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5,738 results for “Standards”
Divide and Remaster v3: Standard German Validation & Test Set
<p>Divide and Remaster v3 is a multilingual rework of the Divide and Remaster v2 dataset by Pétermann et al.</p> <p>This repository contains the <strong>metadata, validation set audio, and test set audio of the</strong> <strong>Standard German variant </strong>of DnR v3.</p> <p>The major changes from DnR v2 are as follows:</p> <ul> <li>the dialogue stem now contains content from more than 30 languages across various language families;</li> <li>speech, vocals, and/or vocalizations have been removed from the music and effects stems;</li> <li>loudness and timing parametrization have been adjusted to approximate the distributions of real cinematic content;</li> <li>the mastering process now preserves relative loudness between stems and approximates standard industry practices.</li> </ul> <p>See the linked GitHub repository for more details.</p>
Table 2: Mean and Standard Deviation of Responses by Field of Knowledge and Parenting Practices
<p><strong><span>Table 2 of 13</span></strong></p> <p><strong><span>Table 2: Mean and Standard Deviation of Responses by Field of Knowledge and Parenting Practices </span></strong></p> <p> </p>
Improved estimation of the prevalence of bovine cysticercosis and the diagnostic test characteristics in the absence of a reference standard using Bayesian Latent Class models, the example of Jimma and Ambo Abattoirs, Ethiopia
<p>Bovine cysticercosis is an infection of cattle musculature with the cestode parasite of humans known as Taenia saginata. This bovine cysticercosis data was collected from two Ambattoirs in Ethiopia namely Ambo and Jimma. Dissection of the predilection site, Ag-ELISA, and meat inspection were the diagnostic methods employed. Cysticerci collected during dissection of the predilection site were also confirmed using multiplex PCR. </p>
Supply chain sustainability standards in temperate farming commodities
<p>Supporting information for Supply chain sustainability standards in temperate farming commodities (Figure 1, Table 1).</p>
Data set for: Proposal for a micromagnetic standard problem for materials with Dzyaloshinskii-Moriya interaction
<p>Scripts and Jupyter notebooks for the data reproduction of the paper: "Proposal for a micromagnetic standard problem for materials with Dzyaloshinskii-Moriya interaction"</p> <p>Files include notebooks and scripts with simulations using the OOMMF, MuMax3 and Fidimag codes. Data analysis is performed using Python tools such as Numpy and Scipy.</p> <p>The latest version of this data set can be found in the Github repository:</p> <p><a href="https://github.com/fangohr/paper-supplement-standard-problem-dmi">https://github.com/fangohr/paper-supplement-standard-problem-dmi</a></p>
Training, executive, attention and motor skills (TEAMS) training versus standard treatment for preschool children with attention deficit hyperactivity disorder: a randomised clinical trial
<p>This is the dataset used in the trial entitled Training, executive, attention and motor skills (TEAMS) training versus standard treatment for preschool children with attention deficit hyperactivity disorder, published in BMC Research Notes.</p>
Manual Dependency Annotation of Three German Text Extracts from the Project hermA (Gold Standard Data)
<p>This dataset was created in the digital humanities project hermA (www.herma.uni-hamburg.de) and comprises annotated extracts of the following three texts:</p> <ul> <li>Modern literature (Lit2009): novel <em>Corpus Delicti: Ein Prozess </em>by German author Juli Zeh, published in Frankfurt/Main in 2009.</li> <li>Non-contemporary literature (Lit1850):<em> Eine Frauenfahrt um die Welt </em>('A woman’s journey around the world') by Austrian author Ida Pfeiffer (1850). Full text available at Deutsches Textarchiv: http://www.deutschestextarchiv.de/pfeiffer_frauenfahrt01_1850/6.</li> <li>Modern academic writing (Aca2009): <em>Stand, Möglichkeiten und Grenzen der Telemedizin in Deutschland</em> ('Telemedicine in Germany: status, chances and limits') by Rüdiger Klar and Ernst Pelikan, published in Bundesgesundheitsblatt ('Federal Health Gazette') in 2009. DOI 10.1007/s00103-009-0787-7.</li> </ul> <p>The texts are annotated for part-of-speech and dependency syntax and are made available in CoNLL file format. We describe the annotation process and report inter-annotator agreements in:</p> <p>Adelmann, Benedikt, Melanie Andresen, Wolfgang Menzel & Heike Zinsmeister. 2018. Evaluation of Out-Of Domain Dependency Parsing for its Application in a Digital Humanities Project. <em>Proceedings of the 14th Conference on Natural Language Processing (KONVENS 2018)</em>. Vienna, Austria.</p>
Beyond the barriers of poetry in the digital world. Is standardization possible in order to achieve interoperability?
<p>The video shows the opening of the 2nd EADH day which took place before the official opening of <em>DHd 2016</em> in Leipzig (7 - 12 März 2016).</p> <p>After welcoming words by Elisabeth Burr, one of the local organisers of the conference, a presentation on the EADH days by Øyvind Eide, representative of EADH, and the awarding of the EADH bursary, Elena Gonzalez-Blanco from the UNED in Madrid, who had organised the 1st EADH day in concomitance with <em>HDH 2015</em> in Madrid, gave her keynote.</p> <p>The programme of the 2nd EADH day is available <a href="http://dhd2016.de/?q=EADH%20day%20programme">here</a>.</p>
Mean and standard deviation of trimmed reads (original reads from PRJNA377625, Berbens et al., 2017)
<p>The original reads were downloaded from the NCBI SRA PRJNA377625 (Berben et al., 2017 mSystems 2:e00102-17).</p> <p>Their maximum length was set to 120nts. For each sample and each read, the read length was extracted into a text file.</p> <p>The read length average and standard deviation was then calculated using R.</p>
Hackathon - TF-TG literature triage Gold Standard corpus
<p>This link contains the gold standard corpus for training the systems aiming at classifying or triaging the documents (PubMed abstracts) in relevant or not relevant for TF-TG relations. Note that this is not purely a curation triage, but we are primarily looking whether the abstracts do describe/characterize TF-TG interactions (positive training set labeled as “1” or they don't (negative training set labeled as “0”). </p> <p>This dataset was manually classified by domain experts into these to classes.</p> <p>Note that in PubMed there is a very considerable class imbalance, implying that there is only a very small fraction of TF-TG relations relevant literature subset. The resulting classifier should be useful to triage the entire PubMed database.</p> <ul> <li> <p>Name: <a href="https://zenodo.org/record/2562939/files/greekc_triage_training_v02.tsv?download=1">greekc_triage_training_v02.tsv</a></p> </li> <li> <p>Example:</p> </li> </ul> <p>11731616 [{"sourceid":"11731616","sourcedb":"PubMed","text":"Homeobox protein Gsh-1-dependent regulation of the rat GHRH gene promoter. Although GHRH is known to play a pivotal role in the regulation of the GHRH-GH-IGF-I axis, the molecular mechanism of GHRH gene expression has not yet been examined. Here we studied the transcriptional regulation of the GHRH gene 5'promoter using an in vitro experimental model system. We especially focused on the role of homeobox transcriptional factor Gsh-1, because a dwarf phenotype and abolished GHRH expression was observed in Gsh-1 knockout mice. First, we cloned human Gsh-1, which showed 87.3% homology with mouse Gsh-1 at the nucleotide level. When the 5'-promoter region of the rat GHRH gene was introduced into the human placental cell line JEG-3, in which we found the endogenous expression of Gsh-1 as well as GHRH mRNA, substantial transcriptional activity of the promoter was recognized. Promoter activity was further enhanced by overexpression of Gsh-1 protein, whereas it was substantially reduced by elimination of Gsh-1 binding sites. EMSA confirmed the actual binding of Gsh-1 on the multiple binding sites of GHRH gene promoter. Finally, coexpression of CREB-binding protein significantly enhanced the Gsh-1-induced GHRH gene expression, suggesting the cooperative role of the coactivator protein. Because Gsh-1 is found to be expressed in the hypothalamus of the adult rat, our data provide evidence that the Gsh-1 homeobox protein plays a key role in the expression of the GHRH gene.","denotations":[{"obj":"Gene:29446","span":{"begin":84,"end":88}},{"obj":"Gene:288457","span":{"begin":17,"end":22}},{"obj":"Gene:29446","span":{"begin":55,"end":59}},{"obj":"Gene:29446","span":{"begin":146,"end":150}},{"obj":"Gene:29446","span":{"begin":193,"end":197}},{"obj":"Gene:29446","span":{"begin":295,"end":299}},{"obj":"Gene:14842","span":{"begin":430,"end":435}},{"obj":"Gene:14601","span":{"begin":477,"end":481}},{"obj":"Gene:14842","span":{"begin":509,"end":514}},{"obj":"Gene:219409","span":{"begin":553,"end":558}},{"obj":"Gene:14842","span":{"begin":599,"end":604}},{"obj":"Gene:29446","span":{"begin":669,"end":673}},{"obj":"Gene:219409","span":{"begin":783,"end":788}},{"obj":"Gene:2691","span":{"begin":800,"end":804}},{"obj":"Gene:288457","span":{"begin":940,"end":945}},{"obj":"Gene:288457","span":{"begin":1010,"end":1015}},{"obj":"Gene:288457","span":{"begin":1068,"end":1073}},{"obj":"Gene:29446","span":{"begin":1107,"end":1111}},{"obj":"Gene:54244","span":{"begin":1152,"end":1172}},{"obj":"Gene:288457","span":{"begin":1200,"end":1205}},{"obj":"Gene:29446","span":{"begin":1214,"end":1218}},{"obj":"Gene:288457","span":{"begin":1304,"end":1309}},{"obj":"Gene:288457","span":{"begin":1408,"end":1413}},{"obj":"Gene:29446","span":{"begin":1473,"end":1477}}]}] 1</p> <ul> <li> <p>Format: tsv-separated columns (PMID, PubAnnotation JSON formated results of Pubtator for this record together with the automatically detected gene mentions using GnormPlus providing the Entrez Gene Identifiers together with the mention offsets, i.e. start and end character positions, corresponding class label of the records (1= relevant, 0=nonrelevant))</p> </li> <li> <p>PubAnnotation format description: <a href="http://www.pubannotation.org/docs/annotation-format/">http://www.pubannotation.org/docs/annotation-format/</a></p> </li> <li> <p>PubTator record retrieval description:</p> </li> </ul> <p>https://www.ncbi.nlm.nih.gov/CBBresearch/Lu/Demo/tmTools/curl.html</p> <p><strong>Remember:</strong> One must notice that this dataset is high imbalanced, with very few cases of the positive class. The additional files could also be explored to build the model or even to build a classifier working at the level of sentences instead of abstracts,</p> <p> </p>
Online Resources Chapter 3 - Decomposition of standing litter biomass in newly constructed wetlands associated with direct effects of sediment and water characteristics and the composition and activity of the decomposer community using Phragmites australis as a single standard substrate
<p>Online Resources to Chapter 3 "Decomposition of standing litter biomass in newly constructed wetlands associated with direct effects of sediment and water characteristics and the composition and activity of the decomposer community using Phragmites australis as a single standard substrate" of PhD thesis from Ciska Overbeek, "Peat formation on a former landfill - Production and decomposition of aquatic pioneer vegetation". </p> <p>Published by Overbeek et al in 2019 in Wetlands 39(1): 113-125. https://doi.org/10.1007/s13157-018-1081-y. </p>
Development of a Standard Test Method for Characterization of Asphalt Modifiers and Aging-Related Degradation Using an Extensional Rheometer
<p>Corresponding data set for Tran-SET Project No. 17BLSU01. Abstract of the final report is stated below for reference:</p> <p>"An extensional deformation test method using a Sentmanat Extensional Rheometer (SER) fixture inside a Dynamic Shear Rheometer (DSR) is developed in this study to investigate the degradation of the polymer due to aging and to investigate the effect of modifier type. A relationship between different percentages of modifier and ductility of the modified binder is also investigated. The sample geometrics used in this study are 1 mm 0.72 mm and 3 mm 0.72 mm. A total of one hundred and sixty-two samples were tested. Three modifiers Styrene-Butadiene-Styrene (SBS), Polyphosphoric Acid (PPA) and latex were used. One PG 76-22, one PG 64-22 and one polymer-modified asphalt emulsion (PAME) were used. First peak elongation force, (F1) is the binders’ stiffness and Second peak elongation force, (F2) is the polymer characteristics. F2 is more visible comparatively at the higher temperature. In most cases, F2 reduces after Rolling Thin Film Oven (RTFO) and Pressure Aging Vessel (PAV) aging. To normalize the stiffness effect of F1 on F2, in this study F2/F1 was used to analyze aging susceptibility of modifiers. All the testing temperatures used in this study exhibited a reduction in F2/F1 due to RTFO aging and further reduction due to PAV aging. Therefore, through this study, it is recommended that this parameter can be used to determine aging susceptibility of polymer in a polymer-modified asphalt binder. F2 is only obtained from the SBS and latex modified binders and emulsions. Addition of PPA did not show any F2, making SBS the most effective modifier among SBS, PPA and latex. F2 has a linear correlation with the percent of the polymer in the PMAE, SBS modified PG 64-22, SBS and PPA modified PG 64-22 and latex modified PG 64-22 with R2 values equal to 0.9934, 0.9323, 0.9893 and 0.9535 respectively, indicating extensional deformation test with SER very promising. Ductility analyses using final angular strain values indicate that modifiers increase ductility significantly while aging reduces ductility. Additional research is required for testing ultra-violet (UV) aged sample, and a DSR-based SER test specification will be developed subsequently."</p>
Small example Eiger 2X 16M data set from Diamond Light Source I04 revised for HDRMX Gold Standard Discussion
<p>Revised useful small (488 frame) Eiger data set recorded during routine testing, useful for software testing as it is small. Data recorded is from a thaumatin crystal by Graeme Winter, The original dataset is <a href="https://zenodo.org/record/3385862">https://zenodo.org/record/3385862</a> which contains two Eiger MX datasets, Therm_6_1 and Them_6_2, each with a data file and two versions each of the metadata -- a "..._master.h5" file and a "....nxs" file. The former are the usual Eiger metadata files using exposed external links to connect the metadata to the date, and the latter are HDF5-1.10 VDS files. This revision has the same data as the original Therm_6_2 data, but now includes with the "master.h5" file a "..._master_rev.h5" file and with the ".nxs" file a "..._rev.nxs" VDS file.</p> <p>The purpose to the changes in the "..._rev" files is to provide a supporting example for the HDRMX discusssion of a new proposed Eiger "gold standard" to improve the ability to process Eiger MX data collected at one facility at other facilties, by ensuring that sufficient metadata is stored with all datasets.</p> <p>The changes were made by the following script</p> <pre>cp Therm_6_2.nxs Therm_6_2_rev.nxs cp Therm_6_2_master.h5 Therm_6_2_master_rev.h5 export LD_LIBRARY_PATH=$HOME/lib export HDF5_PLUGIN_PATH=$HOME/lib export PATH=$HOME/bin:$PATH h5copy -i Therm_6_2_rev.nxs -o Therm_6_2_master_rev.h5 -s /entry/instrument/name -d /entry/instrument/name -f ref h5copy -i Therm_6_2_rev.nxs -o Therm_6_2_master_rev.h5 -s /entry/instrument/source -d /entry/source -f ref h5copy -i Therm_6_2_rev.nxs -o Therm_6_2_rev.nxs -s /entry/instrument/source -d /entry/source -f ref export end_time=`h5dump -d "/entry/end_time" Therm_6_2_master.h5 | grep ":" | sed 's/^.........//'|sed 's/.\$//'` echo "end_time: $end_time" python << 'EOL' import h5py import numpy as np import os end_time=os.environ['end_time'] fvds = h5py.File('Therm_6_2_rev.nxs','r+') fmaster = h5py.File('Therm_6_2_master_rev.h5','r+') fvds_keys=fvds.keys() fmaster_keys=fmaster.keys() fvds_entry=fvds['entry'] fmaster_entry=fmaster['entry'] fvds_entry_keys=fvds_entry.keys() fmaster_entry_keys=fmaster_entry.keys() fvds_entry_instrument=fvds['entry']['instrument'] fmaster_entry_instrument=fmaster['entry']['instrument'] fvds_entry_instrument_keys=fvds_entry_instrument.keys() fmaster_entry_instrument_keys=fmaster_entry_instrument.keys() fvds_entry_instrument_name=(fvds['entry']['instrument']['name']) fmaster_entry_instrument_name=(fmaster['entry']['instrument']['name']) fvds_entry_instrument_short_name=fvds_entry_instrument.attrs['short_name'] fmaster_entry_instrument_short_name=fmaster_entry_instrument.attrs['short_name'] zero_offset=fmaster_entry_instrument['detector']['module']['fast_pixel_direction'].attrs['offset'] fmaster_det_z=fmaster_entry_instrument['transformations']['det_z'] fvds_det_z=fvds_entry_instrument['transformations']['det_z'] print('fvds_keys: ',fvds_keys) print('fmaster_keys: ',fmaster_keys) print('fvds_entry_keys: ',fvds_entry_keys) print('fmaster_entry_keys: ',fmaster_entry_keys) print('fvds_entry_instrument_keys: ',fvds_entry_instrument_keys) print('fmaster_entry_instrument_keys: ',fmaster_entry_instrument_keys) print('fvds_entry_instrument_name: ',fvds_entry_instrument_name) print('fmaster_entry_instrument_name: ',fmaster_entry_instrument_name) print('fvds_entry_instrument_short_name: ',fvds_entry_instrument_short_name) print('fmaster_entry_instrument_short_name: ',fmaster_entry_instrument_short_name) print('fmaster_entry_instrument_detector_module_fast_pixel_direction_offset: ',zero_offset) print('fmaster_entry_instrument_detector_detector_z_det_z: ',fmaster_det_z) print('fmaster_entry_end_time: ',end_time) fmaster.attrs.modify('file_time',np.string_(end_time)) fmaster.attrs.modify('file_name',np.string_('Therm_6_2_master_rev.h5')) fmaster.attrs.modify('HDF5_Version',np.string_('hdf5-1.8.18')) fvds.attrs.modify('file_time',np.string_(end_time)) fvds.attrs.modify('file_name',np.string_('Therm_6_2_master_rev.h5')) fvds.attrs.modify('HDF5_Version',np.string_('hdf5-1.10.5')) fvds_entry_instrument_name.attrs.modify('short_name',np.string_(fvds_entry_instrument.attrs['short_name'])) fmaster_entry_instrument_name.attrs.modify('short_name',np.string_(fmaster_entry_instrument.attrs['short_name'])) fmaster_entry_instrument['attenuator']['attenuator_transmission'].attrs.modify('units',np.string_("")) fmaster_entry_instrument['detector']['count_time'].attrs.modify('units',np.string_("s")) fvds_entry_instrument_name.attrs.modify('short_name',np.string_(fvds_entry_instrument.attrs['short_name'])) fvds_entry_instrument['attenuator']['attenuator_transmission'].attrs.modify('units',np.string_("")) fvds_entry_instrument['detector']['count_time'].attrs.modify('units',np.string_("s")) fmaster_det_z.attrs.modify('offset',zero_offset) fvds_det_z.attrs.modify('offset',zero_offset) fmaster_entry['sample']['transformations']['phi'].attrs.modify('offset',zero_offset) fmaster_entry['sample']['transformations']['chi'].attrs.modify('offset',zero_offset) fmaster_entry['sample']['transformations']['sam_x'].attrs.modify('offset',zero_offset) fmaster_entry['sample']['transformations']['sam_y'].attrs.modify('offset',zero_offset) fmaster_entry['sample']['transformations']['sam_z'].attrs.modify('offset',zero_offset) fmaster_entry['sample']['transformations']['omega'].attrs.modify('offset',zero_offset) fvds_entry['sample']['transformations']['phi'].attrs.modify('offset',zero_offset) fvds_entry['sample']['transformations']['chi'].attrs.modify('offset',zero_offset) fvds_entry['sample']['transformations']['sam_x'].attrs.modify('offset',zero_offset) fvds_entry['sample']['transformations']['sam_y'].attrs.modify('offset',zero_offset) fvds_entry['sample']['transformations']['sam_z'].attrs.modify('offset',zero_offset) fvds_entry['sample']['transformations']['omega'].attrs.modify('offset',zero_offset) print(fmaster['entry']['instrument']['name'].attrs['short_name']) print(fmaster['entry']['instrument']['name'].attrs['short_name'].shape) print(fmaster['entry']['instrument']['name'].attrs['short_name'].dtype) del fvds_entry_instrument.attrs['short_name'] del fmaster_entry_instrument.attrs['short_name'] del fmaster_entry_instrument['source'] fvds.close() fmaster.close() quit() EOL $HOME/bin/nxvalidate -a NXmx -l /home/yaya/hdrmx_rev_29Sep19/hdrmx/definitions Therm_6_2_master_rev.h5 $HOME/bin/nxvalidate -a NXmx -l /home/yaya/hdrmx_rev_29Sep19/hdrmx/definitions Therm_6_2_rev.nxs </pre> <p>The revised cnxvalidate and definitions are available on github</p> <p><a href="https://github.com/HDRMX/cnxvalidate.git">https://github.com/HDRMX/cnxvalidate.git</a></p> <p><a href="https://github.com/HDRMX/definitions.git">https://github.com/HDRMX/definitions.git</a></p> <p> </p> <p> </p>
Figure 2 in Development of empirical standard weight equation for Pursak chub Squalius pursakensis, an endemic cyprinid species of Northwest Anatolia
Figure 2. Area of distribution of Squalius pursakensis (dark gray area).
Figure 1 in Development of empirical standard weight equation for Pursak chub Squalius pursakensis, an endemic cyprinid species of Northwest Anatolia
Figure 1. Squalius pursakensis from Seydi Suyu in Sakarya Basin (445 mm TL).
Fig. 1 in Standard deviation of carabid size in Western German forest succession - a complex picture
Fig. 1. Male (squares) and female (circles) elytrae lengths of C. violaceus (mean ± SD).
Data from: Performance of DNA metabarcoding, standard barcoding and morphological approaches in the identification of insect biodiversity
<p>A repository containing the data and R code for the associated manuscript titled "Performance of DNA metabarcoding, standard barcoding and morphological approaches in the identification of insect biodiversity"</p> <p>Created by Romana K. Salis</p> <div> <h2>Content Overview</h2> <a href="https://github.com/rksalis/LNU_insectbarcoding/tree/main#content-overview"></a></div> <div> <h3>Rcode:</h3> <a href="https://github.com/rksalis/LNU_insectbarcoding/tree/main#rcode"></a></div> <p>analysis_070923.R</p> <div> <h3>Data files:</h3> <a href="https://github.com/rksalis/LNU_insectbarcoding/tree/main#data-files"></a></div> <p>literature_search_210624.csv barcoding_datasets.csv - barcoding datasets match category counts for the butterflies, bees and wasps</p> <p>barcoding_VB_thresholds.csv - barcoding datasets match category counts for the vietnamese butterfly with different similarity thresholds</p> <p>barcoding_VB_families.csv - barcoding datasets match category counts for the vietnamese butterfly families</p> <p>vietkordfinal_x.csv - intraspecific similarity and geographic distance</p> <p>vietnam_area.csv - intraspecific similarity and sampling area</p> <p>BINsvSp.csv - number of BINs and morphospecies</p> <p>Metabarcoding_Results_CommonSpecies.csv - metabarcoding results including the species only those also identified by morphology</p> <p>Metabarcoding_Results_BINSpecies.csv - metabarcoding results BIN species</p> <p>Metabarcoding_Results_BINs.csv - metabarcoding results all BINs</p>
Oregon-R-modENCODE(#25211) wild-type fruit fly (D.melanogaster) lifespan under standard maintenance conditions
<p><span>Aging is a phenomenon that manifests itself as permanent physiological deterioration, resulting in changes like reduction of immune function and fitness-related forms of behavior. Studies on changes in lifespan in response to various environmental alterations can bring knowledge of the mechanisms driving them. To properly conduct these studies, data on lifespan under the standard husbandry conditions are required.</span></p>
FIGURE 7 in Graphic correlation of the upper Eifelian to lower Frasnian (Middle-Upper Devonian) conodont sequences in the Spanish Central Pyrenees and comparison with composite standards from other areas
FIGURE 7. Correlation of the three sections based on the results of the graphic correlation method.
Spectral data for direct detection and quantification of phycocyanin in sediments by hyperspectral imaging: Standard calibration
<p>Accompanying data to publication: <strong>Direct detection and quantification of phycocyanin in sediments by hyperspectral imaging</strong></p> <p>Hyperspectral data with all their processing steps - normalization, ROI, subsets, masking - resulting in RABD indices of Chlorophyll a and Phycocyanin pigments from spiking experiments on sediments.</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.