovered examples of papers classified as ‘articles’ by WoS that were, in fact, reviews. To further filter our results, we searched all available PMIDs in PubMed (1,903 had associated PMIDs - ~96% of set). We then filtered results to identify all records classified as ‘review’, ‘systematic review’, or ‘meta-analysis’, identifying 75 records 3. After examining a sample and agreeing with the PubMed classification, these were removed these from our dataset - leaving a total of 1,902 articles.

From these data, we constructed two datasets via parsing out relevant reference data via the Sci2 Tool [4]. First, we constructed a ‘node-attribute-list’ by first linking unique reference strings (‘Cite Me As’ column in WoS data files) to unique identifiers, we then parsed into this dataset information on the identify of a paper, including the title of the article, all authors, journal publication, year of publication, total citations as recorded from WoS, and WoS accession number. Second, we constructed an ‘edge-list’ that records the citations from a citing paper in the ‘Source’ column and identifies the cited paper in the ‘Target’ column, using the unique identifies as described previously to link these data to the node-attribute-list.

We then constructed a network in which papers are nodes, and citation links between nodes are directed edges between nodes. We used Gephi Version 0.9.2 [5] to manually clean these data by merging duplicate references that are caused by different reference formats or by referencing errors. To do this, we needed to retain both all retrieved records (1,902) as well as including all of their references to papers whether these were included in our original search or not. In total, this produced a network of 46,633 nodes (unique reference strings) and 112,520 edges (citation links). Thus, the average reference list size of these articles is ~59 references. The mean indegree (within network citations) is 2.4 (median is 1) for the entire network reflecting a great diversity in referencing choices among our 1,902 articles.

After merging duplicates, we then restricted the network to include only articles fully retrieved (1,902), and retrained only those that were connected together by citations links in a large interconnected network (i.e. the largest component). In total, 1,892 (99.5%) of our initial set were connected together via citation links, meaning a total of ten papers were removed from the following analysis – and these were neither connected to the largest component, nor did they form connections with one another (i.e. these were ‘isolates’).

This left us with a network of 1,892 nodes connected together by 26,019 edges. It is this network that is described by the ‘node-attribute-list’ and ‘edge-list’ provided here. This network has a mean in-degree of 13.76 (median in-degree of 4). By restricting our analysis in this way, we lose 44,741 unique references (96%) and 86,501 citations (77%) from the full network, but retain a set of articles tightly knitted together, all of which have been fully retrieved due to possessing certain terms related to oxytocin AND social behaviour in their title, abstract, or associated keywords.

Before moving on, we calculated indegree for all nodes in this network – this counts the number of citations to a given paper from other papers within this network – and have included this in the node-attribute-list. We further clustered this network via modularity maximisation via the Leiden algorithm [6]. We set the algorithm to resolution 1, and allowed the algorithm to run over 100 iterations and 100 restarts. This gave Q=0.43 and identified seven clusters, which we describe in detail within the body of the paper. We have included cluster membership as an attribute in the node-attribute-list.

Data description

We include here two datasets: (i) ‘OTSOC-node-attribute-list.csv’ consists of the attributes of 1,892 primary articles retrieved from WoS that include terms indicating a focus on oxytocin and social behaviour; (ii) ‘OTSOC-edge-list.csv’ records the citations between these papers. Together, these can be imported into a range of different software for network analysis; however, we have formatted these for ease of upload into Gephi 0.9.2. Below, we detail their contents:

1. ‘OTSOC-node-attribute-list.csv’ is a comma-separate values file that contains all node attributes for the citation network (n=1,892) analysed in the paper. The columns refer to:

Id, the unique identifier

Label, the reference string of the paper to which the attributes in this row correspond. This is taken from the ‘Cite Me As’ column from the original WoS download. The reference string is in the following format: last name of first author, publication year, journal, volume, start page, and DOI (if available).

Wos_id, unique Web of Science (WoS) accession number. These can be used to query WoS to find further data on all papers via the ‘UT= ’ field tag.

Title, paper title.

Authors, all named authors.

Journal, journal of publication.

Pub_year, year of publication.

Wos_citations, total number of citations recorded by WoS Core Collection to a given paper as of 13 September 2021

Indegree, the number of within network citations to a given paper, calculated for the network shown in Figure 1 of the manuscript.

Cluster, provides the cluster membership number as discussed within the manuscript (Figure 1). This was established via modularity maximisation via the Leiden algorithm (Res 1; Q=0.43|7 clusters)

1. ‘OTSOC-edge -list.csv’ is a comma-separate values file that contains all citation links between the 1,892 articles (n=26,019). The columns refer to:

Source, the unique identifier of the citing paper.

Target, the unique identifier of the cited paper.

Type, edges are ‘Directed’, and this column tells Gephi to regard all edges as such.

Syr_date, this contains the date of publication of the citing paper.

Tyr_date, this contains the date of publication of the cited paper.

Software recommended for analysis

Gephi version 0.9.2 was used for the visualisations within the manuscript, and both files can be read and into Gephi without modification.

Notes

[1] Leng, G., Leng, R. I., Ludwig, M. (Submitted). Oxytocin – a social peptide? Deconstructing the evidence.

[2] Edinburgh University’s subscription to Web of Science covers the following databases: (i) Science Citation Index Expanded, 1900-present; (ii) Social Sciences Citation Index, 1900-present; (iii) Arts & Humanities Citation Index, 1975-present; (iv) Conference Proceedings Citation Index- Science, 1990-present; (v) Conference Proceedings Citation Index- Social Science & Humanities, 1990-present; (vi) Book Citation Index– Science, 2005-present; (vii) Book Citation Index– Social Sciences & Humanities, 2005-present; (viii) Emerging Sources Citation Index, 2015-present.

[3] For those interested, the following PMIDs were identified as ‘articles’ by WoS, but as ‘reviews’ by PubMed: ‘34502097’ ‘33400920’ ‘32060678’ ‘31925983’ ‘31734142’ ‘30496762’ ‘30253045’ ‘29660735’ ‘29518698’ ‘29065361’ ‘29048602’ ‘28867943’ ‘28586471’ ‘28301323’ ‘27974283’ ‘27626613’ ‘27603523’ ‘27603327’ ‘27513442’ ‘27273834’ ‘27071789’ ‘26940141’ ‘26932552’ ‘26895254’ ‘26869847’ ‘26788924’ ‘26581735’ ‘26548910’ ‘26317636’ ‘26121678’ ‘26094200’ ‘25997760’ ‘25631363’ ‘25526824’ ‘25446893’ ‘25153535’ ‘25092245’ ‘25086828’ ‘24946432’ ‘24637261’ ‘24588761’ ‘24508579’ ‘24486356’ ‘24462936’ ‘24239932’ ‘24239931’ ‘24231551’ ‘24216134’ ‘23955310’ ‘23856187’ ‘23686025’ ‘23589638’ ‘23575742’ ‘23469841’ ‘23055480’ ‘22981649’ ‘22406388’ ‘22373652’ ‘22141469’ ‘21960250’ ‘21881219’ ‘21802859’ ‘21714746’ ‘21618004’ ‘21150165’ ‘20435805’ ‘20173685’ ‘19840865’ ‘19546570’ ‘19309413’ ‘15288368’ ‘12359512’ ‘9401603’ ‘9213136’ ‘7630585’

[4] Sci2 Team. (2009). Science of Science (Sci2) Tool. Indiana University and SciTech Strategies. Stable URL: https://sci2.cns.iu.edu

[5] Bastian, M., Heymann, S., & Jacomy, M. (2009).

This dataset was compiled as part of a study on Barriers and Opportunities in the Discoverability and Indexing of Student-led Academic Journals. The list of student journals and their details is compiled from public sources. This list is used to identify the presence of Canadian student journals in Google Scholar as well as in select indexes and databases: DOAJ, Scopus, Web of Science, Medline, Erudit, ProQuest, and HeinOnline. Additionally, journal publishing platform is recorded to be used for a correlational analysis against Google Scholar indexing results. For further details see README.

RESEARCH AND SCIENCE TODAY is a biannual science journal established in 2011. The journal is an informational platform that publishes assessment articles and the results of various scientific research carried out by academics. We provide the authors with the opportunity to create and/or perfect their science writing skills. Thus, each issue of the journal (two per year and at least two supplements) will contain professional articles from any academic field, authored by domestic and international academics. The goal of this journal is to pass on relevant information to undergraduate, graduate, and post-graduate students as well as to fellow academics and researchers; the topics covered are unlimited, considering its multi-disciplinary profile. Regarding the national and international visibility of Research and Science Today, it is indexed in over 30 international databases (IDB) and is present in over 200 online libraries and catalogues; therefore, anybody can easily consult the articles featured in each issue by accessing the databases or simply the website. Research and Science Today is an Open Access Journal. Users have the right to read, download, copy, distribute, print, search, or link to the full texts of articles.

IETE journal of research Abstract & Indexing - ResearchHelpDesk - IETE Journal of Research is a bimonthly journal published by the Institution of Electronics and Telecommunication Engineers (IETE), India. It publishes scientific and technical papers describing original research work or novel product/process development. Occasionally special issues are brought out on new and emerging research areas. This journal is useful to researchers, engineers, scientists, teachers, managers, and students who are interested in keeping track of original research and development work being carried out in the broad area of electronics, telecommunications, computer science, and engineering and information technology. Subjects covered by this journal are: Communications: Digital and analog communication, Digital signal processing, Image processing, Satellite communication, Secure communication, Speech and audio processing, Space communication, Vehicular communications, Wireless communication. Computers and Computing: Algorithms, Artificial intelligence, Computer graphics, Compiler programming and languages, Computer vision, Data mining, High-performance computing, Information technology, Internet computing, Multimedia, Networks, Network Security, Operating systems, Quantum learning systems, Pattern Recognition, Sensor networks, Soft computing. Control Engineering: Control theory and practice- Conventional control, Non-linear control, Adaptive control, Robust Control, Reinforcement learning control, Soft computing tools in control application- Fuzzy logic systems, Neural Networks, Support vector machines, Intelligent control. Electromagnetics: Antennas and arrays, Bio-electromagnetics, Computational electromagnetics, Electromagnetic interference, Electromagnetic compatibility, Metamaterials, Millimeter-wave and Terahertz circuits and systems, Microwave measurements, Microwave Photonics, Passive, active and tunable microwave circuits, Propagation studies, Radar and remote sensing, Radio wave propagation and scattering, RFID, RF MEMS, Solid-state microwave devices and tubes, UWB circuits and systems. Electronic Circuits, Devices, and Components: Analog and Digital circuits, Display Technology, Embedded Systems VLSI Design, Microelectronics technology and device characterization, MEMS, Nano-electronics, Nanotechnology, Physics and technology of CMOS devices, Sensors, Semiconductor device modeling, Space electronics, Solid state devices, and modeling. Instrumentation and Measurements: Automated instruments and measurement techniques, Industrial Electronics, Non-destructive characterization and testing, Sensors. Medical Electronics: Bio-informatics, Biomedical electronics, Bio-MEMS, Medical Instrumentation. Opto-Electronics: Fibre optics, Holography and optical data storage, Optical sensors Quantum Electronics, Quantum optics. Power Electronics: AC-DC/DC-DC/DC-AC/AC-AC converters, Battery chargers, Custom power devices, Distributed power generation, Electric vehicles, Electrochemical processes, Electronic blast, Flexible AC transmission systems, Heating/welding, Hybrid vehicles, HVDC transmission, Power quality, Renewal energy generation, Switched-mode power supply, Solid-state control of motor drives. The IETE Journal of Research is indexed in: British Library CLOCKSS CrossRef EBSCO - Applied Science & Technology Source EBSCO - Academic Search Complete EBSCO - STM Source EI Compendex/ Engineering Village (Elsevier) Google Scholar Microsoft Academic Portico ProQuest - ProQuest Central ProQuest - Research Library ProQuest - SciTech Premium Collection ProQuest - Technology Collection Science Citation Index Expanded (Thomson Reuters) SCImago (Elsevier) Scopus (Elsevier) Ulrich's Periodicals Directory Web of Science (Thomson Reuters) WorldCat Local (OCLC) Zetoc RG Journal Impact: 0.59 * *This value is calculated using ResearchGate data and is based on average citation counts from work published in this journal. The data used in the calculation may not be exhaustive. RG Journal impact history 2020 Available summer 2021 2018 / 2019 0.59 2017 0.39 2016 0.33 2015 0.49 2014 0.49 2013 0.41 2012 0.61 2011 0.90 2010 0.43 2009 0.22 2008 0.19 2007 0.23 2006 0.09 2005 0.11 2004 0.23 2003 0.38 IETE Journal of Research more details H Index - 20 Subject Area and Category: Computer Science, Computer Science Applications, Engineering, Electrical, and Electronic Engineering, Mathematics, Theoretical Computer Science Publisher: Taylor & Francis Publication Type: Journals Coverage : 1979-1989, 1993-ongoing

Academic reception and public dissemination of neurological research between 2012 and 2021 https://doi.org/10.5061/dryad.brv15dvg0 The xlsx.-spreadsheet data.set.neurology.xlsx contains all the raw data used for the present study after removal of any duplicates (identified by the contained DOI) or document with a citation count or Altmetric Attention Score (AAS) of 0. The columns "citation.count" and "altmetric.score" give the individual score for both these parameters for every document. They were correlated across the whole dataset and were used to calculate the "AAS-to-citation-ratio" defined in our paper. Also included is the year for each document to track the development of these parameters over time. The 2021 journal impact factor (JIF), gathered from The Web of Science Journals Citation Reports is also included as a seperate column and was used for the association analysis between citation counts, AAS, the ratio of the two and the JIF. The column "country" gives the country of origin of each individual document's first author's institution, used in the association analyses between dissemination metrics and country of origin. Finally, the last five columns detail, whether the individual document deals with one of the five major neurological subspecialties in a TRUE or FALSE manner. These data were used in the last paragraph of our results section, which looks at potential associations between dissemination metrics and neurologial subspecialties. ## Description of the data and file structure The "data.set.neurology.xlsx" file contains all the raw data used in our analyses and is structured as follows (column-by-column): 1. journal: This column gives the publication the individual document appears in in all caps. 2. doi: The unqiue digital object identifier for each document. 3. year: The year the document was published in. In the case of "online first"-documents, the year of the eventual journal publication was chosen. 4. citation count: The number of citations a document accumulated until the time of data collection. 5. author.keywords: The keywords chosen for the respective document by its authors (info on this metric can be found here: https://images.webofknowledge.com/images/help/WOS/hp_full_record.html). 6. keywords.plus: Index terms automatically generated from the titles of cited articles. KeyWords Plus terms must appear more than once in the bibliography and are ordered from multi-word phrases to single terms (definition taken from: https://images.webofknowledge.com/images/help/WOS/hp_full_record.html). 7. country: The country of origin of the document's first author's institution. 8. type: The type of document, either original research (designated as "ARTICLE") or review ("REVIEW"). 9. altmetric.score: The Altmetric Attention Score for each document by the time of data collection. 10. impact.score: The 2021 journal impact factor according to WoS Journal Citation Records. 11. -15.: The five chosen major neurological subspecialties (Stroke, Alzheimer's, Multiple Sclerosis (MS in the file), Parkinson's, Epilepsy) and whether a given document pertains to one them (TRUE/FALSE) ## Sharing/Access information Data was derived from the following sources: * https://www.webofscience.com/wos/woscc/basic-search * https://jcr.clarivate.com/ * https://www.altmetric.com/ ## Code/Software All statistical and graphical analyses were done using the software R (4.1.2) and its packages bibliometrix, patchwork, and tidyverse. P-values < 0.05 were considered statistically significant. To gain a representative overview of the research in neurology during the decade of interest, we took the top 20 neurology journals by h5 index11 listed on Google Scholar and combined them with the top 50 neurology and clinical neurology journals according to the SCImago Journal Rank (SJR) (https://www.scimagojr.com). Only journals with at least 100 citable documents (i.e. original research or reviews) over the period of interest were considered to avoid potential bias by outliers. Any duplicates were removed. In total, 86 journals were chosen for further analyses. The Web of Science (WoS) Core Collection was used for the identification of articles to be included. Every document from the 86 journals listed as either ‘Article’ or ‘Review’ with a final publication year between 2012 and 2021 was included in the analysis. This timeframe was selected with two reasons in mind: First, the company Altmetric (and with it the AAS) was founded in 2011, so 2012 constitutes the earliest year with full coverage. Second, since the data collection took place in late 2022, the year 2021 was fully covered in the databases and article citations/online dissemination had already been given some time to accumulate. Citation counts and other metadata for each document were retrieved from the WoS Core Collection database. Impact factors for each journal were retrieved through Clari...

IETE journal of research Impact Factor 2025-2026 - ResearchHelpDesk - IETE Journal of Research is a bimonthly journal published by the Institution of Electronics and Telecommunication Engineers (IETE), India. It publishes scientific and technical papers describing original research work or novel product/process development. Occasionally special issues are brought out on new and emerging research areas. This journal is useful to researchers, engineers, scientists, teachers, managers, and students who are interested in keeping track of original research and development work being carried out in the broad area of electronics, telecommunications, computer science, and engineering and information technology. Subjects covered by this journal are: Communications: Digital and analog communication, Digital signal processing, Image processing, Satellite communication, Secure communication, Speech and audio processing, Space communication, Vehicular communications, Wireless communication. Computers and Computing: Algorithms, Artificial intelligence, Computer graphics, Compiler programming and languages, Computer vision, Data mining, High-performance computing, Information technology, Internet computing, Multimedia, Networks, Network Security, Operating systems, Quantum learning systems, Pattern Recognition, Sensor networks, Soft computing. Control Engineering: Control theory and practice- Conventional control, Non-linear control, Adaptive control, Robust Control, Reinforcement learning control, Soft computing tools in control application- Fuzzy logic systems, Neural Networks, Support vector machines, Intelligent control. Electromagnetics: Antennas and arrays, Bio-electromagnetics, Computational electromagnetics, Electromagnetic interference, Electromagnetic compatibility, Metamaterials, Millimeter-wave and Terahertz circuits and systems, Microwave measurements, Microwave Photonics, Passive, active and tunable microwave circuits, Propagation studies, Radar and remote sensing, Radio wave propagation and scattering, RFID, RF MEMS, Solid-state microwave devices and tubes, UWB circuits and systems. Electronic Circuits, Devices, and Components: Analog and Digital circuits, Display Technology, Embedded Systems VLSI Design, Microelectronics technology and device characterization, MEMS, Nano-electronics, Nanotechnology, Physics and technology of CMOS devices, Sensors, Semiconductor device modeling, Space electronics, Solid state devices, and modeling. Instrumentation and Measurements: Automated instruments and measurement techniques, Industrial Electronics, Non-destructive characterization and testing, Sensors. Medical Electronics: Bio-informatics, Biomedical electronics, Bio-MEMS, Medical Instrumentation. Opto-Electronics: Fibre optics, Holography and optical data storage, Optical sensors Quantum Electronics, Quantum optics. Power Electronics: AC-DC/DC-DC/DC-AC/AC-AC converters, Battery chargers, Custom power devices, Distributed power generation, Electric vehicles, Electrochemical processes, Electronic blast, Flexible AC transmission systems, Heating/welding, Hybrid vehicles, HVDC transmission, Power quality, Renewal energy generation, Switched-mode power supply, Solid-state control of motor drives. The IETE Journal of Research is indexed in: British Library CLOCKSS CrossRef EBSCO - Applied Science & Technology Source EBSCO - Academic Search Complete EBSCO - STM Source EI Compendex/ Engineering Village (Elsevier) Google Scholar Microsoft Academic Portico ProQuest - ProQuest Central ProQuest - Research Library ProQuest - SciTech Premium Collection ProQuest - Technology Collection Science Citation Index Expanded (Thomson Reuters) SCImago (Elsevier) Scopus (Elsevier) Ulrich's Periodicals Directory Web of Science (Thomson Reuters) WorldCat Local (OCLC) Zetoc RG Journal Impact: 0.59 * *This value is calculated using ResearchGate data and is based on average citation counts from work published in this journal. The data used in the calculation may not be exhaustive. RG Journal impact history 2020 Available summer 2021 2018 / 2019 0.59 2017 0.39 2016 0.33 2015 0.49 2014 0.49 2013 0.41 2012 0.61 2011 0.90 2010 0.43 2009 0.22 2008 0.19 2007 0.23 2006 0.09 2005 0.11 2004 0.23 2003 0.38 IETE Journal of Research more details H Index - 20 Subject Area and Category: Computer Science, Computer Science Applications, Engineering, Electrical, and Electronic Engineering, Mathematics, Theoretical Computer Science Publisher: Taylor & Francis Publication Type: Journals Coverage : 1979-1989, 1993-ongoing

Microsoft Access Database for bibliometric analysis found in the article: Elaine M. Lasda Bergman, Finding Citations to Social Work Literature: The Relative Benefits of Using Web of Science, Scopus, or Google Scholar, The Journal of Academic Librarianship, Volume 38, Issue 6, November 2012, Pages 370-379, ISSN 0099-1333, http://dx.doi.org/10.1016/j.acalib.2012.08.002. (http://www.sciencedirect.com/science/article/pii/S009913331200119X) Abstract: Past studies of citation coverage of Web of Science, Scopus, and Google Scholar do not demonstrate a consistent pattern that can be applied to the interdisciplinary mix of resources used in social work research. To determine the utility of these tools to social work researchers, an analysis of citing references to well-known social work journals was conducted. Web of Science had the fewest citing references and almost no variety in source format. Scopus provided higher citation counts, but the pattern of coverage was similar to Web of Science. Google Scholar provided substantially more citing references, but only a relatively small percentage of them were unique scholarly journal articles. The patterns of database coverage were replicated when the citations were broken out for each journal separately. The results of this analysis demonstrate the need to determine what resources constitute scholarly research and reflect the need for future researchers to consider the merits of each database before undertaking their research. This study will be of interest to scholars in library and information science as well as social work, as it facilitates a greater understanding of the strengths and limitations of each database and brings to light important considerations for conducting future research. Keywords: Citation analysis; Social work; Scopus; Web of Science; Google Scholar

Dataset belonging to the report: Publication cultures and Dutch research output: a quantitative assessment

On the report:

Research into publication cultures commissioned by VSNU and carried out by Utrecht University Library has detailed university output beyond just journal articles, as well as the possibilities to assess open access levels of these other output types. For all four main fields reported on, the use of publication types other than journal articles is indeed substantial. For Social Sciences and Arts & Humanities in particular (with over 40% and over 60% of output respectively not being regular journal articles) looking at journal articles only ignores a significant share of their contribution to research and society. This is not only about books and book chapters, either: book reviews, conference papers, reports, case notes (in law) and all kinds of web publications are also significant parts of university output.

Analyzing all these publication forms and especially determining to what extent they are open access is currently not easy. Even combining some the largest citation databases (Web of Science, Scopus and Dimensions) leaves out a lot of non-article content and in some fields even journal articles are only partly covered. Lacking metadata like affiliations and DOIs (either in the original documents or in the scholarly search engines) makes it even harder to analyze open access levels by institution and field. Using repository-harvesting databases like BASE and NARCIS in addition to the main citation databases improves understanding of open access of non-article output, but these routes also have limitations. The report has recommendations for stakeholders, mostly to improve metadata and coverage and apply persistent identifiers.

This database was developed in a study titled Hydrological research evolution: A large language modelbased analysis of 310,000 studies published globally between 1980 and 2023 (Miao et al., 2024). It includes data from a quantitative literature review, based on searches performed with the Web of Science (WoS) search engine across all available databases. The search was performed in October 2023, encompassing the fields of title, abstract, journal name, authors names, authors affiliations, authors keywords and WoS generated keywords, and other information provided by WoS. See Miao et al. (2024) for further search method and other study descriptions.

The WoS source data is provided in Text files (*.txt), comprising and organized in four folders which represent search results for different keywords and publication dates. The preprocessed data is provided in a Comma-Separated Values (CSV) file (record_txt_unique.csv), which is the product of merging, deduplicating, and filtering the results of the WoS source data.

Literature search methods: A systematic review was done in November 2014 using the databases Web of Science and Google Scholar to collect and analyse the primary literature to date written about tool use and tool making behaviour in non-human animals. The search for publications on Google Scholar was done using the search terms “tool+using+making+animals”, including only articles, written in a non-limited period of time, sorted by relevance. Since Google Scholar provided a large amount of articles in a descending order from more relevant to less relevant, we detected relevant articles doing a first manual scan looking at the title and at the abstract until relevance was consistent, producing a total of 23 possible publications.The search for literature that was executed using the database Web of Science was done using the search terms “Tool*” (Topic) AND “Use* OR Utilization*” (Topic) AND “Mak*” (Topic) AND “Animal*”(Topic). This produced a result of 316 possible publications. Then we refined the results using the following search categories: “Behavioral Sciences”, “Ecology”, “Zoology”. We also selected only articles. After that, 9 articles were left. Then these underwent a title and abstract scan for relevance to the specific topic. The full text of the remaining articles was processed, and the articles that did not provide specific information about the occurrence of tool use and/or tool behaviour in animals were excluded. We also excluded all the secondary literature as reviewed primary literature without providing its own data. Articles whose content was not focused on the specified topic and articles whose data provided were not enough were also excluded. Of the 339 initial publications, 32 were screened: 2 were removed for not being primary research articles, 24 were directly related to the topic, 6 were excluded with reasons listed above. The remaining 24 studies included in the analysis were composed of experiments from 1973 to 2014. Out of 24 articles, 4 were written in 2005, 2 in 1982, 2 in 1990, 2 in 1994, 2 in 2003 and 2 in 2014. All articles that were included in this review were published in English in a total of 17 journals. Journal of Comparative Psychology published 4 articles out of 24 and Primates published 3. Analysis of the literature: Studies were coded by the geographical location (country's name), the duration (total lenght of the research measured in months), the type of the experiment performed ( observational, experimental), the common name of the animal observed or used as experimental subject, the activity that was the scope of the tool use behaviour, the kind of tool being used.

Abstract Bibliometric analyses provide a clear understanding of the scientific performance and relate them with standards of the global scientific production. Soil science is an outstanding and developing field among environmental sciences. Knowledge about soil characteristics and their distribution in the environment has been enriched by the use of new geotechnologies, resulting in what is known as digital soil mapping. Thus, the objective of this work was to characterize the scientific production in digital soil mapping in Brazil and in the world, in the period from 1996 to 2017, in databases such as Scopus and Web of Science. In the general context of increasing numbers of papers, the journal Geoderma published the highest number of related papers. Among the 10 with most published papers, the Revista Brasileira de Ciência do Solo is the only open access journal. Although there are countries at the cutting edge of digital soil mapping such as the United States and Australia, the position of Brazil in the number of papers and authors cannot be overlooked, showing the importance of the nation’s participation in digital soil mapping, as a field of science that can provide guidelines for public policies for the development of agriculture in the country.

Journal of Mind and Medical Sciences FAQ - ResearchHelpDesk - Journal of Mind and Medical Sciences (JMMS, J Mind Med Sci) pays special attention to papers related to mental and medical topics, focusing primarily on interdisciplinary and integrative perspectives. It is an online and open-access journal, no charges being received for submission, review, and publication of articles. The journal adheres to the philosophy that high quality and original ideas and information should be freely shared within and amongst the scientific community, with the stipulation that the authors be acknowledged for their knowledge and contribution. J Mind Med Sci. is licensed under a CC BY-NC-ND 4.0 License. The journal is conducted by international norms of academic publishing, being listed by the International Committee of Medical Journal Editors (ICMJE), adhere to the most important and comprehensive ethical guidelines of COPE, it is a member of CrossRef and indexed by several International Databases. Authors are encouraged to supply the names of two potential referees, and/or of referees that they do not wish to review their paper. The decision regarding the selection process of the reviewers belongs to Editor(s). Our referees have the opportunity to be recognized as reviewers for their contributions, due to the fact that the Journal of Mind and Medical Sciences is a member of Publons (part of Clarivate Analytics). Journal of Mind and Medical Sciences is currently indexed in the following international databases: Web of Science WorldWideScience World Health Organization (Hinari/ Health Inter-Network Access to Research Initiative) Microsoft Academic Search EBSCO DOAJ Index Copernicus Cabell`s Whitelist Ulrich's Periodicals Directory SHERPA/ RoMEO OAJI J-Gate DRJI SCIPIO OpenAIRE (Horizon 2020) ClavisBCT Gale/ Cengage Learning Medicine and Health Sciences Commons Google Scholar WorldCat J Mind Med Sci. can also be accessed via prestigious medical universities, like: Harvard Library Yale University Library Oxford University Libraries Stanford University Libraries Boston University Libraries The British Library COPAC (Cambridge, Glasgow, Imperial College, Liverpool, Manchester, Sheffield, York, Southampton Universities) Berlin Social Science Center The Saskatoon Public Library BASE (Bielefeld Academic Search Engine) Nelson Mandela Metropolitan University Social Services Knowledge Scotland elibrary, etc.