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15,733 results for “article”
A Short SPIRIT Checklist for Peer Reviewers to Improve the Reporting Quality in Published Articles (SPIRIT-PR)
ClinicalTrials.gov study NCT05820984. IPD Sharing: YES. Countries: 1. Publications: 1.
Investigate the Exposure to Selected Smoke Constituents in Smokers Switching to Distillation Based Smoking Article
ClinicalTrials.gov study NCT00812279. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Data from the article: Narrative Risk Communication as a Lingua Franca for Environmental Hazard Preparation
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Velocity, density and energy budget statistics from the article: Validation and application of the lattice Boltzmann algorithm for a turbulent immiscible Rayleigh-Taylor system
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Data from: Symposium article: Which line to follow? the utility of different line-fitting methods to capture the mechanism of morphological scaling
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Demographic analysis for article Hurricane-induced demographic changes in a nonhuman primate population
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Digital research materials of spectral data for the article: [3+2]-Cycloaddition of azomethine ylides to 5-methylidene-3-aryl-2-сhalcogen-imidazolones: Access to dispiro indolinone-pyrrolidine-imidazolones
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Data for the article: Trophic niche partitioning between two prey and their incidental predators revealed various threats for an endangered species
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The clinical impact of high-profile animal-based research reported in the UK national press: a detailed discussion of articles from 1995, and full search results from the Nexis database
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Phenological data for the article: Phenotypic plasticity drives phenological changes in a Mediterranean blue tit population
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Data from: Exploring media representation of the exotic pet trade, with a focus on welfare: Taxonomic, framing, and language biases in peer-reviewed publications and newspaper articles
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Supplementary material of the article “Elevation patterns and critical environmental drivers of the taxonomic, functional and phylogenetic diversity of small mammals in a karst mountain area”.
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Data for the article: Trophic positions of soil microarthropods in forests increase with elevation, but energy channels remain unchanged
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Processed data file for article "Implications of the iron oxide phase transition on the interiors of rocky exoplanets"
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Data from: Gender disparity in physician authorship among commentary articles in high impact medical journals
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Data of top 50 most cited articles about COVID-19 and the complications of COVID-19
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Supplementary data for article: Central insulin modulates dopamine signaling in the human striatum
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A phononic crystal coupled to a transmission line via an artificial atom. Experimental data for the article figures
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Data for article: Normative drift and self-correction and self-regulation in scholarly publishing: The case of scholarly books published by academics at Makerere University
<p>University academics face multiple pressures to publish. These pressures emanate from contexts with different, often competing, social norms which result in academics publishing for reasons that may run counter to accepted scientific practice. This paper asks what decisions are being taken by academics when it comes to their choice of scholarly book publisher. An analysis of books selected from more than 2,500 self-reported scholarly publications produced by academics at Makerere University in Uganda from 2011 to 2017, reveals that 31 scholarly books were published. Of these books, more than half (54%) were published by publishers that do not follow accepted scholarly publishing practice. Findings also show that there was a sharp decline in books published with suspect publishers in the second half of the seven-year period. The article discusses possible reasons for the selection of suspect publishers and considers four factors that may account for the observable decline: (1) a cyclical downturn; (2) improved research management and reporting; (3) explication of the norms of science; and (4) self-correction.</p> <p><strong>METHODS</strong></p> <p>The specific interest of this study is the publication of scholarly books by academics at Makerere University. </p> <p>The sources of the publications data were the lists of research outputs published in Makerere University’s annual reports from 2011 to 2017. Digital copies of the annual reports in PDF format were downloaded from the university’s website. Data were scraped from the annual report PDFs by exporting the publication lists from the PDFs to MSWord, removing unnecessary line breaks and spacing to create a single publication per line, and copying the publication lists into MSExcel for cleaning and analysis. Data were cleaned to remove (1) duplicate entries (e.g. identical publications in the same annual report or a publication listed as ‘under review’ or ‘in press’ in one year and listed again as a publication in a following year); (2) publications listed as ‘submitted’, unpublished masters and PhD theses, speeches, lectures, responses or retractions; (3) incomplete entries (e.g. no article, book or journal title); and (4) publications prior to 2011 (e.g. a 2008 publication listed in the 2011 annual report).</p> <p>The cleaned data were then coded for ‘year of publication’ (2011 to 2017 inclusive), ‘college’ (any of the colleges at Makerere University to which the authors were affiliated), and ‘publication type’ (book chapter, journal article, edited volume, working paper, policy brief, monograph, conference paper, textbook, report, popular article, poster presentation, newsletter, essay, catalogue, poetry, handbook). Books or parts of books (i.e. ‘book chapter’, ‘edited volume’, ‘monograph’, ‘textbook’, ‘catalogue’, ‘poetry’ and ‘handbook’) were further coded for ‘publisher’ (name); ‘publisher location’ (city, country as indicated on the imprint page of the publication); and ‘URL’ (online reference to publisher or publication). In some cases, publications were listed by type in the annual reports. Where publication lists were not presented in this way, indicators such as ‘journal of’, ‘volume’, ‘issue’ and ISSNs were used to identify journals; conference names, ‘proceedings of’, dates and cities were used to identify conference papers and presentations; ‘news’, ‘magazine’, ISSNs and the absence of ‘journal of’ were used to identify periodicals; and place of publication, publisher and ISBNs were used to identify books. Where these indicators were insufficient to determine a publication type, an online search was done to find the missing data. </p> <p>A limitation of the adopted method is that it relies on self-reporting by the university colleges and the list can therefore not be assumed to be comprehensive. Without knowledge of the reporting guidelines, it is also not possible to know whether all colleges and schools used the same criteria when selecting what to submit for reporting purposes. For example, some colleges may have decided to include working papers, policy briefs or papers presented at conferences, while others may have decided not to do so. </p>
Data of the article "Journal research data sharing policies: a study of highly-cited journals in neuroscience, physics, and operations research"
<p>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.</p> <p>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. </p> <p>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. </p> <p>‘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 <em>specific data types</em> 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.</p> <p>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.<em> </em></p> <p> </p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.