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761 results for “data journal”
Figure 2 from: Kress W, Knapp S, Stoev P, Penev L (2012) On the front line of modern data-management and Open Access publishing: Two years of PhytoKeys – the fastest growing journal in plant systematics. PhytoKeys 19: 1-8. https://doi.org/10.3897/phytokeys.19.4501
Figure 2 - Taxonomic distribution by family of the published nomenclatural novelties in PhytoKeys.
PS-BBICS: Pulse Stretching Bulk Built-in Current Sensor for On-chip Measurement of Single Event Transients (raw data from journal article)
<p>This upload contains raw data from the manuscript "PS-BBICS: Pulse Stretching Bulk Built-in Current Sensor for On-chip Measurement of Single Event Transients". The manuscript was published in Microelectronics Reliability, vol. 138, 2022.; DOI: https://doi.org/10.1016/j.microrel.2022.114726</p> <p>The upload consists of .pdf file of the manuscript and .opj files with raw data related to the figures in the manuscript. </p> <p>This work was supported in part by the European Union’s Horizon 2020 research and innovation programme (Grant No. 857558).</p>
A Design Concept for Radiation Hardened RADFET Readout System for Space Applications (raw data from journal article)
<p>This upload contains raw data from the manuscript "A Design Concept for Radiation Hardened RADFET Readout System for Space Applications". The manuscript was published in Microprocessors and Microsystems, vol. 90, 2022.; DOI: 10.1016/j.micpro.2022.104486</p> <p>The upload consists of .pdf file of the manuscript and .opj files with raw data related to the figures in the manuscript. </p> <p>This work was supported in part by the European Union’s Horizon 2020 research and innovation programme (Grant No. 857558).</p>
Fading of pMOS dosimeters over a long period of time (raw data from journal article)
<p>This upload contains raw data from the manuscript "Fading of pMOS dosimeters over a long period of time". The manuscript was published in the Micro & Nano Letters, 2022; DOI: https://doi.org/10.1049/mna2.12119</p> <p>The upload consists of a .pdf file of the manuscript and .opj files with raw data related to the figures in the manuscript. </p> <p>This work was partly supported by the European Union’s Horizon 2020 research and innovation programme (Grant No. 857558) and the Ministry of Education, Science and Technology Development of the Republic of Serbia (Project No. 43011).</p>
Dataset for journal article "Understanding the timeliness of automated data feeds is important for determining their usability for large-scale surveillance of healthcare-associated infections"
<p>This dataset was used for the journal article "Understanding the timeliness of automated data feeds is important for determining their usability for large-scale surveillance of healthcare-associated infections".</p> <p>For a selection of "activity dates", it contains the number of records available centrally at UKHSA on each day after the specified activity date, from a selection of data feeds that could potentially be used for national surveillance of healthcare-associated infections in England.</p> <p>The associated R code is available from https://github.com/oxfordmmm/ukhsa-datafeeds-timeliness-anon</p>
Data from: Comparison of methodological quality of positive versus negative comparative studies published in Indian medical journals: a systematic review
Open the record for dataset details and reuse information.
Data from: Imbalance in individual researcher’s peer review activities quantified for four British Ecological Society Journals, 2003-2010
Open the record for dataset details and reuse information.
Data to accompany "Riparian buffer zones in production forests create unequal costs among forest owners" in European Journal of Forest Research
<p>This is the data and analysis code to accompany the article "Riparian buffer zones in production forests create unequal costs among forest owners" in European Journal of Forest Research.</p> <p> </p> <p>The repository includes the following files:</p> <ul> <li>"stand_map_buffers.shp" and shapefile associated files. This is the geographical information for the forest map that was analyzed in Heureka.</li> <li>"stand_register_buffers.csv". This is the forest data that is needed to initialize Heureka.</li> <li>"stand_map_buf_real_prop.csv". This is the list of properties that each stand belongs to in the cadastral map of properties of Hässleholm.</li> <li>"alldata_nobuffers_1p_clim.csv", "alldata_buffers_1p_clim.csv", These are the Heureka results for the simulations with and without buffers with a 1% discount rate</li> <li>"alldata_nobuffers_2p_clim.csv", "alldata_buffers_2p_clim.csv", These are the Heureka results for the simulations with and without buffers with a 2% discount rate </li> <li>"alldata_nobuffers_3p_clim.csv", "alldata_buffers_3p_clim.csv", These are the Heureka results for the simulations with and without buffers with a 3% discount rate</li> <li> "code_for_publication.r". This is the R-code that was used for analysis and visualization after the heureka simulations.</li> <li>"hassleholm_buffers.zip" includes all Heureka PlanWise project files needed to run the simulations. </li> <li>"Max NPV with even Flow.hops" is the optimization model used in Heureka to select the management program for each forest stand.</li> </ul> <p> </p>
Data set for journal paper 'Mode I fracture of thick adhesively bonded GFRP composite joints for wind turbine rotor blades' volume2
<p>The description in the read me file is updated here. </p><p>This data set includes all the related raw data about the journal paper 'Mode I fracture of thick adhesively bonded GFRP composite joints for wind turbine rotor blades'<br>1.The raw data of thick adhesive double cantilever beam tests under quasi-static loading, such as the DIC pictures and the load-displacement curve. The strain energy release curve and load-displacement prediction curve are also included. All the data excepts the DIC pictures is within one Excel file for each sample.<br>2.Data for tensile testing (composite and epoxy adhesive).<br>Volume 1 includes the data of UN1,UN2,GN2 and GL2-L.<br>Volume 2 includes the data of 5-GL2-M SAMPLE1.<br>Volume 3 includes the data of 5-GL2-M SAMPLE2 AND 3.<br>Volume 4 includes the data of 5-GL2-M SAMPLE4 and 6-GL2-H SAMPLE 1 and 2.<br>Volume 5 includes the data of 6-GL2-H SAMPLE3 and 4.<br>Volume 6 includes the tensile testing data. </p>
Data set for journal paper 'Mode I fracture of thick adhesively bonded GFRP composite joints for wind turbine rotor blades' volume1
<p>The description in the read me file is updated here. </p><p>This data set includes all the related raw data about the journal paper 'Mode I fracture of thick adhesively bonded GFRP composite joints for wind turbine rotor blades'<br>1.The raw data of thick adhesive double cantilever beam tests under quasi-static loading, such as the DIC pictures and the load-displacement curve. The strain energy release curve and load-displacement prediction curve are also included. All the data excepts the DIC pictures is within one Excel file for each sample.<br>2.Data for tensile testing (composite and epoxy adhesive).<br>Volume 1 includes the data of UN1,UN2,GN2 and GL2-L.<br>Volume 2 includes the data of 5-GL2-M SAMPLE1.<br>Volume 3 includes the data of 5-GL2-M SAMPLE2 AND 3.<br>Volume 4 includes the data of 5-GL2-M SAMPLE4 and 6-GL2-H SAMPLE 1 and 2.<br>Volume 5 includes the data of 6-GL2-H SAMPLE3 and 4.<br>Volume 6 includes the tensile testing data. </p>
Data set for journal paper 'Mode I fracture of thick adhesively bonded GFRP composite joints for wind turbine rotor blades' volume6
<p>The description in the read me file is updated here. </p><p>This data set includes all the related raw data about the journal paper 'Mode I fracture of thick adhesively bonded GFRP composite joints for wind turbine rotor blades'<br>1.The raw data of thick adhesive double cantilever beam tests under quasi-static loading, such as the DIC pictures and the load-displacement curve. The strain energy release curve and load-displacement prediction curve are also included. All the data excepts the DIC pictures is within one Excel file for each sample.<br>2.Data for tensile testing (composite and epoxy adhesive).<br>Volume 1 includes the data of UN1,UN2,GN2 and GL2-L.<br>Volume 2 includes the data of 5-GL2-M SAMPLE1.<br>Volume 3 includes the data of 5-GL2-M SAMPLE2 AND 3.<br>Volume 4 includes the data of 5-GL2-M SAMPLE4 and 6-GL2-H SAMPLE 1 and 2.<br>Volume 5 includes the data of 6-GL2-H SAMPLE3 and 4.<br>Volume 6 includes the tensile testing data. </p>
Data set for journal paper 'Mode I fracture of thick adhesively bonded GFRP composite joints for wind turbine rotor blades' volume4
<p>The description in the read me file is updated here. </p><p>This data set includes all the related raw data about the journal paper 'Mode I fracture of thick adhesively bonded GFRP composite joints for wind turbine rotor blades'<br>1.The raw data of thick adhesive double cantilever beam tests under quasi-static loading, such as the DIC pictures and the load-displacement curve. The strain energy release curve and load-displacement prediction curve are also included. All the data excepts the DIC pictures is within one Excel file for each sample.<br>2.Data for tensile testing (composite and epoxy adhesive).<br>Volume 1 includes the data of UN1,UN2,GN2 and GL2-L.<br>Volume 2 includes the data of 5-GL2-M SAMPLE1.<br>Volume 3 includes the data of 5-GL2-M SAMPLE2 AND 3.<br>Volume 4 includes the data of 5-GL2-M SAMPLE4 and 6-GL2-H SAMPLE 1 and 2.<br>Volume 5 includes the data of 6-GL2-H SAMPLE3 and 4.<br>Volume 6 includes the tensile testing data. </p>
Data set for journal paper 'Mode I fracture of thick adhesively bonded GFRP composite joints for wind turbine rotor blades' volume5
<p>The description in the read me file is updated here. </p><p>This data set includes all the related raw data about the journal paper 'Mode I fracture of thick adhesively bonded GFRP composite joints for wind turbine rotor blades'<br>1.The raw data of thick adhesive double cantilever beam tests under quasi-static loading, such as the DIC pictures and the load-displacement curve. The strain energy release curve and load-displacement prediction curve are also included. All the data excepts the DIC pictures is within one Excel file for each sample.<br>2.Data for tensile testing (composite and epoxy adhesive).<br>Volume 1 includes the data of UN1,UN2,GN2 and GL2-L.<br>Volume 2 includes the data of 5-GL2-M SAMPLE1.<br>Volume 3 includes the data of 5-GL2-M SAMPLE2 AND 3.<br>Volume 4 includes the data of 5-GL2-M SAMPLE4 and 6-GL2-H SAMPLE 1 and 2.<br>Volume 5 includes the data of 6-GL2-H SAMPLE3 and 4.<br>Volume 6 includes the tensile testing data. </p>
Data set for journal paper 'Mode I fracture of thick adhesively bonded GFRP composite joints for wind turbine rotor blades' volume3
<p>The description in the read me file is updated here. </p><p>This data set includes all the related raw data about the journal paper 'Mode I fracture of thick adhesively bonded GFRP composite joints for wind turbine rotor blades'<br>1.The raw data of thick adhesive double cantilever beam tests under quasi-static loading, such as the DIC pictures and the load-displacement curve. The strain energy release curve and load-displacement prediction curve are also included. All the data excepts the DIC pictures is within one Excel file for each sample.<br>2.Data for tensile testing (composite and epoxy adhesive).<br>Volume 1 includes the data of UN1,UN2,GN2 and GL2-L.<br>Volume 2 includes the data of 5-GL2-M SAMPLE1.<br>Volume 3 includes the data of 5-GL2-M SAMPLE2 AND 3.<br>Volume 4 includes the data of 5-GL2-M SAMPLE4 and 6-GL2-H SAMPLE 1 and 2.<br>Volume 5 includes the data of 6-GL2-H SAMPLE3 and 4.<br>Volume 6 includes the tensile testing data. </p>
Data set associated with submitted journal article.
<p>This is a data set associated with submitted journal article. At the moment this data is intended to be open to the reviewers for potential evaluation.</p>
Data Journals: A Survey - Tables
<p>This dataset groups all the tables supplementing the contents of the article "Data Journals: A Survey", which is going to be published by the <em>Journal of the Association for Information Science and Technology</em> (JASIST).</p> <p>Tables are published without header. Any details can be found in the article.</p> <p><strong>Abstract</strong></p> <p>Data occupy a key role in our information society. However, although the amount of published data continues to grow and terms like “data deluge” and “big data” today characterize numerous (research) initiatives, a lot of work is still needed in the direction of publishing data in order to make them effectively discoverable, available, and reusable by others. Several barriers hinder data publishing, from lack of attribution and rewards, vague citation practices, quality issues, to a rather general lack of data sharing culture. Lately, data journals came forward as a solution to overcome some of these barriers. In this study of more than 100 currently existing data journals, we describe the approaches they promote for description, availability, citation, quality and open access or datasets. We close by identifying ways to expand and strengthen the data journals approach as a means to actually promote datasets access and exploitation.</p>
Data from Faculty Survey about Journal Use
<p>Surveyed Faculty to determine what journals they thought were critical, useful, and prestigious. This is the slightly processed results from that survey.</p>
Data contained in "22-Kyr-Long Record Of Surface Faulting Along The Source Of The 30 October 2016 Earthquake (Central Apennines, Italy), From Integrated Paleoseismic Datasets" - Journal of Geophysical Research - Solid Earth - DOI: 10.1029/2019JB017757
<p>Data contained in “22-Kyr-Long Record Of Surface Faulting Along The Source Of The 30 October 2016 Earthquake (Central Apennines, Italy), From Integrated Paleoseismic Datasets” - Journal of Geophysical Research - Solid Earth - DOI: 10.1029/2019JB017757 by Cinti F.R.*, De Martini P.M.*, Pantosti D.*, Baize S.°, Smedile A.*, Villani F.*, Civico R.*, Pucci S.*, Lombardi A.M.*, Sapia V.*, Pizzimenti L.*, Caciagli M.*, Brunori C.A.*<br> * Istituto Nazionale di Geofisica e Vulcanologia, Italy<br> ° Institut de Radioprotection et de Sûreté Nucléaire, France</p>
Digital Accessibility of Life Science Data Portals and Journal Websites
<p>Enhancing the diversity and inclusion of the life sciences workforce has become an important problem as highlighted by many organizations in the US, including NIH, NHGRI, and NSF. People with visual impairments are one of the groups that face barriers to access to the biology workforce. To overcome this challenge, it is important to understand their current barriers in biological research and education. The most common assistive technology used by people with visual impairments is the screen reader (45.2%). However, multiple studies found that many websites largely fail to meet accessibility guidelines, making it challenging or even impossible for screen reader users to access existing resources. To help gain better insights into how well people with visual impairments can access existing biological resources, we evaluated the digital accessibility of two essential resources for data-driven studies—data portals and journal websites. Using an automated evaluation tool, we collected accessibility evaluation data for a large corpus of resources (<i>N</i>=3,943). In addition, we collected metadata of individual resources (e.g., geospatial, temporal, and impact score data) for a more insightful analysis. All datasets, as well as the entire source code, are available online on Zenodo and GitHub under a CC-BY and MIT license, respectively.</p>
Tableau sur 8 data journals
<p>A tabela analisa as características de 8 periodicos de dados (Data Journals)</p>
ScienceDex guides
Understand access before you commit
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.