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252 results for “platform data”
Derived daily timeseries of weather, soil moisture and temperature, flow and nitrogen species (nitrate and nitrite, ammonium) concentrations data for the North Wyke Farm Platform National Biosciences Research Infrastructure, England
<p>For a selection of catchments from the North Wyke Farm Platform in southwest England, where land use conversions have been introduced, daily time series data covering weather conditions (minimum temperature, maximum temperature, total rainfall, wind speed and solar radiation), near-surface soil status (moisture content and temperature), flow and concentrations of key nitrogen species (nitrate and nitrite, ammonium) have been filtered based on attached data quality tags . The datasets run between 2013 and March 2024. For the main climate variables, data gaps were infilled with preceding- and following-on daily data, observations from a nearby weather station or existing national datasets to generate a continuous data series for modelling. For the other data series, annual and seasonal summary statistics on data coverage are provided. Information on significant field events, such as ploughing, drilling and harvest, fertiliser applications and manure spreading were also tabulated.</p>
Commodity Dataset | Retrieving the National Main Commodity Maps in Indonesia Based on High-Resolution Remotely Sensed Data Using Cloud Computing Platform
<p>(Commodity data in raster format) Supplementary materials for “Retrieving the National Main Commodity Maps in Indonesia Based on High-Resolution Remotely Sensed Data Using Cloud Computing Platform” that had been published on Land MDPI (2020). doi:<a href="https://doi.org/10.3390/land9100377">10.3390/land9100377</a> </p> <p>The data included:</p> <p>1) Raster data of commodity maps (TIFF Compressed in ZIP)</p> <p>2) READ ME for the dataset (DOCX)</p> <p>3) Legend for raster data in ArcGIS Format (LYR)</p> <p> </p>
Data of paper Chemically vapor deposited Eu3+:Y2O3 thin films as a material platform for quantum technologies
<p>Data of the figures of the paper:</p> <p>N. Harada, A. Ferrier, D. Serrano, M. Persechino, E. Briand, R. Bachelet, I. Vickridge, J.-J. Ganem, P. Goldner, and A. Tallaire, <em>Chemically Vapor Deposited Eu 3+:Y 2O 3thin Films as a Material Platform for Quantum Technologies</em>, J. Appl. Phys. <strong>128</strong>, 055304 (2020). doi: <a href="https://doi.org/10.1063/5.0010833">10.1063/5.0010833</a></p> <p> </p>
Using a Hybrid Kano-Importance Questionnaire in the Acquisition of Data Related to Students' Expectations from Online Educational Platforms
<p>This dataset contains the data collected for the assessment of the quality attributes of a new online educational platform. The questionnaire used for data collection the Kano methodology and was designed as a hybrid Kano-importance questionnaire. The purpose of this data collection consists of the analysis of the students’ expectations regarding the features proposed for a new online educational platform. This analysis facilitates the identification of student needs during times of COVID-19 pandemic and post-pandemic times, while a transition to an online educational system was used throughout the world. </p>
SURCOM pH and temperature data collection registered at Cortegada Platform (Ria de Arousa - Spain) from 2020 to 2021
<p>This dataset comprises the data recorded by the SURCOM production prototype deployed from 2020 to 2021 at Cortegada Platform (42º 37' 40" N, 8º 46' 57" W), located in the National Park of Atlantic Islands at Ria de Arousa, in the NW of Spain.</p> <p>The measurements were taken continuously with pH and temperature collected at a frecuency of 10.3 minutes<sup>-1</sup>.</p> <p>Real-time adquired data is displayed and can be also downloaded from the following web panel:</p> <ul> <li><a href="https://co2.iim.csic.es/monitoring/d/surcom_cortegada/surcom-cortegada">https://co2.iim.csic.es/monitoring/d/surcom_cortegada/surcom-cortegada</a></li> </ul> <p>These results have been obtained thanks to the support of <a href="http://pti-waterios.csic.es/">CSIC PTI WATER:iOS</a> and are, therefore, a contribution to its efforts.</p>
Processed and annotated yeast gene expression data from yeast2 and ygs98 platforms
<p>This dataset contains the following files:</p> <ul> <li><em>yeast2_processed_rds.tar.gz -</em> processed gene expression matrices from the yeast2 platform. The data is stored in binary R format (.rds).</li> <li><em>ygs98_processed_rds.tar.gz </em>- processed gene expression matrices from the yeast2 platform. The data is stored in binary R format (.rds).</li> <li><em>yeast2-curated-annotations.txt</em> - metadata for the yeast2 platform.</li> <li><em>ygs98-curated-annotations.txt</em> - metadata for the ygs98 platform.</li> </ul> <p> </p>
Comparing coronary stent material performance on a common geometric platform through simulated bench testing: Supporting data
<p>Data including UMATs and Abaqus input files related to the paper 'Comparing coronary stent material performance on a common geometric platform through simulated bench testing' <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.jmbbm.2012.02.013" target="_blank" rel="noreferrer noopener"><span>https://doi.org/10.1016/j.jmbbm.2012.02.013</span></a></p>
Figure 7 in Internet-based data platforms re-define the distributions of some large crabronid wasps in Arkansas (Hymenoptera: Crabronidae)
Figure 7. Map of the known geographic distributions for Sphecius speciosus (circle), Stictia carolina (triangle), Stizus brevipennis (square) in Arkansas.
Figure 8 in Internet-based data platforms re-define the distributions of some large crabronid wasps in Arkansas (Hymenoptera: Crabronidae)
Figure 8. Number of county records for three species of wasps in the University of Arthropod Arthropod Museum (UAAM), and three internet-based data platforms.
Data Report: Educational Pathway on Food and Nutrition in Amyotrophic Lateral Sclerosis on the AVASUS platform
<p><strong>Dataset name:</strong><em> nutri_als_dataset.csv </em></p> <p><strong>Version: </strong>1.0 </p> <p><strong>Dataset period:</strong> 06/01/2021 - 06/05/2024</p> <p><strong>Dataset Characteristics: </strong>Multivalued </p> <p><strong>Number of Instances: </strong>20967</p> <p><strong>Number of Attributes: </strong>9</p> <p><strong>Missing Values: </strong>Yes</p> <p><strong>Area(s): </strong>Health and education<strong> </strong></p> <p><strong>Sources: </strong></p> <ul> <li>Virtual Learning Environment of the Brazilian Health System (AVASUS) (Brasil, 2024a);</li> <li>Brazilian Occupational Classification (CBO) (Brasil, 2024b);</li> <li>National Registry of Health Establishments (CNES) (Brasil, 2024c); </li> <li>Brazilian Institute of Geography and Statistics (IBGE) (Brasil, 2024d). </li> </ul> <p><strong>Description</strong>:<strong> </strong>The “nutri_als_dataset.csv” dataset (see Table 1) originates from participants of the educational pathway on Food and Nutrition in Amyotrophic Lateral Sclerosis. The educational pathway is available on the AVASUS (Brasil, 2024a). This dataset provides elementary data to analyze the scope of the educational pathway courses and the profile of their participants.</p> <p><br><strong>Note</strong>: The content of the dataset is provided in Brazilian Portuguese (pt-br), as it originates from native speakers.</p> <p><strong>Table 1: </strong>Description of AVASUS dataset features. </p> <div> <table> <tbody> <tr> <td> <p><strong>Attributes </strong></p> </td> <td> <p><strong>Description </strong></p> </td> <td> <p><strong>Datatype </strong></p> </td> <td> <p><strong>Value</strong></p> </td> </tr> <tr> <td> <p><strong>user_id</strong></p> </td> <td> <p>Unique identifier for a person (anonymous).</p> </td> <td> <p>Categorical</p> </td> <td> <p>Person unique identifier.</p> </td> </tr> <tr> <td> <p><strong>course_enrollment</strong></p> </td> <td> <p>Course enrollment period.</p> </td> <td> <p>Datetime </p> </td> <td> <p>year-month-day.</p> </td> </tr> <tr> <td> <p><strong>course_name</strong></p> </td> <td> <p>Name in Portuguese referring to the course.</p> </td> <td> <p>Categorical</p> </td> <td> <ul> <li> <p>Alimentação por sonda na ELA;</p> </li> <li> <p>Alimentação e Nutrição na ELA;</p> </li> <li> <p>Orientações nutricionais específicas na ELA; or</p> </li> <li> <p>Modificações Dietéticas na ELA.</p> </li> </ul> </td> </tr> <tr> <td> <p><strong>certificate</strong></p> </td> <td> <p>The period in which the course participant obtained the right to a certificate.</p> </td> <td> <p>Datetime</p> </td> <td> <p>year-month-day hours, minutes, and seconds.</p> </td> </tr> <tr> <td> <p><strong>gender </strong></p> </td> <td> <p>Gender of the course participant. </p> </td> <td> <p>Categorical</p> </td> <td> <ul> <li> <p>Female;</p> </li> <li> <p>Male; or</p> </li> <li> <p>Not informed.</p> </li> </ul> </td> </tr> <tr> <td> <p><strong>region</strong></p> </td> <td> <p>Brazilian region in which the participant resides.</p> </td> <td> <p>Categorical</p> </td> <td> <ul> <li> <p>North;</p> </li> <li> <p>Northeast;</p> </li> <li> <p>Central-West;</p> </li> <li> <p>Southeast;</p> </li> <li> <p>South;</p> </li> <li> <p>Abroad; or</p> </li> <li> <p>Not reported.</p> </li> </ul> </td> </tr> <tr> <td> <p><strong>course_evaluation</strong></p> </td> <td> <p>A score given to the course by the participant. </p> </td> <td> <p>Numerical</p> </td> <td> <p>0, 1, 2, 3, 4, 5, or NaN.</p> </td> </tr> <tr> <td> <p><strong>evaluation_commentary</strong></p> </td> <td> <p>Comment made by the participant about the course.</p> </td> <td> <p>Categorical</p> </td> <td> <p>Free text or NaN.</p> </td> </tr> <tr> <td> <p><strong>CBO</strong></p> </td> <td> <p>Participant occupation.</p> </td> <td> <p>Categorical</p> </td> <td> <p>Text coded according to the Brazilian Classification of Occupations or “Indivíduo sem filiação formal.” (In English, “Individual without formal affiliation.”)</p> </td> </tr> </tbody> </table> </div> <p> </p> <p> </p> <p><strong>REFERENCES</strong></p> <p>Brasil (2024a). AVASUS - Virtual Learning Environment of the Brazilian Health System. Available from: <a href="https://avasus.ufrn.br/local/avasplugin/dashboard/transparencia.php">https://avasus.ufrn.br/local/avasplugin/dashboard/transparencia.php</a>. Accessed Jul 21, 2024.</p> <p>Brasil (2024b). CBO - classificação brasileira de ocupações. Available from: <a href="https://cbo.mte.gov.br/cbosite/pages/home.jsf">https://cbo.mte.gov.br/cbosite/pages/home.jsf</a>. Accessed Jul 21, 2024.</p> <p>Brasil (2024c). CNES - cadastro nacional de estabelecimentos de saúde. Available from: <a href="https://cnes.datasus.gov.br/">https://cnes.datasus.gov.br/</a>. Accessed Jul 21, 2024.</p> <p>Brasil (2024d). IBGE - Instituto Brasileiro de Geografia e Estatística. Estimativas da População. Available from: <a href="https://agenciadenoticias.ibge.gov.br/agencia-noticias/2012-agencia-de-noticias/noticias/39525-censo-2022-informacoes-de-populacao-e-domicilios-por-setores-censitarios-auxiliam-gestao-publica">https://agenciadenoticias.ibge.gov.br/agencia-noticias/2012-agencia-de-noticias/noticias/39525-censo-2022-informacoes-de-populacao-e-domicilios-por-setores-censitarios-auxiliam-gestao-publica</a>. Accessed Jul 21, 2024.</p> <p> </p> <p><strong>ARTICLE:</strong></p> <p>Data Report: Educational Pathway on Food and Nutrition in Amyotrophic Lateral Sclerosis on the AVASUS platform <br> </p> <p><strong>AUTHORS:</strong></p> <p>Karla M. D. Coutinho<sup>1,2</sup>, Felipe Fernandes<sup>2</sup>, Kelson C. Medeiros<sup>2,6</sup>, Karilany D. Coutinho<sup>2,4,5</sup>, Aline de Pinho Dias<sup>2,4</sup>, Ricardo A. M. Valentim<sup>2,4,5</sup>, Lúcia Leite-Lais<sup>3</sup>, Kenio Costa Lima1</p> <p> </p> <p><sup>1</sup>Postgraduate Program in Health Sciences, Federal University of Rio Grande do Norte, Natal, Brazil</p> <p><sup>2</sup>Laboratory of Technological Innovation in Health (LAIS), Federal University of Rio Grande do Norte (UFRN), Natal, Rio Grande do Norte, Brazil </p> <p><sup>3</sup>Department of Nutrition, Federal University of Rio Grande do Norte, Natal, Brazil</p> <p><sup>4</sup>Postgraduate Program in Management and Innovation in Health, Federal University of Rio Grande do Norte, Natal, Brazil</p> <p><sup>5</sup>Department of Biomedical Engineering, Federal University of Rio Grande do Norte, Natal, Brazil</p> <p><sup>6</sup>Federal Institute of Education, Science and Technology of Rio Grande do Norte, Natal, Brazil</p> <p> </p> <p> </p>
Cloud management platform evaluation data generated by CMP²
<p>This repository contains exemplary results from using the CMP² (Comparing Cloud Management Platforms) testbed on CloudcheckR, ManageIQ, MistIO, Boto and Libcloud. The results give insight into the performance of multi-cloud middleware. All experiments were conducted as research in education linked to the Cloud Accounting and Billing research initiative at Service Prototyping Lab, Zurich University of Applied Sciences, Switzerland. Apart from the raw data in JSON format, generated graphs are also included.</p> <p> </p>
Research data supporting "A robust liposomal platform for direct colorimetric detection of sphingomyelinase enzyme and inhibitors"
<p>Raw research data supporting the publication: Holme, M. N. et al., ACS Nano, 2018, DOI: 10.1021/acsnano.8b03308.</p>
Illustrative Darwin core archive to input data on a citizen science platform from a collection management system
<p>Illustrative DwC archive to send data from a collection management system to a citizen sciences platform. This illustrative archive displays the specimens used for the trans-institutional and trans-platform pilot project held in the frame of ICEDIG.</p> <p>Further description of its content in the milestone28 document, worpackage 5.2 of the ICEDIG project.</p>
Example structure of data sent from a collection management system to a citizen science platform, multi-imaged case
<p>Illustrative example of data format following Darwin Core to send from a collection management system to a citizen science platform. Multi-imaged vertebrate specimen case : http://coldb.mnhn.fr/catalognumber/mnhn/zo/2013-152</p> <p>Illustration of the milestone28 document, worpackage 5.2 of the ICEDIG project.</p>
Example structure of data sent from a collection management system to a citizen science platform, simple case
<p>Illustrative example of data format following Darwin Core to send from a collection management system to a citizen science platform. Simple case : http://coldb.mnhn.fr/catalognumber/mnhn/p/p03558024</p> <p>Illustration of the milestone28 document, worpackage 5.2 of the ICEDIG project.</p>
Pol III modeling data and scripts using the Integrative Modeling Platform
<p>This repository contains the data obtained running the Integrative modeling platform with crosslinks and cryoem data, on the RNA Pol III system.</p>
Industrial Big Data Innovation Platform SCADA Dataset
<p>This is the SCADA dataset from the first Industrial Big Data Innovation Competition, for more information, visit: <a href="https://www.industrial-bigdata.com/Challenge/title?competitionId=LEIREZMM8TT5VBU0TLJ61FPAI6WWJOJY&type=">数境创新大赛平台(industrial-bigdata.com)。</a></p>
Data for "An optofluidic platform for interrogating chemosensory behavior and brainwide neural representation in larval zebrafish"
<p>This dataset contains the free arena data and imaging data for the following research paper.<br> <br> Sy, S.K.H., Chan, D.C.W., Chan, R.C.H. <em>et al.</em> An optofluidic platform for interrogating chemosensory behavior and brainwide neural representation in larval zebrafish. <em>Nat Commun</em> <strong>14</strong>, 227 (2023). https://doi.org/10.1038/s41467-023-35836-2</p>
Paired omics Data Platform projects
<p>The Paired Omics Data Platform is a community-based initiative standardizing links between genomic and metabolomics data in a computer readable format to further the field of natural products discovery. The goals are to link molecules to their producers, find large scale genome-metabolome associations, use genomic data to assist in structural elucidation of molecules, and provide a centralized database for paired datasets. This dataset contains the projects in <a href="http://pairedomicsdata.bioinformatics.nl/">http://pairedomicsdata.bioinformatics.nl/</a>.</p> <p>The JSON documents adhere to the <a href="http://pairedomicsdata.bioinformatics.nl/schema.json">http://pairedomicsdata.bioinformatics.nl/schema.json</a> JSON schema.</p>
TopSpec platform (pI-trap/Orbitrap/Omnitrap) combined data
<p>Data 1 name: 20221221_500nulInflix250ngulNIST_180umcell-90minfocusing_2_externalpower_alwayson_omnitrap_ECD40ms_2</p> <p>Description: A 4 µL mixture of infliximab (500ng/µL) and NISTmAb (250ng/µL) is aspirated by the Alias autosampler pI-trap system and transferred into the pI cell for 90-min, 2000V cIEF separation. After the focusing, the sample is slowly injected at 0.5 µL/min to Exploris 480 – omnitrap. Two experiments are set in the data acquisition method: 1. MS full scan with resolution 120 000. 2&3. MS/MS experiment performed by orbi-omnitrap. Two m/z ranges, 2481 ± 5 representing infliximab and 2471 ± 5 representing NISTmAb, respectively, are isolated and injected to the omnitrap, where ECD is executed with filament current 5.65A and irradiation time 40ms. Infliximab is the earlier peak at RT 12 -14 min, NISTmAb is the later peak 22 - 24 min.</p> <p>Data 2 name: 20221221_500nulInflix250ngulNIST_180umcell-90minfocusing_2_externalpower_alwayson_omnitrap_HCD30_1</p> <p>Description: A 4 µL mixture of infliximab (500ng/µL) and NISTmAb (250ng/µL) is aspirated by the Alias autosampler pI-trap system and transferred into the pI cell for 90-min, 2000V cIEF separation. After the focusing, the sample is slowly injected at 0.5 µL/min to Exploris 480 – omnitrap. Three experiments are set in the data acquisition method: 1. MS full scan with resolution 120 000. 2&3. MS/MS experiment performed by orbi-omnitrap. Two m/z ranges, 2481 ± 5 representing infliximab and 2471 ± 5 representing NISTmAb, respectively, are isolated and get fragmented with HCD by orbitrap. HCD collision energy is set at 30%. Infliximab is the earlier peak at RT 12 -14 min, NISTmAb is the later peak 22 - 24 min.</p> <p>Data 3 name: 20221216_1ugulInflix100ngulNIST_180umcell-90minfocusing_2_externalpower_alwayson_omnitrap_EID50ms_2</p> <p>Description: A 4 µL mixture of infliximab (1000ng/µL) and NISTmAb (100ng/µL) is aspirated by the Alias autosampler pI-trap system and transferred into the pI cell for 90-min, 2000V cIEF separation. After the focusing, the sample is slowly injected at 0.5 µL/min to Exploris 480 – omnitrap. Two experiments are set in the data acquisition method: 1. MS full scan with resolution 60 000. 2&3. MS/MS experiment performed by orbi-omnitrap. Two m/z ranges, 2481 ± 5 representing infliximab and 2471 ± 5 representing NISTmAb, respectively, are isolated and injected to the omnitrap, where ECD is executed with filament current 5.65A and irradiation time 40ms. 4. MS full scan with resolution 7500. Infliximab is the earlier peak at RT 12 -14 min, NISTmAb is the later peak 22 - 24 min.</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.