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Calibrated Earthquake Relocations from the TexNet Catalog (2017–2022) and Vertical Surface Deformation (2016–2022)
<p>This repository contains the relocated earthquake catalog for the Southern Delaware Basin, as presented in the manuscript titled "<em><strong>Insights into Spatiotemporal Evolution of Induced Earthquakes in the Southern Delaware Basin Using Calibrated Relocations from the TexNet Catalog (2017-2022)</strong>".</em></p> <h3>Citations:</h3> <p>Asiye Aziz Zanjani, Heather R. DeShon, Vamshi Karanam, Alexandros Savvaidis; <strong>Insights into Temporal Evolution of Induced Earthquakes in the Southern Delaware Basin Using Calibrated Relocations <em>from the TexNet Catalog (2017-2022</em>) (2025)</strong>. <em>Earth and Space Science, 12 (6), e2024EA004027. <a title="https://doi.org/10.1029/2024EA004027" href="https://doi.org/10.1029/2024EA004027"><strong>https://doi.org/10.1029/2024EA004027</strong></a></em></p> <p>The earthquake relocations were conducted using the Hypocentroidal Decomposition technique with the <strong>open-source MLOC code</strong>, achieving enhanced spatial resolution for over 5,000 events from the TexNet catalog. The relocated catalog includes critical hypocentral parameters—latitude, longitude, depth—as well as origin time, associated uncertainties, and magnitude for each event.</p> <p>This dataset is an essential resource for analyzing the spatiotemporal patterns of induced seismicity associated with anthropogenic activities, such as shallow fluid injection, in the Southern Delaware Basin following the operation of TexNet in 2017. It is suitable for use in seismic hazard assessments, modeling studies, and comparisons with other induced seismicity datasets. Additional data produced during this research includes vertical surface deformation measurements from 2016 through the end of 2022.</p> <p>The repository also contains data referenced in the manuscript’s “Data Availability Statement” and “Open Research” sections. </p> <p>List of files attached to this repository:</p> <ul> <li><strong>catalog.xls</strong>: Primary earthquake relocated catalog developed in this study</li> <li><strong>2016_2022_deformation.csv</strong>: Vertical displacement data (2016–2018) developed in this study</li> <li><strong>2019_2022_deformation.csv</strong>: Vertical displacement data (2016–2022) developed in this study</li> <li><strong>post-2017-injection.xlsx</strong>: Injection data from the Railroad Commission of Texas (<a href="https://www.rrc.texas.gov">source</a>)</li> <li><strong>Hydrofracking-post2017.xlsx</strong>: Hydrofracking well data from FracFocus (<a href="https://fracfocus.org">source</a>)</li> <li><strong>GrowClust-common.xls</strong>: 2-D GrowClust catalog for supplemental information (<a href="https://hirescatalog.texnet.beg.utexas.edu/">source</a>), https://doi.org/10.15781/76hj-ed46</li> <li><strong>TexNet-Catalog</strong>: Initial TexNet catalog's origin and phase data, https://doi.org/10.7914/SN/TX</li> </ul>
Global Ionosphere Maps of vertical electron content combined in real-time from the RT-GIMs of CAS, CNES, UPC-IonSAT, and WHU International GNSS Service (IGS) centers (from Dec 1, 2020, to March 1, 2021)
<p>The datasets consists on 91 daily files, in IONEX format (<a href="http://ftp.aiub.unibe.ch/ionex/draft/ionex11.pdf">http://ftp.aiub.unibe.ch/ionex/draft/ionex11.pdf</a>) , corresponding to three months of global ionospheric maps (GIM) of vertical total electron content (VTEC) computed in real-time from the assessed and combined real-time GIMs generated by four analysis centers. Indeed, the Real-Time Working Group (RTWG) of International GNSS Service (IGS) is dedicated to providing high-quality data, high-accuracy products for Global Navigation Satellite System (GNSS) navigation, positioning, timing, and Earth observations. As one of the important part of real-time products, the IGS combined Real-Time Global Ionosphere Map (RT-GIM) have been generated by real-time weighting technique with the help of RT-GIMs from IGS real-time ionosphere centers including the Chinese Academy of Sciences (CAS), Centre National d’Etudes Spatiales (CNES), Universitat Politècnica de Catalunya (UPC), and Wuhan University (WHU). Compared with IGS rapid Global Ionosphere Maps (GIMs) (corg, ehrg, emrg, esrg, igrg, jprg, uhrg, uprg, uqrg, whrg) and IGS final combined GIM (igsg), the IGS combined RT-GIM (irtg) is equivalent to the post-processed GIMs and even better than some rapid GIMs. The IGS RT-GIMs are reliable sources of real-time global VTEC information and has great potential for real-time applications including range error correction for transionospheric radio signals (such as GNSS positioning, search and rescue, air traffic, radar altimetry, and radioastronomy), the monitoring of space weather (such as geomagnetic and ionospheric storms, ionospheric disturbance) and detection of natural hazards on a global scale (such as hurricanes/typhoons, ionospheric anomalies associated with earthquakes)</p>
Accessible Oceans: Auditory Display. Zooplankton Daily Vertical Migration Gets Eclipsed!
<p>The nine tracks make up an auditory display of the daily vertical migration of zooplankton off the coast of Oregon. The tracks in the auditory display are comprised of data sonifications and contextual audio supports (dialogue, auditory icons, and music). You may <a href="https://samply.app/p/92HixRBFY6YEyUgjzO1Y">listen online here</a>.</p> <p>The ocean data comes from the National Science Foundation (NSF) Ocean Observatories Initiative (OOI) and the display is based on the <a href="https://datalab.marine.rutgers.edu/ooi-nuggets/zooplankton-eclipse/">OOI Nugget</a> developed by Dr. Leslie Smith and Dr. Lori Garzio. Please note that there is no track 1B in this version. We removed track 1B in order to reduce redundancy in the display. </p> <p>The “Accessible Oceans” AISL Pilots and Feasibility study aims to inclusively design auditory displays that support the perception and understanding of ocean data in informal learning environments (ILEs). More can be found on the project website: <a href="https://accessibleoceans.whoi.edu/">https://accessibleoceans.whoi.edu/</a></p>
Data supplement to 'Vertical land motion reconstruction unveils non-linear effects on relative sea level changes from 1900-2150'
<p>This is a data supplement to <strong>'Vertical land motion reconstruction unveils non-linear effects on relative sea level changes from 1900-2150</strong>'. It presents a global-scale Vertical Land Motion (VLM) reconstruction that resolves height changes in the period 1995-2020. It is based on the joint probabilistic analysis of an extensive network of more than 11,000 GNSS stations, tide gauges, and satellite altimetry. The approach used to derive this reconstruction is described in the paper. The dataset variables are explained in the .pdf file.</p>
The Jefferson Project 2021 water quality data from three vertical profiler stations in Lake George, NY, USA.
The Jefferson Project at Lake George -- a partnership between Rensselaer Polytechnic Institute, IBM Research, and Lake George Association -- combines Internet of Things technology and powerful analytics with science to create a new model for environmental monitoring and prediction. The project is building a computing platform that captures and analyzes data from a network of sensors tracking water quality and movement. These sensor data are combined with other monitoring and experimental data to create a thorough understanding of the factors that drive the lake's food web, hydrology, and water quality. More information about The Jefferson Project is available at https://jeffersonproject.rpi.edu/ In 2021, The Jefferson Project deployed three vertical profiler stations on the lake, collecting data on water quality and weather. Meteorological data have been included with the Jefferson Project Weather Station dataset for 2021. These vertical profiler stations are named VP_AnthonysNose, VP_HarrisBay, and VP_TeaIsland. The water quality data are collected by a YSI EXO2 Multi-parameter sonde sensors. The sensors collect data at 1 meter or less depth increments, starting at 1 meter and proceeding to 2 meters off bottom. The data are transferred in near real-time to an off-site database for monitoring and review. The data provided here have undergone data correction by Jefferson Project researchers.
The Jefferson Project 2022 water quality data from two vertical profiler stations in Lake George, NY, USA.
The Jefferson Project at Lake George -- a partnership between Rensselaer Polytechnic Institute, IBM Research, and Lake George Association -- combines Internet of Things technology and powerful analytics with science to create a new model for environmental monitoring and prediction. The project is building a computing platform that captures and analyzes data from a network of sensors tracking water quality and movement. These sensor data are combined with other monitoring and experimental data to create a thorough understanding of the factors that drive the lake's food web, hydrology, and water quality. More information about The Jefferson Project is available at https://jeffersonproject.rpi.edu/ In 2022, The Jefferson Project deployed two vertical profiler stations on the lake, collecting data on water quality and weather. Meteorological data have been included with the Jefferson Project Weather Station dataset for 2022. These vertical profiler stations are named VP_HarrisBay and VP_TeaIsland. The water quality data are collected by a YSI EXO2 Multi-parameter sonde sensors. The sensors collect data at 1 meter or less depth increments, starting at 1 meter and proceeding to 2 meters off bottom. The data are transferred in near real-time to an off-site database for monitoring and review. The data provided here have undergone data correction by Jefferson Project researchers.
Limnological data from nearly 400 lakes across the Americas and New Zealand with a focus on vertical profiles of temperature, UV radiation, and optical properties
Two and a half decades of limnological data have been collected from nearly 400 lakes, encompassing a wide range of systems and a broad range of geography. This data set comprises one of the largest and most complete sets of measurements of underwater ultraviolet (UV) transparency available in the world. The data include a suite of 36 variables, with a focus on the optical characteristics. Lakes range from pristine natural lakes to manmade reservoirs. The systems represented in this data set are largely located in North America, from the northeastern United States to Alaska, and alpine and subalpine lakes in the Rocky Mountains of the United States and Canada. Lakes included range from iconic Lake Tahoe, and Castle Lake in northern California, to lakes in the South American Patagonian region, as well as New Zealand. Data were most often collected during the summer, and in some lakes span multiple years (with year-round data since 2006 in Lake Tahoe). The data here are contained in four files, including LakeData.csv, SiteInformation.csv, Methods.csv, and Variables.csv. The main data are in LakeData.csv. SiteInformation.csv, Methods.csv, and Variables.csv support the main data file with descriptions of the sampling sites, methods by which samples were processed, and descriptions of the variables that were measured, respectively. This data set complements the site-intensive limnological data that we published in EDI on 30+ years of data from 3 lakes in the Poconos Mountains region of Pennsylvania, USA. This complementary data set can be accessed at https://portal.edirepository.org/nis/mapbrowse?scope=edi&identifier=186
Global data set of long-term summertime vertical temperature profiles in 153 lakes
Climate change and other anthropogenic stressors have led to long-term changes in the thermal structure, including surface temperatures, deepwater temperatures, and vertical thermal gradients, in many lakes around the world. Though many studies highlight warming of surface water temperatures in lakes worldwide, less is known about long-term trends in full vertical thermal structure and deepwater temperatures, which have been changing less consistently in both direction and magnitude. Here, we present a globally-expansive data set of summertime in-situ vertical temperature profiles from 153 lakes, with one time series beginning as early as 1894. We also compiled lake geographic, morphometric, and water quality variables that can influence vertical thermal structure through a variety of potential mechanisms in these lakes. These long-term time series of vertical temperature profiles and corresponding lake characteristics serve as valuable data to help understand changes and drivers of lake thermal structure in a time of rapid global and ecological change.
Vertical tree air temperature measurements within the canopy of the HJ Andrews Experimental Forest, 2011-2019
Vertical air temperature from 11 trees in the Andrews Forest has been collecting beginning in 2011. The trees are at a variety of elevations and are of various species and ages. The 11 trees were selected form the H.J Andrews phenology study air temperature network (MS045). This study examines air temperatures at multiple heights in each tree. The first sensor is at 1.5 m and subsequent sensors measure every 5 m up the tree. Each sensor includes a light (illumination) sensor, which can be used to assess the value of the data. This is not a measurement of the actual light conditions.
Monthly vertical profiles of salinity, temperature, pressure, oxygen and photosynthetically-available radiation in Sapelo River, Doboy Sound, Duplin River and Altamaha River transect surveys from April 2008 to April 2015
Monthly hydrographic surveys were performed along the Sapelo River, Doboy Sound, Duplin River and Altamaha River from April 2008 to April 2015. Vertical CTD profiles were collected from the surface to bottom during low and high tide phases at fixed stations chosen to coincide with long-term GCE-LTER moorings. Conductivity, temperature, pressure, photosynthetically-available radiation (PAR) and oxygen concentration were measured at 8 Hz using a SeaBird Electronics SBE-37 instrument, and depth, salinity and sigma-t and oxygen saturation were calculated using UNESCO algorithms. Data values collected during the upcast were deleted. This data set was collected as part of the Georgia Coastal Ecosystems LTER monthly hydrographic monitoring program, and will be updated approximately annually to include the latest observations.
StreamFRE: Downstream leaf litter exports in Prieta and lateral and vertical leaf litter inputs.
StreamFRE: Downstream leaf litter exports in Prieta and lateral and vertical leaf litter inputs. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.
Conductivity, temperature, and depth (CTD) vertical profiles from Lake Joyce, McMurdo Dry Valleys, Antarctica, November 2014
Vertical profiles of conductivity, temperature, and depth (CTD) were collected from Lake Joyce, a perennially ice-covered lake in the McMurdo Dry Valleys of Antarctica. Water column observations were made in November 2014 using a YSI 6600 multiparameter probe in the deepest region of the lake, as identified by Mackey et al. (2018). The water column was accessed by drilling a 10-inch wide hole through the perennial ice cover using a Jiffy drill. This data package includes CTD profiles, as well as measurements of salinity, total dissolved solids (TDS), dissolved oxygen (DO), pH, and pressure.
Limno run codes, dates, and locations associated with vertical lake profile data collected in the McMurdo Dry Valleys, Antarctica (1991-2025, ongoing)
This data package provides a summary of "limno runs" performed each season in lakes located throughout the McMurdo Dry Valleys of Antarctica as part of the McMurdo Dry Valleys Long Term Ecological Research program. Each limno run is identified by unique code that allows one to compile a complete set of limnological data from a particular lake and location at specific time points. There are usually two or three limno runs performed per lake per austral summer field season, although the number of runs may vary by lake and by season depending on site access, site conditions, and other external factors.
Underwater photosynthetically active radiation (PAR) vertical profiles collected from lakes in the McMurdo Dry Valleys, Antarctica (1993-2025, ongoing)
As part of the Long Term Ecological Research (LTER) project in the McMurdo Dry Valleys of Antarctica, lakes are monitored for photosynthetic active radiation (PAR) levels. This data set exemplifies the vertical profile of underwater PAR profiles in perennial ice covered lakes and ambient PAR measured at the air-ice interface. Profile data can be used to calculate extinction coefficients for the water column and ice layer.
Conductivity, temperature, and depth (CTD) vertical profiles collected from lakes in the McMurdo Dry Valleys, Antarctica (1993-2025, ongoing)
As part of the Long Term Ecological Research (LTER) project in the McMurdo Dry Valleys of Antarctica, a series of Taylor Valley lakes have been monitored for conductivity, temperature, and depth (CTD). A Seabird instrument was used to record CTD profiles in these perennial ice covered lakes.
LakeBeD-US: Ecology Edition - a benchmark dataset of lake water quality time series and vertical profiles
LakeBeD-US: Ecology Edition is a harmonized lake water quality dataset containing time series and vertical profiles of 21 lakes in the United States monitored by long-term monitoring institutions. These institutions include the North Temperate Lakes Long-Term Ecological Research program (NTL-LTER), Niwot Ridge Long-Term Ecological Research program (NWT-LTER), National Ecological Observatory Network (NEON), and the Carey Lab at Virginia Tech as part of the Virginia Reservoirs Long-Term Research in Environmental Biology (LTREB) site in collaboration with the Western Virginia Water Authority. The data include depth-discrete observations of 17 water quality variables including temperature, dissolved oxygen, chemical properties, Secchi depth, and more. Observations are divided into data collected by automated sensors at a relatively high temporal frequency and manually sampled data at a relatively low temporal frequency. All data were collected in situ. The data are available as Apache Parquet files, and the included R scripts give guidance on how to utilize and query the dataset in R. LakeBeD-US: Ecology Edition is an ecological science-oriented companion to LakeBeD-US: Computer Science Edition. The Computer Science Edition is available on the Hugging Face Hub.
Hydraulic scale model experiments on the two-dimensional run-up of impulse wave trains on steep to vertical slopes
<p>This dataset includes the experimental data and videos, which were generated during the study on the run-up of impulse wave trains at the Laboratory of Hydraulics, Hydrology and Glaciology (VAW), ETH Zurich.</p>
VDMBC_vertical_distribution_soil_microbial_biomass_carbon
<p>Soil microbial biomass carbon (SMBC) is important in regulating soil organic carbon (SOC) dynamics along soil profiles by mediating the decomposition and formation of SOC. The dataset (VDMBC) is about the vertical distributions of SOC, SMBC, and soil microbial quotient (SMQ = SMBC/SOC) and their relations to environmental factors across five continents. Data were collected from literature, with a total of 289 soil profiles and 1040 observations in different soil layers compiled. The associated environment data collectd include climate, ecosystem types, and edaphic factors. We developed this dataset by searching the the Web of Sciene and the China National Knowledge Infrastructure from the year of 1970 to 2019. All the data in this dataset met two creteria: 1) there were at least three mineral soil layers along a soil profile, and 2) SMBC was measured using the fumigation extraction method. The data in tables and texts were obtained from literature directly, and the data in figures were extracted by using the GetData Graph digitizer software version 2.25. When climate and soil properties were not available from publications, we obtainted the data from the World Weather Information Service (https://worldweather.wmo.int/en/home.html) and SoilGrids at a spatial resolution of 250 meters (version 0.5.3, https://soilgrids.org).</p> <p>The units of all the variables were converted to the standard international units or commonly used ones and the values were converted correspondingly. For example, the value of soil organic matter (SOM) was converted to SOC using the equation (SOC = SOM × 0.58). Soil depth was calculated as the arithmetic mean value of the upper and lower boundaries for a given soil layer.</p> <p>This dataset can be used in predicting global SOC change along soil profiles using the multi-layer soil carbon models. It can also be used to analyse how soil microbial biomass changes with plant roots as well as the composition, structure, and functions of soil microbial communities along soil profiles at large spatial scales. This dataset offers opportunities to improve our prediction of SOC dynamics under global changes and to advance our understanding of the environmental controls.</p>
Vertex-transitive Graphs On Fewer Than 48 Vertices
<p><strong><em>Vertex-transitive Graphs On Fewer Than 48 Vertices</em></strong></p> <p>This dataset contains all the vertex-transitive graphs on 10-47 vertices.</p> <p>It consists of a collection of tar files, with names like</p> <p>alltrans26.tar</p> <p>meaning that this tar file contains all the vertex-transitive graphs on 26 vertices.</p> <p>Once the tar file is unpacked (using "tar xf alltrans26.tar") this will create a number of smaller gzipped files with names such as</p> <p>alltrans26_k=03.gz</p> <p>meaning that this file contains all the transitive graphs on 26 vertices with degree (valency) 3. </p> <p>Once the gzip file is unpacked using "gunzip alltrans26_k=03.gz" the resulting file contains all the graphs, one per line, in graph6 format (this format was invented by Brendan McKay and is recognised by SageMath). </p> <p>The first five lines of the file alltrans26_k=03 are as follows:</p> <pre>Ys???C????_CA?@?`?_GO?c?@_?Q??K??O@CG?aA?GAG@?OCCG?GGC?? Ys??WO@?O??O?J?E?A_H??A?C??O?????_?DC?AQ?AAA??oG?C_O?I?? Ys??WWG@?@?A?W?c??g?S?@??G???G??O??S??I?_?Ac??SS??OW??_? Ys?GGSG@?@?A?W?c??g?S?@??G???G??O??S??I?_?Ac??SS??OW??_? Ys?GOO?????c?Q?c?B?@_?I?A??G??A?@?CCC?OP?CCC?C_O?AOC?C_? </pre> <p>These can be directly used as input to SageMath with commands such as</p> <p>g = Graph("Ys???C????_CA?@?`?_GO?c?@_?Q??K??O@CG?aA?GAG@?OCCG?GGC??")</p> <p>No attempt has been made to reduce data storage by removing redundancy. So the tar file for vertex-transitive graphs on n vertices contains files for each feasible valency from 0 to n-1, despite the redundancy inherent in storing both a graph and its complement, and in storing both disconnected and connected graphs.</p> <p> </p>
OMPS-NPP L2 LP USask Aerosol Extinction Vertical Profile swath daily V1.1
<p>The USask OMPS-LP L2 2D Aerosol v1.1 product provides stratospheric aerosol extinction retrievals performed at the University of Saskatchewan for the central slit of the Ozone Mapping and Profiler Suite Limb Profiler (OMPS-LP) instrument on the Suomi-NPP satellite. The two-dimensional retrieval algorithm accounts for variation in the along orbital track dimension, retrieving an entire orbit simultaneously instead of treating each image independently. Stratospheric aerosol is retrieved from approximately the thermal tropopause to 30 km on a 1 km grid with a vertical resolution of approximately 2 km, and is assumed to be sulfate aerosol following a log-normal particle size distribution.</p> <p>Each granule contains data from the daylight portion of each orbit measured for a full month. Spatial coverage is global (-82 to +82 degrees latitude), and there are about 14.5 orbits per day, each has typically 160 profiles with an along orbital track sampling of 125 km. The files are written using NetCDF4.</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.