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1,298 results for “Archive”
Skeleton Test Suite and PRONOM Archive v96
<p><strong>PRONOM Skeleton Suite V96</strong></p>
The Noh Mask Effect - Archive of Research Materials on Noh Masks and Facial Expression
<p>Contains materials related to research on culture and viewpoint-dependent perception of facial expressions portrayed on masks used in the Japanese Noh Theatre. The archive includes the images used in the experiments as well as various documents related to the project.</p> <p><strong>Animations</strong></p> <ul> <li>animated gif of the antique Magojiro mask tilting forwards & back</li> <li>mp4 file with a comparison of new & old masks at different tilts</li> </ul> <p><strong>Article</strong></p> <ul> <li>pdf of article on the research project</li> <li>atr99.pdf contains a short summary of the project that may be helpful</li> <li>manuscript of the article (latex source files)</li> <li>correspondence with the publisher</li> <li>final versions of the article figures</li> </ul> <p><strong>Composites</strong></p> <ul> <li>composite figures of masks and human face at varying tilts</li> </ul> <p><strong>Experimental Stimuli</strong></p> <ul> <li>folders XA, XC, XH, XT</li> <li>only XA and XH were used for experiments reported in the article</li> <li>tilt angles range from -30 to 30 degrees in 5 degree steps</li> <li>XA: antique Magojiro mask from Edo period</li> <li>XC: Magojiro mask from the current era (1980s or 90s)</li> <li>XH: female human face, images rendered from 3D scan</li> <li>XT: Ko-omote mask made by an amateur carver (collection of MJL)</li> </ul> <p><strong>Misc</strong></p> <ul> <li>'behind the scenes' photos</li> <li>view of the Noh stage at the Nara Shin Kokai Do in Nara Koen</li> <li>view of the camera and apparatus used to adjust the tilt angle</li> <li>shape images rendered from scans of the Ko-omote mask and human face</li> <li>view of the Magojiro mask from the current era (collection of the Komparu family)</li> <li>close up of mouth area of the Magojiro mask from the current era</li> <li>view of the antique Edo period Magojiro mask</li> <li>view of the reverse of the antique Magojiro mask showing inscriptions</li> </ul> <p>Thank you for your interest in the project.</p> <p>Michael Lyons, Ph.D.<br> Professor of Image Arts and Science<br> Ritsumeikan University<br> Kyoto, Japan</p>
NoCORA - Northern Cameroon Observed Rainfall Archive
<p><strong>Description:</strong> The NoCORA dataset represents a significant effort to compile and clean a comprehensive set of daily rainfall data for Northern Cameroon (North and Extreme North regions). This dataset, overing more than 1 million observations across 418 rainfall stations on a temporal range going from 1927 to 2022, is instrumental for researchers, meteorologists, and policymakers working in climate research, agricultural planning, and water resource management in the region. It integrates data from diverse sources, including Sodecoton rain funnels, the archive of Robert Morel (IRD), Centrale de Lagdo, the GHCN daily service, and the TAHMO network.</p><p>The construction of NoCORA involved meticulous processes, including manual assembly of data, extensive data cleaning, and standardization of station names and coordinates, making it a hopefully robust and reliable resource for understanding climatic dynamics in Northern Cameroon.</p><p><strong>Data Sources:</strong> The dataset comprises eight primary rainfall data sources and a comprehensive coordinates dataset. The rainfall data sources include extensive historical and contemporary measurements, while the coordinates dataset was developed using reference data and an inference strategy for variant station names or missing coordinates.</p><p><strong>Dataset Preparation Methods:</strong> The preparation involved manual compilation, integration of machine-readable files, data cleaning with OpenRefine, and finalization using Python/Jupyter Notebook. This process should ensured the accuracy and consistency of the dataset.</p><p><strong>Discussion:</strong> NoCORA, with its extensive data compilation, presents an invaluable resource for climate-related studies in Northern Cameroon. However, users must navigate its complexities, including missing data interpretations, potential biases, and data inconsistencies. The dataset's comprehensive nature and historical span require careful handling and validation in research applications.</p><p><strong>Access to Dataset:</strong> The NoCORA dataset, while a comprehensive resource for climatological and meteorological research in Northern Cameroon, is subject to specific access conditions due to its compilation from various partner sources. The original data sources vary in their openness and accessibility, and not all partners have confirmed the open-access status of their data. As such, to ensure compliance with these varying conditions, access to the NoCORA dataset is granted on a request basis. Interested researchers and users are encouraged to contact us for permission to access the dataset. This process allows us to uphold the data sharing agreements with our partners while facilitating research and analysis within the scientific community.</p><p><strong>Authors Contributions:</strong></p><ul><li>Data treatment: Victor Hugo Nenwala, Carmel Foulna Tcheobe, Jérémy Lavarenne.</li><li>Documentation: Jérémy Lavarenne.</li></ul><p><strong>Funding:</strong> This project was funded by the DESIRA INNOVACC project.</p><p><strong>Changelog:</strong> </p><ul><li>v1.0.2 : corrected interversion in column names in the coordinates dataset </li><li>v1.0.1 : dataset specification file has been updated with complementary information regarding station locations</li><li>v1.0.0 : initial submission</li></ul>
Filling knowledge gaps in insect conservation by leveraging genetic data from public archives
<p>Based on data collection from NCBI GenBank and BOLD, we edited a georeferenced database of barcoding data for the insect taxa within the Italian IUCN Red Lists: saproxylic beetles, butterflies, bees, and dragonflies.</p> <p>The goal of this database is to support the estimation of the genetic diversity of the listed insect species. The database populated with barcoding sequences and additional metadata will allow studies in order to define biodiversity pattern models in Italy and Europe.</p> <p>Our database allows recycling and re-analysing data from two major repositories such as NCBI GenBank and BOLD, increasing accessibility to big data for comparative study to facilitate genetic and spatial analyses on a large scale. Our findings suggest to fill many gaps in the knowledge of species occurrence, distribution, and patterns of genetic diversity for insects in Europe.</p>
Sabina Ott archive item 14
Source: Objaverse 1.0 / Sketchfab
DAMP-VP1k: Digital Archive of Mobile Performances - Smule Vocal Performances 100x10
<p>Digital Archive of Mobile Performance DAMP-VP1k archive of Smule vocal performances, 100 singers, 10 Performance each.</p> <p>The dataset contains sung musical performances from the Smule app. Data files include audio.zip with all the compressed audio files, and metadata.csv describing some metadata about each performance, including unique identifiers for each recording, song, and singer, as well as binary gender labels, region labels, and social "love" counts from the Smule app.</p> <p>This archive is a subset of the DAMP-Multiple Songs archive hosted at https://ccrma.stanford.edu/damp/, which contains multiple performances from each of multiple singers, singing different songs, without much verification of the data. This subset has been reduced to a subset of 10 performances per singer, with cleaner recordings for each singer preselected.</p> <p>Users of this dataset must read and accept Smule's Research Data License Agreement (LICENSE.txt).</p>
DAMP-VPB: Digital Archive of Mobile Performances - Smule Vocal Performances Balanced
<p>The DAMP-balanced dataset contains 24874 solo singing performances from 5429 singers singing a collection of 14 songs.<br> The structure of the DAMP-balanced is that the last 4 songs are designed to be the test set, and the first 10 songs<br> could be partitioned into any 6/4 train/validation split (permutation) that the singers in train and validation set sang<br> the same 6/4 songs collections according to the 6/4 split (the number of total recordings for train and validation set<br> are different from split to split, since there are different number of singers that all sang the same 6/4 split for<br> different split).</p> <p>For example, a subset from the dataset splitting the 14 songs into 6/4/4 train/validation/test sets having 276/88/224<br> performances sang by 46/22/56 singers could be extracted from the dataset and be used for machine learning tasks.<br> Each singer in the train, validation and test set, sang each of the 6/4/4 songs once respectively, thus making the<br> collections of performances "balanced" respect to the song collections.</p> <p>List of songs:</p> <ol> <li>one call away - Charlie Puth(3912)</li> <li>say you won`t let go - James Arthur(3255)</li> <li>allof me - John Legend(2856)</li> <li>closer -The Chainsmokers(2873)</li> <li>seven years - Lukas Graham(2942)</li> <li>despacito- Luis Fonsi(1287)</li> <li>more than words - Extreme(586)</li> <li>lostboy - Ruth B.(1183)</li> <li>loveyourself - Justin Bieber(3019)</li> <li>rockabye- Clean Bandit(2737)</li> <li>part of your world - Jodi Benson(56)</li> <li>when I was your man - Bruno Mars(56)</li> <li>chandelier- Sia(56)</li> <li>cups - Anna Kendrick(56)</li> </ol> <p>Users of this dataset must read and accept Smule's Research Data License Agreement (LICENSE.txt).</p>
DAMP-VSEP: Smule Digital Archive of Mobile Performances - Vocal Separation
<p>This dataset contains audio content for performing vocal separation research. It contains performances with (1) backing tracks, (2) one or more isolated vocals files, and (3) a mixture of the two. This is a real-world dataset from performances on the Smule app, which includes non-linear effects processes on the mixture of vocals and backing track. The dataset contains data from 155 countries, 36 languages, 6456 artists, and 11494 compositions.</p> <p>Users of this dataset must read and accept Smule's Research Data License Agreement (LICENSE.txt).</p>
Urban-PLUMBER: Flux tower data archive – MX-Escandon
<p>Eddy covariance flux tower dataset from Escandon, Mexico City (Jun. 2011 – Sep. 2012) for the URBAN-PLUMBER model evaluation project (<a href="https://urban-plumber.github.io/MX-Escandon/">https://urban-plumber.github.io/MX-Escandon/</a>). Urban-PLUMBER evaluates the performance of land surface models used in meteorological or climatic simulations of urban areas (<a href="https://urban-plumber.github.io/">https://urban-plumber.github.io/</a>).</p>
Urban-PLUMBER: Flux tower data archive – SG-TelokKurau
<p>Eddy covariance flux tower dataset from Telok Kurau, Singapore (March 2015 – Feb. 2016) for the URBAN-PLUMBER model evaluation project (<a href="https://urban-plumber.github.io/SG-TelokKurau/">https://urban-plumber.github.io/SG-TelokKurau/</a>). Urban-PLUMBER evaluates the performance of land surface models used in meteorological or climatic simulations of urban areas (<a href="https://urban-plumber.github.io/">https://urban-plumber.github.io/</a>).</p>
Urban-PLUMBER: Flux tower data archive – PL-Narutowicza
<p><br> # Urban-PLUMBER site data collection</p> <p>Files in this folder are associated with the manuscript:</p> <p>> "Harmonized, gap-filled dataset from 20 urban flux tower sites"</p> <p>Use of any data must give credit through citation of the above manuscript and other sources as appropriate.<br> We recommend data users consult with site contributing authors and/or the coordination team in the project planning stage. <br> Relevant contacts are included in timeseries metadata.</p> <p>For site information and timeseries plots see https://urban-plumber.github.io/sites.</p> <p>For processing code see https://github.com/matlipson/urban-plumber_pipeline.</p> <p>### Included files</p> <p>Within each site folder:</p> <p>- `index.html`: A summary page with site characteristics and timeseries plots.<br> - `SITENAME_sitedata_vX.csv`: comma seperated file for numerical site characteristics e.g. location, surface cover fraction etc.<br> - `timeseries/` (following files available as netCDF and txt)<br> - `SITENAME_raw_observations_vX`: site observed timeseries before project-wide quality control.<br> - `SITENAME_clean_observations_vX`: site observed timeseries after project-wide quality control. <br> - `SITENAME_metforcing_vX`: site observed timeseries after project-wide quality control and gap filling.<br> - `SITENAME_era5_corrected_vX`: site ERA5 surface data (1990-2020) with bias corrections as applied in the final dataset.<br> - `log_processing_SITENAME_vX.txt`: a log of the print statements through running the create_dataset_SITENAME scripts.</p> <p>### Authors</p> <p>Mathew Lipson, Sue Grimmond, Martin Best, Andreas Christen, Andrew Coutts, Ben Crawford, Bert Heusinkveld, <br> Erik Velasco, Helen Claire Ward, Hirofumi Sugawara, Je-Woo Hong, Jinkyu Hong, Jonathan Evans, Joseph McFadden, <br> Keunmin Lee, Krzysztof Fortuniak, Leena Järvi, Matthias Roth, Nektarios Chrysoulakis, Nigel Tapper, Oliver Michels, <br> Simone Kotthaus, Stevan Earl, Sungsoo Jo, Valéry Masson, Winston Chow, Wlodzimierz Pawlak, Yeon-Hee Kim.</p> <p>Corresponding author: Mathew Lipson <m.lipson@unsw.edu.au></p>
Urban-PLUMBER: Flux tower data archive – PL-Lipowa
<p># Urban-PLUMBER site data collection</p> <p>Files in this folder are associated with the manuscript:</p> <p>> "Harmonized, gap-filled dataset from 20 urban flux tower sites"</p> <p>Use of any data must give credit through citation of the above manuscript and other sources as appropriate.<br> We recommend data users consult with site contributing authors and/or the coordination team in the project planning stage. <br> Relevant contacts are included in timeseries metadata.</p> <p>For site information and timeseries plots see https://urban-plumber.github.io/sites.</p> <p>For processing code see https://github.com/matlipson/urban-plumber_pipeline.</p> <p>### Included files</p> <p>Within each site folder:</p> <p>- `index.html`: A summary page with site characteristics and timeseries plots.<br> - `SITENAME_sitedata_vX.csv`: comma seperated file for numerical site characteristics e.g. location, surface cover fraction etc.<br> - `timeseries/` (following files available as netCDF and txt)<br> - `SITENAME_raw_observations_vX`: site observed timeseries before project-wide quality control.<br> - `SITENAME_clean_observations_vX`: site observed timeseries after project-wide quality control. <br> - `SITENAME_metforcing_vX`: site observed timeseries after project-wide quality control and gap filling.<br> - `SITENAME_era5_corrected_vX`: site ERA5 surface data (1990-2020) with bias corrections as applied in the final dataset.<br> - `log_processing_SITENAME_vX.txt`: a log of the print statements through running the create_dataset_SITENAME scripts.</p> <p>### Authors</p> <p>Mathew Lipson, Sue Grimmond, Martin Best, Andreas Christen, Andrew Coutts, Ben Crawford, Bert Heusinkveld, <br> Erik Velasco, Helen Claire Ward, Hirofumi Sugawara, Je-Woo Hong, Jinkyu Hong, Jonathan Evans, Joseph McFadden, <br> Keunmin Lee, Krzysztof Fortuniak, Leena Järvi, Matthias Roth, Nektarios Chrysoulakis, Nigel Tapper, Oliver Michels, <br> Simone Kotthaus, Stevan Earl, Sungsoo Jo, Valéry Masson, Winston Chow, Wlodzimierz Pawlak, Yeon-Hee Kim.</p> <p>Corresponding author: Mathew Lipson <m.lipson@unsw.edu.au></p>
DAMP-MVP: Digital Archive of Mobile Performances - Smule Multilingual Vocal Performance 300x30x2
<p>The Smule 300x30x2 dataset contains recordings of sung karaoke tracks, lyrics text files, and some metadata describing the songs being performed by each singer. This dataset was collected from performances on Smule by selecting the most popular singers, female and male, of the 300 most popular arrangements in 30 countries.</p> <p>The most popular arrangements were determined by counting song starts or joins (duet/group) of recordings for each arrangement, within the country of interest. The term "arrangement" is used, because there might be multiple arrangements of the same song.</p> <p>The most popular performances and singers of those arrangements were determined by counting Listens (and/or Loves, if no complete Listens) for all performances of each arrangement.</p> <p>Users of this dataset must read and accept Smule's Research Data License Agreement (LICENSE.txt).</p>
heidENC: Heidelberg Encyclopedia Archive
<p>The repository contains the binary files of <em>The Heidelberg Encyclopedia Database </em>heidENC, by Rudolf G. Wagner(†) . It is accompanied by an <a href="https://hcts-hra.github.io/heidenc/">annotated bibliography </a> and a separate repository for <a href="https://github.com/hcts-hra/heidenc-txt">text files</a>.</p> <p>The data has been slightly restructured and cleaned up to prepare for this upload, but all contents reflect the state of the last edit on May 14, 2019.</p> <p> </p>
Y1 T1 Archival Dataset for DRP/CRREL
<p>Scanned archival data and notes gathered during the Y1 field season in October 2022 and December 2022. Repositories include: University of Alaska-Fairbanks, University of Alaska-Anchorage Consortium, Alaska State Library and Archive</p>
Y1 T1 K Archival Dataset for DRP/CRREL
<p>Full datas set of archival materials from the Otto Geist collection of the University of Alaska Fairbanks Archives. Includes historical mining maps, reports on mining deposits, census data, ecosystem data, economic data and cultural practice information. Geographical focus of the data is the Nome region of Alaska, St. Lawrence Island, Point Hope and Savoonga. Contains approximately 200 archival documents with ~1000 pages of text, plus maps and photographs. </p>
NASA Expendable Launch Vehicle Launch Archive 2013
A list of launch vehicles launched for NASA missions in 2013.
NASA Expendable Launch Vehicle Launch Archive 2003
A list of launch vehicles launched for NASA missions in 2003.
OSIRIS-REx SPICE Kernel Archive Bundle
This bundle contains OSIRIS-REx SPICE kernels and related documentation.
NASA Expendable Launch Vehicle Launch Archive 2000
A list of launch vehicles launched for NASA missions in 2000.
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.