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767 results for “switzerland”
Alpine Structure Ruins, Grisons, Switzerland
Ruins of an alpine structure situated at around 2200 m a.s.l. in the Val Urschai, Lower Engadine, Switzerland (see [here](https://s.geo.admin.ch/8b6c79dd3e) for a map). The structure might have been a cellar for cooling milk. Its exact age is unknown, it belongs most probably to the Middle Ages or Early Modern Age. Nearby lie the seemingly associated ruins of a [building](https://sketchfab.com/3d-models/alpine-building-ruins-grisons-switzerland-539df679807249ab840fe9e8f9060275). Imagery shot in July 2011 using Kite Aerial Photography, see [https://silvrettahistorica.wordpress.com/2011/07/05/kinderspielzeug-im-dienste-der-archaologie/](https://silvrettahistorica.wordpress.com/2011/07/05/kinderspielzeug-im-dienste-der-archaologie/) (in German), and reprocessed in August 2020. Source: Objaverse 1.0 / Sketchfab
Schweizer Haus - Canton of Glarus, Switzerland
Amazing 3D - One of Glarus` most beautiful houses with amazing views to the surrounding alps. This very old house has seen some history! Check it out! Source: Objaverse 1.0 / Sketchfab
Cham-Bibersee ZG, Switzerland, HolzNr. 268
Worked medieval wood from now renaturated Bibersee lake, Canton of Zug, Switzerland (see https://s.geo.admin.ch/7d5a411948 for a map view). Excavated by the Amt für Denkmalpflege und Archäologie, Direktion des Innern, in 2014. Low resolution model generated by Structure from Motion photogrammetry. Source: Objaverse 1.0 / Sketchfab
Mammoth molar - Cham-Oberwil ZG, Switzerland
[Deutsche Version siehe [hier](https://sketchfab.com/3d-models/f1f5440e8d684291890897eb4a490fa3).] Upper right molar (M3) of a mammoth found in 2018 in a gravel pit near Cham-Oberwil (Canton Zug, Switzerland, see [https://s.geo.admin.ch/86165de2fe](https://bit.ly/2tawtvS)). The tooth was slightly damaged before or during extraction by an excavator. A preliminary C14 date gives an age of at least 29,000 years BP - the molar belongs, just like older finds from the same gravel pit, in the time before the Last Glacial Maximum (LGM) of the Weichselian (or, locally speaking, Birrfeld) glaciation!<br> <br> If you use this model, please attribute it to "Amt für Denkmalpflege und Archäologie, Kanton Zug, Jochen Reinhard" and/or link to the [German version of this site](https://sketchfab.com/3d-models/f1f5440e8d684291890897eb4a490fa3). <br> <br> **References** S. Maier/D. Jecker/G. Schaeren, Cham, Oberwil, Hof: Fundmeldung. Tugium 35, 2019, 35. https://bit.ly/34mvwgY. Source: Objaverse 1.0 / Sketchfab
Basilisk fountain Basel Switzerland
Basilisk fountain Basel Switzerland Made with [Scaniverse](https://scaniverse.com). Source: Objaverse 1.0 / Sketchfab
"Celtic Stone", Leukerbad, Switzerland
So called "Celtischer Stein" (celtic stone) south of Leukerbad, Switzerland (for a map see https://goo.gl/5y4RKY) showing an artificially incised circular shaped groove. Undated, but attributed to the "Neolithic" (sic!) by local folklore. The stone has apparently been destroyed in the 20th century, parts of it have been rediscovered in 2011/2012. Today, a picnic spot has been created around it. Lacking a "proper camera", the model is the result of a spontaneous comparison of the photogrammetry related image quality of two cell phones, the Huawei P10 and a Lumia 640 LTE. The resulting mesh is derived by combining the images from both phones, the texture uses only the Lumia phone pictures as the Huawei phone pictures somehow caused problems with flickering pixels. For further details (in German) see http://ssdi.ch/Inventar/VS/3954.01.pdf or 'German Bregy, Der Ringstein von Leukerbad. Walliser Jahrbuch 2017, 78-79'. Recorded in October 2017. Higher resolution model on request. Source: Objaverse 1.0 / Sketchfab
Results from national testing programs on the occurrence of chemical contaminants in food and feed - Switzerland
<p>In the framework of Articles 23 and 33 of Regulation (EC) No 178/2002 EFSA has received from the European Commission a mandate (M-2010-0374) to collect all available data on the occurrence of chemical contaminants in food and feed. These data are used in EFSA’s scientific opinions and reports on contaminants in food and feed. </p> <p>The presence of unauthorised substances or chemical contaminants in food may pose a risk factor for public health and can cause a negative impact on the quality of food. </p> <p>Commission Recommendations and Regulations on occurrence monitoring are in place for several contaminants of interest, some of which can be found here below: </p> <ul> <li>Commission Regulation (EU) 625/2017, on the application of food and feed law</li> <li>Commission Delegated Regulation (EU) 2022/931</li> <li>Commission Implementing Regulation (EU) 2022/932</li> <li>Commission Regulation (EU) 2023/915, on maximum levels for certain contaminants in food and repealing Regulation (EC) No 1881/2006</li> </ul> <p>These datasets contain the results of sampling that was designed according to national testing programs for a variety of contaminants in food and feed, as reported under the Chemical Monitoring Data Collection 2023 split by sampling year (data element ‘sampY’). </p> <p>More details are available in last year's finalised call for data ‘<a href="https://www.efsa.europa.eu/en/call/call-continuous-collection-chemical-contaminants-occurrence-data-food-and-feed-2023">Call for continuous collection of chemical contaminants occurrence data in food and feed | EFSA (europa.eu)</a>’.</p> <p>REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION: </p> <p>OCC-CHEMMON2023 – Federal Food Safety and Veterinary Office</p>
Fig. 9 in Pleistocene South American native ungulates (Notoungulata and Litopterna) of the historical Roth collections in Switzerland, from the Pampean Region of Argentina
Fig. 9 (See legend on previous page.)
Fig. 4 in The first Jurassic coelacanth from Switzerland
Fig. 4 (See legend on previous page.)
Fig. 2 in A new pachypleurosaur from the Early Ladinian Prosanto Formation in the Eastern Alps of Switzerland
Fig. 2 (See legend on previous page.)
Fig. 1 in A new pachypleurosaur from the Early Ladinian Prosanto Formation in the Eastern Alps of Switzerland
Fig. 1 (See legend on previous page.)
Fig. 3 in A new pachypleurosaur from the Early Ladinian Prosanto Formation in the Eastern Alps of Switzerland
Fig. 3 (See legend on previous page.)
Fig. 5 in A new pachypleurosaur from the Early Ladinian Prosanto Formation in the Eastern Alps of Switzerland
Fig. 5 (See legend on previous page.)
Fig. 3 in The first Jurassic coelacanth from Switzerland
Fig. 3 (See legend on previous page.)
Data and appendices: Genetic structure of the European white elm (Ulmus laevis Pall., Ulmaceae) in Switzerland
<p>This dataset is linked to the following article published in Annals of Forest Science: Dermelj, L., Fragnière, Y., Jacob, G. et al. Genetic structure of the European white elm (Ulmus laevis Pall., Ulmaceae) in Switzerland. Annals of Forest Science 81, 28 (2024). <a href="https://urldefense.com/v3/__https://doi.org/10.1186/s13595-024-01245-8__;!!Dc8iu7o!yKfGPXx0qHn-nE984OtuCUPPKaVjkUX03CZMhD3un5K_DjKgv8OrJB1nXYJdoWBTDKXDNA196eOKhBbjLjqqPgOm$" target="_blank" rel="noopener noreferrer">https://urldefense.com/v3/__https://doi.org/10.1186/s13595-024-01245-8__;!!Dc8iu7o!yKfGPXx0qHn-nE984OtuCUPPKaVjkUX03CZMhD3un5K_DjKgv8OrJB1nXYJdoWBTDKXDNA196eOKhBbjLjqqPgOm$</a></p> <p> </p> <pre> </pre>
Fig. 8 in Pleistocene South American native ungulates (Notoungulata and Litopterna) of the historical Roth collections in Switzerland, from the Pampean Region of Argentina
Fig. 8 (See legend on previous page.)
Elevation bias due to penetration of spaceborne radar signal on Grosser Aletschgletscher, Switzerland - supplementary datasets
<h1><strong>Introduction</strong></h1> <p>We provide DEMs from Pléiades stereo images and TanDEM-X acquired in March 2021 and their difference DEM (dDEM) used to estimate the elevation bias due to radar penetration on Grosser Aletschgletscher, Switzerland. Additionally, we provide the reference DEM (i.e., swissALTI3D) used for the Pléiades DEM co-registration and TanDEM-X production, stable terrain masks used for the co-registration and the glacier outline</p> <p>These are supplementary datasets associated to the publication by Bannwart et al., (2024a): “Elevation bias due to penetration of spaceborne radar signal on Grosser Aletschgletscher, Switzerland”, Journal of Glaciology. DOI: <a href="https://doi.org/10.1017/jog.2024.37">https://doi.org/10.1017/jog.2024.37</a></p> <h1><strong>Datasets and Citation</strong></h1> <p>The following datasets have been used and/or produced as part of the study above. Below you find a description of the individual datasets and their generation, including a citation example for each dataset. In general, when one or more datasets are used, both the individual dataset as well as the study (Bannwart et al. 2024) need to be cited. If you refer to the entire dataset, cite the Zenodo entry as well as the study.</p> <ul> <li> <p>TanDEM-X_DEM_6m_EPSG_32632_non_coreg.tif</p> </li> <li> <p>TanDEM-X_DEM_6m_EPSG_32632_coreg.tif</p> </li> <li> <p>Pleiades_DEM_2m_EPSG_32632_non_coreg.tif</p> </li> <li> <p>Pleiades_DEM_6m_EPSG_32632_coreg.tif </p> </li> <li> <p>swissALTI3D_2m_EPSG_32632.tif</p> </li> <li> <p>dDEM_non_corrected_6m_EPSG_32632.tif</p> </li> <li> <p>dDEM_corrected_6m_EPSG_32632.tif</p> </li> <li> <p>stable_terrain_mask_coreg_Pléiades_2m_EPSG_32632.tif</p> </li> <li> <p>stable_terrain_mask_coreg_TanDEM-X_6m_EPSG_32632.tif</p> </li> <li> <p>stable_terrain_mask_coreg_TanDEM-X_modified_6m_EPSG_32632.tif</p> </li> <li> <p>glacier_outline_2021.shp</p> </li> </ul> <h1><strong>Data and Methods</strong></h1> <h2>TanDEM-X DEMs (non co-registered and co-registered):</h2> <p>We used an InSAR DEM generated from TanDEM-X Coregistered Single look Slant range Complex (CoSSC) data provided by the German Aerospace Center (DLR) through the project XTI_GLAC7746. The DEM originates from a single bistatic X-band (9.65 GHz) InSAR acquisition in the polarisations VV and HH from 30 March 2021 at 5:45 Central Europe Time. We used the operational processing system of the TanDEM-X mission to generate the DEM. The removal of artefacts resulted in data voids. The TanDEM-X DEM was then co-registered with the Pléiades DEM (see publication).</p> <p>Resolution: 6 m</p> <p>Coordinate reference system: EPSG:32632</p> <p><strong>Citation of individual dataset: </strong></p> <p>TanDEM-X © DLR 2024</p> <p>DLR-IMF: TanDEM-X Payload Ground Segment - CoSSC Generation and Interferometric Considerations, German Aerospace Center (DLR), Remote Sensing Technology Institute (IMF) Oberpfaffenhofen, Germany, Issue 1.0, available at: https://tandemx-science.dlr.de/ (last access: 3 May 2024), doc. TD-PGS-TN-3129.</p> <p>DLR-EOC: TanDEM-X Ground Segment – DEM Products Specification Document, German Aerospace Center (DLR) – Earth Observation Center (EOC), EOC, DLR, Oberpfaffenhofen, Germany, 3.2 Edn., available at: https://tandemx-science.dlr.de/ (last access: 3 May 2024), doc. TD-GS-PS-0021, 2018.</p> <p><strong>Citation example:</strong></p> <p>“The TanDEM-X DEM (DLR 2024; DLR-IMF 2024; DLR-EOC 2024) from the study of Bannwart et al. (2024a)....”</p> <p><strong>Licence:</strong></p> <p>This dataset is licensed under a Creative Commons CC BY-NC-SA 4.0 International License (Attribution-NonCommercial-ShareAlike).</p> <h2>Pléiades DEMs (non co-registered and co-registered):</h2> <p>The stereo pair was acquired on 31 March 2021 at 10:40 Central Europe Time. The images were processed with the NASA Ames Stereo Pipeline (ASP, Beyer and others, 2018) to generate the DEM with a ground-sampling distance of 2 m using the Semi-Global-Matching algorithm and the processing parameters from Deschamps-Berger and others (2020) without ground control points (GCPs). The Pléiades DEM was then co-registered with the reference DEM (see publication). To calculate the DEM differencing, the Pléiades DEM was resampled using bilinear interpolation to 6 m to match the resolution of the TanDEM-X DEM.</p> <p>Resolution: 2 m (non co-registered), 6 m (co-registered)</p> <p>Coordinate reference system: EPSG:32632</p> <p><strong>Citation of individual dataset: </strong></p> <p>Pléiades © CNES 2023, distribution AIRBUS DS</p> <p>Berthier, E., Lebreton, J., Fontannaz, D., Déprez, A., Michéa, D., Malet, J.-P., LEGOS-OMP / Data Terra (ForM@Ter-Theia) (2024). Pléiades Glacier Observatory Data Products. EOST. (Collection). doi: 10.25577/313a-a978</p> <p><strong>Citation example:</strong></p> <p>“The Pléiades DEM (CNES 2023; Berthier et al. 2024) from the study of Bannwart et al. (2024a)....”</p> <p><strong>Licence:</strong></p> <p>This dataset is licensed under a Creative Commons CC BY-NC 4.0 International License (Attribution-NonCommercial).</p> <h2>swissALTI3D: </h2> <p>We used the swissALTI3D DEM from swisstopo (Swiss Federal Office of Topography (2021a) as a reference DEM for (a) the co-registration of the Pléiades DEM and (b) the generation of the TanDEM-X DEM (i.e., phase unwrapping). This swissALTI3D DEM has a resolution of 2 m and was generated using aerial images acquired between July and September 2017. The downloaded version was provided in orthometric heights and swiss coordinate system CH1903+ / LV95 (EPSG:2056). Therefore, we converted to WGS84 UTM projection (EPSG:32632) using cubic interpolation and to ellipsoidal heights using the Swiss geoid model provided by swisstopo (Swiss Federal Office of Topography, 2021b). The geoid is provided in the geographic coordinate system (EPSG:4258), which was projected to UTM using the cubic method.</p> <p>Resolution: 2 m</p> <p>Coordinate reference system: EPSG:32632</p> <p><strong>Citation of individual dataset: </strong> </p> <p>Swiss Federal Office of Topography (2021). swissALTI3D. Das hochpräzise digitale Höhenmodell der Schweiz. Bundesamt für Landestopografie swisstopo, ed. Wabern. <a href="https://www.swisstopo.admin.ch/de/geodata/height/alti3d.html">https://www.swisstopo.admin.ch/de/geodata/height/alti3d.html</a>.</p> <p><strong>Citation example:</strong></p> <p>“The swissALTI3D (Swiss Federal Office of Topography 2021) as used in Bannwart et al. (2024a)....”</p> <p><strong>Licence:</strong></p> <p>This dataset is licensed under a Creative Commons CC BY 4.0 International License (Attribution).</p> <h2>DEM differencing (dDEM, non corrected and corrected):</h2> <p>We used DEM differencing to quantify the elevation difference (dh) between the TanDEM-X DEM and the Pléiades DEM. To calculate the dDEM we subtracted the Pléiades DEM from the TanDEM-X DEM (after co-registration). Values larger than ±50m in the dDEM are considered outliers and removed. Further, on the tongue of Grosser Aletschgletscher we encountered a bias in the dDEM originating from the phase unwrapping during the TanDEM-X DEM production. This resulted in unrealistic positive elevation differences at the tongue (up to 50 m). Therefore, on-glacier, we additionally removed positive differences larger than 5 m. For direct comparison of the elevation differences with the GPR, snow pit and snow core measurements one has to assume a signal propagation velocity within the snow and ice medium, which will lead to a smaller height of ambiguity in the snow volume and a reduced actual penetration depth. As a measure for the actual radar penetration depth the previously calculated dDEM due to signal penetration is scaled proportionally with (approx. 78%). The resulting file is called “dDEM_corrected”. For more information we refer to the publication.</p> <p>Resolution: 6 m</p> <p>Coordinate reference system: EPSG:32632</p> <p><strong>Citation of individual dataset: </strong> </p> <p>Bannwart, J., Piermattei, L., Dussaillant, I., Krieger, L., Floricioiu, D., Berthier, E., Roeoesli, C., Machguth, H. and Zemp, M. (2024). Elevation bias due to penetration of spaceborne radar signal on Grosser Aletschgletscher, Switzerland - supplementary datasets [Data set]. Zenodo. https://doi.org/10.5281/zenodo.11071899</p> <p><strong>Citation example:</strong></p> <p>“The dDEM (Bannwart et al. 2024b) as produced in Bannwart et al. (2024a)....”</p> <p><strong>Licence:</strong></p> <p>This dataset is licensed under a Creative Commons CC BY-NC-SA 4.0 International License (Attribution-NonCommercial-ShareAlike).</p> <h2>Stable terrain masks:</h2> <p>The stable terrain masks have been used to co-register the Pléiades DEM to the swissALTI3D and the TanDEM-X DEM to the Pléiades DEM. The two masks were created using the Pléiades orthophoto and a supervised classification method following the approach by Deschamps-Berger C and others (2020). The masks consist of off-glacier areas where no changes are expected between the two DEMs, and only snow-free pixels were retained. The masks are a binary file with a resolution of 2m and 6 m, respectively, in UTM32N projection. To evaluate the sensitivity of the radar penetration bias to co-registration, we tested two co-registration algorithms on two stable terrain masks used to co-register the TanDEM-X DEM. In the modified stable mask, we manually removed pixels in the sparse forest and dark shadow areas based on a visual inspection of the Pléiades orthophoto.<strong> </strong></p> <p>Resolution: 2 m (mask used to co-register Pléiades DEM to the swissALTI3D), 6 m (masks used to co-register the TanDEM-X DEM to the Pléiased DEM)</p> <p>Coordinate reference system: EPSG:32632</p> <p><strong>Citation of individual dataset:</strong></p> <p>Bannwart, J., Piermattei, L., Dussaillant, I., Krieger, L., Floricioiu, D., Berthier, E., Roeoesli, C., Machguth, H. and Zemp, M. (2024). Elevation bias due to penetration of spaceborne radar signal on Grosser Aletschgletscher, Switzerland - supplementary datasets [Data set]. Zenodo. https://doi.org/10.5281/zenodo.11071899<a href="https://doi.org/10.5281/zenodo.11071899"> </a></p> <p><strong>Citation example:</strong></p> <p>“The stable terrain mask to co-register the Pléiades DEM (Bannwart et al. 2024b) in Bannwart et al. (2024a)....”</p> <p><strong>Licence:</strong></p> <p>This dataset is licensed under a Creative Commons CC BY-NC 4.0 International License (Attribution-NonCommercial).</p> <h2>Glacier outline:</h2> <p>The outline as a shapefile of Grosser Aletschgletscher was manually adjusted to the glacier’s outline in 2021 based on the GLIMS outlines from 2015 (Paul and others, 2019) and the Pléiades orthophoto.</p> <p><strong>Citation of individual dataset:</strong></p> <p>Bannwart, J., Piermattei, L., Dussaillant, I., Krieger, L., Floricioiu, D., Berthier, E., Roeoesli, C., Machguth, H. and Zemp, M. (2024). Elevation bias due to penetration of spaceborne radar signal on Grosser Aletschgletscher, Switzerland - supplementary datasets [Data set]. Zenodo. https://doi.org/10.5281/zenodo.11071899</p> <p>Paul, F. (submitter), Azzoni, R.S., Fugazza, D., Le Bris, R., Nemec, J., Paul, F., Rabatel, A., Ramusovic, M.; Rastner, P., Schaub, Y., Schwaizer (nee Bippus), G (analysts). (2019) GLIMS Glacier Database. Boulder, Co. National Snow and Ice Data Center. http://dx.doi.org/10.7265/N5V98602.</p> <p><strong>Citation example:</strong></p> <p>“The glacier outline of Grosser Aletschgletscher in 2021 (Bannwart et al 2024b; Paul et al. 2019) as produced in Bannwart et al. (2024a)....”</p> <p><strong>Licence:</strong></p> <p>This dataset is licensed under a Creative Commons CC BY-NC 4.0 International License (Attribution-NonCommercial).</p> <h1>Acknowledgements</h1> <p>We thank swisstopo for providing the swissALTI3D and CNES for their support.</p> <p> </p>
Fig. 6. O in First description of Onchocerca jakutensis (Nematoda: Filarioidea) in red deer (Cervus elaphus) in Switzerland
Fig. 6. O. jakutensis female: Ratio of cuticular annulation (A) to medullar striae (S) 1:4.
Fig. 2 in First description of Onchocerca jakutensis (Nematoda: Filarioidea) in red deer (Cervus elaphus) in Switzerland
Fig. 2. Anterior end of O. jakutensis female, with granular lumps in process of degeneration.
Rock-temperature, fracture displacement and acoustic/micro-seismic data measured at Matterhorn Hörnligrat, Switzerland
<p>This repository contains data, which were acquired in the context of project X-Sense2 (financed by nano-tera.ch, ref. no. 530659) at the Matterhorn Hörnligrat fieldsite on 3500 m a.s.l. from 2015 until 1 April 2018. These data were used in the following publication:</p> <p>Weber, S., Faillettaz, J., Meyer, M., Beutel, J., and Vieli, A.: Acoustic and micro-seismic characterization in steep bedrock permafrost on Matterhorn (CH), Journal of Geophysical Research: Earth Surface, 123(6), 1363-1385, doi: 10.1029/2018JF004615, 2018.</p> <p><strong>AM-DATA</strong> This repository contains selected accelerometer data with SI unit m/s<sup>2</sup> (hourly .miniseed-files, MH40 refers to AM<sub>scarp</sub>). These data were measured continuously using an accelerometer based on a Wilcoxon 728A/T (10 − 10000 Hz, 24 kHz resonance frequency), netADC data acquisition system and netSP+ seismological processor of Institute of Mine Seismology. Data were synchronized to a global time reference using GPS (<1 μs). The data is stored in .miniseed-format and splitted in hourly files.</p> <p><strong>SM-DATA</strong> This repository contains selected raw seismometer data in counts (hourly .miniseed-files, MHDL refers to SM<sub>scarp</sub> and MHDT refers to SM<sub>ridge</sub>). These data were measured using a Lennartz electronic low-noise seismometer LE-3Dlite MKIII (1−100 Hz) and Nanometrics Centaur digital recorder, a 24-bit high-resolution seismic data acquisition system disciplined by GPS (<100 μs) with a sampling rate of 1000 sps. The data is stored in .miniseed-format and splitted in hourly files.</p> <p><strong>TIMESERIES</strong> This repository contains 8 timeseries:</p> <ul> <li> <p><em>AS_scarp_high.csv</em> describes the threshold triggeres acoustic emission hits acquired with a piezoelectric sensor Mistras Physical Acoustics Corporation R6α, 35−100 kHz, 55 kHz resonance frequency.</p> </li> <li> <p><em>AS_scarp_low.csv</em> describes the threshold triggeres acoustic emission hits acquired with a piezoelectric sensor Mistras Physical Acoustics Corporation R.45, 5−30 kHz, 20 kHz resonance frequency.</p> </li> <li> <p><em>CR_old.csv</em> described the measured fracture displacement in mm.</p> </li> <li> <p><em>SMridge_nofilter.csv</em> describes automatically triggered events using a recursive short-term/long-term average (STA/LTA ) algorithm without filtering. Peak amplitude in µm/s and energy in µm<sup>2</sup>/s<sup>2</sup>.</p> </li> <li> <p><em>SMridge_filtered.csv</em> describes automatically triggered events using a recursive short-term/long-term average (STA/LTA ) algorithm in the frequency band 33-67 Hz. Peak amplitude in µm/s and energy in µm<sup>2</sup>/s<sup>2</sup>.</p> </li> <li> <p><em>SMscarp_filtered.csv</em> describes automatically triggered events using a recursive short-term/long-term average (STA/LTA ) algorithm without filtering. Peak amplitude in µm/s and energy in µm<sup>2</sup>/s<sup>2</sup>.</p> </li> <li> <p><em>SMscarp_nofilter.csv</em> describes automatically triggered events using a recursive short-term/long-term average (STA/LTA ) algorithm in the frequency band 33-67 Hz. Peak amplitude in µm/s and energy in µm<sup>2</sup>/s<sup>2</sup>.</p> </li> <li> <p><em>temperature.csv</em> describes the rock temperature (in °C) at different depths: 5, 10, 20, 30, 50 and 100 cm.</p> </li> </ul> <p>All time stamps are in UTC.</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.