Australian and New Zealand journal of statistics Impact Factor 2024-2025 - ResearchHelpDesk - The Australian & New Zealand Journal of Statistics is an international journal managed jointly by the Statistical Society of Australia and the New Zealand Statistical Association. Its purpose is to report significant and novel contributions in statistics, ranging across articles on statistical theory, methodology, applications and computing. The journal has a particular focus on statistical techniques that can be readily applied to real-world problems, and on application papers with an Australasian emphasis. Outstanding articles submitted to the journal may be selected as Discussion Papers, to be read at a meeting of either the Statistical Society of Australia or the New Zealand Statistical Association. The main body of the journal is divided into three sections. The Theory and Methods Section publishes papers containing original contributions to the theory and methodology of statistics, econometrics and probability, and seeks papers motivated by a real problem and which demonstrate the proposed theory or methodology in that situation. There is a strong preference for papers motivated by, and illustrated with, real data. The Applications Section publishes papers demonstrating applications of statistical techniques to problems faced by users of statistics in the sciences, government and industry. A particular focus is the application of newly developed statistical methodology to real data and the demonstration of better use of established statistical methodology in an area of application. It seeks to aid teachers of statistics by placing statistical methods in context. The Statistical Computing Section publishes papers containing new algorithms, code snippets, or software descriptions (for open source software only) which enhance the field through the application of computing. Preference is given to papers featuring publically available code and/or data, and to those motivated by statistical methods for practical problems. In addition, suitable review papers and articles of historical and general interest will be considered. The journal also publishes book reviews on a regular basis. Abstracting and Indexing Information Academic Search (EBSCO Publishing) Academic Search Alumni Edition (EBSCO Publishing) Academic Search Elite (EBSCO Publishing) Academic Search Premier (EBSCO Publishing) CompuMath Citation Index (Clarivate Analytics) Current Index to Statistics (ASA/IMS) Journal Citation Reports/Science Edition (Clarivate Analytics) Mathematical Reviews/MathSciNet/Current Mathematical Publications (AMS) RePEc: Research Papers in Economics Science Citation Index Expanded (Clarivate Analytics) SCOPUS (Elsevier) Statistical Theory & Method Abstracts (Zentralblatt MATH) ZBMATH (Zentralblatt MATH)

BackgroundAs statisticians develop new methodological approaches, there are many factors that influence whether others will utilize their work. This paper is a bibliometric study that identifies and quantifies associations between characteristics of new biostatistics methods and their citation counts. Of primary interest was the association between numbers of citations and whether software code was available to the reader.MethodsStatistics journal articles published in 2010 from 35 statistical journals were reviewed by two biostatisticians. Generalized linear mixed models were used to determine which characteristics (author, article, and journal) were independently associated with citation counts (as of April 1, 2017) in other peer-reviewed articles.ResultsOf 722 articles reviewed, 428 were classified as new biostatistics methods. In a multivariable model, for articles that were not freely accessible on the journal’s website, having code available appeared to offer no boost to the number of citations (adjusted rate ratio = 0.96, 95% CI = 0.74 to 1.24, p = 0.74); however, for articles that were freely accessible on the journal’s website, having code available was associated with a 2-fold increase in the number of citations (adjusted rate ratio = 2.01, 95% CI = 1.30 to 3.10, p = 0.002). Higher citation rates were also associated with higher numbers of references, longer articles, SCImago Journal Rank indicator (SJR), and total numbers of publications among authors, with the strongest impact on citation rates coming from SJR (rate ratio = 1.21 for a 1-unit increase in SJR; 95% CI = 1.11 to 1.32).ConclusionThese analyses shed new insight into factors associated with citation rates of articles on new biostatistical methods. Making computer code available to readers is a goal worth striving for that may enhance biostatistics knowledge translation.

Version: 6

Date of data collection: May 2025

General description: Publication of datasets according to the FAIR principles could be reached publishing a data paper (and/or a software paper) in data journals as well as 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_v6.xlsx: full list of 177 academic journals in which data papers or/and software papers could be published
- data_articles_journal_list_v6.csv: full list of 177 academic journals in which data papers or/and software papers could be published
- readme_v6.txt, with a detailed descritption of the dataset and its variables.

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: 6th version
- Information updated: number of journals (17 were added and 4 were deleted), URL, document types associated to a specific journal.
- Information added: diamond journals were identified.

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 162 academic journals in which data papers or/and software papers could be published
- data_articles_journal_list_v5.csv: full list of 162 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.
163 journals (excel y csv)

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.

Overall journal rankings, which are generated with sample articles in different research fields, are commonly used to measure the research productivity of academic economists. In this article, we investigate a growing concern in the profession that the use of the overall journal rankings to evaluate scholars’ relative research productivity may exhibit a downward bias toward researchers in some specialty fields if their respective field journals are under-ranked in the overall journals rankings. To address this concern, we constructed new journal rankings based on the intellectual influence of research in 8 specialty fields using a sample consisting of 26,401 articles published across 60 economics journals from 1998 to 2007. We made various comparisons between the newly constructed journal rankings in specialty fields and the traditional overall journal ranking. Our results show that the overall journal ranking provides a considerably good mapping for the article quality in specialty fields. Supplementary materials for this article are available online.

Annual review of statistics and its application Impact Factor 2024-2025 - ResearchHelpDesk - The Annual Review of Statistics and Its Application informs statisticians, and users of statistics about major methodological advances and the computational tools that allow for their implementation. The Annual Review of Statistics and Its Application debuted in the 2016 Release of the Journal Citation Report (JCR) with an Impact Factor of 3.045.

International Journal of Data Science and Analytics Impact Factor 2024-2025 - ResearchHelpDesk - International Journal of Data Science and Analytics - Data Science has been established as an important emergent scientific field and paradigm driving research evolution in such disciplines as statistics, computing science and intelligence science, and practical transformation in such domains as science, engineering, the public sector, business, social science, and lifestyle. The field encompasses the larger areas of artificial intelligence, data analytics, machine learning, pattern recognition, natural language understanding, and big data manipulation. It also tackles related new scientific challenges, ranging from data capture, creation, storage, retrieval, sharing, analysis, optimization, and visualization, to integrative analysis across heterogeneous and interdependent complex resources for better decision-making, collaboration, and, ultimately, value creation. The International Journal of Data Science and Analytics (JDSA) brings together thought leaders, researchers, industry practitioners, and potential users of data science and analytics, to develop the field, discuss new trends and opportunities, exchange ideas and practices, and promote transdisciplinary and cross-domain collaborations.

By encouraging and requiring that authors share their data in order to publish articles, scholarly journals have become an important actor in the movement to improve the openness of data and the reproducibility of research. But how many social science journals encourage or mandate that authors share the data supporting their research findings? How does the share of journal data policies vary by discipline? What influences these journals’ decisions to adopt such policies and instructions? And what do those policies and instructions look like? We discuss the results of our analysis of the instructions and policies of 291 highly-ranked journals publishing social science research, where we studied the contents of journal data policies and instructions across 14 variables, such as when and how authors are asked to share their data, and what role journal ranking and age play in the existence and quality of data policies and instructions. We also attempt to compare our results to the results of other studies that have analyzed the policies of social science journals, although differences in the journals chosen and how each study defines what constitutes a data policy limit this comparison. We conclude that a little more than half of the journals in our study have data policies. A greater share of the economics journals have data policies and mandate sharing, followed by political science/international relations and psychology journals. Finally, we use our findings to make several recommendations: Policies should include the terms “data”, “dataset” or more specific terms that make it clear what to make available; policies should include the benefits of data sharing; journals, publishers, and associations need to collaborate more to clarify data policies; and policies should explicitly ask for qualitative data.

etc)

1. Sample: economics journals indexed in Journal Citation Reports (JCR) compiled by the Institute for Scientific Information, for the years of 2008 and 20132. We surveyed the journal editors to obtain the numbers of submissions.3. Acceptance rate = Number of articles published/Number of submission, a rough approximation for the real acceptance rate4. Other information such as impact factor is from the JCR

Journal of business analytics Impact Factor 2024-2025 - ResearchHelpDesk - Business analytics research focuses on developing new insights and a holistic understanding of an organisation’s business environment to help make timely and accurate decisions, and to survive, innovate and grow. Thus, business analytics draws on the full spectrum of descriptive/diagnostic, predictive and prescriptive analytics in order to make better (i.e., data-driven and evidence-based) decisions to create business value in the broadest sense. The mission of the Journal of Business Analytics Journal (JBA) is to serve the emerging and rapidly growing community of business analytics academics and practitioners. We aim to publish articles that use real-world data and cases to tackle problem situations in a creative and innovative manner. We solicit articles that address an interesting research problem, collect and/or repurpose multiple types of data sets, and develop and evaluate analytics methods and methodologies to help organisations apply business analytics in new and novel ways. Reports of research using qualitative or quantitative approaches are welcomed, as are interdisciplinary and mixed methods approaches. Topics may include: Applications of AI and machine learning methods in business analytics Network science and social network applications for business Social media analytics Statistics and econometrics in business analytics Use of novel data science techniques in business analytics Robotics and autonomous vehicles Methods and methodologies for business analytics development and deployment Organisational factors in business analytics Responsible use of business analytics and AI Ethical and social implications of business analytics and AI Bias and explainability in analytics and AI Our editorial philosophy is to publish papers that contribute to theory and practice. Journal of Business Analytics is indexed in: AIS eLibrary Australian Business Deans Council (ABDC) Journal Quality List British Library CLOCKSS Crossref Ei Compendex (Engineering Village) Google Scholar Microsoft Academic Portico SCImago Scopus Ulrich's Periodicals Directory

This paper demonstrates the potential problem in using existing economics journal rankings to evaluate the research productivity of scholars by constructing a new ranking of economics journals and articles. Based on 2142 econometrics sample articles published from 2000 to 2005, our ranking results show that the intellectual influence of an econometrics article published in several econometrics/statistics journals is much higher than if it were published in the most prestigious general-interest journal. Given that a study's potential influence is integrated into the submission decision, this suggests a substantial downward bias toward econometricians when existing rankings are used to evaluate their research productivity.

The SCImago Institutions Rankings (SIR) is a classification of academic and research-related institutions ranked by a composite indicator that combines three different sets of indicators based on research performance, innovation outputs and societal impact measured by their web visibility. It provides a friendly interface that allows the visualization of any customized ranking from the combination of these three sets of indicators. Additionally, it is possible to compare the trends for individual indicators of up to six institutions. For each large sector it is also possible to obtain distribution charts of the different indicators. For comparative purposes, the value of the composite indicator has been set on a scale of 0 to 100. However the line graphs and bar graphs always represent ranks (lower is better, so the highest values are the worst).

Data sharing is crucial to the advancement of science because it facilitates collaboration, transparency, reproducibility, criticism, and re-analysis. Publishers are well-positioned to promote sharing of research data by implementing data sharing policies. While there is an increasing trend toward requiring data sharing, not all journals mandate that data be shared at the time of publication. In this study, we extended previous work to analyze the data sharing policies of 447 journals across several scientific disciplines, including biology, clinical sciences, mathematics, physics, and social sciences. Our results showed that only a small percentage of journals require data sharing as a condition of publication, and that this varies across disciplines and Impact Factors. Both Impact Factors and discipline are associated with the presence of a data sharing policy. Our results suggest that journals with higher Impact Factors are more likely to have data sharing policies; use shared data in peer review; require deposit of specific data types into publicly available data banks; and refer to reproducibility as a rationale for sharing data. Biological science journals are more likely than social science and mathematics journals to require data sharing.

Journal of Big Data Impact Factor 2024-2025 - ResearchHelpDesk - The Journal of Big Data publishes high-quality, scholarly research papers, methodologies and case studies covering a broad range of topics, from big data analytics to data-intensive computing and all applications of big data research. The journal examines the challenges facing big data today and going forward including, but not limited to: data capture and storage; search, sharing, and analytics; big data technologies; data visualization; architectures for massively parallel processing; data mining tools and techniques; machine learning algorithms for big data; cloud computing platforms; distributed file systems and databases; and scalable storage systems. Academic researchers and practitioners will find the Journal of Big Data to be a seminal source of innovative material. All articles published by the Journal of Big Data are made freely and permanently accessible online immediately upon publication, without subscription charges or registration barriers. As authors of articles published in the Journal of Big Data you are the copyright holders of your article and have granted to any third party, in advance and in perpetuity, the right to use, reproduce or disseminate your article, according to the SpringerOpen copyright and license agreement. For those of you who are US government employees or are prevented from being copyright holders for similar reasons, SpringerOpen can accommodate non-standard copyright lines.

Bivariate associations between citation counts and article, author, and journal characteristics.

Journal recommendations prepared on results from JANE and whichjournal.com based on 4 abstracts from the disciplines dentistry, psychology and aerosol chemistry. The factsheets with data for each journal should help to decide for the best journal. The data is provided as spreadsheet (xls) and factsheet (pdf).

Introduction: These datasets contain information about journals in the eight regions of the world based on United Nations SDG classification (Central& Southern Asia, Europe, Eastern &South Eastern Asia, Latin America, North Africa& Western Asia, Oceania, North America and Sub-Saharan Africa) that are indexed in Web of Science/Scopus and are available in Ulrich periodical directory. The datasets were created by matching Ulrich journal information with journal information from Web of Science and Scopus.

Data Creation: A single Web of Science master journal list was created for SSCI, SCI, AHCI and ESCI by combining and removing duplicate records from their lists; the Web of Science master journal contained 21,908 unique journals. Only active scholarly journals from Scopus were included in this study; i.e. duplicates, all inactive sources, trade journals, book series, monographs and conference proceedings were removed. 26,029 active journals of the 43,013 sources in Scopus were included. Journal lists from 239 countries were collected from Ulrich comprehensive periodical directory and analyzed by region. After removal of duplicates, this generated a database of 83,429 unique active academic journals. To compile regional and global datasets, duplicate journals in the regional and global levels, respectively, were removed. The master journal lists created from Web of Science, Scopus and Ulrich were transferred to an SQL database for querying. Journal matching was carried out in two steps. Firstly, the ISSN numbers of journals in Web of Science and Scopus were used to match journal records to Ulrich. In the second step, the remaining journals were then matched using their titles, and these matches were manually verified to reduce the chances of false positives. Using these two steps, we were able to match 20,255 (92.46%) of the journals in Web of Science, and 23,349 (89.70%) of the academic journals from Scopus, with Ulrichsweb journal list.

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.

Datasets for publication: 'Measuring the excellence contribution at the journal level: An alternative to Garfield's Impact Factor'.

Overview. Overview of the number of journals, publications, excellent publications and multidisciplinarity for each category considered.

ALL. Journal indicators for all the document types by JCR category.

ALL_JCR. Journal indicators for all the document types by JCR category (only journals indexed in the JCR category are taken into account).

AR. Journal indicators for only articles and reviews by JCR category.

AR_JCR. Journal indicators for only articles and reviews by JCR category (only journals indexed in the JCR category are taken into account).

Quarterly Journal of Economics Impact Factor 2024-2025 - ResearchHelpDesk - The Quarterly Journal of Economics is a peer-reviewed academic journal published by the Oxford University Press for the Harvard University Department of Economics. Its current editors-in-chief are Robert J. Barro, Lawrence F. Katz, Nathan Nunn, Andrei Shleifer, and Stefanie Stantcheva (Harvard University). It is the oldest professional journal of economics in the English language and covers all aspects of the field—from the journal's traditional emphasis on micro theory to both empirical and theoretical macroeconomics. According to the Journal Citation Reports, the journal has a 2015 impact factor of 6.662, ranking it first out of 347 journals in the category "Economics". It is generally regarded as one of the top 5 journals in economics, together with the American Economic Review, Econometrica, the Journal of Political Economy, and the Review of Economic Studies. The Quarterly Journal of Economics is the oldest professional journal of economics in the English language. Edited at Harvard University's Department of Economics, it covers all aspects of the field. QJE is invaluable to professional and academic economists and students around the world. Scope of the Journal The Quarterly Journal of Economics is the oldest professional journal of economics in the English language. Edited at Harvard University's Department of Economics, it covers all aspects of the field-from the journal's traditional emphasis on micro theory, to both empirical and theoretical macroeconomics. QJE is invaluable to professional and academic economists and students around the world. Impact Factor and Ranking Year Impact Factor Ssi: Economics 2020 15.563 1 out of 377 2019 11.375 1 out of 371 2018 11.775 1 out of 363 2017 7.863 1 out of 353 2016 6.662 1 out of 347 2015 5.538 2 out of 344 2014 6.654 1 out of 333 2013 5.966 3 out of 332 2012 5.278 2 out of 332 2011 5.920 2 out of 320 2010 5.940 2 out of 304 2009 5.647 2 out of 245 This information is taken from the Journal Citation Reports™ (Clarivate, 2021). Abstracting & Indexing Services The Quarterly Journal of Economics is covered by the following abstracting and indexing services: ABI-INFORM Book Review Digest Plus CAB Abstracts Coal Abstracts Criminal Justice Abstracts Current Contents: Social & Behavioral Sciences Current Index to Statistics Dietrich's Index Philosophicus Documentation in Public Administration EconLit Emerald Management Reviews Environmental RouteNet Environmental Sciences & Pollution Management Database Expanded Academic ASAP Family Index Historical Abstracts Human Resources Abstracts IBZ: International Bibliography of Periodical Literature Index of Economic Articles in Journals & Collected Volumes Index to Periodical Articles Related to Law International Bibliography of Humanities & Sociological Literature Leisure, Recreation, and Tourism Abstracts Leisure Tourism Database LexisNexis Operations Research - Management Science Peace Research Abstracts ProQuest Central Public Administration Abstracts Quality Control & Applied Statistics RePec Risk Abstracts SCOPUS Social Science Source Social Sciences Citation Index/Social SciSearch Social Sciences Index Social Work Abstracts Wilson Business Abstracts World Agricultural Economics & Rural Sociology Abstracts Zentralblatt MATH