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13,117 results for “Maps”
Augmented emission maps: 1969 cc 140 kW Euro 6dT diesel engine
<p>In order to enable the sharing of data the emission data for vehicles is standardized. The data exchange format contains all data that is applicable for a specific engine taxonomy code.</p> <p>This specific data set refers to the 1969 cc 140 kW Euro 6dT diesel engine that has been applied in the Volvo XC40, V60, XC60, V90, and S90.</p> <p>The standardized emission map has a “.map.txt” extension and is also human readable. The files starts with metadata which contains information about:</p> <ul> <li>the engine taxonomy code,</li> <li>total driven kilometers over which the data was gathered,</li> <li>total time in hours over which the data was gathered,</li> <li>the number of vehicles which were tested to create the emission map,</li> <li>the DOI (Digital Object Identifier) reference,</li> <li>Which emission maps are available in the file.</li> </ul> <p>The DOI <a href="http://doi.org/10.5281/zenodo.4268034">http://doi.org/10.5281/zenodo.4268034</a> refers to a updated meta-data document that provides the full description of the standardized emission map.</p>
Augmented emission maps: 1950 cc 110 kW Euro 6c diesel engine
<p>In order to enable the sharing of data the emission data for vehicles is standardized. The data exchange format contains all data that is applicable for a specific engine taxonomy code.</p> <p>This specific data set refers to the 1950 cc 110 kW Euro 6c diesel engine that has been applied in the Mercedes E200D.</p> <p>The standardized emission map has a “.map.txt” extension and is also human readable. The files starts with metadata which contains information about:</p> <ul> <li>the engine taxonomy code,</li> <li>total driven kilometers over which the data was gathered,</li> <li>total time in hours over which the data was gathered,</li> <li>the number of vehicles which were tested to create the emission map,</li> <li>the DOI (Digital Object Identifier) reference,</li> <li>Which emission maps are available in the file.</li> </ul> <p>The DOI <a href="http://doi.org/10.5281/zenodo.4268034">http://doi.org/10.5281/zenodo.4268034</a> refers to a updated meta-data document that provides the full description of the standardized emission map.</p>
Augmented emission maps: 1596 cc 74 kW Euro 3 petrol engine
<p>In order to enable the sharing of data the emission data for vehicles is standardized. The data exchange format contains all data that is applicable for a specific engine taxonomy code.</p> <p>This specific data set refers to the 1596 cc 74 kW Euro 3 petrol engine that has been applied in the Ford.</p> <p>The standardized emission map has a “.map.txt” extension and is also human readable. The files starts with metadata which contains information about:</p> <ul> <li>the engine taxonomy code,</li> <li>total driven kilometers over which the data was gathered,</li> <li>total time in hours over which the data was gathered,</li> <li>the number of vehicles which were tested to create the emission map,</li> <li>the DOI (Digital Object Identifier) reference,</li> <li>Which emission maps are available in the file.</li> </ul> <p>The DOI <a href="http://doi.org/10.5281/zenodo.4268034">http://doi.org/10.5281/zenodo.4268034</a> refers to a updated meta-data document that provides the full description of the standardized emission map.</p>
Augmented emission maps: 2191 cc 110 kW Euro 6b diesel engine
<p>In order to enable the sharing of data the emission data for vehicles is standardized. The data exchange format contains all data that is applicable for a specific engine taxonomy code.</p> <p>This specific data set refers to the 2191 cc 110 kW Euro 6b diesel engine that has been applied in the Mazda.</p> <p>The standardized emission map has a “.map.txt” extension and is also human readable. The files starts with metadata which contains information about:</p> <ul> <li>the engine taxonomy code,</li> <li>total driven kilometers over which the data was gathered,</li> <li>total time in hours over which the data was gathered,</li> <li>the number of vehicles which were tested to create the emission map,</li> <li>the DOI (Digital Object Identifier) reference,</li> <li>Which emission maps are available in the file.</li> </ul> <p>The DOI <a href="http://doi.org/10.5281/zenodo.4268034">http://doi.org/10.5281/zenodo.4268034</a> refers to a updated meta-data document that provides the full description of the standardized emission map.</p>
Augmented emission maps: 1242 cc 48 kW Euro 4 petrol engine
<p>In order to enable the sharing of data the emission data for vehicles is standardized. The data exchange format contains all data that is applicable for a specific engine taxonomy code.</p> <p>This specific data set refers to the 1242 cc 48 kW Euro 4 petrol engine that has been applied in the Fiat Punto, Doblo.</p> <p>The standardized emission map has a “.map.txt” extension and is also human readable. The files starts with metadata which contains information about:</p> <ul> <li>the engine taxonomy code,</li> <li>total driven kilometers over which the data was gathered,</li> <li>total time in hours over which the data was gathered,</li> <li>the number of vehicles which were tested to create the emission map,</li> <li>the DOI (Digital Object Identifier) reference,</li> <li>Which emission maps are available in the file.</li> </ul> <p>The DOI <a href="http://doi.org/10.5281/zenodo.4268034">http://doi.org/10.5281/zenodo.4268034</a> refers to a updated meta-data document that provides the full description of the standardized emission map.</p>
Augmented emission maps: 1560 cc 73 kW Euro 6b diesel engine
<p>In order to enable the sharing of data the emission data for vehicles is standardized. The data exchange format contains all data that is applicable for a specific engine taxonomy code.</p> <p>This specific data set refers to the 1560 cc 73 kW Euro 6b diesel engine that has been applied in the - Peugeot Partner, 208, and 2008, Citroen C4 Cactus, Berlingo, C3, and DS3.</p> <p>The standardized emission map has a “.map.txt” extension and is also human readable. The files starts with metadata which contains information about:</p> <ul> <li>the engine taxonomy code,</li> <li>total driven kilometers over which the data was gathered,</li> <li>total time in hours over which the data was gathered,</li> <li>the number of vehicles which were tested to create the emission map,</li> <li>the DOI (Digital Object Identifier) reference,</li> <li>Which emission maps are available in the file.</li> </ul> <p>The DOI <a href="http://doi.org/10.5281/zenodo.4268034">http://doi.org/10.5281/zenodo.4268034</a> refers to a updated meta-data document that provides the full description of the standardized emission map.</p>
Augmented emission maps: 1968 cc 100 kW Euro 5b diesel engine
<p>In order to enable the sharing of data the emission data for vehicles is standardized. The data exchange format contains all data that is applicable for a specific engine taxonomy code.</p> <p>This specific data set refers to the 1968 cc 100 kW Euro 5b diesel engine that has been applied in the Volkswagen Crafter, Passat, Sharan, and Tiguan, Audi A3, Q3, A4, A5, and A6, Seat Alhambra.</p> <p>The standardized emission map has a “.map.txt” extension and is also human readable. The files starts with metadata which contains information about:</p> <ul> <li>the engine taxonomy code,</li> <li>total driven kilometers over which the data was gathered,</li> <li>total time in hours over which the data was gathered,</li> <li>the number of vehicles which were tested to create the emission map,</li> <li>the DOI (Digital Object Identifier) reference,</li> <li>Which emission maps are available in the file.</li> </ul> <p>The DOI <a href="http://doi.org/10.5281/zenodo.4268034">http://doi.org/10.5281/zenodo.4268034</a> refers to a updated meta-data document that provides the full description of the standardized emission map.</p>
Augmented emission maps: 2993 cc 190 kW Euro 6b diesel engine
<p>In order to enable the sharing of data the emission data for vehicles is standardized. The data exchange format contains all data that is applicable for a specific engine taxonomy code.</p> <p>This specific data set refers to the 2993 cc 190 kW Euro 56b diesel engine that has been applied in the BMW.</p> <p>The standardized emission map has a “.map.txt” extension and is also human readable. The files starts with metadata which contains information about:</p> <ul> <li>the engine taxonomy code,</li> <li>total driven kilometers over which the data was gathered,</li> <li>total time in hours over which the data was gathered,</li> <li>the number of vehicles which were tested to create the emission map,</li> <li>the DOI (Digital Object Identifier) reference,</li> <li>Which emission maps are available in the file.</li> </ul> <p>The DOI <a href="http://doi.org/10.5281/zenodo.4268034">http://doi.org/10.5281/zenodo.4268034</a> refers to a updated meta-data document that provides the full description of the standardized emission map.</p>
Augmented emission maps: 1499 cc 96 kW Euro 6dT diesel engine
<p>In order to enable the sharing of data the emission data for vehicles is standardized. The data exchange format contains all data that is applicable for a specific engine taxonomy code.</p> <p>This specific data set refers to the 1499 cc 96 kW Euro 6dT diesel engine that has been applied in the Peugeot 308, 3008, 508, 5008, and Partner, Opel Grandland X and Combo, Citroen Berlingo, C4 Spacetourer, and C5 Aircross, DS 7 Crossback.</p> <p>The standardized emission map has a “.map.txt” extension and is also human readable. The files starts with metadata which contains information about:</p> <ul> <li>the engine taxonomy code,</li> <li>total driven kilometers over which the data was gathered,</li> <li>total time in hours over which the data was gathered,</li> <li>the number of vehicles which were tested to create the emission map,</li> <li>the DOI (Digital Object Identifier) reference,</li> <li>Which emission maps are available in the file.</li> </ul> <p>The DOI <a href="http://doi.org/10.5281/zenodo.4268034">http://doi.org/10.5281/zenodo.4268034</a> refers to a updated meta-data document that provides the full description of the standardized emission map.</p>
Augmented emission maps: 1199 cc 55 kW Euro 4 petrol engine
<p>In order to enable the sharing of data the emission data for vehicles is standardized. The data exchange format contains all data that is applicable for a specific engine taxonomy code.</p> <p>This specific data set refers to the 1199 cc 55 kW Euro 4 petrol engine that has been applied in the Opel Corsa, Agila, and Astra.</p> <p>The standardized emission map has a “.map.txt” extension and is also human readable. The files starts with metadata which contains information about:</p> <ul> <li>the engine taxonomy code,</li> <li>total driven kilometers over which the data was gathered,</li> <li>total time in hours over which the data was gathered,</li> <li>the number of vehicles which were tested to create the emission map,</li> <li>the DOI (Digital Object Identifier) reference,</li> <li>Which emission maps are available in the file.</li> </ul> <p>The DOI <a href="http://doi.org/10.5281/zenodo.4268034">http://doi.org/10.5281/zenodo.4268034</a> refers to a updated meta-data document that provides the full description of the standardized emission map.</p>
Augmented emission maps: 1587 cc 80 kW Euro 3 petrol engine
<p>In order to enable the sharing of data the emission data for vehicles is standardized. The data exchange format contains all data that is applicable for a specific engine taxonomy code.</p> <p>This specific data set refers to the 1587 cc 80 kW Euro 3 petrol engine that has been applied in the Citroen Berlingo, C2, C3, C3 Pluriel, C4, and Xsara. Peugeot 206, 307, and Partner.<br> NB: this is only the PSA cars. The Volvos have alliance code VOLV and have a different engine.</p> <p>The standardized emission map has a “.map.txt” extension and is also human readable. The files starts with metadata which contains information about:</p> <ul> <li>the engine taxonomy code,</li> <li>total driven kilometers over which the data was gathered,</li> <li>total time in hours over which the data was gathered,</li> <li>the number of vehicles which were tested to create the emission map,</li> <li>the DOI (Digital Object Identifier) reference,</li> <li>Which emission maps are available in the file.</li> </ul> <p>The DOI <a href="http://doi.org/10.5281/zenodo.4268034">http://doi.org/10.5281/zenodo.4268034</a> refers to a updated meta-data document that provides the full description of the standardized emission map.</p>
Augmented emission maps: 1124 cc 44 kW Euro 3 petrol engine
<p>In order to enable the sharing of data the emission data for vehicles is standardized. The data exchange format contains all data that is applicable for a specific engine taxonomy code.</p> <p>This specific data set refers to the 11124 cc 44 kW Euro 3 petrol engine that has been applied in the Peugeot 106, 206, and Partner. Citroen Saxo, C2, C3, and Berlingo.</p> <p>The standardized emission map has a “.map.txt” extension and is also human readable. The files starts with metadata which contains information about:</p> <ul> <li>the engine taxonomy code,</li> <li>total driven kilometers over which the data was gathered,</li> <li>total time in hours over which the data was gathered,</li> <li>the number of vehicles which were tested to create the emission map,</li> <li>the DOI (Digital Object Identifier) reference,</li> <li>Which emission maps are available in the file.</li> </ul> <p>The DOI <a href="http://doi.org/10.5281/zenodo.4268034">http://doi.org/10.5281/zenodo.4268034</a> refers to a updated meta-data document that provides the full description of the standardized emission map.</p>
Augmented emission maps: 1997 cc 100 kW Euro 3 petrol engine
<p>In order to enable the sharing of data the emission data for vehicles is standardized. The data exchange format contains all data that is applicable for a specific engine taxonomy code.</p> <p>This specific data set refers to the 1997 cc 100 kW Euro 3 petrol engine that has been applied in the Citroen C4, C5, C8, Xsara, and Xsara Picasso. Peugeot 206, 307, 406, 407, 607, 806, 807, and Expert.</p> <p>The standardized emission map has a “.map.txt” extension and is also human readable. The files starts with metadata which contains information about:</p> <ul> <li>the engine taxonomy code,</li> <li>total driven kilometers over which the data was gathered,</li> <li>total time in hours over which the data was gathered,</li> <li>the number of vehicles which were tested to create the emission map,</li> <li>the DOI (Digital Object Identifier) reference,</li> <li>Which emission maps are available in the file.</li> </ul> <p>The DOI <a href="http://doi.org/10.5281/zenodo.4268034">http://doi.org/10.5281/zenodo.4268034</a> refers to a updated meta-data document that provides the full description of the standardized emission map.</p>
Data Set htwddKogRob-TSDChangesSim for Localization and Lifelong Mapping
<p>This dataset provides log files recorded in a changed indoor environment with 18 dynamic obstacles. The changes from the original map to the simulated world are highlighted in the figure htwddKogRob-TSDChangesSim_changesHighlighted.png. The total distance travelled in this data set is 179.8 km. The prior knowledge map the robot got to localize and update is shown in htwddKogRob-TSDChangesSim_prior.png and the simulated now changed map is shown in htwddKogRob-TSDChangesSim_groundTruth.png (for both maps: 1px <span class="math-tex">\(\widehat{=}\)</span> 0.1m).<br> </p> <p>The work was first presented in:</p> <ul> <li>A Fuzzy-based Adaptive Environment Model for Indoor Robot Localization</li> <li>Authors: Frank Bahrmann, Sven Hellbach, Hans-Joachim Böhme</li> <li>Date of Publication: 2016/10/6</li> <li>Conference: Telehealth and Assistive Technology / 847: Intelligent Systems and Robotics</li> <li>Publisher: ACTA Press</li> </ul> <p>Additionally, we present a video with the proposed algorithm and an insight of this dataset under:</p> <ul> <li>youtube.com/AugustDerSmarte</li> <li>https://www.youtube.com/watch?v=26NBFN_XeQg</li> </ul> <p><strong>Instructions for use</strong></p> <p>The zip archives contain ascii files, which hold the log files of the robot observations and robot poses. Since this data set was recorded in a simulated environment, the logfiles include both a changed starting position and a ground-truth pose. For further information, please refer to the header of the logfile. To simplify the parsing of the files, you can use these two Java snippets:</p> <p><strong>Laser Range Measurements:</strong></p> <pre><code class="language-java"> List<Double> ranges = new ArrayList<>(numOfLaserRays); List<Error> errors = new ArrayList<>(numOfLaserRays); String s = line.substring(4); String delimiter = "()"; StringTokenizer tokenizer = new StringTokenizer(s, delimiter); while(tokenizer.hasMoreElements()){ String[] arr = tokenizer.nextToken().split(";"); boolean usable = (arr[0].equals("0")?false:true); double range = Double.parseDouble(arr[1]); ranges.add(range); errors.add(usable?Error.OKAY:Error.INVALID_MEASUREMENT); }</code></pre> <p><strong>Poses:</strong></p> <pre><code class="language-java"> String poseString = line.split(":")[2]; String[] elements = poseString.substring(1, poseString.length()-1).split(";"); double x = Double.parseDouble(elements[0]); double y = Double.parseDouble(elements[1]); double phi = Double.parseDouble(elements[2]);</code></pre> <p> </p>
Data Set htwddKogRob-TSDReal for Localization and Lifelong Mapping
<p>This dataset represents a 4.7 km long tour (odometry path shown in htwddKogRob-TSDReal_path.png) in an environment whose representation (see map htwddKogRob-TSDReal.png | 1px <span class="math-tex">\(\widehat{=}\)</span> 0.1m) is now obsolete. Several static objects have been moved or removed, and there are varying numbers of dynamic obstacles (people walking around).</p> <p>The work was first presented in:</p> <ul> <li>A Fuzzy-based Adaptive Environment Model for Indoor Robot Localization</li> <li>Authors: Frank Bahrmann, Sven Hellbach, Hans-Joachim Böhme</li> <li>Date of Publication: 2016/10/6</li> <li>Conference: Telehealth and Assistive Technology / 847: Intelligent Systems and Robotics</li> <li>Publisher: ACTA Press</li> </ul> <p>Additionally, we present a video with the proposed algorithm and an insight of this dataset under:</p> <ul> <li>youtube.com/AugustDerSmarte</li> <li>https://www.youtube.com/watch?v=26NBFN_XeQg</li> </ul> <p><strong>Instructions for use</strong></p> <p>The zip archive contains ascii files, which hold the log files of the robot observations and robot poses. Since this data set was recorded in a real environment, the logfiles hold only the odometry based robot poses. For further information, please refer to the header of the logfiles. To simplify the parsing of the files, you can use these two Java snippets:</p> <p><strong>Laser Range Measurements:</strong></p> <pre><code class="language-java"> List<Double> ranges = new ArrayList<>(numOfLaserRays); List<Error> errors = new ArrayList<>(numOfLaserRays); String s = line.substring(4); String delimiter = "()"; StringTokenizer tokenizer = new StringTokenizer(s, delimiter); while(tokenizer.hasMoreElements()){ String[] arr = tokenizer.nextToken().split(";"); boolean usable = (arr[0].equals("0")?false:true); double range = Double.parseDouble(arr[1]); ranges.add(range); errors.add(usable?Error.OKAY:Error.INVALID_MEASUREMENT); }</code></pre> <p><strong>Poses:</strong></p> <pre><code class="language-java"> String poseString = line.split(":")[2]; String[] elements = poseString.substring(1, poseString.length()-1).split(";"); double x = Double.parseDouble(elements[0]); double y = Double.parseDouble(elements[1]); double phi = Double.parseDouble(elements[2]);</code></pre> <p> </p>
Data Set htwddKogRob-InfReal for Localization and Lifelong Mapping
<p>This small dataset contains real world log files from a 2.2 km long patrol between two points of a previously known map (see htwddKogRob-InfReal.png | 1px <span class="math-tex">\(\widehat{=} \)</span> 0.1m). The environment changes slightly and there are some dynamic obstacles. The figure (see htwddKogRob-InfReal_path.jpg) shows the path driven by the robots according to the real kilometers driven and the patrol points.</p> <p>The work was first presented in:</p> <ul> <li>A Fuzzy-based Adaptive Environment Model for Indoor Robot Localization</li> <li>Authors: Frank Bahrmann, Sven Hellbach, Hans-Joachim Böhme</li> <li>Date of Publication: 2016/10/6</li> <li>Conference: Telehealth and Assistive Technology / 847: Intelligent Systems and Robotics</li> <li>Publisher: ACTA Press</li> </ul> <p>Additionally, we present a video with the proposed algorithm and an insight of this dataset under:</p> <ul> <li>youtube.com/AugustDerSmarte</li> <li>https://www.youtube.com/watch?v=26NBFN_XeQg</li> </ul> <p><strong>Instructions for use</strong></p> <p>The zip archive contains ascii files, which contain the log files of the robot observations and robot poses. Since this data set was recorded in a real environment, the logfile provides only the odometry based robot poses. For further information, please refer to the header of the logfile. To simplify the parsing of the files, you can use these two Java snippets:</p> <p><strong>Laser Range Measurements:</strong></p> <pre><code class="language-java"> List<Double> ranges = new ArrayList<>(numOfLaserRays); List<Error> errors = new ArrayList<>(numOfLaserRays); String s = line.substring(4); String delimiter = "()"; StringTokenizer tokenizer = new StringTokenizer(s, delimiter); while(tokenizer.hasMoreElements()){ String[] arr = tokenizer.nextToken().split(";"); boolean usable = (arr[0].equals("0")?false:true); double range = Double.parseDouble(arr[1]); ranges.add(range); errors.add(usable?Error.OKAY:Error.INVALID_MEASUREMENT); }</code></pre> <p><strong>Poses:</strong></p> <pre><code class="language-java"> String poseString = line.split(":")[2]; String[] elements = poseString.substring(1, poseString.length()-1).split(";"); double x = Double.parseDouble(elements[0]); double y = Double.parseDouble(elements[1]); double phi = Double.parseDouble(elements[2]);</code></pre> <p> </p> <p> </p>
QTL Mapping for Resistance to Cankers Induced by Pseudomonas syringae pv. actinidiae (Psa) in a Tetraploid Actinidia chinensis Kiwifruit Population
<p>Raw Illumina R1 sequence reads for individual plants genotyped for the study entitled "QTL Mapping for Resistance to Cankers Induced by <em>Pseudomonas syringae</em> pv. <em>actinidiae</em> (Psa) in a Tetraploid <em>Actinidia chinensis</em> Kiwifruit Population" accepted in MDPI Pathogen journals, Special issue <em>"</em><em>Pseudomonas syringae</em> Species Complex"</p>
QTL Mapping for Resistance to Cankers Induced by Pseudomonas syringae pv. actinidiae (Psa) in a Tetraploid Actinidia chinensis Kiwifruit Population
<p>Raw Illumina R2 sequence reads for individual plants genotyped for the study entitled "QTL Mapping for Resistance to Cankers Induced by <em>Pseudomonas syringae</em> pv. <em>actinidiae</em> (Psa) in a Tetraploid <em>Actinidia chinensis</em> Kiwifruit Population" accepted in MDPI Pathogen journals, Special issue <em>"</em><em>Pseudomonas syringae</em> Species Complex"</p>
Biodiversity Hotspots Map (no text)
<p>This map displays the global <a href="https://zenodo.org/record/3261807#.X8_HgNhKg2x">Biodiversity Hotspots 2016.1 dataset</a>. The colors assigned to the hotspots are only used to distinguish adjacent hotspots and have no other meaning. The biodiversity hotspots represent terrestrial biodiversity only. The offshore lines are a cartographic device to group and highlight islands that are part of the same hotspots (e.g. Polynesia-Micronesia, Indo-Burma). The background image is from Natural Earth. This version is without labels; a version with the hotspots labelled in English is available: 10.5281/zenodo.4311850</p> <p>There are currently <a href="https://www.cepf.net/node/1996">36 recognized biodiversity hotspots</a>. These are Earth’s most biologically rich—yet threatened—terrestrial regions.</p> <p>To qualify as a biodiversity hotspot, an area must meet two strict criteria:</p> <ul> <li>Contain at least 1,500 species of vascular plants found nowhere else on Earth (known as "endemic" species).</li> <li>Have lost at least 70 percent of its primary native vegetation.</li> </ul> <p>Many of the biodiversity hotspots exceed the two criteria. For example, both the Sundaland Hotspot in Southeast Asia and the Tropical Andes Hotspot in South America have about <strong>15,000</strong> endemic plant species. The loss of vegetation in some hotspots has reached a startling <strong>95</strong> percent.</p>
Building age map, Vienna, around 1920
<p><strong>This data respository</strong> includes the following datasets:</p> <ol> <li>Building stock map 1920 (BSM_1920.shp) and its attribute table (BSM_1920_attribute_table.csv)</li> <li>Areas out of scope 1920 (AOOS_1920.shp)</li> <li>Scope of analog building age map 1920 (SABAM_1920.shp)</li> </ol>
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.