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6,782 results for “project”
Ouse and Derwent Project: Samian ware
A fragment of a Roman cup was discovered by a metal detectorist working with the Ouse and Derwent Project on the site of our 2018 excavation at North Duffield. It was red *terra sigillata*, 'Samian ware' that was imported from Central Gaul in modern day France. Another distinctive sherd of Samian ware was recovered during the excavation, part of a flanged bowl. Both probably date to the 2nd century AD and are characteristically fine Roman table wares. This is a 3D reconstruction of what the vessels would have looked like when new. Source: Objaverse 1.0 / Sketchfab
Artemis sculpture for Metateca Project
Phogrammetric model of Artemide of Dresda. 3D models realized for Metateca Project. https://www.youtube.com/watch?v=2-wgzQlbD6A For more info http://www.metateca.it/ https://www.academia.edu/37421551/Dallo_scavo_allesperienza_immersiva_Il_progetto_Metateca_nellarea_archeologica_di_Aquinum Source: Objaverse 1.0 / Sketchfab
9 Items Box Project
9 Items Box Project I did for work experiance for college. Please follow and leave a like for future contant. Source: Objaverse 1.0 / Sketchfab
Prison of the death (modular asset project)
project that i got from my school to make modular asset and i made an old prisoner, where there is a witch that tried to summon a demon. i make all of the asset and the concept. -i make the concept -modeling -uv -texturing (substance) -lighting -render Collaboration Audio with: Emil Ribeiro Source: Objaverse 1.0 / Sketchfab
Ouse and Derwent Project 2019 - Trench 2
Trench 2 at Wheldrake revealed one small and two very large linear features. In the end we didn't have time to excavate these, but they confirmed the geophysical survey results -- these features are the enclosure ditches surrounding the round-house settlement. The [Ouse and Derwent Project](https://www.facebook.com/IAOuseandDerwent/) is a three year community project examining the Iron Age landscape in the Vale of York. It is funded by a grant from the Heritage Lottery Fund. Source: Objaverse 1.0 / Sketchfab
Exemplar Output to demonstrate FAIR Projection from a CSV file
<p>This is 1000 lines of sample data from UniProt that I will use to demonstrate the ability of FAIR Projection to dynamically project it out as RDF triples</p>
Standardizing ID-Labels for seaweed samples used for chemical composition analyses and refinery processes in Nordic and European research projects
<p><strong>Introduction</strong></p> <p>Seaweed samples can be divided into two groups:</p> <ol> <li>Small samples (½-3 kg wet weight (ww)) often used for chemical content analyses including seasonal variation and testing different cultivation conditions or preliminary lab scale experiments on storage, extraction, separation, fermentation, etc.</li> <li>Larger samples (>3 kg ww) for lab- or pilot scale experiments on storage, extraction, separation, fermentation, etc.</li> </ol> <p>Seaweed samples will always have the following information-tracks:</p> <ol> <li><strong>Sample Code: </strong>A ID containing the most important information and the sample code will follow the sampled biomass from harvest to final research results.</li> <li><strong>Seaweed Processing Code:</strong> The sample code will be extended with 8 digits and 1 letter if processing of biomass occurs.</li> <li><strong>Batch Number:</strong> A code describing details about the harvest and origin of the seaweed.</li> <li><strong>Sample Overview:</strong> An Excel file describing all details about the sample: first <strong>sample code</strong>, then species, grinding, freezing/drying specifications, seeding and harvesting information, planed aim of the sample (e.g. polysaccharides), place stored, seaweed processing details, analyse results, etc. Maintained by the sample provider.</li> </ol>
Infant Sibling Project: Sample Files
<p>These electroencephalography (EEG) data files were collected through the Infant Sibling Project (ISP), a prospective investigation examining infants at high versus low familial risk for autism spectrum disorder over the first 3 years of life. Here we provide a subset of the full dataset, as example files for the Batch EEG Automated Processing Pipeline (BEAPP), and the Harvard Automated Processing Pipeline for EEG (HAPPE). Both BEAPP and HAPPE may be downloaded at www.github.com.</p> <p>Baseline EEG data was collected while a young child sat in a parent’s lap watching a research assistant blow bubbles or show toys for several minutes.<sup>1</sup> 12 sample baseline EEGs are provided here, in .mat format. Auditory (event-related) EEG data was collected using an auditory double oddball paradigm, in which a stream of consonant-vowel stimuli was presented. Stimuli included a “Standard” /ɖa/ sound 80% of the time, “Native” /ta/ sound 10% of the time, and “Non-Native” /da/ sound 10% of the time.<sup>2</sup> 10 sample auditory EEGs are provided here, in .mff format.</p> <p>This sample dataset was chosen for demonstration of BEAPP and HAPPE for several reasons. First, the longitudinal nature of the study led to data collection with different sampling rates (250 Hz and 500 Hz) and acquisition setups (64-channel Geodesic Sensor Net v2.0, and 128-channel HydroCel Geodesic Sensor Net, both from Electrical Geodesics, Inc., Eugene, OR). Additionally, because young children cannot follow instructions to “rest” or remain still, EEG in these children typically contains greater amounts of artifact than EEG in typical adults. BEAPP and HAPPE are targeted towards addressing these challenges.</p> <p>The Infant Sibling Project was carried out in accordance with the recommendations of the Institutional Review Board at Boston University and Boston Children’s Hospital (#X06-08-0374), with written informed consent from all caregivers prior to their child’s participation in the study. All files here have been deidentified, including alteration of exact acquisition dates. Acquisition times have not been altered.</p> <p>For additional information about data collection paradigms, and sample studies published on the larger ISP data set, please see the following references:</p> <p>1. Levin, A. R., Varcin, K. J., O’Leary, H. M., Tager-Flusberg, H., and Nelson, C. A. (2017). EEG power at 3 months in infants at high familial risk for autism. <em>J. Neurodev. Disord.</em> 9, 1–13.</p> <p>2. Seery A, Tager-Flusberg H, Nelson CA. Event-related potentials to repeated speech in 9-month-old infants at risk for autism spectrum disorder. J. Neurodev. Disord. 2014;6:43.</p>
Dataset for IDRC Project: Exploring the opportunities and challenges of implementing open research strategies within development institutions. International Development Research Center.
<p>Data Package: Exploring the opportunities and challenges of implementing open research strategies within development institutions</p> <p>DOI for this package: https://doi.org/10.5281/zenodo.844394<br> Project Description: https://doi.org/10.3897/rio.2.e8880<br> Data Management Plan: https://doi.org/10.3897/rio.3.e14672<br> Other Related Documents and Reports: https://riojournal.com/collection/18/<br> Funder: International Development Research Centre/Centre de rechereches pour le développement international, https://doi.org/10.13039/501100000193</p> <p><br> Abstract<br> ========</p> <p>This is the Data Package for the project "Exploring the opportunities and challenges of implementing open research strategies within development institutions" the proposal for which was published as https://doi.org/10.3897/rio.2.e8880. The research project conducted open data pilot case studies with seven IDRC grantees to develop and implement open data management and sharing plans. The results of the case studies served to refine guidelines for the implementation of development research funders’ open research data policies.</p> <p>Contents<br> ========</p> <p>The Data Package contains all the public data generated by the project. The package was curated and metadata generated, including an HTML Catalog using the Calcyte Tool (https://codeine.research.uts.edu.au/eresearch/calcyte) developed at University of Technology Sydney.</p> <p>The project had two major phases:</p> <p>1. A review, based on desk work and interviews with data management experts<br> 2. Case studies, based on implementing open data practices within seven IDRC funded research projects</p> <p>Review<br> ------</p> <p>The review, published at https://riojournal.com/article/14673/ was supported by desk work and interviews. The materials related to the interviews can be found in the directory:</p> <p>* Policy and Implementation Review Interviews</p> <p>Case Studies<br> ------------</p> <p>Seven IDRC-funded projects were contributed to the pilot project.</p> <p>The materials generated by the case studies and used to support the final report (to be published with the collection at https://riojournal.com/collection/18/) are found in the following directories.</p> <p>* Introductory_Data_Workshop_Materials<br> * Introductory_Workshop_Presentations<br> * Data Management Planning<br> * SciDataCon Presentations<br> * Final_Project_Workshop_Materials<br> * Final_Project_Workshop_Presentations</p> <p>The files are encoded with a three letter code that identifies the relevant contributing project in each case. The contributing projects were:</p> <p>* Crowd Sourcing Data to fight Social Crimes: Harassmap, Egypt (HMP)<br> * The Brazilian Virtual Herbarium: CRIA, Brazil(BVH)<br> * Strengthening the Economic Committee of the National Assembly in Vietnam: Centre for Analysis and Forecasting, Vietnam (ECV)<br> * The Impact of Copyright User Rights: Derechos Digitales, Columbia (DED)<br> * Establishing a clearinghouse for tobacco economic data in Africa: DataFirst, South Africa (TED)<br> * Les problèmes négligés des systèmes de santé en Afrique : une incitation aux réformes: LASDEL, Niger (NDF)<br> * Indigenous Knowledge in Climate Change: Natural Justice, South Africa (IKC)</p> <p>More details will be found in the Case Studies and in the Final Report (forthcoming at https://riojournal.com/collection/18/)</p> <p>References<br> ==========</p> <p>* Neylon C, Chan L (2016) Exploring the opportunities and challenges of implementing open research strategies within development institutions. Research Ideas and Outcomes 2: e8880. https://doi.org/10.3897/rio.2.e8880<br> * Neylon C (2017) Data Management Plan: IDRC Data Sharing Pilot Project. Research Ideas and Outcomes 3: e14672. https://doi.org/10.3897/rio.3.e14672<br> * Neylon C, Chan L (2016-17) Exploring the opportunities and challenges of implementing open research strategies within development institutions: A project of the International Development Research Center, Research Ideas and Outcomes Collection, https://riojournal.com/collection/18/</p> <p> </p>
Replication Kit for Paper: "Are There Any Unit Tests? An Empirical Study on Unit Testing in Open Source Python Projects"
<p>Replication Kit for the Paper "Are there any Unit Tests? An Empirical Study on Open Source Python Projects" by Fabian Trautsch, Jens Grabowski.</p> <p>You can cite the paper via:</p> <p>@inproceedings{trautsch2017there,<br> title={Are There Any Unit Tests? An Empirical Study on Unit Testing in Open Source Python Projects},<br> author={Trautsch, Fabian and Grabowski, Jens},<br> booktitle={Proceedings of the IEEE International Conference on Software Testing, Verification and Validation (ICST)},<br> pages={207--218},<br> year={2017},<br> organization={IEEE}<br> }</p> <p> </p> <p>Contents:<br> 1) Used version of the vcsSHARK<br> - located in “vcsSHARK”<br> 2) Used version of the testImpSHARK<br> - located in “testImpSHARK”<br> 3) Analysis implementations<br> - located in “testImpSHARK/testimpshark/analysis”<br> 4) Raw Data CSV Files<br> - located in “testImpSHARK/testimpshark/analysis/data<br> 5) Raw MongoDB<br> - located in “mongo_backup”</p> <p><br> Usage:<br> 1) Usage instructions for the vcsSHARK is given on its github homepage (http://ftrautsch.github.io/vcsSHARK/index.html) or directly in the “vcsSHARK/pyvcsshark/main.py” file</p> <p>2) Usage instructions for the testImpSHARK:<br> - if only one revision should be analyzed use “testImpSHARK/main.py”<br> - if all revisions should be analyzed use “testImpSHARK/execution.py”<br> - in both files concrete instructions can be found</p> <p>3) Each analysis file is commented. For some of them (rq1_boxplot.py and rq4.py the connection to the MongoDB must be changed). For the R files, the path to the data must be adapted. Otherwise, the files can be directly executed.</p> <p>4) The MongoDB can be restored via:<br> mongorestore --gzip --archive=smartshark040816.gz --db smartshark --host <HOST> --port <PORT> --username <USERNAME> --password <PASSWORD> --authenticationDatabase <AUTHENTICATION_DATABASE></p> <p><br> Tests:<br> 1) The tests can be run directly via the unittest framework of python: e.g., python -m unittest tests/test_common.py</p>
First picture of the Deep Mapping Project
<p>This is a picture taken by a professionnal kitesurfer in Le Morne, Mauritius.</p>
NANCY SNS-JU PROJECT "ITALTEL ITALIAN IN-LAB TESTBED - LATENCY METRICS"
<p>In the context of the NANCY project (https://nancy-project.eu/), this Dataset provides input data for the development of the B-RAN and attacks models for the NANCY framework, to model training and model inference functions. The data collected plays the role of ML algorithm-specific data preparation. The dataset contains time-series, collected transmitting a video content through the Italtel "VTU - video streaming and transcoding application", that can convert audio and video streams from one format to another, at multiple encodings schemes, changing resolution, bitrate, and video parameters. The data collected are related to the observation of some of the resources involved in the Usage Scenario: “Fronthaul network of fixed topology – Direct Connectivity/CoMP Connectivity”. In the Italtel Italian in-lab testbed, a MEC assisted 5G network scenario with a video streaming application for generating traffic is provided. Two different scenarios were set-up, related to downstream and upstream video flows. Each file captured is associated to a 10min video streaming of the “Big Buck Bunny” video. This video was transmitted with different resolutions, 480p, 720p, 1080p, 2160p; both in uplink (UL) and in downlink (DL); the type of metrics monitored is RTT (Round Trip Time).</p>
Project Data TERRA and Telomeres
<p>Dados produzidos durante o desenvolvimento do projeto:</p> <p><span>PAPEL DO TERRA NA REGULAÇÃO DA MANUTENÇÃO DOS TELÔMEROS E NA SENECÊNCIA REPLICATIVA EM <em>Leishmania major</em></span></p> <p><strong><span>Bolsista</span></strong><span>: Luiz Henrique de Castro Assis</span></p> <p><span> </span></p> <p><strong><span>Supervisor(a)</span></strong><span>: Professora Dr<sup>a</sup>. Maria Isabel Nogueira Cano</span></p> <p><strong><span> </span></strong></p> <p><strong><span>Processo</span></strong><span>: FAPESP 2021/04253-7 - <strong>Vigência</strong>: 06/2021 a 03/2024</span></p>
Subset of global model sea level data for "Challenges, Advances and Opportunities in Regional Sea Level Projections: the Role of Ocean-shelf Dynamics"
<p>Monthly sea surface height above the geoid data in NW European seas from six global simulations using the NEMO ocean model (https://www.nemo-ocean.eu/) for 1990 to 2009</p> <p><strong>ORCA0083_DFS_NWS_ssh_1990_2009, ORCA025_DFS_NWS_ssh_1990_2009, ORCA1_DFS_NWS_ssh_1990_2009,</strong> are the N006 simulation set created by Andrew Coward and the NOC Marine Systems Modelling team as used by:</p> <p>Baker et al 2022 Biological Carbon Pump Sequestration Efficiency in the North Atlantic: A Leaky or a Long-Term Sink? Global Biogeochemical Cycles <a href="https://doi.org/10.1029/2021GB007286">https://doi.org/10.1029/2021GB007286</a>,</p> <p>Wilson, C. <em>et al.</em> 2021 Significant variability of structure and predictability of Arctic Ocean surface pathways affects basinwide connectivity. <em>Commun. Earth Environ.</em> <strong>2</strong>, 164. <a href="https://doi.org/10.1038/s43247-021-00237-0">https://doi.org/10.1038/s43247-021-00237-0</a> (2021).</p> <p>These simulations are forced by the Drakkar Forcing Set 5.2 (DFS) and initialised at 1958, with a nominal 1/12, 1/4 and 1 degree resolution. See references for further model details.</p> <p><strong>ORCA025_JRA_NWS_ssh_1990_2009, ORCA025_JRA_tides_NWS_ssh_1990_2009, ORCA025_JRA_ShelfPhysics_NWS_ssh_1990_2009, </strong>are new simulations produced by Chris Wilson, James Harle and the Shelf Enabled NEMO team. All are forced by the JRA reanalysis, initialised in 1976.</p> <p><strong>ORCA025_JRA_NWS_ssh_1990_2009</strong> is a reference run based on GO9, an evolution of the Joint Marine Modelling Programme configuration described by Storkey et al 2018 UK Global Ocean GO6 and GO7: a traceable hierarchy of model resolutions, Geoscientific Model Development https://gmd.copernicus.org/articles/11/3187/2018/</p> <p><strong>ORCA025_JRA_tides_NWS_ssh_1990_2009</strong> adds explicit tides to this.</p> <p><strong>ORCA025_JRA_ShelfPhysics_NWS_ssh_1990_2009</strong> adds tides, Generic Length Scale Mixing and Multi-envelope vertical coordinates</p> <p>Details of these simulations can be found here:</p> <p>https://github.com/NOC-MSM/SE-NEMO </p>
Machine Learning for O2 Project (ML4O2)
<p>Gridded maps of dissolved oxygen based on machine learning algorithms. </p>
Simulations dataset and pre-trained models of "Deep learning in real-time on the astrophysical data obtained from the Čerenkov CTA Observatory" Ph.D. project
<p>Ph.D. project datasets and models release, <br><em>Deep learning in real-time on the astrophysical data obtained from the Čerenkov CTA Observatory.</em></p>
Spotlight Project Data - How people of colour experience and engage with climate change in Britain
<div> <div> <div> <div> <p>This repository contains data from a survey which was designed by Charles Ogunbode and Jeremy Kidwell to capture climate change-related experiences, perceptions, emotions, actions and policy preferences among UK people of colour. We are grateful for input on instrument design and analysis by Nick Anim, Dr Amiera Sawas and Serayna Solanki as well as from the project steering group: Zarina Ahmad (University of Manchester), Sara Jane Nii-Adjei (Christian Aid), Meena Rajput (Greenpeace), Reuben Fakoya-Brooks (REED Ecological Network/British Ecological Society) and Dr Neema Begum (University of Nottingham).</p> <p>Respondents included ethnic minority UK residents aged 18 years or over (N = 1,008) and the sample was gathered in March 2022 by Qualtrics Research Services. The instrument was pre-tested with a smaller number of respondents (N = 180) on 25 Feb 2022.</p> <p>The data is provided in plain-text tab-separated values format (.tsv) as well as in SPSS .sav file format. The latter is recommended for analysis, and there is an associated code repository (linked below) which contains R code used to load and analyse this data (using the haven() SPSS library). We have also included the original instrument used to collect survey data in qualtrics .qsf format and docx format. Please note: some data columns have been redacted and are not included in this data release.</p> <p>The research was funded by a Research England QR-PSF award made through the University of Birmingham.</p> <p>We very much hope that by making this data as widely available as possible, other colleagues may find opportunities to expand on this research. Towards that end, we have also made available (a) <a href="https://zenodo.org/records/11130504">an open-access plain language report </a>analysing this data, (b) <a href="https://github.com/climate-experiences/spotlight-report">all of the R code written to produce the analysis in our report</a> which others may freely use and appropriate and (c) an open access online textbook which introduces the R programming language to researchers who may not have existing data science expereince. <a href="https://kidwellj.github.io/hacking_religion_textbook/chapter_2.html">Chapter two of that textbook</a> makes explicit (and more basic) use of this dataset with specific examples and explanations of how to build the code.</p> </div> </div> </div> </div>
Dataset belonging to SNF project: Use of physiologically based pharmacokinetic modelling to simulate dosing requirements of long-acting intramuscular antiretroviral drugs in special populations and to manage drug-drug interactions
Open the record for dataset details and reuse information.
Projections of Earth's technosphere: Worldbuilding pipelines
<p>This repository contains the ten worldbuilding pipeline documents from the paper titled "Projections of Earth’s technosphere: Scenario modeling, worldbuilding, and overview of remotely detectable technosignatures" by Haqq-Misra, Profitiliotis, and Kopparapu (2025, <em>Technological Forecasting and Social Change</em>, 218: 124194, <a href="https://doi.org/10.1016/j.techfore.2025.124194" target="_blank" rel="noopener">doi:10.1016/j.techfore.2025.124194</a>).</p> <p>For more information about this project, visit <a href="https://futures.bmsis.org/" target="_blank" rel="noopener">futures.bmsis.org</a>.</p>
2023 Results of Complex Academic Integrity and Open Science Surveys of OPTIMA Project
<p>We publish the list of questions and results (datasets) of the complex survey conducted at the National level in Ukraine and within the Ukrainian partner universities of the <a href="https://lpnu.ua/en/optima">OPTIMA project</a> from Dec 04 – Dec 31, 2023. Identical surveys were conducted in <a href="https://doi.org/10.5281/zenodo.8067080">2021</a> and <a href="https://doi.org/10.5281/zenodo.8067262">2022</a>.</p> <p>The survey aims to study the attitude of Ukrainian students and the academic community toward the values of academic integrity and open scientific practices, as well as to identify typical examples of dishonest behavior in Ukrainian higher education institutions. Participation in the survey was voluntary and anonymous, and its results (collected data and their analysis) will be published in open access. Ethical approval for the survey was waived by the Ethics Committee of the Lviv Polytechnic National University Academic Board. This waiver of approval was provided due to non-sensitive data obtained from the survey respondents. </p> <p><strong>Number of participants in the complex survey in 2023:</strong></p> <ul> <li>National Survey - 4560</li> <li>Lviv Polytechnic National University - 530</li> <li>Sumy State University - 327</li> <li>Vasyl Stus Donetsk National University - 231</li> <li>Lutsk National Technical University - 146</li> </ul>
ScienceDex guides
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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.