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390 results for “template”
UNIC Templates for uploading corpus metadata v1.11
<p>The UNIC platform (https://unic.dipintra.it) accepts a JSON file for uploading corpus metadata based on the template here. Alternatively, use the spreadsheet template to input the corpus metadata and convert the resulting .xlsm file to JSON using this application at https://huggingface.co/spaces/nannanliu/UNIC_metadata_conversion. When opening the Excel spreadsheet template, please enable Macros, which will automatically validate your input in the columns. Please do not change the order of the columns because they are embedded with code. To add elements and components not included by the UNIC schema, create new columns after the existing ones.</p>
Vascular Territory template and atlases in MNI space
<p><strong>Data</strong></p> <p>Sixteen subjects (mean age (sd): 69.6 (8.2); 37.5% female) were recruited to generate a high-resolution template. The cohort consists of twelve stroke-free, non-demented patients with the sporadic form of cerebral amyloid angiopathy (CAA), and similarly-aged healthy controls (n=4). Each participant underwent high-resolution MRI with a Siemens Magnetom Prisma 3T scanner (using a 32-channel head coil) as part of a separate study. The standardized protocol included a Multiecho T1-weighted (voxel size: 1x1x1 mm<sup>3</sup>; Repetition Time [TR]: 2510 ms), a 3D-FLAIR (voxel size: 0.9x0.9x0.9 mm<sup>3</sup>; TR: 5000 ms; TE: 356 ms), and a T2-weighted Turbo Spin Echo (voxel size: 0.5x0.5x2.0 mm<sup>3</sup>; TR: 7500 ms; TE: 84 ms) sequence. Scans were manually assessed to ensure no gross pathology was present, such as hemorrhage or silent brain infarcts.</p> <p><strong>Template and territorial map creation</strong></p> <p>We employed Advanced Normalization Tools (ANTs) for image processing (Avants et al., 2010, 2011) for creating a brain template based on multimodal information using T1, T2 and 3D-FLAIR sequences. After template creation, we smoothed the resulting templates (FSL; Gaussian smoothing, sigma = 1) and registered the resulting templates into MNI space, again using ANTs (Avants et al., 2011).</p> <p>Vascular territories were outlined on the right hemisphere in the T1-weighted atlas image and contain anatomically validated ACA, MCA, and PCA territories supratentorially. The right hemispheric map was then mirrored onto the left hemisphere to create a full-brain vascular territory map, which was manually assessed and corrected where necessary.</p> <p> </p> <p>For more details, please see the original publication that utilized the template. If you utilize this template, please also cite</p> <p>Schirmer, Markus D., et al. "Spatial signature of white matter hyperintensities in stroke patients." <em>Frontiers in neurology</em> 10 (2019): 208.</p> <p><a href="https://doi.org/10.3389/fneur.2019.00208">https://doi.org/10.3389/fneur.2019.00208</a></p> <p> </p> <p><strong>Files</strong></p> <p><strong>FLAIR template</strong>: caa_flair_in_mni_template_smooth.nii.gz<br> <br> <strong>FLAIR template after brain extraction and intensity normalization</strong>: caa_flair_in_mni_template_smooth_brain_intres.nii.gz<br> <br> <strong>T1 template</strong>: caa_t1_in_mni_template_smooth.nii.gz 27.7 Mb<br> <br> <strong>T2 template</strong>: caa_t2_in_mni_template_smooth.nii.gz 27.7 Mb<br> <br> <strong>Vascular territory map</strong>: mni_vascular_territories.nii.gz</p>
SQLite database to accompany the paper, "Statistical learning mitigation of false positives from template-detected data in automated acoustic wildlife monitoring"
<p>This dataset is a SQLite database that accompanies methods and analysis described in the paper, "Statistical learning mitigation of false positives from template-detected data in automated acoustic wildlife monitoring" (Balantic & Donovan 2019, Bioacoustics, https://www.tandfonline.com/doi/full/10.1080/09524622.2019.1605309). </p> <p>A Github repository containing code for using the SQLite database also accompanies this paper at: <a href="https://github.com/cbalantic/false-positive-mitigation">http://github.com/cbalantic/false-positive-mitigation</a></p>
A unified template for sediment source fingerprinting databases
<p>Over the last few years, the sediment source fingerprinting community has been engaged in promoting best practices to improve the design and the implementation of sediment fingerprinting techniques (<a href="https://doi.org/10.1007/s11368-022-03203-1">Evrard et al., 2022</a>). Data sharing is a key part of open science making research more reliable and accessible to the community. To move forward and improve data sharing, we propose these templates for databases and metadata.</p> <p>These templates include: common metadata for samples (soil, river flood deposit, sediment core...) description (name, IGSN, location, sampling date...), list and description of common properties (elemental geochemistry, organic matter, radionuclides…) used in sediment source fingerprinting studies. These templates are intended to evolve thanks to the participation of the community, as part of a collaborative project.</p> <p>In addition, the <strong>collectionneur </strong>R package was designed to help researchers and data managers maintain an up-to-date and well-organized database. is avalaible on <a href="https://github.com/tchalauxclergue/collectionneur"><strong>GitHub</strong> (https://github.com/tchalauxclergue/collectionneur)</a> and <a href="https://doi.org/10.5281/zenodo.15146958"><strong>Zenodo</strong> (https://doi.org/10.5281/zenodo.15146958)</a>. It facilitates the comparison and integration of new data entries into an existing database while keeping a detailed report of all modifications. All database formats are allowed, although it was initially designed for sediment source fingerprinting databases.</p> <p>Published databases following these templates are listed in the References section below. </p>
Dataset of the publication "Halide Perovskites as Disposable Epitaxial Templates for the Phase-Selective Synthesis of Lead Sulfochloride Nanocrystals"
<p>This dataset provides the raw data associated with the publication "Halide Perovskites as Disposable Epitaxial Templates for the Phase-Selective Synthesis of Lead Sulfochloride Nanocrystals".It contains:</p> <ul> <li>A readme file meant to help the user navigate the database</li> <li>The raw data associated with all the plots and charts found in the Main Text and in the Supplementary information.</li> <li>The raw data collected during the 3D electron diffraction experiments on Pb<sub>3</sub>S<sub>2</sub>Cl<sub>2</sub> Nanocrystals. </li> <li>The CIF files of all the crystal structures refined in the work</li> <li>An atomistic model of the Pb<sub>4</sub>S<sub>3</sub>Cl<sub>2</sub>/CsPbCl<sub>3</sub> interface, which can be visualized with the freeware software Vesta. </li> </ul>
Zeolite Templated Carbon Materials - DFTB Structural Database
<p>Zeolite-templated carbon (ZTC) is a unique porous carbonaceous material in that its structure is ordered at the nanometre scale, enabling a representative periodic description at the atomistic level. A structural library for ZTC of varying compositions was created using density functional tight binding (DFTB) potentials parameterized for materials science applications (matsci-0-3). We provide here quantum chemical-refined structures of models with CH, CHO, CHON, CHOB, and CHOBN compositions with various degrees of heteroatom substitution. The "initial ZTC structure" files correspond to the initial model used in our work that was developed using molecular mechanics, empirical force fields. These structural models comprise the characteristic morphological features of highly porous carbon materials, such as open-blade surfaces, edges, saddles, and closed-strut formations, spanning a range of curvatures and characteristic sizes. The optimized structures in CIF and native DFTB file formats are organized in the "stationary structure" file based on the optimization pathways that lead to the stationary structures.</p> <p>Secondly, we carried out alternating compression and expansion of the CHO model unit cell to determine the lowest energy structure as well as to obtain the bulk modulus. The file "bulk modulus" contains two data sets that describe the deformational energy landscape of pure faujasite zeolite, Na-substituted zeolite, and the ZTC model structure.</p> <p>The file "analysis tools" is a representative compilation of utilities for file format conversion, fractional vs. Cartesian crystal coordinates, and structural analysis spreadsheets.</p> <p>The agreement between experimental measurements and the computational model is remarkable that demonstrates the power of approximate density functional theory as a cost-effective computational tool with chemical accuracy for the investigation of structure/property relationships in real-world carbon-based solids.</p>
OpenAIRE and FAIR Data Expert Group survey about Horizon 2020 template for Data Management Plans
<p>This dataset is published in 2017 by the OpenAIRE project and the FAIR Data Expert Group.</p> <p>It contains two survey data files, two pdf-files summarising the results in a report and an infographic, and a Readme.txt file.</p> <p>The OpenAIRE project supports the open science ambitions of the European Commission. The project and in particular the Research Data Management team provide support, training and information on the Open Research Data Pilot. In this context, a survey was carried out to collect feedback on the Horizon 2020 template for Data Management Plans (DMPs). The team collaborated with the FAIR data expert group, which is providing recommendations to the European Commission on turning FAIR data into reality. One of the specific tasks of the Expert Group is contributing to an evaluation of the Horizon 2020 approach to DMPs, including future revisions of the template and the development of additional sector/ discipline-specific guidance. The aim of the survey was to collect experiences of researchers and DMP reviewers with the DMP template and guidelines on FAIR data management in Horizon 2020. The survey assesses the usefulness of the guidelines and any aspects that are confusing and unclear to determine what improvements can be made.</p> <p>Feedback was sought from both researchers and research support staff. The survey was initially scheduled to run from 22 May to 21 June 2017. Several organisations were asked to help announce the survey, including OpenAIRE’s National Open Access Desks, the FAIR data expert group, FOSTER, LIBER, and the RDA Interest Group on Active DMPs. When the first survey responses showed only a small share of researchers, more stakeholders were contacted to specifically target this community. The European Research Area was approached, whose project officers circulated the survey call among award holders of EC projects. Early-career researchers were also informed through the YEAR network and EURODOC. This resulted in an extension of the survey to 21 July 2017.</p> <p>At the close of the survey on 21 July 2017, a total number of 289 responses were reached. 50% of the respondents indicated that they were researchers, and 60% that they were (also) research support staff. OpenAIRE and the FAIR data expert group are very pleased with this balanced outcome and would like to thank all colleagues and organisations who promoted the survey, as well as everyone who took part in it.</p> <p> </p>
Excel template for the aggregate database on descriptive representation of the ActEU project
<p>This is the Excel template used to structure the databases that provide data at the legislature / party level for each of the six countries studied in Tasks 4.1 and 4.2 of the ActEU project.</p>
Feature Template Angular Power Spectra
<p>This data was used in the machine learning analysis of the Cosmic Microwave Background data in: https://github.com/IndiraOcampo/CMB_ML_based_model_selection.git and https://dx.doi.org/10.1088/1475-7516/2025/02/004</p> <p>The objective is to train a neural network architecture on the different polarization modes (TT, TE, EE and joint) to perform model selection between the standard cosmological model, ΛCDM and a model that introduces a Feature Template (FT) in the primordial power spectrum - related to the early Universe physics.</p> <p>The first row corresponds to the multipole moment "\ell" and the remaining ones correspond to the different components of the Cl's angular power spectrum, for the different values of A_lin (the feature oscilation parameter). While A_0 = 10^-2 is a reasonable value that still agrees with observations, A_0 = 0 corresponds to the ΛCDM model.</p> <p>Finally, our aim is to apply SHAP to perform feature importance (interpretability) in our results.</p>
PROSEU Collective Renewable Energy Prosumers Stakeholders Database (Template)
<p>As part of work package nº2 of the H2020 PROSEU project, which aimed to establish a baseline review and characterisation of renewable energy sources (RES) prosumer (self-consumption) initiatives across Europe, databases identifying the diversity of collective forms of RES prosumers and related stakeholders were built by the project partners using the templates and respective variables presented here (English language). The databases served to create a stratified sample of RES prosumer initiatives for purposes of a survey, as well as distinguish them from other stakeholders in the field.</p>
Human Brain MRI Template and Myelin Atlas
<p>The structural template, quantitative myelin water imaging atlases, tissue segmentations, and regions of interest (ROIs) generated and analyzed for <em>An atlas for human brain myelin content throughout the adult life span</em></p> <p><a href="https://www.nature.com/articles/s41598-020-79540-3">https://www.nature.com/articles/s41598-020-79540-3</a></p>
Supplementary data files for manuscript titled "From spreadsheet lab data templates to knowledge graphs: A FAIR data journey in the domain of AMR research"
<div>This data repository contains all the necessary supplementary files for the manuscript titled "<strong>From spreadsheet lab data templates to knowledge graphs: A FAIR data journey in the domain of AMR research.</strong>"</div> <div> </div> <div>The repository is a copy of the <a href="https://github.com/IMI-COMBINE/template2graphs">GitHub page</a> with the source code used to generate the graph and additional files required for the Lab Data Template.</div> <div> </div> <div>Below we provide a brief overview of the data files in the `additional folder` and their underlying purpose:</div> <div> <ul> <li>The <strong>Data Survey</strong> collects relevant project and data set information to set up a Data Management Plan. It can serve as an input for Lab Data Template development.</li> <li>The <strong>Lab Data Templates</strong> facilitate the collection of AMR research data (in vivo and in vitro) in several sub-tables. The Excel format is compatible with upload procedures into the data repository 'grit' and serves as input for a knowledge graph workflow.</li> <li>The <strong>Data dictionary</strong> is connected to the Lab Data Templates and ensures harmonized data entries. In addition, the dictionaries collect metadata beyond the content of the Lab Data Template (e.g. bacterial strain information or compound information) and link to ontologies where possible.</li> <li>The <strong>FAIR assessments</strong> have been used as a primer for improving the template. This report is generated using the FAIR-DSM model.</li> </ul> </div> <div>The templates have been used during the IMI2 GNA NOW project to collect information and have been improved according to FAIR standards in collaboration with the IMI FAIRplus project ("post FAIRification").</div>
Template for HFLAV results in Zenodo
<h2>HFLAV results for Unitarity Triangle March 2024</h2> Cite the results presented as<br> S. Banerjee et al., <i>Averages of b-hadron, c-hadron, and tau-lepton properties as of 2023</i>, <a href="https://arxiv.org/abs/2411.18639">arXiv:2411.18639</a>, with specific result from <a href="https://doi.org/10.5072/zenodo.16917540">doi:10.5072/zenodo.16917540</a>.<br> Alternatively use the bibtex record<br> <code> @article{HeavyFlavorAveragingGroupHFLAV:2024ctg,<br> author = "Banerjee, Swagato and others",<br> collaboration = "Heavy Flavor Averaging Group (HFLAV)",<br> title = "{Averages of $b$-hadron, $c$-hadron, and $\tau$-lepton properties as of 2023}",<br> eprint = "2411.18639",<br> archivePrefix = "arXiv",<br> primaryClass = "hep-ex",<br> month = "11",<br> year = "2024"<br> note = "{with specific result from \href{https://doi.org/10.5072/zenodo.16917540}{{\texttt{doi:10.5072/zenodo.16917540}}}}"<br> }<br> </code>
High-resolution earthquake catalog obtained through template-matching in the Southern Apennine (Italy)
<p>This is an enhanced, high-resolution earthquake catalog obtained through template-matching (TM). It covers the area of the Southern Apennines (Italy), for the period 2009-2014</p> <p>Starting from about 4000 events used as templates, TM allowed to detect the hidden, small-magnitude seismicity in the 0-1 magnitude range, allowing a significant decrease of the magnitude of completeness in the resulting earthquake catalog.</p> <p>The catalog contains:</p> <ul> <li>templates (events catalogued by INGV and used as templates)</li> <li>template-matching detections (i.e. newly detected events by TM)</li> <li>events catalogued by INGV that are also found through template-matching</li> </ul> <p>All events are located with the same 1-D velocity model obtained by averaging several models that have been proposed in the literature, covering different portion of the Southern Apennines. </p> <p><strong>DATA STRUCTURE</strong></p> <p><strong>id</strong>: id of event. Events detected by template-matching start with 'TM', otherwise the id is the same as in the official INGV catalog.</p> <p><strong>lon</strong>: longitude (degrees)</p> <p><strong>lat</strong>: latitude (degrees)</p> <p><strong>depth</strong>: depth in km</p> <p><strong>time</strong>: origin time</p> <p><strong>M_l</strong>: local magnitude</p> <p><strong>lon_error</strong>: error on longitude (degrees)</p> <p><strong>lat_error</strong>: error on latitude (degrees)</p> <p><strong>depth_error</strong>: error on depth (km)</p> <p><strong>RMS</strong>: root-mean-square (sec)</p> <p><strong>az_gap</strong>: azimuthal gap</p> <p><strong>n_phases</strong>: total number of P and S arrivals </p> <p><strong>n_stations</strong>: total number of station recording the event</p> <p><strong>mag_diff</strong>: difference in magnitude between detection and its template</p> <p><strong>dt</strong>: difference in origin time between template and detected event (sec)</p> <p><strong>templ_id</strong>: id of the template event</p> <p><strong>as_template</strong>: =1 if the event was used as template, 0 otherwise</p> <p><strong>matched_TM</strong> (for events already catalogued by INGV): =1 if the events matched a detection made by template matching, =0 otherwise</p> <p><strong>matched_BSI</strong>: ==id of the corresponding event catalogued by INGV. For newly detected events (thus never catalogued before) this field is 'NA'</p>
EUGAIN Policy Influence Plan Template
<p>This is the EUGAIN Policy Influence Plan Template.</p> <p>It was created within the European Union COST Action CA-19122 in 2024, published as figure in Deliverable 8, the Handbook.</p>
Ultrathin epitaxial Bi film growth on 2D HfTe2 template (data)
<p>This dataset contains the raw data files connected to the figures included in the paper "<em>Ultrathin epitaxial Bi film growth on 2D HfTe<sub>2</sub> template</em>" by E. Xenogiannopoulou et al., 2022 <em>Nanotechnology</em> <strong>33</strong> 015701; <a href="https://doi.org/10.1063/5.0038799">https://doi.org/10.1088/1361-6528/ac2d08</a></p> <p>An Open Access version of the paper can be found here: <a href="https://zenodo.org/record/4562057#.YaDC4NBBxPY">https://zenodo.org/record/5720132#.YaDKWNBBxPb</a></p>
ACR PET phantom raw data and templates for advanced analysis
<p>A zipped folder containing raw PET data of the ACR phantom, which was acquired first for 30 minutes without any activity outside the axial field of view (FOV), followed by another 30 minutes of acquisition with activity outside the FOV.</p> <p>Each acquisition comes with the UTE mu-map in DICOM format, included in both raw data folders, <raw> and <raw_ofov>.</p> <p>Since the MR-based mu-maps are not of sufficient accuracy, the synthetic mu-map has been included (and also the generated hardware mu-map).</p> <p>The design for the templates for generating the synthetic mu-map, NAC PET image, and sampling VOIs are included in folder <design>.</p> <p> </p>
Templates for BWS IPA and NPS project evaluations
<p>Templates with example data to facilitate the completion of project evaluations using Excel to undertake three analyses:</p> <p>1. Importance-Performance Analysis (IPA) with Gap Analysis</p> <p>2. Net Promoter Score</p> <p>3. Best-Worst-Scaling template in seperate file in version 1</p>
Spreadsheet template for Body Size Data for North American Orthopteroid Insects
<p>Body size data for orthopteroid insects extracted from:</p> <p>Vickery, V.R., Kevan, D.K.McE., 1985. The insects and arachnids of Canada, Part 14. The Grasshoppers, Crickets, and Related Insects of Canada and Adjecent Regions. Research Branch Agriculture Canada Publication 1777:1-918.</p>
Spreadsheet Template for Body Size Data for North American Hemiptera
<p>Body size data for North American Hemiptera extracted from The Insects and Arachnids of Canada:</p> <p>Hamilton, K.G.A., 1982. The insects and arachnids of Canada, Part 10. The Spittlebugs of Canada. Homoptera: Cercpidae. Research Branch Agriculture Canada Publication 1740:1-102.</p> <p>Kelton, L.A., 1978. The insects and arachnids of Canada, Part 4. The Anthocoridae of Canada and Alaska: Heteroptera, Anthocoridae. Research Branch Agriculture Canada Publication 1639:1-101.</p> <p>Kelton, L.A., 1980. The insects and arachnids of Canada, Part 8. The plant bugs of the prairie provinces of Canada (Heteroptera: Miridae). Research Branch Agriculture Canada Publication 1703:1-408.</p> <p>Matsuda, R., 1977. The insects and arachnids of Canada, Part 3. The Aradidae of Canada: Hemiptera: Aradidae. Research Branch Agriculture Canada Publication 1634:1-116.</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.