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8,020 results for “pilots”
OpenAIRE Dataset for SciLake cancer research pilot
<p>This dataset is related to the subset of the OpenAIRE graph relevant to the cancer research pilot. The dataset is built according to the <a href="https://graph.openaire.eu/docs/data-model/">data model</a> of the OpenAIRE Graph dataset. </p>
GeoERA RESOURCE CHAKA data set which contains time series of precipitation and discharge of springs in the CHAKA pilot areas (D5.5)
<p>Dataset which contains time series of precipitation and discharge of springs in the pilot areas of the CHAKA work package of the GeoERA RESOURCE project. The file contains precipitation and spring discharge data of 16 pilot areas in the Karst & Chalk work package. A description of the application of the dataset for the characterisation of the typology of karst systems in given in the D5.3 deliverable of GeoERA RESOURCE of which the pdf is provided. Further information about the CHAKA results can be assessed though the webservices of the European Geological Data Infrastructure (EGDI). </p>
SAAM pilot study WP8 2020-2021
<p>The dataset includes data from the pilot study conducted with senior users from Austria and Bulgaria in 2020-2021 under Horizon 2020 project SAAM. It includes anonymised quantitative demographic, quality of life, technology acceptance, user experience, sleep related and social life related data.</p> <p>For more information, please, see the Final Pilot Study report, published at <a href="https://saam2020.eu/?p=results.saam">SAAM project website</a>.</p>
SENSEI D8.2 Pilot Assessment Calculations
<p>Within this deliverable of the SENSEI project, on overview of meaningful “smart” technologies in the context of a building is given in a so called service catalogue acting as a single point of access to an overview for technologies in the context of smart buildings actively contributing to the KPI of a smart readiness indicator. Within SENSEI, those services are seen in the context of the P4P – Pay for Performance schemes and if certain services are more beneficial than others in another context than die original indicator. Services are characterized by their domain, their market share on pre-existing conditions, mostly technology which has to be in place in order to enable the mentioned technology. Those services are set and put in context with simulations and calculations with documented adjustments to the original SRI. Taking these adjustments into account, the impact evaluation consists of separately simulating /calculating the changes to the building properties achieved by a P4P program in conjunction with the individual SBT groups, and assess the resulting smart readiness. The difference between the SRI value after the basic P4P program and these new values constitute a quantified impact evaluation rate of the associated SBT group, which can be evaluated and compared to those obtained by other groups of SBTs. </p>
AmelHap pilot: filter4 data
<p>Honey bee <em>Apis mellifera</em> drones are typically haploid, developing from an unfertilized egg, inheriting only their queen’s alleles and none from the many drones she mated with. Being haploid, the ordered combination or ‘phase’ of alleles is known, making drones a valuable haplotype resource. We collated whole genome sequence data for 688 drones, including 45 newly sequenced Scottish drones, which collectively represent 13 countries, 7 subspecies and various hybrids strains. After alignment to the reference assembly Amel_Hav3.1, and haploid variant calling, we identified 18.9M variants. </p> <p>Whole-genome sequencing data underpinning the dataset is available from the European Nucleotide Archive (ENA), <a href="https://www.ebi.ac.uk/ena">https://www.ebi.ac.uk/ena</a>, with the project accession codes: PRJEB16533, PRJNA311274, PRJNA363032, PRJNA516678, PRJNA544324, and PRJEB39369.</p> <p>Sequencing reads were aligned to the Amel_HAv3.1 reference genome using BWA-MEM v0.7.17. Reads were sorted with SAMtools v1.9 and duplicates marked (MarkDuplicates) with GATK v4.0.11.0. Variants for each sample were called using GATK’s HaplotypeCaller with the following non-default parameters --ERC GVCF, --sample-ploidy 1 and -A AlleleFraction. Joint variant calling was performed across all samples using GATK’s GenomicDBImport and GenotypeGVCFs with --sample-ploidy 1 and a window size of 2.5 Mb. </p> <p>This dataset is the result of applying filters to exclude samples or variants with call rate <90% in the <a href="https://zenodo.org/record/6563443">filter3 dataset</a>, leaving 14.8M variants. A subset of this dataset comprising 1.8M variants is included, in which variants were pruned to remove those in high linkage disequilibrium (r<sup>2</sup> > 0.1 for variant pairs up to 10kb apart). The code used in filtering is outlined here: <a href="https://bitbucket.org/scriptBee/hapmap-pilot">https://bitbucket.org/scriptBee/hapmap-pilot</a>.</p>
AmelHap pilot: filter3 data
<p>Honey bee <em>Apis mellifera</em> drones are typically haploid, developing from an unfertilized egg, inheriting only their queen’s alleles and none from the many drones she mated with. Being haploid, the ordered combination or ‘phase’ of alleles is known, making drones a valuable haplotype resource. We collated whole genome sequence data for 688 drones, including 45 newly sequenced Scottish drones, which collectively represent 13 countries, 7 subspecies and various hybrids strains. After alignment to the reference assembly Amel_Hav3.1, and haploid variant calling, we identified 18.9M variants. </p> <p>Whole-genome sequencing data underpinning the dataset is available from the European Nucleotide Archive (ENA), <a href="https://www.ebi.ac.uk/ena">https://www.ebi.ac.uk/ena</a>, with the project accession codes: PRJEB16533, PRJNA311274, PRJNA363032, PRJNA516678, PRJNA544324, and PRJEB39369.</p> <p>Sequencing reads were aligned to the Amel_HAv3.1 reference genome using BWA-MEM v0.7.17. Reads were sorted with SAMtools v1.9 and duplicates marked (MarkDuplicates) with GATK v4.0.11.0. Variants for each sample were called using GATK’s HaplotypeCaller with the following non-default parameters --ERC GVCF, --sample-ploidy 1 and -A AlleleFraction. Joint variant calling was performed across all samples using GATK’s GenomicDBImport and GenotypeGVCFs with --sample-ploidy 1 and a window size of 2.5 Mb. </p> <p>This dataset is the result of applying filters to monomorphic variants in the <a href="https://zenodo.org/record/6563420">filter2 dataset</a>, leaving 16.2M variants. The code used in filtering is outlined here: <a href="https://bitbucket.org/scriptBee/hapmap-pilot">https://bitbucket.org/scriptBee/hapmap-pilot</a>.</p>
AmelHap pilot: raw data
<p>Honey bee <em>Apis mellifera</em> drones are typically haploid, developing from an unfertilized egg, inheriting only their queen’s alleles and none from the many drones she mated with. Being haploid, the ordered combination or ‘phase’ of alleles is known, making drones a valuable haplotype resource. We collated whole genome sequence data for 688 drones, including 45 newly sequenced Scottish drones, which collectively represent 13 countries, 7 subspecies and various hybrids strains. After alignment to the reference assembly Amel_Hav3.1, and haploid variant calling, we identified 18.9M variants. </p> <p>Whole-genome sequencing data underpinning the dataset is available from the European Nucleotide Archive (ENA), <a href="https://www.ebi.ac.uk/ena">https://www.ebi.ac.uk/ena</a>, with the project accession codes: PRJEB16533, PRJNA311274, PRJNA363032, PRJNA516678, PRJNA544324, and PRJEB39369.</p> <p>Sequencing reads were aligned to the Amel_HAv3.1 reference genome using BWA-MEM v0.7.17. Reads were sorted with SAMtools v1.9 and duplicates marked (MarkDuplicates) with GATK v4.0.11.0. Variants for each sample were called using GATK’s HaplotypeCaller with the following non-default parameters --ERC GVCF, --sample-ploidy 1 and -A AlleleFraction. Joint variant calling was performed across all samples using GATK’s GenomicDBImport and GenotypeGVCFs with --sample-ploidy 1 and a window size of 2.5 Mb. </p> <p>This dataset is unfiltered, and contains all variants regardless of quality or call rate.</p> <p> </p>
Improving students' privacy awareness – Analysis of a pilot survey to design a VR environment for self-paced learning
<p>In this research, we measured the knowledge of students at the University of Debrecen in the field of data privacy awareness, online and password security.</p> <p><strong>Description</strong></p> <ul> <li>In the questionnaire, green-highlighted answer signs the correct answer to each question.</li> <li>Total data set contains the answers to each question and the respondent's age.</li> <li>Correct/incorrect data set contains information if the answer is correct to each question, and it also contains the respondent's age. One means the answer was correct, and zero means the answer was incorrect.</li> </ul>
Heritage Dataset around TAPI Pipeline, Afghanistan by EAMENA/ICONEM- Pilot Phase
This dataset contains 433 heritage sites documented by EAMENA and ICONEM along over 338 km of the TAPI (Turkmenistan-Afghanistan-Pakistan-India) gas pipeline project in Kandahar and Helmand provinces, Afghanistan, using remote sensing techniques.
Fastprk2 - Data (pilot Antwerp)
<p>Raw data from the project pilot in Antwerp (2018). </p> <p>25 FP-2 sensors have been tested.</p> <p><strong>Venue: </strong> </p> <p><em>15 Van Wesenbekestraat</em></p> <p><em>Antwerp, Belgium</em></p> <p><em>GPS location:</em></p> <p><em>51.2197107,4.4207293</em></p> <p> </p>
Fastprk2 - Data (pilot Barcelona - UPC)
<p>Raw data from the project pilot in Barcelona (UPC premises) in 2018. </p> <p>12 FP-2 sensors have been tested.</p> <p><strong>Venue: </strong> </p> <p>UPC</p> <p><em>Calle Jordi Girona, 31</em></p> <p><em>08034 Barcelona, Spain</em></p> <p><em>GPS coordinates: 41.3889784344569,2.1138623938485956</em></p>
Fastprk2 - Data (pilot Bouffemont)
<p>Raw data from the project pilot in Bouffemont (AFAPARK premises) in 2018. </p> <p>5 FP-2 sensors have been tested.</p> <p><strong>Venue: </strong> </p> <p><em>Parc D'activité de a Gare</em></p> <p><em>Rue Louise Michel</em></p> <p><em>95570 Bouffémont</em></p> <p><em>France</em></p> <p><em>GPS location: N49.044141 E2.3218549</em></p>
Fastprk2 - Data (pilot Grudziadz)
<p>Raw data from the project pilot in Grudziadz (2018). </p> <p>30 FP-2 sensors have been tested.</p> <p><strong>Venue:</strong></p> <p><em>28 Mickiewicza, 86-300 Grudziadz, Poland<strong> </strong> </em></p> <p><em>GPS location: 53.490854, 18.753113</em></p>
Fastprk2 - Data (pilot Wattens)
<p>Raw data from the project pilot in Wattens (2018). </p> <p>47 FP-2 sensors have been tested.</p> <p><strong>Venue: </strong></p> <p><em><a href="https://maps.google.com/?q=Blattenwaldweg+8+%0D+A-6112+Wattens&entry=gmail&source=g">Blattenwaldweg 8</a><br> A-6112 Wattens (Austria)</em></p> <p><em>GPS coordinates: 47.288307, 11.586749 </em></p>
CATCH-EyoU: Processes in Youth's Construction of Active EU Citizenship: Pilot Questionnaires: Estonia
<p>The data set was generated within the research project Constructing AcTive CitizensHip with European Youth: Policies, Practices, Challenges and Solutions (CATCH-EyoU) funded by European Union, Horizon 2020 Programme - Grant Agreement No 649538. The data set is a truncated version of the adolescents’ and young adults’ survey that was carried out in Estonia from May to June 2016. It merges results of two polls (16-18 and 20-26 year olds). Survey was conducted by University of Tartu (UT) within the WP7 research activity which aims at testing processes influencing societal and political engagement of young people.</p>
RAGE - Data Evaluation JobQuest pilot 2
<p><strong>General description: </strong>Data from the second (summative) Evaluation of the JobQuest game - pilot round 2</p> <p><strong>Topic</strong><br> ACM CSS 2012: Human-centered computing - Human computer interaction (HCI) - User studies, Usability testing<br> PsycINFO Classification: 3530 Curriculum & Programs & Teaching Methods</p> <p><strong>Name entitites</strong><br> Organizational information: Graz University of Technology, RANDSTAD<br> Geographical information: France<br> Time information: June-August 2018</p> <p><strong>Types</strong>: SPSS data file</p> <p><strong>RAGCS target group: </strong>target groups - demand side - end users - adults - unemployed, temporary workers</p> <p><strong>Evaluation dimensions</strong><br> Evaluation object: JobQuest game<br> Methodology/design: Pre-post test design<br> Evaluation variables: usability; user experience - usefulness, enjoyment; job search efficacy</p> <p><strong>Instruments:</strong> questionnaire items adapted from Career Self Efficacy Scale - CSES (Solberg et al., 1994), Job Seeking Self-Efficacy Scale - JSS (Barlow, Wright, & Cullen, 2002), Game User Experience Satisfaction Scale - GUESS (Phan, Keebler, & Chaparro, 2016), Intrinsic Motivation Inventory - IMI (Ryan, 1982)</p> <p><strong>Knowledge/skill elements</strong><br> RAGCS skills: cognitive skills - understanding, remembering, applying, creating; affective skills - interpersonal, intrapersonal<br> ESCO skills: provide assistance with job search (http://data.europa.eu/esco/skill/7903f946-aeff-4024-b146-8e48018d4eb9), prepare for job interview (http://data.europa.eu/esco/skill/929e89f9-ac69-4bcb-9eea-37257aa5aff9)<br> <br> <strong>Relationships</strong>: D8.4 Second RAGE Evaluation Report<br> Related dataset: <a href="https://doi.org/10.5281/zenodo.1209194">10.5281/zenodo.1209194</a>.</p>
VRTogether Pilot 2 Presenter video
<p>Video of the presenter in stereo format and green background for real-time background removal.</p> <p>Codec: H264 - MPEG-4 AVC</p> <p>Dimensions: 1040x600</p> <p>Framerate: 29.97 fps</p> <p>Bitrate: 13500kbps</p> <p>Audio: Stereo 48000 kHz</p>
VRTogether Pilot 2 Howard Anchor video
<p>Video of the news anchor in stereo format.</p> <p>Codec: H264 - MPEG-4 AVC</p> <p>Dimensions: 1536x768</p> <p>Framerate: 30 fps</p> <p>Bitrate: 3579kbps</p> <p>Audio: Stereo 48000 kHz</p>
VRTogether Pilot 2 connection with the reporter video
<p>Video of the reporter in stereo format 180º.</p> <p>Codec: H264 - MPEG-4 AVC</p> <p>Dimensions: 5760x2880</p> <p>Framerate: 29.97 fps</p> <p>Bitrate: 8805kbps</p> <p>Audio: Stereo 48000 kHz</p>
Supplemental data for: Mapping lifestyle factors in blood glucose variability in adolescents with Type 1 Diabetes Mellitus- A pilot study
<div> <p>The dataset was used in the paper “Mapping lifestyle factors in blood glucose variability in adolescents with Type 1 Diabetes Mellitus- A pilot study”. The article is currently under review for publication. DOI to be inserted.</p> </div> <div> <p>A data-in-brief article is to be published to give in-depth information about the data collected to improve reproducibility "Dataset for: Lifestyle Factors and Blood Glucose Variability in Adolescents with Type 1 Diabetes Mellitus". DOI to be inserted. </p> <p> </p> <p>The aim of the study was to assess whether adolescents with T1D in Ireland meet current nutrition and physical activity (PA) guidelines and to explore the impact of nutrition and PA on glycaemic variability (GV). The dataset includes continuous glucose monitoring (CGM) data, dietary intake records, and PA metrics, providing a comprehensive view of the participants' glucose levels and associated lifestyle behaviours.</p> </div>
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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.