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1,838 results for “location”
MS-based orthophotos (50 cm): the dynamics of the prehistoric communities located in the Mostiștea Valley and Danube Plain (between Oltenița and Călărași)
<p>This dataset is part of a larger project on the dynamics of the prehistoric communities located in the Mostiștea Valley and Danube Plain (between Oltenița and Călărași), supervised by the ArchaeoSciences Division of the Research Institute of the University of Bucharest (ICUB) and Kiel University (Germany), in partnership with HOGENT, University of Applied Sciences and Arts (Belgium), Museum of Bucharest, Museum of the Lower Danube Călărași, Museum of Gumelnița Civilization Oltenița, and "Vasile Pârvan" Institute of Archaeology (Romania), under the "Sultana School of Archaeology" initiative.</p> <p>Spatial data play a crucial role in archaeological research, and orthophotos, digital elevation models, and 3D models are frequently used for the mapping, documentation, and monitoring of archaeological sites. Thanks to the availability of compact and low-cost uncrewed airborne vehicles, the use of UAV-based photogrammetry is well matured in this field over the last two decades. More recently, compact airborne systems are also available that allow the recording of thermal data, multispectral data, and airborne laser scanning. For this project, various platforms and sensors are applied at the Chalcolithic archaeological sites in the Mostiștea Basin and Danube Valley (Southern Romania). By analyzing the performance of the systems and the resulting data, insight is given into the selection of the appropriate system for the right application. This analysis requires thorough knowledge of data acquisition and data processing as well. As both laser scanning and photogrammetry typically result in very large amounts of data, a special focus is also required on the storage and publication of the data. Hence, the objective of this project is to provide a full overview of various aspects of 3D data acquisition for UAV-based mapping. Based on the conclusions drawn in our related publications, it is stated that photogrammetry and laser scanning can result in data with similar geometrical properties when acquisition parameters are appropriately set. On the one hand, however, the used ALS-based system outperforms the photogrammetric platforms in terms of operational time and the area covered. On the other hand, conventional photogrammetry provides flexibility that might be required for very low-altitude flights, or emergency mapping. Furthermore, as the used ALS sensor only provides a geometrical representation of the topography, photogrammetric sensors are still required to obtain true color- or false color composites of the surface. Lastly, the variety of data, like pre- and post-rendered raster data, 3D models, and point clouds, requires the implementation of multiple methods for the online publication of data. Various client-side and server-side solutions are presented to make the data available for other researchers.</p>
Global ice drilling and archive location data for select ice cores
<p>This document includes ice drill site information and ice core repository information for select ice cores retrieved between 1958 and 2022. Included data are not representative of all ice cores drilled during this time period, nor are they representative of all ice core samples collected and maintained by all of the contributing programs and facilities. Data are presented as they were provided by contributing facilities in 2022, when they were used to generate a figure for an article in Past Global Changes Magazine (doi.org/10.22498/pages.30.2.98).</p> <p>The data describe ice core drilling sites (latitude, longitude, elevation, site name), ice core samples (bottom depth, bottom age, core diameter, core completion date, corresponding publications), and ice core storage facilities (latitude, longitude, name).</p> <p>Contributing facilities include the following: Alfred Wegener Institute (Germany), Australian Antarctic Division (Australia), Australian Antarctic Program Partnership (Australia), Byrd Polar Center - University of Ohio (United States of America), Canadian Ice Core Lab (Canada), Chiba University (Japan), Commonwealth Scientific and Industrial Research Organization (Australia), Institute of Environmental Geosciences - University of Grenoble (France), Institute of Low Temperature Science - University of Hokkaido (Japan), Institute of Polar Science and Engineering - Jilin University (China), Karakoram International University (Pakistan), Lanzhou Institute of Glaciology and Geocryology (China), Nagoya University (Japan), National Institute of Polar Research (Japan), National Science Foundation Ice Core Facility (United States of America), New Zealand National Ice Core Facility (New Zealand, Physics of Ice Climate and Earth - University of Copenhagen (Denmark), Polar Research Institute of China (China), Research Institute for Humanity and Nature (Japan), and Tibet University. </p> <p>We are grateful to each of these facilities for contributing details of their ice core collections for this work. </p> <p> </p> <p> </p> <p>Electronic data accessibility and sample request procedures for a few of these facilities of which the authors are aware are listed below.</p> <p>Australia: data can be obtained from the Australian Antarctic Data Centre (<a href="https://urldefense.com/v3/__https://data.aad.gov.au/__;!!K-Hz7m0Vt54!k4oxTmHZ_w1LKmpFwH8LzlfLDG73TEDLZwozl9Q6dL-wfS_EQG7S75R9T3faMQA7BHyK5mv3Br0-kyWRnumedvhR$">https://data.aad.gov.au</a>); access to ice from the Australian Antarctic Program is via application (see <a href="https://urldefense.com/v3/__https://www.antarctica.gov.au/science/information-for-scientists/__;!!K-Hz7m0Vt54!k4oxTmHZ_w1LKmpFwH8LzlfLDG73TEDLZwozl9Q6dL-wfS_EQG7S75R9T3faMQA7BHyK5mv3Br0-kyWRnosG8VPm$">https://www.antarctica.gov.au/science/information-for-scientists/)</a></p> <p>Denmark: data can be obtained from <a href="https://www.iceandclimate.nbi.ku.dk/data/">www.iceandclimate.nbi.ku.dk/data</a>; the ice sampling request procedure is listed here: <a href="https://www.iceandclimate.nbi.ku.dk/data/samplingprocedure/">https://www.iceandclimate.nbi.ku.dk/data/samplingprocedure/</a> </p> <p>United States: many ice core datasets can be found at the NOAA World Data Center (<a href="https://www.ncei.noaa.gov/products/paleoclimatology/ice-core">https://www.ncei.noaa.gov/products/paleoclimatology/ice-core</a>); the allocation policy for ice core samples can be found here: <a href="https://icecores.org/policy">https://icecores.org/policy</a>.</p>
Map of locations in bylines from al-Ḥaqāʾiq
<p>Geographic distribution and relative frequencies of locations mentioned in bylines. This update contains more maps with different regions and much improved titles and legends. In addition, unknown locations (or NA values) were mapped to a location in the Black Sea.</p>
Map of locations in bylines from al-Ḥasnāʾ
<p>Geographic distribution and relative frequencies of locations mentioned in bylines. This update contains more maps with different regions and much improved titles and legends. In addition, unknown locations (or NA values) were mapped to a location in the Black Sea.</p>
Map of locations in bylines from al-Muqtabas
<p>Geographic distribution and relative frequencies of locations mentioned in bylines. This update contains more maps with different regions and much improved titles and legends. In addition, unknown locations (or NA values) were mapped to a location in the Black Sea.</p>
Conductivity Temperature and Depth Data Various Location Throughout Alfacs Bay
<p>A dye tracing study was conducted in Alfacs Bay, Catalonia in March 2019. A CastAway profiling conductivity, temperature and depth (CTD) meter was used to take several CTD profiles across the study area throughout the study.</p>
Supporting Information for "New 3D velocity model (mTAB3D) for absolute hypocenter location in southern Iberia and the westernmost Mediterranean"
<p>These files comprise supplementary information for the paper entitled "New 3D velocity model (mTAB3D) for absolute hypocenter location in southern Iberia and the westernmost Mediterranean" (Sánchez-Roldán et al., 2024a)</p> <p>These results were obtained after performing a relocation using the 3D P-wave velocity model mTAB3D (Sánchez-Roldán et al. 2024b).</p> <p>In "Files.zip", we provide the eight files with the absolute locations and the uncertainty parameters (extracted from the 68% confidence ellipse of the PDF’s) obtained after performing the relocation using mIGN1D and mTAB3D. The absolute location files follow this format:</p> <p>origin_time(YYYY-mm-ddTHH:MM:SS) longitude(º) latitude(º) depth(km) magnitude(mbLg)</p> <p>• origin_time: Hypocenter’s origin time after the relocation.</p> <p>• longitude: Hypocenter’s longitude in decimal degrees after the relocation.</p> <p>• latitude: Hypocenter’s latitude in decimal degrees after the relocation.</p> <p>• depth: Hypocenter’s depth in kilometers.</p> <p>• magnitude: Hypocenter’s magnitude (mbLg) computed by the Spanish Seismic Network.</p> <p>The files with the uncertainty values:</p> <p>horizontal_uncertainty(km) vertical_uncertainty(km) rms(s) no_arrivals</p> <p>• horizontal_uncertainty: Obtained after computing the geometrical mean between the horizontal semi-minor and semi-major axes of the 68% confidence ellipse in kilometers.</p> <p>• vertical_uncertainty: Vertical semi-axis of the 68% confidence ellipse.</p> <p>• rms: root-mean-square of residuals at maximum likelihood or expectation hypocenter.</p> <p>• no_arrivals: number of readings used for the absolute location.</p> <p><br>File S1. File_S1.dat: Eastern Betics Shear Zone catalog’s absolute locations with mIGN1D.</p> <p>File S2. File_S2.dat: Eastern Betics Shear Zone catalog’s statistics with mIGN1D.</p> <p>File S3. File_S3.dat: Eastern Betics Shear Zone catalog’s absolute locations with mTAB3D.</p> <p>File S4. File_S4.dat: Eastern Betics Shear Zone catalog’s statistics with mTAB3D.</p> <p>File S5. File_S5.dat: Al Hoceima 2016 catalog’s absolute locations with mIGN1D.</p> <p>File S6. File_S6.dat: Al Hoceima 2016 catalog’s statistics with mIGN1D.</p> <p>File S7. File_S7.dat: Al Hoceima 2016 catalog’s absolute locations with mTAB3D.</p> <p>File S8. File_S8.dat: Al Hoceima 2016 catalog’s statistics with mTAB3D.</p> <p>Additionally, we provide two figures showing the location of those hypocenters (alboran.jpg and ebsz.jpg), which are included as Figures 3 and 5, respectively, in Sánchez-Roldán et al. (2024a).</p> <p>References:</p> <p><span>Sánchez-Roldán, J. L.</span>, <span>Álvarez-Gómez, J. A.</span>, <span>Martínez-Díaz, J. J.</span>, <span>Herrero-Barbero, P.</span>, <span>Perea, H.</span>, <span>Cantavella, J. V.</span>, & <span>Lozano, L.</span> (<span>2024a</span>). <span>New 3D velocity model (mTAB3D) for absolute hypocenter location in southern Iberia and the westernmost mediterranean</span>. <em>Earth and Space Science</em>, <span>11</span>, e2023EA00299. <a href="https://doi.org/10.1029/2023EA002993">https://doi.org/10.1029/2023EA002993</a></p> <p>Sánchez-Roldán, J. L., Álvarez-Gómez, J. A., Martínez-Díaz, J. J., Herrero-Barbero, P., Perea, H., Lozano, L., & Cantavella, J. V. (2024b). MTAB3D: a 3-D velocity model for absolute hypocenter location in southern Iberia and westernmost Mediterranean. (v1.0) [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.7766525" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.7766525</a></p> <div> </div> <p> </p> <p> </p>
Dataset assoziated with the paper "Optimisation of mobility hub locations for a sustainable mobility system"
<p>This is supplementary data for the paper 'Optimisation of mobility hub locations for a sustainable mobility system'. The Excel file 'InputParameters' contains the parameters used as input for the bilevel optimization model. Note that it contains two sheets: one for the calibrated parameters in the utility function, and one for the mode-specific input parameters. The external cost data are based on the study by Bieler, C. & Sutter, D. (2019), whereas the cost parameters were derived from the websites of the local service providers.</p> <p>The result folder contains the result files of all the experiments discussed in the paper. Each subfolder corresponds to one test instance. The subfolders contain the information on the built mobility hubs (build_mobilityhubs.csv), the modal split information (wegcount.rating.csv for both absolute and proportional data), the number of transfers for each mode at each station (transfercount.csv), and also the full list of modes that each user group used in their travels (user_paths.csv). Note that the stations are given by ID, and the ID is taken from the GTFS data for Aachen.</p> <p>The additional experiments from Section 5.5 on the modal split for a higher number of bike- and car-sharing stations are contained in the "Further Maximization of Sharing Modes Test.zip." Each subfolder contains specific data for the test instances, while the Excel sheet modal_split_Percent.xlsx summarizes and visualizes the modal split data.</p> <p>Further result data can be provided upon request.</p> <p><a name="_CTVL00166b62df5ea8545b3990eea974b27cf8a"></a>Bieler, C., Sutter, D., 2019. Externe Kosten des Verkehrs in Deutschland: Straßen-, Schienen-, Luft- und Binnenschiffverkehr 2017.</p>
Earthquake Connection Indicator (ECI) table for the locations of the cult of Poseidon with earthquake-related epithets in the ancient Aegean Sea region
<p>The rationale behind this table is to categorize the spatial attachment of the evidence of the earthquake-related epithets of Poseidon to earthquake proxies in the region of the ancient Aegean Sea.</p> <h2>Attributes</h2> <h3><strong>Location</strong></h3> <p>States the location of a findspot of the evidence of an earthquake-related epithet of Poseidon.</p> <h3><strong>Epithet</strong></h3> <p>Identifies a specific earthquake-related epithet of Poseidon at a particular location.</p> <h3><strong>Earthquake_connection_indicator</strong></h3> <p>Each location of the cult of Poseidon with an earthquake-related epithet is attributed with a number from 1 to 3 based on its spatial ties to earthquake proxies. Earthquake proxies consist of active fault lines (Ganas, A., I. A. Oikonomou, and C. Tsimi. 2013. ‘NOAfaults: A Digital Database for Active Faults in Greece’. Bulletin of the Geological Society of Greece 47 (2): 518–30. https://doi.org/10.12681/bgsg.11079), and locations of ancient earthquake reports (Guidoboni, Emanuela, Graziano Ferrari, Gabriele Tarabusi, Giulia Sgattoni, Alberto Comastri, Dante Mariotti, Cecilia Ciuccarelli, Maria Giovanna Bianchi, and Gianluca Valensise. 2019. ‘CFTI5Med, the New Release of the Catalogue of Strong Earthquakes in Italy and in the Mediterranean Area’. Scientific Data 6 (1). https://doi.org/10.1038/s41597-019-0091-9; National Geophysical Data Center. 1972. ‘Global Significant Earthquake Database’. NOAA National Centers for Environmental Information. https://doi.org/10.7289/V5TD9V7K).</p> <p>ECI 1: A location with an attested cult of Poseidon with an earthquake-related epithet located more than 5 kilometers from the nearest active fault or an ancient earthquake report.</p> <p>ECI 2: A location with an attested cult of Poseidon with an earthquake-related epithet located within a 5-kilometer radius from an active fault line.</p> <p>ECI 3: A location with an attested cult of Poseidon with an earthquake-related epithet located either a) within a 5-kilometer radius from an active fault line with an ancient earthquake report anywhere along the particular fault; or b) within a 5-kilometer radius from an ancient earthquake report itself.</p> <h3><strong>Lat</strong></h3> <p>Latitude</p> <h3><strong>Long</strong></h3> <p>Longitude</p> <h3><strong>DB MAP testimony #</strong></h3> <p>ID number of a testimony of Poseidon with an earthquake-related epithet based on Bonnet C. (dir.), ERC Mapping Ancient Polytheisms 741182 (DB MAP), Toulouse 2017-2023: <a href="https://base-map-polytheisms.huma-num.fr/">https://base-map-polytheisms.huma-num.fr</a>. DOI: <a href="https://doi.org/10.34847/nkl.1e19sne6">https://doi.org/10.34847/nkl.1e19sne6.</a></p> <h3><strong>PHI ID</strong></h3> <p>IDs of inscriptions mentioning Poseidon with an earthquake-related epithet from the Searchable Greek Inscriptions (PHI, https://inscriptions.packhum.org/) as listed in the Greek Inscriptions in Space and Time dataset (GIST, Kaše, Vojtěch, Petra Heřmánková, and Adéla Sobotková. 2023. ‘GIST’. Zenodo. https://doi.org/10.5281/zenodo.10139110.). To search the ID at PHI, put the number at the end of the URL in the following format https://epigraphy.packhum.org/text/32602.</p> <h3><strong>Thely</strong></h3> <p>Indicates whether the evidence is listed in the book Thély, Ludovic. 2016. Les Grecs face aux catastrophes naturelles: savoirs, histoire, mémoire. Bibliothèque des Écoles françaises d’Athènes et de Rome : BEFAR. Athènes, Paris: École française ; diffusion De Boccard.</p>
Rakhterā (रखतेरा or Rakhetrā, Ashoknagar). Location of the Bhiyāṃdāṃt caves with inscriptions and images of Ādinātha and other deities.
<p>Rakhterā (रखतेरा or Rakhetrā, Ashoknagar). Location of the Bhiyāṃdāṃt caves with inscriptions and images of Ādinātha and other deities.</p>
Installing a EC Sensor on a remote location.
<p><strong>1.Introduction</strong></p> <p>The objective of this document is to provide a description of the dataset entitled “Installing an EC Sensor on a remote location”.</p> <p>The guidelines on how to use the files are included in this document.</p> <p>The dataset is part of the deliverables D9.4 (First data management plan) and D9.5 (Final data management plan).</p> <p><strong>2.Description of the data</strong></p> <p><strong>2.1.Origin</strong></p> <p>This dataset includes data collected from the experiments related to the task “Installing a EC Sensor on a remote location” as part of the WP8 “validation in the industrial scenario”.</p> <p><strong>2.2.Type</strong></p> <p>The data consists of Eddy Current (EC) measurements.</p> <p><strong>2.3.Formats</strong></p> <p>The acquired data are available in several formats.</p> <p>2.3.1.*.sidata files</p> <p>These files are proprietary format that can be opened with the software “UPecView” supplied by Sensima Inspection (http://www.sensimainsp.com).<br> This software provides an interface familiar to what expected by eddy-current inspectors.</p> <p>Each file includes all the relevant information that may be used for analysis: the measurements and the instrument configuration (ex. Excitation frequency of the probe) is contained in this file.</p> <p>2.3.2.*.csv files</p> <p>The csv files contain an export of the measurements only (without instrument settings); a comma separator is used. Each row is composed of the following variables: Time (s), Signal (in-phase), Signal (out-of-phase), Channel/state, Extra signal (ADC), Encoder coordinate 1 (x), Encoder coordinate 2 (y), Encoder coordinate 3 (z), Encoder error status.</p> <p> </p> <p> </p> <p><strong>3.Measurements indexing</strong></p> <p>Folder</p> <p>Filename</p> <p>Creation date</p> <p>Description</p> <p>Target</p> <p>Location</p> <p> </p> <p>EXP001</p> <p>0001A</p> <p>12.03.2019</p> <p>Calibration block scan</p> <p>Calibration block</p> <p>Seville, Spain</p> <p> </p> <p>EXP001</p> <p>0001B</p> <p>12.03.2019</p> <p>Manual reference scan on weld pipe</p> <p>Calibration block</p> <p>Seville, Spain</p> <p> </p> <p>EXP001</p> <p>0002A</p> <p>12.03.2019</p> <p>Drone overall scan inspection and sensor deployment</p> <p>Cement kiln</p> <p>Seville, Spain</p> <p> </p> <p>EXP001</p> <p>0002B</p> <p>12.03.2019</p> <p>Deployed sensor</p> <p>Cement kiln</p> <p>Seville, Spain</p> <p> </p> <p>EXP001</p> <p>0002C</p> <p>12.03.2019</p> <p>Deployed sensor</p> <p>Cement kiln</p> <p>Seville, Spain</p> <p> </p> <p>EXP001</p> <p>0002D</p> <p>12.03.2019</p> <p>Permanent sensor removal</p> <p>Cement kiln</p> <p>Seville, Spain</p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p>
Rhodamine fluorometry fixed location data Alfacs bay
<p>Rhodamine dye was released from a waste water outfall in Alfacs Bay, Catalonia. This dye has a strong red/pink colour and can be used to trace the movement of the waster water plume. These fluorimetry data were generated using fluorimeters that were in fixed locations and measured the rhodamine concentrations over 96 hours.</p> <p>Times are Central European Time (GMT+1)</p>
Atmospheric, hydrodynamic and water quality observations from environmental-quality stations, water level sensors, acoustic Doppler velocimeters, and meteorological stations located at the Guadalquivir river estuary (2008 - 2010)
<p>The dataset included in this repository was obtained during the project entitled “Propuesta metodológica para diagnósticar las consecuencias de las actuaciones humanas en el estuario del Guadalquivir” funded by the Autoridad Portuaria de Sevilla (APS), by the Consejería de Innovación, Ciencia y Empresa (Junta de Andalucía), CTM2011-22580, MedEX (CTM2008-04036-E) and PR11-RNM-7722. The data were collected in real time from 2008 until 2010 with a remote monitoring system installed by the Institute of Marine Sciences of Andalusia (ICMAN-CSIC) (Navarro et al., 2011).</p> <p> </p> <p>The environmental quality station recorded turbidity, temperature, conductivity, normalized turbidity, dissolved oxygen, oxygen, oxygen saturation, percentage of oxygen saturation, fluorescence, normalized fluorescence, and salinity every thirty minutes. Current data were measured every 15 minutes by means of acoustic current profilers. The former datasets were obtained at several depths and different locations along the Guadalquivir estuary. Water level sensors recorded the position of the free water surface every 10 minutes at several locations along the Guadalquivir estuary. Wind velocity and direction and solar radiation were measured every 10 minutes in a meteorological station at the mouth of the Guadalquivir estuary.</p> <p>Brief description of dataset.</p> <ul> <li> <p>velocities.csv (in m/s)</p> </li> <li> <p>Turbidity.csv (in Volts), temperature (in Celsius), conductivity (in Siemens/m), normalized turbidity (in FNU), dissolved oxygen (mg/L), oxygen (in Volts), fluorescence (in Volts), normalized fluorescence (in Volts), oxygen saturation (mg/L), percentage of oxygen saturation (%), salinity (in PSU).</p> </li> <li> <p>qual_Salmedina.csv, R_mean (mean radiative flux in W/m²), R_max (max radiative flux in W/m²), Rel_humidity (relative humidity in %), D_mean (wind mean direction in degrees), D_max (wind maximum direction in degrees), D_sig (standard deviation of the wind direction in degrees), V_mean (mean wind velocity in m/s), V_max (maximum wind velocity in m/s), V_sig (standard deviation of the wind velocity in m/s), P_atm_mean (mean atmospheric pressure in mbar), T_mean (mean air temperature in Celsius), T_max (maximum air temperature in Celsius), T_sig (standard deviation of the air temperature in Celsius).</p> </li> <li> <p>Sealevel.csv (in meters)</p> </li> </ul> <p>A wide description of the datasets can be found in Navarro et al (2011).</p> <p>Contact person: infogdfa@ugr.es (or mcobosb@ugr.es)</p>
Water temperature measurements collected during austral summer 2017/2018 on lakes located in the Schirmacher oasis, East Antarctica.
<p>Lakes’ water temperature are measured on lakes of three types (epiglacial, epishelf and land-locked) located in the Schirmacher oasis, East Antarctica. The temporal hydrological network is equipped by 11 temperature sensors, which are measured both surface and bottom water temperature of lakes. The surface temperature is recorded with the temperature loggers iButton DS1922L/DS1922T (https://www.maximintegrated.com/en/datasheet/index.mvp/id/4088) on 8 lakes. The sensors are deployed within a distance of 1–3 m from a lake’s coast, on a depth of 0.02 m. The lake’s surface temperature is also measured on two lakes with the temperature sensors by HOBO Water Level U20L (https://www.onsetcomp.com/products/data-loggers/u20l-01), which are deployed on the depth of 0.2 m. One HOBO sensor is installed to be attached to a lake’s ground on a depth approximately 0.5 m. The measurements cover the period of over 12–36 days depending on a lake. The data set includes the field campaign’s report of 63 RAE in the Schirmacher oasis (a text, in Russian) as a pdf-file, the metadata for the measurements (name, elevation, lon/lat of the temperature sensors deployed; name of the lakes; period with measurements; comments) as a shp-file, and the tables with water temperature measured for each lakes (as files of CSV format). Also, the deployment of the temperature sensor on the Lake Pomornik is presented in the jpg-file.</p> <p> </p>
3D wind speed and CO2/H20 concentration measurements collected during austral summer 2017/2018 over an ice free surface of a shallow lake located in the Schirmacher oasis, East Antarctica.
<p>The data set includes measurements collected by the integrated CO2 and H2O open-path gas analyzer and 3-D sonic anemometer (Irgason by Campbell Scientific with serial number 1243, https://www.campbellsci.com/irgason). The instrument was operated from 01.01.2018 to 07.02.2018. It was deployed on the north-west shore of the Lake Zub/Priyadarshini (S70° 45′ 41.5″, E011° 44′ 16.6″) on the distance of 10 m from the coast. The instrument was placed on the aluminum tripod on the height of 2 m, and directed to south-eastwards (137 SE). Six metal guidelines were linked to anchors, and the boom was fixed on the tripod. Two rechargeable batteries (12V/33Ah) were used in additional to two solar panels to power supply of the instrument (irgason_deployment.jpg). The format of the output files is given in Irgason_output.pdf. The raw data are packed into the *.dat files (one per day) and then compressed (bz2). The calibration of the Irgason was done 21.08.2017 in the lab of the Finnish Meteorological Institute with standard zero-and-span procedure, and then the instrument is adjusted accordingly.</p>
Pressure distribution and schlieren for various locations of transonic compressor profiles
<p>One of the primary objectives of the EU TFAST and TEAMAero projects is to study the shock wave and boundary layer interaction on the suction side of the transonic compressor blade. In this context, the test section is designed and assembled at the IMP PAN laboratory to replicate the flow structure in a transonic compressor cascade.</p> <p>The system's sensitivity to variable parameters in the test section is crucial for achieving the design conditions and ensuring that the flow is influenced solely by the target parameter under study.</p> <p><strong>The provided data</strong> pertains to a study on the system's sensitivity to small changes in the position of the profiles relative to the nozzle (~±2% x/c). The results indicated that the profile position does not significantly alter the overall flow structure or the inflow Mach number. However, it affects the Mach number distribution over the lower profile, particularly upstream of the passage shock within the range of 0.3-0.4x/c.</p> <p><span>Data can be used for CFD validation and sensitivity study. </span>The pressure files and schlieren images are grouped by date.</p> <p> </p>
Deep Submergence Dive location dataset from Bell et al. Sci Advances: How Little We've Seen: A Visual Coverage Estimate of the Deep Seafloor
<p><span>How Little We’ve Seen: A Visual Coverage Estimate of the Deep Seafloor </span></p> <p><span>Katherine L.C. Bell,</span><sup><span>1</span></sup><em><sup><span>∗</span></sup></em><em><sup><span> </span></sup></em><span>Kristen N. Johannes,</span><sup><span>1<em>,</em>2</span></sup><span> </span></p> <p><span>Brian R.C. Kennedy,</span><sup><span>1<em>,</em>3 </span></sup><span>Susan E. Poulton</span><sup><span>1</span></sup><span> </span></p> <p><sup><span>1</span></sup><span>Ocean Discovery League, Saunderstown, RI 02874, USA, </span></p> <p><sup><span>2</span></sup><span>Integrative Oceanography Division, Scripps Institution of Oceanography, University of California San Diego, San Diego, CA 92037, USA </span></p> <p><sup><span>3</span></sup><span>Biology Department, Boston University, Boston, MA 02215 USA </span></p> <p><em><sup><span>∗</span></sup></em><span>To whom correspondence should be addressed: croff@alum.mit.edu. </span></p> <p><span><br>Despite the importance of visual observation in the ocean, we have imaged a minuscule fraction of the deep seafloor. Sixty-six percent of the entire planet is deep ocean (≥200 m), and our data show we have visually observed less than 0.001%, a total area approximately a tenth of the size of Belgium. Data gathered from over 44 thousand deep-sea dives indicate we have also seen an incredibly biased sample. Sixty-five percent of all in situ visual seafloor observations in our dataset were within 200 nm of only three countries: the United States, Japan, and New Zealand. Ninety-seven percent of all dives we compiled have been conducted by just five countries: the United States, Japan, New Zealand, France, and Germany. This small and biased sample is problematic when attempting to characterize, understand, and manage a global ocean.</span></p>
The Interseismic Seismicity of the East Anatolian Fault Between 2007-2012 and Aftershock Locations of the 2020 Mw6.8 Sivrice Earthquake
<p>The two files include the seismicity along the Eastern Anatolian Fault In Turkey between 2007 and 2012 and the Aftershocks of the January 24, 2020 Mw6.8 Sivrice (Elazığ) earthquake.</p>
Map. The early Gupta kingdom with the approximate location of surrounding powers that offered submission to Samudragupta as recounted in the Allahābād Pillar inscription.
<p>Map. The early Gupta kingdom with the approximate location of surrounding powers that offered submission to Samudragupta as recounted in the <a href="https://siddham.network/object/ob00001/">Allahābād Pillar inscription</a>.</p>
Location of ground stations, targets and spacecraft for Spire Global case study
<p>Datasets for case study in article:<br> "Data sink selection using consensus leadership: improving target connectivity for a spacecraft constellation"</p>
ScienceDex guides
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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.