This dataset contains the data availability statements (DAS) from four Nature Portfolio journals from January 2017 to December 2021. This covers two periods; one prior to integrating the figshare repository with the submission system of each journal (January 2017 to December 2021) and one following the integration (April 2022 to July 2023).Each DAS is assigned one or more of seven categories based on its content and any links to available data. This enables analysis of changes in data sharing behaviour, for example either side of the figshare integration.Summary statistics by year and the DAS categories are provided in separate tabs of the worksheet. DAS were initially assigned by basic text-matching (for example the presence of key terms like 'request' in the DAS indicating data are available on request). A human curator then verified each article's categorisation and amended if necessary.

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

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

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

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

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

BackgroundTo enhance reproducibility and transparency, the International Committee of Medical Journal Editors (ICMJE) required that all trial reports submitted after July 2018 must include a data sharing statement (DSS). Accordingly, emerging biomedical journals required trial authors to include a DSS in submissions for publication if trial reports were accepted. Nevertheless, it was unclear whether endocrinology and metabolism journals had this request for DSS of clinical trial reports. Therefore, we aimed to explore whether endocrinology and metabolism journals requested DSS in clinical trial submissions, and their compliance with the declared request in published trial reports.MethodsJournals that were from the category of “Endocrinology & Metabolism” defined by Journal Citation Reports (JCR, as of June 2023) and published clinical trial reports between 2019 and 2022, were included for analysis. The primary outcome was whether a journal explicitly requested a DSS in its manuscript submission instructions for clinical trials, which was extracted and verified in December 2023. We also evaluated whether these journals indeed included a DSS in their published trial reports that were published between December 2023 and May 2024.ResultsA total of 141 endocrinology and metabolism journals were included for analysis, among which 125 (88.7%) requested DSS in clinical trial submissions. Journals requesting DSS had a significantly lower JCR quartile and higher impact factor when compared with those journals without DSS request. Among the 90 journals requesting DSS, 14 (15.6%) journals indeed did not publish any DSS in their published trial reports between December 2023 and May 2024.ConclusionOver 10% of endocrinology and metabolism journals did not request DSS in clinical trial submissions. More than 15% of the journals declaring to request DSS from their submission instructions, did not publish DSS in their published trial reports. More efforts are needed to improve the practice of endocrinology and metabolism journals in requesting and publishing DSS of clinical trial reports.

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

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

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

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

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

This collection shares pre-prints of videos with tips, how-to, lessons, and other content to help researchers make their results more reproducible. Authors create a new Hydroshare resource that includes meta data and the video file. Authors request the Collection Owners add their resource to this collection. Then authors submit a short brief in the Editorial Manager system of the American Society of Civil Engineers (ASCE) Journal of Water Resources Planning and Management (https://ascelibrary.org/journal/jwrmd5) for publication. The brief includes a one-sentence citation to the Hydroshare resource containing the video content. The video undergoes a peer-review process. On acceptance, ASCE Publishing will attach branding to the video. The content will receive a digital object identifier (DOI) and be published in the Journal -- same as regular articles, case studies, etc. ASCE will also push videos out on their video and social media feeds.

The intent of collection of videos and the review process is to make peer-reviewed videos findable, accessible, interoperable, and repeatable (FAIR). This process also provides authors of reproducibility content an incentive to create and share new videos and content -- a peer-reviewed publication in the Journal of Water Resources Planning and Management.

There are limited open source data available for determining water production/treatment and required energy for cities across the United States. This database represents the culmination of a two-year effort to obtain data from cities across the United States via open records requests in order to determine the state of the U.S. urban energy-water nexus. Data were requested at the daily or monthly scale when available for 127 cities across the United States, represented by 253 distinct water and sewer districts. Data were requested from cities larger than 100,000 people and from each state. In the case of states that did not have cities that met these criteria, the largest cities in those states were selected. The resulting database represents a drinking water service population of 81.4 million and a wastewater service population of 86.2 million people. Average daily demands for the United States were calculated to be 560 liters per capita for drinking water and 500 liters per capita of wastewater. The embedded energy within each of these resources is 340 kWh/1000 m3 and 430 kWh/1000 m3, respectively. Drinking water data at the annual scale are available for production volume (89 cities) and for embedded energy (73 cities). Annual wastewater data are available for treated volume (104 cities) and embedded energy (90 cities). Monthly data are available for drinking water volume and embedded energy (73 and 56 cities) and wastewater volume and embedded energy (88 and 70 cities). Please see the two related papers for this metadata are included with this submission. Each folder name is a city that contributed data to the collection effort (City+State Abbreviation). Within each folder is a .csv file with drinking water and wastewater volume and energy data. A READ-ME file within each folder details the contents of the folder within any relevant information pertaining to data collection. Data are on the order of a monthly timescale when available, and yearly if not. Please cite the following papers when using the database: Chini, C.M. and Stillwell, A.S. (2017). The State of U.S. Urban Water: Data and the Energy-Water Nexus. Water Resources Research. 54(3). DOI: https://doi.org/10.1002/2017WR022265 Chini, C.M., and Stillwell, A. (2016). Where are all the data? The case for a comprehensive water and wastewater utility database. Journal of Water Resources Planning and Management. 143(3). DOI: 10.1061/(ASCE)WR.1943-5452.0000739

Journal of International Economics - ResearchHelpDesk - The Journal of International Economics is intended to serve as the primary outlet for theoretical and empirical research in all areas of international economics. These include, but are not limited to the following: trade patterns, commercial policy; international institutions; exchange rates; open economy macroeconomics; international finance; international factor mobility. The Journal especially encourages the submission of articles which are empirical in nature, or deal with issues of open economy macroeconomics and international finance. Theoretical work submitted to the Journal should be original in its motivation or modelling structure. Empirical analysis should be based on a theoretical framework, and should be capable of replication. It is expected that all materials required for replication (including computer programs and data sets) should be available upon request to the authors. Abstracting and Indexing Current Contents Journal of Economic Literature Social Sciences Citation Index ABI/Inform UMI Data Courier RePEc

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

Journal of International Economics Abstract & Indexing - ResearchHelpDesk - The Journal of International Economics is intended to serve as the primary outlet for theoretical and empirical research in all areas of international economics. These include, but are not limited to the following: trade patterns, commercial policy; international institutions; exchange rates; open economy macroeconomics; international finance; international factor mobility. The Journal especially encourages the submission of articles which are empirical in nature, or deal with issues of open economy macroeconomics and international finance. Theoretical work submitted to the Journal should be original in its motivation or modelling structure. Empirical analysis should be based on a theoretical framework, and should be capable of replication. It is expected that all materials required for replication (including computer programs and data sets) should be available upon request to the authors. Abstracting and Indexing Current Contents Journal of Economic Literature Social Sciences Citation Index ABI/Inform UMI Data Courier RePEc

Journal of International Economics Impact Factor 2024-2025 - ResearchHelpDesk - The Journal of International Economics is intended to serve as the primary outlet for theoretical and empirical research in all areas of international economics. These include, but are not limited to the following: trade patterns, commercial policy; international institutions; exchange rates; open economy macroeconomics; international finance; international factor mobility. The Journal especially encourages the submission of articles which are empirical in nature, or deal with issues of open economy macroeconomics and international finance. Theoretical work submitted to the Journal should be original in its motivation or modelling structure. Empirical analysis should be based on a theoretical framework, and should be capable of replication. It is expected that all materials required for replication (including computer programs and data sets) should be available upon request to the authors. Abstracting and Indexing Current Contents Journal of Economic Literature Social Sciences Citation Index ABI/Inform UMI Data Courier RePEc

Raw sequencing data from Denitrifying Anaerobic Methane Oxidation (DAMO) experiments and the relevant statistical data generated by various bioinformatics tools. This dataset is not publicly accessible because: All the experiments for this study were not performed in EPA but in co-authors' institution which has managed the project and prepared a manuscript for peer-reviewed journal submission. It can be accessed through the following means: The raw data will be made available by the authors on request (Dr. Yaohuan Gao, gaoyaohuan@xjtu.edu.cn). Format: Not available because the raw data was not generated in EPA. This dataset is associated with the following publication: Xia, L., Y. Wang, P. Yao, H. Ryu, Z. Dong, C. Tan, S. Deng, H. Liao, and Y. Gao. The effects of model insoluble copper compounds in anoxic sedimentary environment on denitrifying anaerobic methane oxidation (DAMO) activity. Microorganisms. MDPI, Basel, SWITZERLAND, 12(11): 2259, (2024).

A portion of the data used is publicly available through John Hopkins Coronavirus Resource Center and CDC COVID Data Tracker. Another portion data is password protected through HHS Protect. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: https://covid.cdc.gov/covid-data-tracker/#county-view and https://coronavirus.jhu.edu/map.html. For the data through HHS Protect, interested parties must submit a request to HHS. Format: Much of the data is publicly available at https://coronavirus.jhu.edu/map.html and https://covid.cdc.gov/covid-data-tracker/#county-view. What is not publicly available is through HHS Protect which is password protected. This dataset is associated with the following publication: Baxter, L., J. Baynes, A. Weaver, A. Neale, T. Wade, M. Mehaffey, D. Lobdell, K. Widener, and W. Cascio. Development of the United States Environmental Protection Agency’s Facilities Status Dashboard for the COVID-19 Pandemic: Approach and Challenges.. International Journal of Public Health. Springer Basel AG, Basel, SWITZERLAND, 61(1604761): 9, (2022).

Journals sometimes focus the attention of the research community by having a special collection, sometimes an entire special issue, devoted to a single topic. A reasonable question to ask is whether the extra effort of organizing, promoting, and maintaining the special collection is worthwhile. The paper that this data set accompanies examines paper impact in the Journal of Geophysical Research Space Physics, separating the special collection papers from the non-special-collection submissions. The conclusion is that special collections are worth the extra work.

This publication contains several datasets that have been used in the paper "Crowdsourcing open citations with CROCI – An analysis of the current status of open citations, and a proposal" submitted to the 17th International Conference on Scientometrics and Bibliometrics (ISSI 2019), available at https://arxiv.org/abs/1902.03287.

Additional information about the analyses described in the paper, including the code and the data we have used to compute all the figures, is available at https://github.com/sosgang/asn2016-issi2019. The datasets contain the following information.

[asncv | dblp | dblp_asncv]-data.csv: these CSV files contains all the final data used for the experiment with three conditions as described in the paper. The columns of the CSV file are the following ones (each row represents a particular candidate's application):

• level: the professor level (1: Full Professor, 2: Associate Professor) to which the candidate wants to get the habilitation;
• session_date: the date of the session for submitting the application;
• journal_number_open: the number of journal article published by the candidate according to the open data available;
• citation_number_open: the number of citations received by candidate's articles according to the open data available;
• h_index_open: the h-index of the candidate according to the open data available;
• journal_number_real: the number of journal article published by the candidate according to the official ASN 2016 data;
• citation_number_real: the number of citations received by candidate's articles according to the official ASN 2016 data;
• h_index_real: the h-index of the candidate according to the the official ASN 2016 data.

All the other CSV files are intermediated data used to calculate the aforementioned one.

Journal of International Economics Acceptance Rate - ResearchHelpDesk - The Journal of International Economics is intended to serve as the primary outlet for theoretical and empirical research in all areas of international economics. These include, but are not limited to the following: trade patterns, commercial policy; international institutions; exchange rates; open economy macroeconomics; international finance; international factor mobility. The Journal especially encourages the submission of articles which are empirical in nature, or deal with issues of open economy macroeconomics and international finance. Theoretical work submitted to the Journal should be original in its motivation or modelling structure. Empirical analysis should be based on a theoretical framework, and should be capable of replication. It is expected that all materials required for replication (including computer programs and data sets) should be available upon request to the authors. Abstracting and Indexing Current Contents Journal of Economic Literature Social Sciences Citation Index ABI/Inform UMI Data Courier RePEc

There is substantial evidence that systemic biases influence the scholarly peer review process. Many scholars have advocated for double-blind peer review (also known as double-anonymous review) to reduce these biases. However, the effectiveness of double‐blind peer review in eliminating biases is uncertain because few randomized trials have manipulated blinding of author identities for journal submissions, and those that have are generally small or provide few insights on how it influences reviewer biases.

In 2019, Functional Ecology began a large randomized trial, using real manuscript submissions, to evaluate the various consequences of shifting to double-blind peer review. Research papers submitted to the journal were randomly assigned to be reviewed with author identities blinded to reviewers (double‐blind review) or with authors identified to reviewers (single-blind review). In this paper, we explore the effect of blinding on the outcomes of peer review, examining reviewer ratings and editorial decisions, and ask whether author gender and/or location mediate the effects of review type.

Double-blind review reduced the average success of manuscripts in peer review; papers reviewed with author identities blinded received on average lower ratings from reviewers and were less likely to be invited for revision or resubmission. However, the effect of review treatment varied with author location.

Papers with first authors residing in countries with a higher human development index (HDI) and/or higher average English proficiency fared much better than those from countries with a lower HDI and lower English proficiency, but only when author identities were known to reviewers; outcomes were similar between demographic groups when author identities were not known to reviewers.

Blinding author identities had no effect on gender differences in reviewer ratings or editor decisions.

Our data provide strong evidence that authors from higher income and/or English-speaking countries receive significant benefits (a large positive bias) to being identified to reviewers during the peer review process, and that anonymizing author-identities (e.g., double-blind review) reduces this bias, making the peer review process more equitable. We suggest that offering optional blinding of author identities, as some journals allow, is unlikely to substantially reduce the biases that exist because authors from higher-income and English-speaking countries are the least likely to choose to be reviewed with their identity anonymized.

International Journal of Building Performance Simulation FAQ - ResearchHelpDesk - The Journal of Building Performance Simulation (JBPS) aims to make a substantial and lasting contribution to the international building community by supporting our authors and the high-quality, original research they submit. The journal also offers a forum for original review papers and researched case studies. JBPS welcome building performance simulation contributions that explore the following topics related to buildings and communities: Theoretical aspects related to modelling and simulating the physical processes (thermal, airflow, moisture, lighting, acoustics). Theoretical aspects related to modelling and simulating conventional and innovative energy conversion, storage, distribution, and control systems. Theoretical aspects related to occupants, weather data, and other boundary conditions. Methods and algorithms for optimizing the performance of buildings and communities and the systems which service them, including interaction with the electrical grid. Uncertainty, sensitivity analysis, and calibration. Methods and algorithms for validating models and for verifying solution methods and tools. Development and validation of controls-oriented models that are appropriate for model predictive control and/or automated fault detection and diagnostics. Techniques for educating and training tool users. Software development techniques and interoperability issues with direct applicability to building performance simulation. Case studies involving the application of building performance simulation for any stage of the design, construction, commissioning, operation, or management of buildings and the systems which service them are welcomed if they include validation or aspects that make a novel contribution to the BPS knowledge base. The following topics are outside the journal's scope and will not be considered: Case studies involving the routine application of commercially available building performance simulation tools that do not include validation or aspects that make a novel contribution to the knowledge base. The structural performance of buildings and the durability of building components. Studies focused on the performance of buildings and the systems that serve them, rather than on modelling and simulation. The Journal of Building Performance Simulation (JBPS) Journal operates a double-blind peer review and all submissions are to be made online using the JBPS ScholarOne site. For more information on contributing a manuscript visit our Instructions for Authors page. Society information Journal of Building Performance Simulation is the Official Journal of the International Building Performance Simulation Association (IBPSA). Members of IBPSA can receive an individual print subscription at a special society members rate. Please see the pricing or subscribe page for details. (JBPS) Journal information Journal of Building Performance Simulation is abstracted and indexed by: British Library Inside, Cambridge Scientific Abstracts, EBSCO Databases and Scopus. International Building Performance Simulation Association (IBPSA) and our publisher Taylor & Francis make every effort to ensure the accuracy of all the information (the "Content") contained in our publications. However, International Building Performance Simulation Association (IBPSA) and our publisher Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by International Building Performance Simulation Association (IBPSA) and our publisher Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. International Building Performance Simulation Association (IBPSA) and our publisher Taylor & Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to, or arising out of the use of the Content. RG Journal Impact: 2.14 * *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 2018 / 2019 2.14 2017 2.10 2016 2.66 2015 2.36 2014 2.55 2013 3.05 2012 1.85 2011 1.69 2010 1.12 2009 0.61 Journal of Building Performance Simulation (JBPS) Additional details Cited half-life 3.50 Immediacy index 0.66 Eigenfactor 0.00 Article influence 0.61 Other titles Journal of building performance simulation ISSN 1940-1493 OCLC 173313893 Material type Periodical, Internet resource Document type Journal / Magazine / Newspaper, Internet Resource Journal of Building Performance Simulation (JBPS) details SJR

Peer review represents the primary mechanism used by funding agencies to allocate financial support and by journals to select manuscripts for publication, yet recent Cochrane reviews determined literature on peer review best practice is sparse. Key to improving the process are reduction of inherent vulnerability to high degree of randomness and, from an economic perspective, limiting both the substantial indirect costs related to reviewer time invested and direct administrative costs to funding agencies, publishers and research institutions. Use of additional reviewers per application may increase reliability and decision consistency, but adds to overall cost and burden. The optimal number of reviewers per application, while not known, is thought to vary with accuracy of judges or evaluation methods. Here I use bootstrapping of replicated peer review data from a Post-doctoral Fellowships competition to show that five reviewers per application represents a practical optimum which avoids large random effects evident when fewer reviewers are used, a point where additional reviewers at increasing cost provides only diminishing incremental gains in chance-corrected consistency of decision outcomes. Random effects were most evident in the relative mid-range of competitiveness. Results support aggressive high- and low-end stratification or triaging of applications for subsequent stages of review, with the proportion and set of mid-range submissions to be retained for further consideration being dependent on overall success rate.

International Journal of Building Performance Simulation Impact Factor 2024-2025 - ResearchHelpDesk - The Journal of Building Performance Simulation (JBPS) aims to make a substantial and lasting contribution to the international building community by supporting our authors and the high-quality, original research they submit. The journal also offers a forum for original review papers and researched case studies. JBPS welcome building performance simulation contributions that explore the following topics related to buildings and communities: Theoretical aspects related to modelling and simulating the physical processes (thermal, airflow, moisture, lighting, acoustics). Theoretical aspects related to modelling and simulating conventional and innovative energy conversion, storage, distribution, and control systems. Theoretical aspects related to occupants, weather data, and other boundary conditions. Methods and algorithms for optimizing the performance of buildings and communities and the systems which service them, including interaction with the electrical grid. Uncertainty, sensitivity analysis, and calibration. Methods and algorithms for validating models and for verifying solution methods and tools. Development and validation of controls-oriented models that are appropriate for model predictive control and/or automated fault detection and diagnostics. Techniques for educating and training tool users. Software development techniques and interoperability issues with direct applicability to building performance simulation. Case studies involving the application of building performance simulation for any stage of the design, construction, commissioning, operation, or management of buildings and the systems which service them are welcomed if they include validation or aspects that make a novel contribution to the BPS knowledge base. The following topics are outside the journal's scope and will not be considered: Case studies involving the routine application of commercially available building performance simulation tools that do not include validation or aspects that make a novel contribution to the knowledge base. The structural performance of buildings and the durability of building components. Studies focused on the performance of buildings and the systems that serve them, rather than on modelling and simulation. The Journal of Building Performance Simulation (JBPS) Journal operates a double-blind peer review and all submissions are to be made online using the JBPS ScholarOne site. For more information on contributing a manuscript visit our Instructions for Authors page. Society information Journal of Building Performance Simulation is the Official Journal of the International Building Performance Simulation Association (IBPSA). Members of IBPSA can receive an individual print subscription at a special society members rate. Please see the pricing or subscribe page for details. (JBPS) Journal information Journal of Building Performance Simulation is abstracted and indexed by: British Library Inside, Cambridge Scientific Abstracts, EBSCO Databases and Scopus. International Building Performance Simulation Association (IBPSA) and our publisher Taylor & Francis make every effort to ensure the accuracy of all the information (the "Content") contained in our publications. However, International Building Performance Simulation Association (IBPSA) and our publisher Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by International Building Performance Simulation Association (IBPSA) and our publisher Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. International Building Performance Simulation Association (IBPSA) and our publisher Taylor & Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to, or arising out of the use of the Content. RG Journal Impact: 2.14 * *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 2018 / 2019 2.14 2017 2.10 2016 2.66 2015 2.36 2014 2.55 2013 3.05 2012 1.85 2011 1.69 2010 1.12 2009 0.61 Journal of Building Performance Simulation (JBPS) Additional details Cited half-life 3.50 Immediacy index 0.66 Eigenfactor 0.00 Article influence 0.61 Other titles Journal of building performance simulation ISSN 1940-1493 OCLC 173313893 Material type Periodical, Internet resource Document type Journal / Magazine / Newspaper, Internet Resource Journal of Building Performance Simulation (JBPS) details SJR

Objectives: A rapidly developing scenario like a pandemic requires the prompt production of high-quality systematic reviews, which can be automated using artificial intelligence (AI) techniques. We evaluated the application of AI tools in COVID-19 evidence syntheses. Study design: After prospective registration of the review protocol, we automated the download of all open-access COVID-19 systematic reviews in the COVID-19 Living Overview of Evidence database, indexed them for AI-related keywords, and located those that used AI tools. We compared their journals’ JCR Impact Factor, citations per month, screening workloads, completion times (from pre-registration to preprint or submission to a journal) and AMSTAR-2 methodology assessments (maximum score 13 points) with a set of publication date matched control reviews without AI. Results: Of the 3999 COVID-19 reviews, 28 (0.7%, 95% CI 0.47-1.03%) made use of AI. On average, compared to controls (n=64), AI reviews were published in journals...