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354 results for “data access”
Data from: Access to resources buffers against effects of current reproduction on future ability to provide care in a burying beetle
<p>Studies investigating the trade-off between current and future reproduction often find that increased allocation to current reproduction is associated with a reduction in the number or quality of future offspring. In species that provide parental care, this effect on future offspring may be mediated through a reduced future ability to provide care. Here, we test this idea in the burying beetle <em>Nicrophorus vespilloides</em>, a species in which parents shift the cost of reproduction towards future offspring and provide elaborate parental care. We manipulated brood size to alter the costs females experienced in association with current reproduction and measured the level of parental care during a subsequent breeding attempt. Given that these beetles breed on carcasses of small vertebrates, it is important to consider confounding effects due to benefits associated with resource access during breeding. We therefore manipulated access to carrion and measured the level of parental care during a subsequent breeding attempt. We found that females provided the same level of care regardless of previous brood size and resource access, suggesting that neither affected future ability to provide care. This may reflect that parents feed on carrion during breeding, which may buffer against any costs of previous breeding attempts. Our results show that increased allocation to current reproduction is not necessarily associated with a reduction in future ability to provide care. Nevertheless, this may reflect unique aspects of our study system, and we encourage future work on systems where parents do not have access to a rich resource during breeding.</p>
Raw data for the article "Copper-Catalyzed Alkynylation of Hydrazides: An Easy Access to Functionalized Azadipeptides"
<p>Raw NMR, IR and MS data for the article "Copper-Catalyzed Alkynylation of Hydrazides: An Easy Access to Functionalized Azadipeptides" published in Organic Letters, DOI: </p> <p><a href="https://doi.org/10.1021/acs.orglett.2c02625">https://doi.org/10.1021/acs.orglett.2c02625</a></p> <p>The number of the folders correspond to compounds numbers in the article. All details concerning conditions and equipment for measurements can be found in the supporting information of the article.</p>
Raw Data for 'Efficient Access of Phenyl-Spaced 5,5´-Bridged Dinuclear Ruthenium Metal Complexes and the Effect of Dynamic Ligand Exchange on Catalysis'
<p>Herein, we provide the raw data for all figures being part of either the mansucript or the supporting information of the publication 'Efficient Access of Phenyl-Spaced 5,5’-Bridged Dinuclear Ruthenium Metal Complexes and the Effect of Dynamic Ligand Exchange on Catalysis'.</p>
Data for "The APC-Barrier and its effect on stratification in open access publishing"
<p>Dataset to reproduce the analysis of the paper "The APC-Barrier and its effect on stratification in open access publishing". An earlier version of the manuscript with the title "The APC-Effect: Stratification in Open Access Publishing" is available at <a href="https://doi.org/10.31222/osf.io/w5szk">https://doi.org/10.31222/osf.io/w5szk</a>.</p> <p>Data is licensed under CC-BY-SA International (4.0), see the file LICENSE.</p> <p>A full description of the dataset is provided in the README.md.</p>
Extracted data for meta-analysis: Distal versus proximal radial access in coronary angiography
<p>Data base underlying quantitative meta-analysis in the manuscript titled "Distal versus proximal radial access in coronary angiography: A meta-analysis" by Lueg, Schulze, Stöhr, & Leistner.</p> <p>Data allows meta-analysis of primary endpoint (RAO), secondary endpoints, meta-regression for moderator analysis, and publication bias analysis.</p>
Ontology-Based Data Access Using Ontop
<p>This data set includes example software artifacts and a guide on how to materialize the data architecture for the use of Ontop in Ontology-Based Data Access (OBDA).</p>
Code + simulated + publically accessable data for "Evaluating health facility access using Bayesian spatial models and location analysis methods"
<p># README</p> <p>These files contain r data objects and R files that represent the key details of the paper, "Evaluating health facility access using Bayesian spatial models and location analysis methods".</p> <p>The following datasources are available for simulation of some of the ideas in the paper.</p> <p>- dat_grid_sim: simulated data of the grid and grid cells<br> - dat_ohca_cv_sim: simulated data containing the cross validated test/training sets of OHCA data<br> - dat_ohca_sim: simulated OHCA event data<br> - dat_aed_sim: simulated AED location data<br> - dat_bldg_sim: simulated building location data<br> - dat_municipality_sim: simulated municipality information<br> - table_1: Table 1 information containing key demographic data</p> <p>These data were produced using the code in 01-create-sim-data.R, and one of the statistical models is demonstrated in 02-demo-inla-model.R</p> <p>In terms of the paper itself, the functions and code used in the manuscript are located in:</p> <p>* 01_tidy.Rmd - analysis code used to tidy up the data</p> <p>* 02_fit_fixed_all_cv.Rmd - analysis code used to place AEDs</p> <p>* 02_model.Rmd - analysis code used to fit the model in INLA</p> <p>* 03_manuscript.Rmd - Full code and text used to create the paper</p> <p>* 04_supp_materials.Rmd - full code and text used to create the supplementary materials</p> <p>The following files are a part of an R package "swatial" that was developed along with the paper. These files are:</p> <p>* DESCRIPTION</p> <p>* NAMESPACE</p> <p>* LICENSE</p> <p>* LICENSE.md</p> <p>* decay.R</p> <p>* spherical-distance.R</p> <p>* test-figure-data-matches.R</p> <p>* test-table-data-matches.R</p> <p>* testthat.R</p> <p>* tidy-inla.R</p> <p>* tidy-posterior-coefs.R</p> <p>* tidy-predictions.R</p> <p>* utils-pipe.R</p> <p>* All files that end in .Rd are documentation files for the functions.</p> <p>## Regarding data sources</p> <p>Census information for Ticino was transcribed from the Annual Statistical Report of Canton Ticino from years 2010 to 2015. This data was taken from their publicly accessible annual reports - for example: (https://www3.ti.ch/DFE/DR/USTAT/allegati/volume/ast_2015.pdf). The raw data was extracted from these annual reports, and placed into the file: "swiss_census_popn_2010_2015.xlsx". These data are put into analysis ready format in the file “01_tidy.Rmd”</p> <p>Housing and other relevant geospatial data can be accessed via http://map.housing-stat.ch/ and https://data.geo.admin.ch/. The maps of buildings from the REA (Register of Buildings and Dwellings) can be found here: https://map.geo.admin.ch/?zoom=11&bgLayer=ch.swisstopo.pixelkarte-grau&lang=en&topic=ech&layers=ch.bfs.gebaeude_wohnungs_register,ch.swisstopo.swissboundaries3d-gemeinde-flaeche.fill,ch.bfs.volkszaehlung-gebaeudestatistik_gebaeude,ch.bfs.volkszaehlung-gebaeudestatistik_wohnungen,ch.swisstopo.swissbuildings3d_1.metadata,ch.swisstopo.swissbuildings3d_2.metadata&E=2717616.28&N=1096597.25&catalogNodes=687,696&layers_timestamp=,,2016,2016,,&layers_visibility=true,false,false,false,false,false&layers_opacity=1,1,1,1,1,0.75</p> <p>For further enquiries on this data, contact the Swiss federal Office of Statistics at the details listed here: https://www.bfs.admin.ch/bfs/en/home/services/contact.html</p> <p>The shapefiles of the Comuni can be accessed here: https://www4.ti.ch/dfe/de/ucr/documentazione/download-file/?noMobile=1</p> <p>Data from the people living in the Municipalities in Ticino can be downloaded here: https://www3.ti.ch/DFE/DR/USTAT/index.php?fuseaction=dati.home&tema=33&id2=61&id3=65&c1=01&c2=02&c3=02</p> <p>## Future work</p> <p>In the future, these functions from the paper may be generalised and put into their own package. If that happens, this repository will be updated with a link to updated functions.</p>
ACCESS-AM2 campaign data
<p>The ACCESS-AM2 (Australian Community Climate and Earth-System Simulator - Atmospheric Model Version 2) data used for the study described in Fiddes et al. (2024) '<em>The ACCESS-AM2 climate model strongly underestimates aerosol concentration in the Southern Ocean, but improving it could be problematic for the modelled climate system</em>' submitted to Atmospheric Chemistry and Physics </p> <p>Included, for each experimental simulation, are the modelled fields at either the specific campaign location or along the ship track. </p> <p>The experiments include: </p> <ul> <li>Control - dd657</li> <li>Control* - bx400</li> <li>BL NPF - cg283</li> <li>OM2 - ch543 </li> <li>PMO - cq687</li> <li>H22 - cq686</li> <li>PMO+H22 - dd153</li> <li>SSA Gust - dd154</li> </ul> <p>The campaigns include:</p> <ul> <li>CAPRICORN1</li> <li>CAPRICORN2</li> <li>MARCUS</li> <li>CAMMPCAN</li> <li>Ice2Equator</li> <li>Cold Water Trial</li> <li>PCAN</li> <li>Kennaook-Cape Grim</li> <li>Macquarie Island</li> <li>Syowa</li> </ul> <p>The code that processed the attached model data and the subsequent analysis can be found at: https://github.com/sfiddes/ACCESS_aerosol_eval</p> <p> </p>
Primary data for Manuscript provisionally titled Stereoselective access to bioactive cyclopropanes (+)-PPCC and (1R,2S)-2-aminomethyl-1-arylcyclopropane-1-carboxamides from (−)-levoglucosenone
<p><span>Contains HRMS and FID data for compounds described in the manuscript titled, "<span>Stereoselective access to bioactive cyclopropanes (+)-PPCC and (1<em><span>R</span></em>,2<em><span>S</span></em>)-2-aminomethyl-1-arylcyclopropane-1-carboxamides from (−)-levoglucosenone"</span></span></p> <p><span>FIDs can be opened using SpinWorks or Topspin programs.</span></p> <p> </p>
DiCARN-DNase: Enhancing Cell-to-Cell Hi-C Resolution Using Dilated Cascading ResNet with Self-Attention and DNase-seq Chromatin Accessibility Data
<p>This repository contains the training, validation, and testing data for the DiCARN-DNase project. The GitHub repository is available via https://github.com/OluwadareLab/DiCARN_DNase</p>
ACCESS-ESM-1.5 net-zero emissions 1000-year long simulations: Seasonal temperature and precipitation gridded data with area-average timeseries of temperature, precipitation and sea ice data
<p>NetCDF files used in analysis shown in King et al. (2024) https://egusphere.copernicus.org/preprints/2024/egusphere-2023-2961/.</p> <p>Seasonal-average mapped 1.5 metre air temperature temperature data are in NetCDFs with "fld_s03i236" in their name. These files are for boreal summer "JJA" or boreal winter "DJF". The "B20__" represents the start year of the net-zero emissions simulation from which these data are drawn. These files each have 1000 time-steps and the data are in native resolution of ACCESS-ESM-1.5: 1.875 degrees longitude by 1.25 degrees latitude.</p> <p>Seasonally-averaged precipitation rate (kg/m2/s) data are in NetCDFs with "fld_s05i216" in their name. Seasons and simulation information follow the same format as the temperature files.</p> <p>The file "ts_gwl.nc" includes several timeseries used in the paper including global-average SST ("TEMP_SURFACE"), global mean ocean temperature ("TEMP_GLOBAL"), and March/September Arctic ("ICEN") and Antarctic ("ICES") sea ice extent.</p> <p>The scripts used to make the Figures are included and run using IDL version 9.0. </p> <p>For any advice on using these files please feel free to contact me: andrew.king@unimelb.edu.au.</p>
Data Matrix Theme-Specific Analysis of the Recommendation on Science and Scientific Researchers (RSSR): Open Access, Open Data, and Open Science
<p>This Table sets out findings from the mapping exercise conducted as part of the objectives of subtask 6.1 of the RRING project.</p> <p>Aim: Alignment of RRI to advance the UN SDGs.</p> <p>Objectives:</p> <ul> <li>Mapping the RSSR to the SDGs </li> </ul> <p>Mapping the RSSR to the SDGs is aimed at providing new perspectives, ideas and approaches that can help to improve the operationalization and implementation of each SDG, <em>by facilitating the integration of RRI (or RRI-like) practices in the SDGs, to make them more achievable.</em> The impact of the new perspectives, ideas and approaches in SDG operationalization and implementation will be aimed at the level of <em>national and international policy (making); future research and innovation projects (in industry and academia); as well as education and training of researchers, policy makers and other stakeholders.</em></p> <p>Two documents were used for this task:</p> <ul> <li>2017 Recommendation on Science and Scientific Researchers ([RSSR], UNESCO), and</li> <li>the United Nations 2030 Agenda for Sustainable Development with the 17 Sustainable Development Goals (SDGs).</li> </ul>
Single cell ATAC-seq Mouse Kidney Data: Chromatin-accessibility estimation from single-cell ATAC data with scOpen
<p>We provide results regarding the bioinformatic analysis of scATAC-seq from mouse UUO kidney at different time points.</p>
The interpretation of temperature and salinity variables in numerical ocean model output and the calculation of heat fluxes and heat content - ACCESS-CM2 data and code
<p>This dataset contains post-processed ACCESS-CM2 PI control CMIP6 climate model output and code used to produce Figs. 5, 6 and 9 in the published article:</p> <p>McDougall, T., J., Barker, P.M., Holmes, R.M., Pawlowicz, R., Griffies, S. and Durack, P. (2021): The interpretation of temperature and salinity variables in numerical ocean model output and the calculation of heat fluxes and heat content, <strong>Geoscientific Model Development</strong>, 14, 1–21, <a href="https://doi.org/10.5194/gmd-2020-426">https://doi.org/10.5194/gmd-2020-426</a></p> <p>The processed ACCESS-CM2 data is included as .mat files and is accompanied by Matlab processing routines (including code from the TEOS-10 Gibbs SeaWater Oceanographic Toolbox, https://www.teos-10.org/software.htm#1) to produce the figures. A more detailed description of the data are included in README.md. The code and data is also available under version control at <a href="https://github.com/rmholmes/ACCESS_CM2_SpecificHeat/tree/GMD_Published">https://github.com/rmholmes/ACCESS_CM2_SpecificHeat/tree/GMD_Published</a>.</p>
Data for the article on 'Non-syntactic factors and accessibility to relativization: evidence from Armenian', published in Linguistics
<p>Data for the article on 'Non-syntactic factors and accessibility to relativization: evidence from Armenian', published in Linguistics</p>
A Versatile and Secure Data Management System API facilitating the Interconnection of any software component and Easy Data Access.
<p>In the context of the EU-funded project PILOTING (No. 871542), a versatile Data Management System (DMS) was deployed and facilitated the easy integration of nine different robotic systems and various payloads and the storing of all the data observations produced during the inspections. The DMS is designed under the DMS-Data Model (DMS-DM) and operates on top of a representational state transfer (REST) application programming interface (API) that provides a simplified way to exchange data through HTTP(S) requests from a client to the server. One of its key advantages is that it provides a great deal of flexibility so the model could accommodate extensions if needed. Data is not tied to resources or methods, so REST can handle multiple types of calls, return different data formats and even change structurally with the correct implementation of hypermedia. <br> It supports CRUD operations via GET, POST, PUT, PATCH, and DELETE HTTP methods and stores the data on a PostgreSQL object-relational database system. The REST API has been created with Python's Django (web framework) and Django REST Framework, a powerful and flexible toolkit for building Web APIs. <br> The constructed document presents the communication endpoints (DMS API’s Uniform Resource Identifiers (URIs)) under which an authorized user can have access to the DMS API and subsequently to the collected data. </p>
Web Accessibility Evaluation Data - March to September 2021
<p>This dataset contains the dump of a PostgreSQL database with the contents of automated web accessibility evaluation of nearly 3 million webpages obtained with QualWeb between March and September 2021.</p>
Supplementary materials for: Actually accessible data: An update and a call to action
<p>These are the supplementary materials for the article "Actually Accessible Data: An Update and a Call to Action." The project contains three files:</p> <ol> <li>Colon-Karcher-Goben_Accessibility-of-Popular-Data-Repositories.xlsx shows the results of automated accessibility checks of seven popular data repositories in the United States and Europe. For each repository a search or browse page as well as a typical dataset landing page were selected and checked with two prominent accessibility tools AXE (https://www.deque.com/axe/) and WAVE (https://wave.webaim.org/). Checks were initially performed in Spring 2022. The reported (mostly unchanged) results are from tests on April 25, 2023. They were performed using Firefox 112.0.2 for Windows with both browser add-ons installed, AXE v. 4.6.3, WAVE v. 3.2.</li> <li>Colon-Goben-Karcher_Acessibility-FLOSS-Repositories.xlsx describes the treatment of digital accessibility in the developer-oriented documentation of six popular open-source (data) repository software projects. The project documentation was reviewed by two researchers with a background in open source software (Karcher as well as a graduate assistant at the Qualitative Data Repository) who looked for specific sections on accessibility and also used search terms to identify relevant sections. This document reflects the status as of April 2022.</li> <li>Colon-Goben-Karcher_Search-Strategies.docx Briefly discusses the literature search strategies conducted for relevant literature. Initial searches in Google Scholar and Scopus were performed in March-April 2022. Additional searches in LISTA are from March-April 2023.</li> </ol>
Raw data: Potential of different common (Fagopyrum esculentum Moench) and Tartary (Fagopyrum tataricum (L.) Gaertn.) buckwheat accessions to sustainably manage surrounding weeds
<p>Twenty-nine accessions of two buckwheat species (<em>Fagopyrum esculentum</em> Moench (common buckwheat) and <em>Fagopyrum tataricum</em> (L.) Gaertn. (Tartary buckwheat) were evaluated for their allelopathic potential against two resistant weeds, i.e. the monocot <em>Lolium rigidum</em> Gaud. and the dicot <em>Portulaca oleracea</em> L. The bulking use of synthetic herbicides and their consequent contamination of the environment and resulting increment of resistant weeds, imminently requires a solution to achieve sustainable weed management without the use of chemical inputs. The results obtained in this study suggest that buckwheat accessions can sustainably manage weeds through plant interference as competition or allelopathy. This research showed that accessions differ in their potential for sustainably manage both weeds, with <em>F. esculentum</em> accessions being more effective against <em>L. rigidum</em> and <em>F. tataricum</em> accessions against both, monocot and dicot weeds. The chemical profile of buckwheat accessions was evaluated to know the content of polyphenols in common and Tartary buckwheat accessions and to know more about their ability to sustainably manage weeds. Differences in the chemical profile between the two buckwheat species were clear. While common buckwheat accessions showed more orientin, vitexin and hyperoside, Tartary buckwheat accessions had higher amounts of rutin, quercetin and kaempferol. We propose that the screening and selection of accessions with strong polyphenol content and vigorous growth can be a step towards organic farming due to its relation to the weed management.</p>
ACCESS-OM2 1° resolution global repeat decade forcing control simulation data for 1972-2018
<p>This data set contains <strong>control </strong>simulation output from the global ocean-sea ice model ACCESS-OM2 in the 1° horizontal configuration over the period 1972-2018.</p> <p>The model was spun-up using modified repeat decade forcing for the period 1962-1971 to equilibrate the ocean to this period prior to most of the anthropogenic ocean heat uptake. This repeat decade forcing simulation was then continued up to present time and relabeled as the control simulation. The output 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>
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.