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107 results for “ZIP”
German ZIP codes, Kreisschlüssel (Administration Unit), Kreis, Inhabitant per ZIP, City Names, responsible Arbeitsagentur (Social Agency
<p>This dataset from 2019 contains all German ZIP codes, city names associated with it, Kreisschlüssel (Administration Unit ID) Kreis, (Administration Unit), Bundesland (State), Inhabitants, responsible Arbeitsagentur (Social Agency). Note that especially the PLZ ZIP Codes and the responsible Arbeitsagentur change from time to time due to administrative reasons.</p>
Trait records sample: Carnivora traits from traitdb (ZIP of CSV files)
This file is part of an API design process and is placed here for internal review. It contains trait records for Carnivora, and neighboring files.<p></p>This is going to similar to the previous set of CSV files, but with fewer tables and fewer columns, since it is derived from the neo4j traitdb instead of the whole back-end SQL database
NO2, O3, PM10 and PM2.5 concentrations - Daily geographical aggregates at ZIP-code level from CAMS European Air Quality Re-analyses.
<p>This dataset offers daily aggregated measurements of air pollutants – NO2, O3, PM10, and PM2.5 – across distinct ZIP-code areas in Germany. The temporal coverage spans from January 1, 2013, to December 31, 2022, providing a comprehensive temporal context for analyzing long-term air quality dynamics.</p> <p>Each daily entry comprises key statistical descriptors, encompassing mean, maximum, minimum, and standard deviation values of pollutant concentrations specific to each ZIP-code area. Additionally, for O3, the dataset includes an eight-hour rolling mean daily maximum.</p> <p>Spatial reference is established via shapefiles provided by ESRI Deutschland (<a href="https://opendata-esri-de.opendata.arcgis.com/datasets/5b203df4357844c8a6715d7d411a8341_0">https://opendata-esri-de.opendata.arcgis.com/datasets/5b203df4357844c8a6715d7d411a8341_0</a>). These shapefiles link the air quality data to precise ZIP-code areas .</p> <p>The concentration data spanning from 2018 to 2022 originate from the European Air Quality Reanalyses dataset of the Atmosphere Data Store (ADS), an initiative by the Copernicus Atmosphere Monitoring Service (CAMS). Accessible via <a href="https://ads.atmosphere.copernicus.eu/cdsapp#!/dataset/cams-europe-air-quality-reanalyses?tab=doc">https://ads.atmosphere.copernicus.eu/cdsapp#!/dataset/cams-europe-air-quality-reanalyses?tab=doc</a>, this dataset offers a robust foundation for assessing air quality. For the years 2013 to 2017, data were previously obtained from a former download platform for the same dataset. Important: in future all data will be migrated to the Atmosphere Data Store (ADS) platform.</p> <p>The native resolution of the CAMS data is 0.1° x 0.1° spatially and hourly temporally. To enhance spatial accuracy, the spatial resolution was virtually increased by a factor of 5 using bilinear interpolation, resulting in a refined grid. The daily mean concentrations were subsequently computed for this augmented grid.</p> <p>Aggregated statistics were derived for each ZIP-code polygon, employing all grid cells intersecting with the polygons. The computation was based on the proportion of cell area included within the respective polygons.</p> <p>This dataset constitutes a valuable resource for conducting ecologically designed epidemiological studies, as it facilitates the exploration of potential associations between air quality and health trends across broad geographical areas.</p> <p>Generated using Copernicus Atmosphere Monitoring Service Information 2013-2022</p>
Port Places App - Zip folders of experience data
<p>These zip folders are exports from the Safarnama authoring tool on the 3rd of July, 2023. The tool was hosted at <a href="https://safarnama.lancs.ac.uk">https://safarnama.lancs.ac.uk</a> at the time of deposit. The folders contain all media items, icons, and a JSON representation of the experiences created for the Port Places app by the Ports, Past and Present project. English and Welsh Language experiences are deposited as separate items.</p> <p>For more information about Safarnama, see <a href="https://github.com/jwoodmansey/">https://github.com/jwoodmansey/</a>.</p>
Data for ZIP Model, Tanzania Precision Mapping 2021
<p>Socio-demographic data to be imported into the ZIP model</p>
XML_corpus_zip
<p>All texts are from TextGrid licenced under CC-BY 3.0 (https://creativecommons.org/licenses/by/3.0/de/) and put together as a corpus by Dr. Katrin Dennerlein (http://www.germanistik.uni-wuerzburg.de/lehrstuehle/computerphilologie/mitarbeiter/dennerlein/).</p> <p>The corpus is mentioned in The Schiller-Kleist Uncertainty Principle (http://dragonfly.hypotheses.org/708).</p>
GM EEG data zip 2 of 2
<p>This is the EEG dataset part 2 of 2 for the paper "Reduction of Pavlovian bias in schizophrenia"</p> <p>See part 1 for more information: 10.5281/zenodo.29601</p>
Stack Overflow's Hidden Nuances: How Does Zip Code Define User Contribution?
<p>Collective intelligence constitutes a foundational element within online community question-and-answering (CQA) platforms, such as Stack Overflow, being the source of most programming-related issues. Despite this relevance, concerns remain regarding issues surrounding user participation. Precedent research tends to focus on simple numerical measurements to analyse participation, which may sideline the inherent, subtler aspects.</p> <p>The proposed study aims to bridge this gap by operationalising 11 distinct metrics to represent user participation, behaviour, and community value across different regions of the USA. The study also conducts inductive content analysis to understand the impact of regional contextual factors on users' knowledge sharing patterns.</p> <p>This replication package is provided for those interested in further examining our research methodology.</p>
Stack Overflow's Hidden Nuances: How Does Zip Code Define User Contribution?
<p>--Collective intelligence constitutes a foundational element within online community question-and-answering (CQA) platforms, such as Stack Overflow, being the source of most programming-related issues. Despite this relevance, concerns remain regarding issues surrounding user participation. Precedent research tends to focus on simple numerical measurements to analyse participation, which may sideline the inherent, subtler aspects.</p> <p>The proposed study aims to bridge this gap by operationalising 11 distinct metrics to represent user participation, behaviour, and community value across different regions of the USA. The study also conducts inductive content analysis to understand the impact of regional contextual factors on users' knowledge sharing patterns.</p> <p>This replication package is provided for those interested in further examining our research methodology.</p>
Small ZIP file for decompression tests/demos
<p>This is a small test file containing the GitHub SVG logo and the MD5 checksum.</p> <p>This is used to demo CMake download, verify and extract in https://github.com/scivision/cmake-utils</p>
Freshwater and Marine Image Bank, University Libraries, U Washington: Original zip resource
The Freshwater and Marine Image Bank is a digital collection from the University of Washington Libraries of images related to freshwater and marine topics, in all their diversity. It includes images of fish, shellfish, and marine mammals, pictures of fish hatcheries and dams and vessels, materials related to polar exploration, regional and traditional fisheries, and limnological (freshwater) subjects. Its scope is global. <p></p>http://content.lib.washington.edu/fishweb/index.html<p></p>
Airborne and drone from Asiago (Italy) forest area before and after logging activities (ZIPPED archive version)
<ul> <li>lidar DSM and DTM (tif format) from airborne laser scanning before logging activities</li> <li>drone DSM (tif format) from photogrammetry after logging activities</li> <li><a href="https://zenodo.org/api/files/58082214-481c-44ce-9d3f-3dfdb311aa70/tarif_forest_parcels.gpkg">tarif_forest_parcels.gpkg</a> : tarif parcels polygons in geopackage format</li> <li>trees32632.csv: tree positions in delimited text format</li> <li>tarifVolumeTables.xlsx: tarif look-up-tables</li> <li><a href="https://zenodo.org/api/files/58082214-481c-44ce-9d3f-3dfdb311aa70/treeExtractionFromDSM_DTM_version02Dec2022.R">treeExtractionFromDSM_DTM_version02Dec2022.R</a> - R script to extract tree positions from a CHM</li> </ul>
Zip archive containing datasets described in the manuscript entitled "Distribution-agnostic Deep Learning Enables Accurate Single‐Cell Data Recovery and Transcriptional Regulation Interpretation"
<p>The datasets used in the manuscript entitled "Distribution-agnostic Deep Learning Enables Accurate Single‐Cell Data Recovery and Transcriptional Regulation Interpretation". These datasets encompass all the experiments conducted in the manuscript, including simulation experiments, downsampling experiments, clustering, differential expression analysis, enrichment analysis, trajectory inference, batch correction, and clinical case discovery.</p> <p>The open-source software is available at https://github.com/XuYuanchi/Bis.</p>
New Mexico PM2.5 concentrations by ZIP code for 4 smoke exposure estimates
Open the record for dataset details and reuse information.
GM EEG data zip 1 of 2
<p>This is the EEG dataset part 1 of 2 as well as the trial-by-trial behavioural data for the paper "Reduction of Pavlovian bias in schizophrenia" under submission at PLoS One.</p> <p>EEG data contains the cleaned, ICA eye-blink corrected data in EEGLAB format. Also included is an ICA decomposition using the AMICA algorithm.</p> <p>Triggers: Triggers are also included in the behavioural R data file "BehaviouralData&M6Fits.RData" as a data.table (will need the 'data.table' package in R) named "dftr". Model fits are in the R data file, also as a data.table, labelled dfM3.</p> <p>Stimulus onset codes are: 1 & 101 = Go-to-Avoid; 2 & 202 = Go-to-Win; 3 & 303 = NoGo-to-Avoid; 4 & 104 = NoGo-to-Win. (with 100s as invalid stimuli, or requiring the opposite response based on the contingency)</p> <p>Feedback onset codes are as follows: 21, 121, 41, 141 = win (thumbs up); 29, 129, 9, 109 = lose (thumbs down); 20, 120, 40, 140, 30, 130, 10, 110 = no change (horizontal thumb).</p> <p>Response onset codes are: 301, 302, 303, 304 for a response to a 'valid' stimulus (not necessarily correct - refers to contingency); 401, 402, 403, 404 for a response to an invalid stimulus.</p> <p>Hope you enjoy!</p>
DepthTrack Test Set in one zip
<p>The original link in here: https://zenodo.org/record/5792146</p> <p>Here I zip them into one zip file and add a unzip script in it. It is also ready for vot-toolkit-python analysis.</p>
Frictionless Data Test Dataset Zipped Single File Without Package File
<p>This is a test dataset.</p>
Tirelire Zip
/ Source: Objaverse 1.0 / Sketchfab
Global Gross Primary Productivity (GPP) Dataset 2020 (GeoTIFF) - ZIP file
<p>Product: Gross Primary Productivity (GPP)</p> <p>Year: 2020</p> <p>Region: Global (in MODIS tile grid)</p> <p>Temporal Scale: 8 Days</p> <p>Spatial Resolution: 500 meters</p> <p>Method: Light-use-efficiency (LUE) approach.</p> <p>Referred Publications: https://www.sciencedirect.com/science/article/pii/S0048969718307149</p> <p>https://onlinelibrary.wiley.com/doi/10.1111/gcb.12261</p> <p>This archive has been uploaded as a .zip file, due to repeated difficulties uploading single GeoTIFFs to Zenodo. </p> <p><strong>NOTE:</strong> This dataset has been produced in the MODIS tile format, to allow comparison to existing products. </p>
Stack Overflow's Hidden Nuances: How Does Zip Code Define User Contribution? – Replication Package
<p>Collective intelligence constitutes a foundational element within online community question-and-answering (CQA) platforms, such as Stack Overflow, being the source of most programming-related issues. Despite this relevance, concerns remain regarding issues surrounding user participation. Precedent research tends to focus on simple numerical measurements to analyse participation, which may sideline the inherent, subtler aspects.</p> <p>The proposed study aims to bridge this gap by operationalising 11 distinct metrics to represent user participation, behaviour, and community value across different regions of the USA. The study also conducts inductive content analysis to understand the impact of regional contextual factors on users' knowledge sharing patterns.</p> <p>This replication package is provided for those interested in further examining our research methodology.</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.