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354 results for “data accessibility”
Raw data: Specialized metabolites accumulation pattern in buckwheat is strongly influenced by accession choice and co-existing weeds
<p>Screening suitable allelopathic crops and crop genotypes that are competitive with weeds can be a sustainable weed control strategy to reduce the massive use of herbicides. In this study, three accessions of common buckwheat <em>Fagopyrum esculentum</em> Moench. (Gema, Kora, and Eva) and one of Tartary buckwheat <em>Fagopyrum tataricum</em> Gaertn. (PI481671) were screened against the germination and growth of the herbicide-resistant weeds <em>Lolium rigidum </em>Gaud. and <em>Portulaca oleracea</em> L. The chemical profile of the four buckwheat accessions was characterised in their shoots, roots, and root exudates in order to know more about their ability to sustainably manage weeds and the relation of this ability with the polyphenol accumulation and exudation from buckwheat plants. Our results show that different buckwheat genotypes may have different capacities to produce and exude several types of specialized metabolites, which lead to a wide range of allelopathic and defence functions in the agroecosystem to sustainably manage the growing weeds in their vicinity. The ability of the different buckwheat accessions to suppress weeds was accession-dependent without differences between species, as the common (Eva, Gema, and Kora) and Tartary (PI481671) accessions did not show any species-dependent pattern in their ability to control the germination and growth of the target weeds. Finally, Gema appeared to be the most promising accession to be evaluated in organic farming due to its capacity to sustainably control target weeds while stimulating the root growth of buckwheat plants.</p>
ACCESS-OM2 1° resolution global repeat decade full forcing interannual simulation data for 1972-2018
<p>This data set contains the <strong>full forcing</strong> interannual simulation output from the global ocean-sea ice model ACCESS-OM2 in the 1° horizontal configuration over the period 1972-2018.</p> <p>This simulation was branched off from the repeat decade forcing spin-up and alongside the control simulation (see light blue and black lines in Fig. 1c in the publication linked below).</p> <p>The control simulation output can be found here: https://zenodo.org/record/8339578 The output here as well as in the control simulation is saved in sets of ten years (output200, output201, ...) in the ocean/ and ice/ folders as netcdf files.</p> <p>The last output folder contains the data for 2012-2018 with the last four years of this output folder (output204) are again the 1972-1975 period and should be omitted from any analysis.</p> <p>For more information on the spin-up and the model configuration, see the Methods section and Fig. 1 in Huguenin, M.F., Holmes, R.M. & England, M.H. Drivers and distribution of global ocean heat uptake over the last half century. <em>Nat Commun</em> 13, 4921 (2022). https://doi.org/10.1038/s41467-022-32540-51</p> <p> </p>
Data for Research Assessment in the Transition to Open Science. 2019 EUA Open Science and Access Survey Results
<p>This database refers to the data collected by the European University Association (EUA) for its Open Science and Access Survey 2019, which gathered responses from universities and higher education institutions across Europe. The full report published by the association is available at <a href="https://eua.eu/resources/publications/888:research-assessment-in-the-transition-to-open-science.html">https://eua.eu/resources/publications/888:research-assessment-in-the-transition-to-open-science.html</a>.</p> <p>The data included in this database refers only to those universities and higher education institutions that accepted their data to be available in open access (n=174). All information that could lead to the identification of individual universities and higher education institutions was removed from the database (cf. cells highlighted in red). The following files are available:</p> <ul> <li>2019 EUA Open Science and Access Survey</li> <li>Database in the following formats: .xlsx (Microsoft Excel)</li> <li>Survey Codebook: includes information on all the variables and their coding.</li> </ul>
Data_supplemental Figure 3_11β-Hydroxysteroid dehydrogenases control access of 7β,27-dihydroxycholesterol to retinoid-related orphan receptor γ
<p>Data of supplemental figure 3 from 11β-Hydroxysteroid dehydrogenases control access of 7β,27-dihydroxycholesterol to retinoid-related orphan receptor γ</p> <p>Dataset (doi:10.1194/jlr.M092908) contains the original figure as PNG-format (10.1194_jlr.M092908_Fig. S3). Corresponding raw data obtained from liquid scintillation analysis provided as three files in CSV format (31003A-179400_DATE_SK_KB_27Oxysterol_11_6_1-3). All further experiment related information and subsequent data analysis provided as meta-data-file (31003A-179400_DATE_SK_KB_27Oxysterol_11_6_M) as TXT format</p>
Data_Figure 8_11β-Hydroxysteroid dehydrogenases control access of 7β,27-dihydroxycholesterol to retinoid-related orphan receptor γ
<p>Data of figure 8 from 11β-Hydroxysteroid dehydrogenases control access of 7β,27-dihydroxycholesterol to retinoid-related orphan receptor γ</p> <p>Dataset (doi:10.1194/jlr.M092908) contains the original figure as TIF-format (10.1194_jlr.M092908_Fig. 8). Corresponding raw data obtained from luminescence measurement analysis (Spectra Max L, Molecular devices, Serial Nr. LU01049) provided as eight files in CSV format (31003A-179400_DATE_SI_KB_27Oxysterol_18_1-2_1-4). All further experiment related information and subsequent data analysis provided as two meta-data-files (31003A-179400_DATE_SI_KB_27Oxysterol_18_1-2_M) as TXT format.</p>
Data_Figure 6_11β-Hydroxysteroid dehydrogenases control access of 7β,27-dihydroxycholesterol to retinoid-related orphan receptor γ
<p>Data of figure 6 from 11β-Hydroxysteroid dehydrogenases control access of 7β,27-dihydroxycholesterol to retinoid-related orphan receptor γ</p> <p>Dataset (doi:10.1194/jlr.M092908) contains the original figure as TIF-format (10.1194_jlr.M092908_Fig. 6). Corresponding raw data obtained from docking calculation analysis and calculations provided as four files in TXT format (31003A 179400_DATE_KB_27Oxysterol_19_1-4_1). All further experiment related information and subsequent data analysis provided as four meta-data-files (31003A-179400_DATE_KB_27Oxysterol_19_1-4_M) as TXT format.</p>
Data_Figure 5_11β-Hydroxysteroid dehydrogenases control access of 7β,27-dihydroxycholesterol to retinoid-related orphan receptor γ
<p>Data of figure 5 from 11β-Hydroxysteroid dehydrogenases control access of 7β,27-dihydroxycholesterol to retinoid-related orphan receptor γ</p> <p>Dataset (doi:10.1194/jlr.M092908) contains the original figure as TIF-format (10.1194_jlr.M092908_Fig. 5). Corresponding raw data obtained from liquid scintillation analysis provided as seven files in CSV format (31003A-179400_DATE_SK_KB_27Oxysterol_11_4-5_1-4). All further experiment related information and subsequent data analysis provided as two meta-data-file: (31003A-179400_DATE_SK_KB_27Oxysterol_11_4-5_M_1,) as TXT format.</p>
Data_Figure 1_11β-Hydroxysteroid dehydrogenases control access of 7β,27-dihydroxycholesterol to retinoid-related orphan receptor γ
<p>Data of figure 1 from 11β-Hydroxysteroid dehydrogenases control access of 7β,27-dihydroxycholesterol to retinoid-related orphan receptor γ</p> <p>Dataset (doi:10.1194/jlr.M092908) contains the original figure as TIF-format (10.1194_jlr.M092908_Fig. 1). Corresponding raw data obtained from LC-MS/MS analysis provided three files in CSV format (31003A-179400_DATE_KB_27Oxysterol_4_1_1-3). All further experiment related information and subsequent data analysis provided as two meta-data-files as TXT format and PDF format.</p>
Ancient Greek Literature for Advanced Data Processing: A Text Fabric Representation of Open Access Texts in TEI XML
<p>This data set contains a full conversion of Greek texts available in the Perseus Digital Library and the Open Greek and Latin Project to the Text Fabric data format. The main advantage of the Text Fabric datatype over the original TEI XML format is that it utilizes a strict separation of text and annotation in a flat data structure. At the same time, it permits multiple distinct formats of the same text as well as an unlimited depth of (embedded) annotations. Because of its flat data structure, it facilitates easy and clean procedures to analyze, transform, and enrich the available data. Many of these processes are very difficult to conduct while departing from the hierarchically organized XML tree representation.</p>
Supplementary data for a study of Open Access Article Processing Charges - 2014
<p>Article Processing Charges levied by a set of Gold Open Access journals and hybrid journals in 2014, as collected from the publishers' web sites. Supplementary data to 10.2314/CERN/C26P.W9DT</p>
ROARMAP Open Access Policy data
<p>This data is a dump from ROARMAP [http://roarmap.eprints.org/] taken in June 2015.</p> <p>ROARMAP is the Registry of Open Access Repository Mandates and Policies, a searchable international registry charting the growth of open access mandates and policies adopted by universities, research institutions and research funders that require or request their researchers to provide open access to their peer-reviewed research article output by depositing it in an open access repository.</p> <p>A number of fields have been added including country names, repository urls, continent etc.</p> <p>The data is being used for a series of data visualisations [http://pasteur4oa-dataviz.okfn.org/] for the PATEUR4OA Project [http://pasteur4oa.eu/].</p> <p> </p> <p>PASTEUR4OA (Open Access Policy Alignment Strategies for European Union Research) aims to support the European Commission’s Recommendation to Member States of July 2012 that they develop and implement policies to ensure Open Access to all outputs from publicly-funded research. </p> <p>PASTEUR4OA will help develop and/or reinforce open access strategies and policies at the national level and facilitate their coordination among all Member States. It will build a network of centres of expertise in Member States that will develop a coordinated and collaborative programme of activities in support of policymaking at the national level under the direction of project partners.</p>
ROARMAP Open Access Policy data
<p>This data is a dump from ROARMAP [http://roarmap.eprints.org/] taken on 24th August 2015.</p> <p>ROARMAP is the Registry of Open Access Repository Mandates and Policies, a searchable international registry charting the growth of open access mandates and policies adopted by universities, research institutions and research funders that require or request their researchers to provide open access to their peer-reviewed research article output by depositing it in an open access repository.</p> <p>A number of fields have been added including country names, repository urls, continent etc.</p> <p>The data is being used for a series of data visualisations [http://pasteur4oa-dataviz.okfn.org/] for the PATEUR4OA Project [http://pasteur4oa.eu/].</p> <p> </p> <p>PASTEUR4OA (Open Access Policy Alignment Strategies for European Union Research) aims to support the European Commission’s Recommendation to Member States of July 2012 that they develop and implement policies to ensure Open Access to all outputs from publicly-funded research. </p> <p>PASTEUR4OA will help develop and/or reinforce open access strategies and policies at the national level and facilitate their coordination among all Member States. It will build a network of centres of expertise in Member States that will develop a coordinated and collaborative programme of activities in support of policymaking at the national level under the direction of project partners.</p>
Data on which institutions have access to a 1949 paper, paywalled at Taylor & Francis
<p>This is a dataset collecting various tweets from twitter, sent to @rmounce that report on whether various institutional library affiliations allow the user to download the full text of this paywalled article, that is otherwise only accessible via a payment of $38 + tax:<br /> <br /> <em>Hincks, W. D. 1949. IV.—systematic and synonymic notes on passalidæ (col.). Annals and Magazine of Natural History 2:56-64</em> http://dx.doi.org/10.1080/00222934908653958</p> <p>From the data given, it appears that 81 institutions do not have subscription access to this paper. 11 institutions do have subscription access to this paper.</p> <p>Of the data from 41 UK-based institutions, only 3 have subscription access to this paper, namely: Cambridge, Oxford & Glasgow.</p> <p>Many thanks to all those who took part in this survey and/or spread it around twitter.<br /> <br /> A blog post was written on the basis of this informal survey data: <a href="http://rossmounce.co.uk/2015/09/16/who-actually-has-access-to-paywalled-research/">http://rossmounce.co.uk/2015/09/16/who-actually-has-access-to-paywalled-research/</a></p> <p> </p>
SNSF Open Access Monitoring: Data Publications 2013-2014
<p>This spreadsheet contains supplemental data to the report: "Open Access to Publications: SNSF monitoring report 2013 - 2015" (http://doi.org/10.5281/zenodo.584131), where it was found that at least 39% of publications out of SNSF funded grants are either Gold or Green Open Access.</p> <p>The initial data is based on the reported publications to the Swiss National Science Foundation via the grant administration system mySNF as of <strong>11. September 2015.</strong> This data is also available as open data on p3.snf.ch. Please be aware, that grant beneficiaries can update the metadata to the reported publications, including the Open Access status anytime during and after the end of a grant.</p> <p>Prior to validation, the actual publication date of publications with “in press/accepted” status was verified insofar as possible, and the details updated (approx. 3'000 publications). For further processing only publications with <strong>publication date 2013-2014</strong> were considered. Publications with the status “in press/accepted” status were excluded. Duplicates, i.e. publications cited as output for more than one project (approx. 2'500) are also filtered out. Where identifiable as such, pure abstracts (e.g. in journal supplements), working papers and pre-prints were also excluded.</p> <p><br> The basic goal was to locate a DOI for the publication and update the metadata. 78% of the 17'420 publications scrutinised have in the meantime been assigned a DOI. Using the DOI and the linked metadata available in CrossRef, unique searches could be performed in additional sources such as DOAJ, Pubmed and Pubmed Central, OpenAIRE (repository aggregator) and ADS (Astrophysics Data System). After the initial search for open access full text in these external sources, a search was made in Google Scholar using the DOI of the remaining publications still to be validated and links to any open access full text were extracted. Where even the Google Scholar search failed to turn up open access full text, the status was set to “closed access”. The OA status of 4'212 publications from the period 2013 to 2014 remained unclear, but it is more likely that they are in closed rather than open access mode.</p>
Data for "Open Access impact on citations: a case study"
<p>This dataset is a list of 347 papers published in 2010 and retrieved from the Web of Science, Scopus and Google Scholar. For each paper, the number of citations and the citation date(s) have been collected. If the full-text is available online, the date of "liberation" and the URL of the file have been retrieved as well. The objective was to assess the impact of Open access on citation rate and more particularly the impact before and after full-text "liberation".</p> <p> </p>
Introduction to Ancient Metagenomics Textbook (Edition 2025): Accessing Ancient Metagenomic Data
<p>Data and conda software environment file for the chapter 'Accessing Ancient Metagenomic<br> Data' of the SPAAM Community's textbook: Introduction to Ancient Metagenomics (https://www.spaam-community.org/intro-to-ancient-metagenomics-book).</p>
Data for: Making 1H-1H couplings more accessible and accurate with selective 2DJ NMR experiments aided by 13C satellites
<p><sup>1</sup>H-<sup>1</sup>H coupling constants are one of the primary sources of information for NMR structural analysis. Several selective 2DJ experiments have been proposed that allow their individual measurement at pure shift resolution. However, all these experiments fail in the not uncommon case when coupled protons have very close chemical shifts. Firstly, the coupling between protons with overlapping multiplets is inaccessible due to the inability of a frequency-selective pulse to invert just one of them. Secondly, the strong coupling condition affects the accuracy of coupling measurements involving third spins. These shortcomings impose a limit on the effectiveness of state-of-the-art experiments, such as G-SERF or PSYCHEDELIC. Here, we introduce two new and complementary selective 2DJ experiments that we coin SERFBIRD and SATASERF. These experiments overcome the aforementioned issues by utilizing the <sup>13</sup>C satellite signals at natural isotope abundance, which resolve the chemical shift degeneracy. We demonstrate the utility of these experiments on the tetrasaccharide stachyose and the challenging case of norcamphor, for the latter achieving measurement of all <em>J</em><sub>HH</sub> couplings while only few were accessible with PSYCHEDELIC. The new experiments are applicable to any organic compound and will prove valuable for configurational and conformational analyses.</p> <p>This deposit contains Bruker pulse sequences of the SERFBIRD and SATASERF experiments, and the Bruker NMR experimental data. See the readme.pdf file for an overview of the latter.</p>
Estimation of forest height and biomass from open-access multi-sensor satellite imagery and GEDI Lidar data: high-resolution maps of metropolitan France
<p>Maps of forest height, aboveground biomass (AGB)* and volume (VOL)* at 10 m spatial resolution for the year 2020 on France. </p> <p>* AGB and Volume maps are available on request.</p> <p>The methodology and validation of the maps are presented here: https://hal.science/hal-04249151</p> <p>Please cite :</p> <p>David Morin, Milena Planells, Stéphane Mermoz, Florian Mouret. Estimation of forest height and biomass from open-access multi-sensor satellite imagery and GEDI Lidar data: high-resolution maps of metropolitan France. 2023. hal-04249151</p>
Accession passport and sequence data
<p>Accession passport data corresponding to <em>An2-like</em> and <em>Ant1 </em>sequence data.</p>
Data from: Pitfalls and pointers: an accessible guide to marker gene amplicon sequencing in ecological applications
<p>Next Generation Sequencing (NGS) is a powerful tool that has been rapidly adopted by many ecologists studying microbial communities. Despite the exciting demonstration of NGS technology as a tool for ecological research, cryptic pitfalls inherent to its use can obscure correct interpretation of NGS data. Here, we provide an accessible overview of a NGS process that uses marker gene amplicon sequences (MGAS) that will allow scientists, particularly community ecologists, to make appropriate methodological choices and understand limits on inference about community composition and diversity that can be drawn from MGAS data.</p> <p>We describe the MGAS pipeline, focusing specifically on cryptic sources of variation that have received less emphasis in the ecological literature, but which may substantially impact inference about microbial community diversity and composition. By simulating communities from published microbiome data, we demonstrate how these sources of variation can generate inaccurate or misleading patterns.</p> <p>We specifically highlight sample dilution without researcher awareness and lane-to-lane variability, two cryptic sources of variation arising during the MGAS pipeline. These sources of variation affect estimates of species presence and relative abundance, particularly for species with moderate to low abundances. Each of these sources of bias can lead to errors in the estimation of both absolute and relative abundance within, and turnover among, microbial communities.</p> <p>Awareness and understanding of what happens and, specifically, why it happens during MGAS generation is key to generating a strong data set and building a robust community matrix. Requesting sample dilution information from the sequencing center, including technical replicates across sequencing lanes, and understanding how sampling intensity and community taxa distribution patterns shape the measurement of community richness, evenness, and diversity are critical for drawing correct ecological inferences using MGAS data.</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.