Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
6,568
datasets available to search
ShareScore release 0.7.1
Dataset results
6,568 results for “Pressure”
Groundwater well pressure, temperature, conductance, salinity and oxygen measurements for GCE-LTER study hammock HN_i_1 from 30-Oct-2008 to 03-Dec-2013
Groundwater pressure, temperature and other parameters (e.g. conductance, salinity, oxygen and pH) were measured using various instruments installed in PVC wells at the GCE-LTER HN_i_1 holocene study hammock from 30-Oct-2008 to 03-Dec-2013. Observations were logged continuously at 15 minute intervals, and accumulated data were downloaded from loggers using manufacturer-provided communications software semi-monthly, then imported into MATLAB for post-processing, quality control and documention. Raw, unvented pressure readings were corrected for atmospheric pressure and sensor height from the bottom of the well to generate corrected pressure readings. Separate data tables are provided for each combination of instrument and well due to differences in parameters measured and post-processing steps, but all tables include detailed information on location and well characteristics to support integration and analysis. These data were collected as part of the Georgia Coastal Ecosystems LTER Intensive Hammock Characterization and Hammock Groundwater Modeling projects, and will be used for groundwater modeling studies at two marsh hammocks on Sapelo Island, Georgia.
Groundwater well pressure, temperature, conductance, salinity and oxygen measurements for GCE-LTER study hammock PC_i_29 from 15-Aug-2008 to 13-Dec-2013
Groundwater pressure, temperature and other parameters (e.g. conductance, salinity, oxygen and pH) were measured using various instruments installed in PVC wells at the GCE-LTER PC_i_29 pleistocene study hammock from 15-Aug-2008 to 13-Dec-2013. Observations were logged continuously at 15 minute intervals, and accumulated data were downloaded from loggers using manufacturer-provided communications software semi-monthly, then imported into MATLAB for post-processing, quality control and documention. Raw, unvented pressure readings were corrected for atmospheric pressure and sensor height from the bottom of the well to generate corrected pressure readings. Separate data tables are provided for each combination of instrument and well due to differences in parameters measured and post-processing steps, but all tables include detailed information on location and well characteristics to support integration and analysis. These data were collected as part of the Georgia Coastal Ecosystems LTER Intensive Hammock Characterization and Hammock Groundwater Modeling projects, and will be used for groundwater modeling studies at two marsh hammocks on Sapelo Island, Georgia.
Hubbard Brook Experimental Forest: 15 Minute Barometric Pressure Measurements, 2018 – present
Barometric pressure has been measured at 15-minute intervals at the Headquarters Station at the Hubbard Brook Experimental Forest since 2018. These data are gathered at the Hubbard Brook Experimental Forest in Woodstock, NH, which is operated and maintained by the USDA Forest Service, Northern Research Station.
PIE LTER measurements of water column depth at 15 minute intervals in the Parker River near Rt 1A bridge, Newbury, MA, year 2000. Water depths are relative to the sonde pressure transducer and not associated with a datum.
PIE LTER, year 2000,15 minute readings of water column depth in the lower Parker River Estuary at Fernalds Marina bulkhead off Rt. 1A., Newbury, MA. Water depths are relative to the sonde pressure transducer and not associated with a datum.
PIE LTER measurements of water column depth at 15 minute intervals in the Parker River near Rt 1A bridge, Newbury, MA, year 2001. Water depths are relative to the sonde pressure transducer and not associated with a datum.
PIE LTER, year 2001,15 minute readings of water column depth in the lower Parker River Estuary at Fernalds Marina bulkhead off Rt. 1A., Newbury, MA. Water depths are relative to the sonde pressure transducer and not associated with a datum.
PIE LTER measurements of water column depth at 15 minute intervals in the Parker River near Rt 1A bridge, Newbury, MA, year 2002. Water depths are relative to the sonde pressure transducer and not associated with a datum.
PIE LTER, year 2002, 15 minute readings of water column depth in the lower Parker River Estuary at Fernalds Marina bulkhead off Rt. 1A., Newbury, MA. Water depths are relative to the sonde pressure transducer and not associated with a datum.
PetrocShelley/Measured-solid-state-and-sub-cooled-liquid-vapour-pressures-of-nitroaromatics-using-KEMS-Data-Set: Measured-solid-state-and-sub-cooled-liquid-vapour-pressures-of-nitroaromatics-using-KEMS-Data-Set
<p>All data files for the Measured solid state and sub-cooled liquid vapour pressures of nitroaromatics using Knudsen effusion mass spectrometry by Shelley et al.</p>
Raw data for: Pressure and inertia sensing drifters for glacial hydrology flow path measurements
<p>Raw data for paper</p> <p>Title: Pressure and inertia sensing drifters for glacial hydrology flow path measurements</p> <p>Authors: A.Alexander, M.Kruusmaa, J.A. Tuhtan, A.J. Hodson, T.V. Schuler, A. Kääb</p> <p>Journal: The Cryosphere</p> <p>Year, 2020</p>
Simulated Seafloor Pressures for "The Ocean's Impact on Slow Slip Events"
<p>These files in this archive contain the simulated seafloor pressures used in the study of Gomberg et al. (2020). These seafloor pressures were derived from a Regional Ocean Modeling System (ROMS) on the seafloor of the Hikurangi subduction zone off New Zealand [<em>Hadfield et al.</em>, 2007] at offshore sites deployed during the 10-month 2014-2015 Hikurangi Ocean Bottom Investigation of Tremor and Slow Slip (HOBITSS) experiment [<em>Wallace et al.</em>, 2016]. Details of each file are described in the Readme.pdf file.These files in this archive contain the simulated seafloor pressures used in the study of Gomberg et al. (2020). These seafloor pressures were derived from a Regional Ocean Modeling System (ROMS) on the seafloor of the Hikurangi subduction zone off New Zealand [<em>Hadfield et al.</em>, 2007] at offshore sites deployed during the 10-month 2014-2015 Hikurangi Ocean Bottom Investigation of Tremor and Slow Slip (HOBITSS) experiment [<em>Wallace et al.</em>, 2016]. Details of each file are described in the Readme.pdf file.</p>
Impact on pressure in above zone monitoring interval from unintentional CO2 release from a CCS reservoir
<p>The data set was created by running dynamic numerical simulations with the CMG-software on a static geologic model. It consists of simulations of 16 different CO2 release scenarios from a subsurface storage formation and describes the change in pressure in the above zone monitoring interval over time. The data are daily means of the pressure over a period of 1001 days and are defined on a 160x160 grid. It contains data from 4 release locations where for each location it is simulated 4 different release rates.</p>
Mangrove diversity loss under sea-level rise triggered by bio-morphodynamic feedbacks and anthropogenic pressures
<p>To whom concerned,</p> <p>This dataset is the supplementary dataset for the publication in <em>Environmental Research Letters</em> entitled '<a href="https://dx.doi.org/10.1088/1748-9326/abc122"><em>Mangrove diversity loss under sea-level rise triggered by bio-morphodynamic feedbacks and anthropogenic pressures</em></a>' authored by Danghan Xie, et al. in 2020. The publication can be freely downloaded here: <a href="https://iopscience.iop.org/article/10.1088/1748-9326/abc122">https://iopscience.iop.org/article/10.1088/1748-9326/abc122</a>. The dataset consists of both model results and corresponding codes that one can easily reproduce figures either in the manuscript or the supplementary document. </p> <p>To use the code, one needs to pre-install the Matlab (R2017a) and changes the pre-set route (in the code) to the directory where the dataset is stored. The figure shapes may vary with the size of the user's monitor so output figures may be either squeezed or extended in unpredictable ways, but the window size of the figure can be adjusted to match the shape and the results will not be affected.</p> <p>The author is appreciated that any potential concerns or questions regarding our research from any party or person, so please contact me through the email: <a href="mailto:d.xie@uu.nl">d.xie@uu.nl</a> or <a href="mailto:xiedanghan@gmail.com">xiedanghan@gmail.com</a>. To know more about my research, you can also follow the <a href="https://www.researchgate.net/profile/Danghan_Xie">ResearchGate</a>.</p> <p>With Kind Regards,</p> <p>Danghan</p> <p>11th of November, 2020</p>
Daily ocean bottom pressure anomalies 2007-2009 from global numerical models
<p>Data supplement to: Schindelegger, M., Harker, A. A., Ponte, R. M., Dobslaw, H., & Salstein, D. A. (2021). Convergence of daily GRACE solutions and models of submonthly ocean bottom pressure variability. <em>Journal of Geophysical Research: Oceans</em>, 126, e2020JC017031. <a href="https://doi.org/10.1029/2020JC017031">https://doi.org/10.1029/2020JC017031</a></p> <p><strong>Contents:</strong></p> <p>Daily ocean bottom pressure anomalies over 2007-2009 obtained from two global forward simulations:</p> <ol> <li><strong>DEBOT</strong> (<em>David Einspigel Barotropic Ocean Tide Model</em>): 1/3° horizontal grid spacing, single-layer model</li> <li><strong>MITgcm LLC270</strong> (<em>Massachusetts Institute of Technology general circulation model, Lat-Lon-Cap 270</em>): nominal 1/3° horizontal grid spacing, 50 vertical layers</li> </ol> <p>Common specifications:</p> <ul> <li>Yearly files (<em>yyyy</em>) for each model run (<em>DEBOT_OBP_n180_yyyy.nc</em>, <em>LLC270_OBP_n180_yyyy.nc</em>)</li> <li>Temporal mean 2007-2009 reduced</li> <li>Daily fields centered at 12 UTC</li> <li>Units: cm of equivalent water height</li> <li>Data given on regular 1° grid</li> <li>Synthesized from spherical harmonic expansion truncated at degree 180 (<em>n180</em>)</li> <li>Degree 1 terms: included</li> <li>Static atmospheric contribution to bottom pressure: included</li> <li>Atmospheric forcing: ERA-Interim (6-hourly)</li> </ul> <p> </p> <p>Contact: M. Schindelegger (schindelegger@igg.uni-bonn.de)</p>
Resilient farm demographics withstand, adapt, or transform in the face of competitive pressure, technological change, and the expected lifestyles of future generations
<p>Farm demographics has been recognized as an important driver of structural change in European agriculture. Focus groups and computer simulations on farm demographic change were used to better understand its role for the case study regions of the Altmark in the eastern part of Germany and Flanders in the northern part of Belgium. According to these analyses, many potential agricultural entrants are deterred by what they view as a poor quality of life that farming offers. This applies to farm successors as well as hired workers. For higher attractiveness of agriculture, policy objectives should address the social image of farming as well as revitalize rural areas. Increasingly critical is the demand for skilled hired labour. However, policies dealing with farm demographic change ignore these needs and focus almost exclusively on farm succession. Particularly, the direct payment system, including additional support for small farms and young farmers, must be re-evaluated for its effectiveness. The analyses provide evidence that this system constrains European agricultural development more than assists it; ultimately preventing farms from adapting and transforming.</p>
Supplementary Dataset for "Extracting near-field seismograms from ocean-bottom pressure gauge inside the focal area: application to the 2011 Mw 9.1 Tohoku-Oki earthquake"
<p>Datasets S1 contains the results obtained by the analysis in this study, such as the spatial and temporal configuration of the basis functions. Dataset S2 contains the ocean-bottom pressure gauge data used in this study.</p> <p>The manuscript is available at: https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2020GL091664</p> <p> </p> <p> </p> <div> </div>
Experimental measurements of creep deformation of Tournemire shale loaded at specified pressure (10 MPa) and room temperature (26°C)
<p>Following the experimental protocol used in (Geng<em> et al.</em>, 2018), we performed the stepping creep experiments at a confining pressure of 10 MPa. We first loaded the samples under hydrostatic conditions up to 10 MPa at a pressure rate of 0.3 MPa/min. Hydrostatic conditions were maintained for ~18 h at 26 °C. Next, differential stress (axial stress minus confining pressure) was increased to a fixed initial stress (30 MPa) and maintained (creep status) for 24 h. The differential stress was repeatedly increased by 5 MPa and maintained for 24 h, until brittle failure. All the experiments were conducted using the triaxial apparatus installed at the Laboratoire de Géologie of ENS-Paris (France). There were few constraints on the natural saturation state of the samples because of their low permeability (10<sup>-19</sup> 10<sup>-21</sup> m<sup>2</sup>). To avoid exposition redundancy, an additional description of the technical performance of the triaxial apparatus can be referred to (Brantut<em> et al.</em>, 2011, Sarout & Guéguen, 2008).</p> <p>Compressive stresses and compactive strains are denoted as positive. Axial creep deformation was measured using three capacitive gap sensors that externally monitored the overall axial displacement of the piston during creep deformation. Volumetric strain during creep was estimated by adding the average of axial strains (axial displacement of the piston divided by the sample length) and two average radial strains measured by four radial strain gauges glued uniformly around the cylindrical rock surface. As the deformation rate generally stabilized during the last 8 h in most creep periods (Geng<em> et al.</em>, 2018), we estimated the average axial strain rate over the last 8 h of each step to characterize the creep strain rate under the corresponding axial loading stress. More technical details of the sample configuration and creep rates estimation can be found in (Geng<em> et al.</em>, 2018).</p>
Computed Light Fields Within a Sea Ice Pressure Ridge
<p>Calculated light fields in and around a sea-ice pressure ridge. The dataset contains total scalar irradiance and downwelling planar irradiance calculated in horizontal slices at the given distance form the ice surface. Calculations were performed using Monte-Carlo ray-tracing using Zemax Optic-Studio. In addition horizontal slices through the ridge geometry, as well as total and partial ice thickness in each point of the ridge are given. The fields are provided in python and matlab readable formats.</p> <p>For details please refer to the respective publication "The three-dimensional light field within sea ice ridges" by C. Katlein et al.</p>
Mammals under pressure: presence data for assessing extinction of endemic, threatened, and mammals subject to use, in Colombia
<p>This is the first dataset that provides a complete compilation of mammal records based on camera traps, human observations, and specimens deposited in biological collections in Colombia. We compiled a dataset with unpublished information, including 97,943 records corresponding to 136 species, of which 38 are endemic, 92 are identified as species subject to use by humans in the literature, and 33 are categorized either as Data Deficient or threatened according to international or unofficial national assessments. The information comes from 31 out of 32 departments of Colombia and constitutes relevant input for future distribution and conservation assessments. Most records (n=96,417, 98.44%) come from non-invasive sampling methods such as camera traps. However, we highlight the contribution of museum specimens (n= 1,332), especially for small and medium-sized species, many of them with restricted distributions in the country. This dataset constitutes a joint collaborative and interinstitutional effort that serves as the basis for cooperative work to comprehensively assess the current conservation status of all mammal species in Colombia.</p>
MAPO-18 Catalysts for the Methanol to Olefins Process: Influence of Catalyst Acidity in a High-Pressure Syngas (CO + H2) Environment
<p>Supplementary Material: Catalyst characterization (XRD, SEM–EDS, N2 physisorption, IR spectroscopy, and propylamine-TPD), catalyst performance, and DFT calculations</p>
Dataset of publication "Speed of Sound Measurements in Helium at Pressures from 15 to 100 MPa and Temperatures from 273 to 373 K"
<p>This is a dataset of the speed of sound in helium, which was measured along five isotherms in a temperature range from 273 to 373 K at pressures from 15 to 100 MPa with a relative expanded uncertainty (k = 2) from 0.02 to 0.04%. A dual-path pulse-echo device was utilized to conduct these measurements.</p>
University of New Hampshire Pressure Mapped Munition (PMM) Experiments 2019 - 2021
<p>This project contains the data collected by the University of New Hampshire (UNH) Coastal Processes Lab for three field experiments focusing on investigating munition mobility in nearshore/surfzone regions. The first experiment took place on May 17 2019, the second experiment took place on February 1-2 2021, and the last experiment to place on October 26-27 2021. The data was collected at Wallis Sands Beach in Rye, New Hampshire. </p> <p>The main instrument utilized was the Pressure Mapped Munition (PMM), which is a fully autonomous cylindrical surrogate munition that can resolve the pressure field on its surface. The PMM is constructed from a 229 mm long section of 304 stainless steel pipe with a 140 mm outside diameter and 12.7 mm wall thickness. To make autonomous measurements of surface pressure and relative position, the PMM houses 16 high resolution TE Connectivity MS5837-02BA absolute pressure sensors and a Lord MicroStrain 3DM®-GX5-25 inertial measurement unit (IMU). There are two rings of pressure sensors around the cylinder. Pressure sensors 1-8 are in ring 1 and pressure sensors 9-16 are in ring 2. Each ring is 6.35 cm from the ends of the cylinder and the rings are 15.24 cm apart. The radial spacing between sensors around each ring is 45°, which minimizes the arc length and height difference between sensors while maintaining axial pairs of sensors. This orientation allows for sensor redundancy in the case of sensor failure and allows for error correction if faulty values from one of the sensors is suspected. When the PMM is lying flat the vertical displacement between the topmost and bottommost sensor is 129 - 140 mm depending on the orientation of the instrument. </p> <p>For the May experiment, a Nortek Vector was deployed along with the PMM. The Nortek Vector is an Acoustic Doppler Velocimeter (ADV) which collects high-resolution, single-point, 3-dimensional velocity data (Nortek, 2022b). For this experiment the ADV transducer was about 30 cm above the sediment bed while the ADV pressure sensor was about 50 cm above the sediment bed. The Nortek Vector was not deployed for the Feburary and October experiments.</p> <p>For the February and October experiments, another instrument, the Pressure Stick (PS), was deployed with the PMM. The Pressure Stick is a fully autonomous pressure-profiling instrument. The PS contains eight micro-controlled, time-synced TE Connectivity MS5837-02BA absolute pressure and temperature sensors distributed along a 70 cm distance to measure pressure throughout the water column and into the sediment bed. The Pressure Stick allows for a quantification of intermittent bed instability (momentary liquefaction) and its potential role in munition mobility. More information about the PS can be found in Marry & Foster (2024).</p> <p>Global Positioning System (GPS) surveys of the beach profile were also completed on February 2, 2021 (at the end of the experiment) and October 26, 2021 (at the beginning of the experiment), and the survey data is included in this project. Data of the offshore wave conditions as measured by the Jeffrey's Ledge waverider buoy (station 44098) from the National Data Buoy Center (NDBC) (https://www.ndbc.noaa.gov/station_page.php?station=44098) for all three experiments are given here as well.</p> <p>This effort was supported by Strategic Environmental Research and Development Program (SERDP, Project Number 17 MR-2731). These datasets are presented in the final report for Project Number 17 MR-2731.</p> <h2>Dataset files</h2> <p>A description of each data file is given below:</p> <h3>Pressure Mapped Munition (PMM) Data</h3> <p>1. PMM_20190517.txt<br> This file contains the raw data from the PMM for the experiment on May 17, 2019<br> - Date = date of sample<br> - Time = time of sample<br> - P1 = pressure from sensor 1 in mbar<br> - P2 = pressure from sensor 2 in mbar<br> - P3 = pressure from sensor 3 in mbar<br> - P4 = pressure from sensor 4 in mbar<br> - P5 = pressure from sensor 5 in mbar<br> - P6 = pressure from sensor 6 in mbar<br> - P7 = pressure from sensor 7 in mbar<br> - P8 = pressure from sensor 8 in mbar<br> - P9 = pressure from sensor 9 in mbar<br> - P10 = pressure from sensor 10 in mbar<br> - P11 = pressure from sensor 11 in mbar<br> - P12 = pressure from sensor 12 in mbar<br> - P13 = pressure from sensor 13 in mbar<br> - P14 = pressure from sensor 14 in mbar<br> - P15 = pressure from sensor 15 in mbar<br> - P16 = pressure from sensor 16 in mbar<br> - T = temperature in degrees Celsius</p> <p>2. IMU_20190517.txt<br> This file contains the raw IMU data from the PMM for the experiment on May 17, 2019<br> - Date = date of sample<br> - Time = time of sample<br> - yaw = orientation of the IMU in the yaw direction, measured in degrees<br> - pitch = orientation of the IMU in the pitch direction, measured in degrees. Due to the orientation of the IMU in the PMM, the pitch time series refers to when there are changes in rotation along the long axis of the PMM (i.e. when it rolls). <br> - roll = orientation of the IMU in the roll direction, measured in degrees. Due to the orientation of the IMU in the PMM, the roll time series refers to when there are changes in rotation along the short axis of the PMM (i.e. when it tilts and one end of the cylinder is higher than the other end). </p> <p>3. PMM_20210202.txt<br> This file contains the raw data from the PMM for the experiment on February 1-2, 2021<br> - Date = date of sample<br> - Time = time of sample<br> - P1 = pressure from sensor 1 in mbar<br> - P2 = pressure from sensor 2 in mbar<br> - P3 = pressure from sensor 3 in mbar<br> - P4 = pressure from sensor 4 in mbar<br> - P5 = pressure from sensor 5 in mbar<br> - P6 = pressure from sensor 6 in mbar<br> - P7 = pressure from sensor 7 in mbar<br> - P8 = pressure from sensor 8 in mbar<br> - P9 = pressure from sensor 9 in mbar<br> - P10 = pressure from sensor 10 in mbar<br> - P11 = pressure from sensor 11 in mbar<br> - P12 = pressure from sensor 12 in mbar<br> - P13 = pressure from sensor 13 in mbar<br> - P14 = pressure from sensor 14 in mbar<br> - P15 = pressure from sensor 15 in mbar<br> - P16 = pressure from sensor 16 in mbar<br> - T = temperature in degrees Celsius</p> <p>4. IMU_20210202.txt<br> This file contains the raw IMU data from the PMM for the experiment on February 1-2, 2021<br> - Date = date of sample<br> - Time = time of sample<br> - yaw = orientation of the IMU in the yaw direction, measured in degrees<br> - pitch = orientation of the IMU in the pitch direction, measured in degrees. Due to the orientation of the IMU in the PMM, the pitch time series refers to when there are changes in rotation along the long axis of the PMM (i.e. when it rolls). <br> - roll = orientation of the IMU in the roll direction, measured in degrees. Due to the orientation of the IMU in the PMM, the roll time series refers to when there are changes in rotation along the short axis of the PMM (i.e. when it tilts and one end of the cylinder is higher than the other end). </p> <p>5. PMM_20211026.txt<br> This file contains the raw data from the PMM for the experiment on October 26-27, 2021<br> - Date = date of sample<br> - Time = time of sample<br> - P1 = pressure from sensor 1 in mbar<br> - P2 = pressure from sensor 2 in mbar<br> - P3 = pressure from sensor 3 in mbar<br> - P4 = pressure from sensor 4 in mbar<br> - P5 = pressure from sensor 5 in mbar<br> - P6 = pressure from sensor 6 in mbar<br> - P7 = pressure from sensor 7 in mbar<br> - P8 = pressure from sensor 8 in mbar<br> - P9 = pressure from sensor 9 in mbar<br> - P10 = pressure from sensor 10 in mbar<br> - P11 = pressure from sensor 11 in mbar<br> - P12 = pressure from sensor 12 in mbar<br> - P13 = pressure from sensor 13 in mbar<br> - P14 = pressure from sensor 14 in mbar<br> - P15 = pressure from sensor 15 in mbar<br> - P16 = pressure from sensor 16 in mbar<br> - T = temperature in degrees Celsius</p> <p>6. IMU_20211026.txt<br> This file contains the raw IMU data from the PMM for the experiment on October 26-27, 2021<br> - Date = date of sample<br> - Time = time of sample<br> - yaw = orientation of the IMU in the yaw direction, measured in degrees<br> - pitch = orientation of the IMU in the pitch direction, measured in degrees. Due to the orientation of the IMU in the PMM, the pitch time series refers to when there are changes in rotation along the long axis of the PMM (i.e. when it rolls). <br> - roll = orientation of the IMU in the roll direction, measured in degrees. Due to the orientation of the IMU in the PMM, the roll time series refers to when there are changes in rotation along the short axis of the PMM (i.e. when it tilts and one end of the cylinder is higher than the other end). </p> <h3>Nortek Vector Data</h3> <p>Vector_20190517.txt<br> This file contains the Nortek Vector data from the experiment on May 17 2019.<br> - Vec_time = time of Vector samples<br> - Vpress = pressure in mbar<br> - Vpress_smooth = smoothed pressure in mbar<br> - Vu = cross-shore velocity in m/s<br> - Vv = along-shore velocity in m/s<br> - Vw = vertical velocity in m/s</p> <h3>Pressure Stick (PS) Data</h3> <p>1. PS_20210202.txt</p> <p> This file contains the raw data from the Pressure Stick for the experiment on February 1-2, 2021<br> - Date = date of sample<br> - Time = time of sample<br> - P1 = pressure from sensor 1 (topmost sensor) in mbar, sensor 1 is about 25 cm above the sediment bed<br> - P2 = pressure from sensor 2 in mbar, sensor 2 is about 15 cm above the sediment bed<br> - P3 = pressure from sensor 3 in mbar, sensor 3 is about 9 cm above the sediment bed<br> - P4 = pressure from sensor 4 in mbar, sensor 4 is about 3 cm above the sediment bed<br> - P5 = pressure from sensor 5 in mbar, sensor 5 is about 3 cm in the sediment bed<br> - P6 = pressure from sensor 6 in mbar, sensor 6 is about 13 cm in the sediment bed<br> - P7 = pressure from sensor 7 in mbar, sensor 7 is about 28 cm in the sediment bed<br> - P8 = pressure from sensor 8 (bottom-most sensor) in mbar, sensor 8 is about 43 cm in the sediment bed<br> - T1 = temperature from sensor 1 (topmost sensor) in degrees Celsius, sensor 1 is about 25 cm above the sediment bed<br> - T2 = temperature from sensor 2 in degrees Celsius, sensor 2 is about 15 cm above the sediment bed<br> - T3 = temperature from sensor 3 in degrees Celsius, sensor 3 is about 9 cm above the sediment bed<br> - T4 = temperature from sensor 4 in degrees Celsius, sensor 4 is about 3 cm above the sediment bed<br> - T5 = temperature from sensor 5 in degrees Celsius, sensor 5 is about 3 cm in the sediment bed<br> - T6 = temperature from sensor 6 in degrees Celsius, sensor 6 is about 13 cm in the sediment bed<br> - T7 = temperature from sensor 7 in degrees Celsius, sensor 7 is about 28 cm in the sediment bed<br> - T8 = temperature from sensor 8 (bottom-most sensor) in degrees Celsius, sensor 8 is about 43 cm in the sediment bed </p> <p>2. PS_20211026.txt</p> <p> This file contains the raw data from the Pressure Stick for the experiment on October 26-27, 2021<br> - Date = date of sample<br> - Time = time of sample<br> - P1 = pressure from sensor 1 (topmost sensor) in mbar, sensor 1 is about 19 cm above the sediment bed<br> - P2 = pressure from sensor 2 in mbar, sensor 2 is about 9 cm above the sediment bed<br> - P3 = pressure from sensor 3 in mbar, sensor 3 is about 3 cm above the sediment bed<br> - P4 = pressure from sensor 4 in mbar, sensor 4 is about 3 cm in the sediment bed<br> - P5 = pressure from sensor 5 in mbar, sensor 5 is about 9 cm in the sediment bed<br> - P6 = pressure from sensor 6 in mbar, sensor 6 is about 19 cm in the sediment bed<br> - P7 = pressure from sensor 7 in mbar, sensor 7 is about 34 cm in the sediment bed<br> - P8 = pressure from sensor 8 (bottom-most sensor) in mbar, sensor 8 is about 49 cm in the sediment bed<br> - T1 = temperature from sensor 1 (topmost sensor) in degrees Celsius, sensor 1 is about 19 cm above the sediment bed<br> - T2 = temperature from sensor 2 in degrees Celsius, sensor 2 is about 9 cm above the sediment bed<br> - T3 = temperature from sensor 3 in degrees Celsius, sensor 3 is about 3 cm above the sediment bed<br> - T4 = temperature from sensor 4 in degrees Celsius, sensor 4 is about 3 cm in the sediment bed<br> - T5 = temperature from sensor 5 in degrees Celsius, sensor 5 is about 9 cm in the sediment bed<br> - T6 = temperature from sensor 6 in degrees Celsius, sensor 6 is about 19 cm in the sediment bed<br> - T7 = temperature from sensor 7 in degrees Celsius, sensor 7 is about 34 cm in the sediment bed<br> - T8 = temperature from sensor 8 (bottom-most sensor) in degrees Celsius, sensor 8 is about 49 cm in the sediment bed </p> <h3>GPS Data</h3> <p>1. UNH_GPS_WS_20210202.txt (.pos)</p> <p> This file contains data from a GPS survey taken on February 2nd 2021 as the post-deployment survey for the February experiment. <br> - GPST = time stamp of the survey sample <br> - latitude = latitude in degrees<br> - longitude = longitude in degrees<br> - height = elevation height, relative to WGS84/ellipsoidal in meters<br> - Q = quality of the data point. Q = 1 is a 'good' data point, Q = 2 is an 'okay' data point, and Q > 2 are 'bad' data points. <br> - ns = Number of satellites<br> <br>2. UNH_GPS_WS_20211026.txt (.pos)</p> <p> This file contains data from a GPS survey taken on October 26th 2021 as the pre-deployment survey for the October experiment. <br> - GPST = time stamp of the survey sample <br> - latitude = latitude in degrees<br> - longitude = longitude in degrees<br> - height = elevation height, relative to WGS84/ellipsoidal in meters<br> - Q = quality of the data point. Q = 1 is a 'good' data point, Q = 2 is an 'okay' data point, and Q > 2 are 'bad' data points. <br> - ns = Number of satellites</p> <h3>Waverider Buoy (NDBC station 44098) Data</h3> <p>1. NDBC_44098_JeffreysLedgeBuoy_May2019.txt</p> <p> This file contains offshore wave data from Jeffrey's Ledge waverider buoy (station 44098) from the National Data Buoy Center (NDBC)(https://www.ndbc.noaa.gov/station_page.php?station=44098) throughout the May 2019 experiment (May 17th 2019 00:08:00 - May 18th 2019 12:38:00). Please see "Description of Measurements" at https://www.ndbc.noaa.gov/measdes.shtml for a discussion of each of the variables in this file.</p> <p>2. NDBC_44098_JeffreysLedgeBuoy_February2021.txt</p> <p> This file contains offshore wave data from Jeffrey's Ledge waverider buoy (station 44098) from the National Data Buoy Center (NDBC)(https://www.ndbc.noaa.gov/station_page.php?station=44098) throughout the February 2021 experiment (February 1st 2021 01:26:00 - Feburary 2nd 2021 09:56:00). Please see "Description of Measurements" at https://www.ndbc.noaa.gov/measdes.shtml for a discussion of each of the variables in this file.</p> <p>3. NDBC_44098_JeffreysLedgeBuoy_October2021.txt</p> <p> This file contains offshore wave data from [Jeffrey's Ledge waverider buoy (station 44098) from the National Data Buoy Center (NDBC)](https://www.ndbc.noaa.gov/station_page.php?station=44098) throughout the October 2021 experiment (October 26th 2021 00:26:00 - October 27th 2021 23:56:00). Please see "Description of Measurements" at https://www.ndbc.noaa.gov/measdes.shtml for a discussion of each of the variables in this file.</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.