100+ datasets found
  1. d

    (TEST) Join Data 4

    • catalog.data.gov
    • data.wa.gov
    • +2more
    Updated May 10, 2025
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    data.wa.gov (2025). (TEST) Join Data 4 [Dataset]. https://catalog.data.gov/dataset/test-join-data-4
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    Dataset updated
    May 10, 2025
    Dataset provided by
    data.wa.gov
    Description

    This is a test of the Publishing API metadata update.

  2. d

    Zip Code Join Data

    • datasets.ai
    • detroitdata.org
    • +3more
    15, 21, 25, 3, 57, 8
    Updated Aug 7, 2024
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    City of Ferndale, Michigan (2024). Zip Code Join Data [Dataset]. https://datasets.ai/datasets/zip-code-join-data-7ba32
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    8, 21, 3, 57, 25, 15Available download formats
    Dataset updated
    Aug 7, 2024
    Dataset authored and provided by
    City of Ferndale, Michigan
    Description

    The Kresge early childhood interactive map contains data relating to early childhood and education. It is meant to help stakeholders better understand the early childhood landscape better.

  3. NSF/NCAR GV HIAPER 1 Minute Data Merge

    • data.ucar.edu
    ascii
    Updated Dec 26, 2024
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    Gao Chen; Jennifer R. Olson; Michael Shook (2024). NSF/NCAR GV HIAPER 1 Minute Data Merge [Dataset]. http://doi.org/10.26023/R1RA-JHKZ-W913
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    asciiAvailable download formats
    Dataset updated
    Dec 26, 2024
    Dataset provided by
    University Corporation for Atmospheric Research
    Authors
    Gao Chen; Jennifer R. Olson; Michael Shook
    Time period covered
    May 18, 2012 - Jun 30, 2012
    Area covered
    Description

    This data set contains NSF/NCAR GV HIAPER 1 Minute Data Merge data collected during the Deep Convective Clouds and Chemistry Experiment (DC3) from 18 May 2012 through 30 June 2012. These are updated merges from the NASA DC3 archive that were made available 13 June 2014. In most cases, variable names have been kept identical to those submitted in the raw data files. However, in some cases, names have been changed (e.g., to eliminate duplication). Units have been standardized throughout the merge. In addition, a "grand merge" has been provided. This includes data from all the individual merged flights throughout the mission. This grand merge will follow the following naming convention: "dc3-mrg60-gV_merge_YYYYMMdd_R5_thruYYYYMMdd.ict" (with the comment "_thruYYYYMMdd" indicating the last flight date included). This data set is in ICARTT format. Please see the header portion of the data files for details on instruments, parameters, quality assurance, quality control, contact information, and data set comments.

  4. c

    (TEST) Library Join Data 3

    • s.cnmilf.com
    • catalog.data.gov
    Updated May 10, 2025
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    data.wa.gov (2025). (TEST) Join Data 3 [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/test-join-data-3
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    Dataset updated
    May 10, 2025
    Dataset provided by
    data.wa.gov
    Description

    This is a test of the Publishing API metadata update.

  5. Data from: TRACE-P Merge Data

    • catalog.data.gov
    • s.cnmilf.com
    • +4more
    Updated May 28, 2025
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    NASA/LARC/SD/ASDC (2025). TRACE-P Merge Data [Dataset]. https://catalog.data.gov/dataset/trace-p-merge-data-43290
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    Dataset updated
    May 28, 2025
    Dataset provided by
    NASAhttp://nasa.gov/
    Description

    TRACE-P_Merge_Data is the merge data files created from data collected during during the Transport and Chemical Evolution over the Pacific (TRACE-P) suborbital campaign. Data collection for this product is complete.The NASA TRACE-P mission was a part of NASA’s Global Tropospheric Experiment (GTE) – an assemblage of missions conducted from 1983-2001 with various research goals and objectives. TRACE-P was a multi-organizational campaign with NASA, the National Center for Atmospheric Research (NCAR), and several US universities. TRACE-P deployed its payloads in the Pacific between the months of March and April 2001 with the goal of studying the air chemistry emerging from Asia to the western Pacific. Along with this, TRACE-P had the objective studying the chemical evolution of the air as it moved away from Asia.  In order to accomplish its goals, the NASA DC-8 aircraft and NASA P-3B aircraft were deployed, each equipped with various instrumentation. TRACE-P also relied on ground sites, and satellites to collect data. The DC-8 aircraft was equipped with 19 instruments in total while the P-3B boasted 21 total instruments. Some instruments on the DC-8 include the Nephelometer, the GCMS, the Nitric Oxide Chemiluminescence, the Differential Absorption Lidar (DIAL), and the Dual Channel Collectors and Fluorometers, HPLC. The Nephelometer was utilized to gather data on various wavelengths including aerosol scattering (450, 550, 700nm), aerosol absorption (565nm), equivalent BC mass, and air density ratio. The GCMS was responsible for capturing a multitude of compounds in the atmosphere, some of which include CH4, CH3CHO, CH3Br, CH3Cl, CHBr3, and C2H6O. DIAL was used for a variety of measurements, some of which include aerosol wavelength dependence (1064/587nm), IR aerosol scattering ratio (1064nm), tropopause heights and ozone columns, visible aerosol scattering ratio, composite tropospheric ozone cross-sections, and visible aerosol depolarization. Finally, the Dual Channel Collectors and Fluorometers, HPLC collected data on H2O2, CH3OOH, and CH2O in the atmosphere. The P-3B aircraft was equipped with various instruments for TRACE-P, some of which include the MSA/CIMS, the Non-dispersive IR Spectrometer, the PILS-Ion Chromatograph, and the Condensation particle counter and Pulse Height Analysis (PHA). The MSA/CIMS measured OH, H2SO4, MSA, and HNO3. The Non-dispersive IR Spectrometer took measurements on CO2 in the atmosphere. The PILS-Ion Chromatograph recorded measurements of compounds and elements in the atmosphere, including sodium, calcium, potassium, magnesium, chloride, NH4, NO3, and SO4. Finally, the Condensation particle counter and PHA was used to gather data on total UCN, UCN 3-8nm, and UCN 3-4nm. Along with the aircrafts, ground stations measured air quality from China along with C2H2, C2H6, CO, and HCN. Finally, satellites imagery was used to collect a multitude of data, some of the uses were to observe the history of lightning flashes, SeaWiFS cloud imagery, 8-day exposure to TOMS aerosols, and SeaWiFS aerosol optical thickness. The imagery was used to best aid in planning for the aircraft deployment.

  6. a

    Election Results Data Join 2020 General Election

    • hub.arcgis.com
    • share-open-data-crawfordcountypa.opendata.arcgis.com
    Updated Nov 2, 2020
    + more versions
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    Crawford County Government (2020). Election Results Data Join 2020 General Election [Dataset]. https://hub.arcgis.com/maps/fde867aab8d84a998f91cf4a822511c1
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    Dataset updated
    Nov 2, 2020
    Dataset authored and provided by
    Crawford County Government
    Area covered
    Description

    Election Results | Join Data from 2020 General Election. All election results are official and have been certified by the Crawford County Pennsylvania Election Board

  7. g

    (TEST) Library Join Data 3

    • gimi9.com
    Updated Jun 2, 2025
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    (2025). (TEST) Library Join Data 3 [Dataset]. https://gimi9.com/dataset/data-gov_test-join-data-3
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    Dataset updated
    Jun 2, 2025
    License

    ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
    License information was derived automatically

    Description

    🇺🇸 미국 English This is a test of the Publishing API metadata update.

  8. NAAMES C-130 Aircraft Merge Data Files

    • data.nasa.gov
    • cmr.earthdata.nasa.gov
    • +1more
    Updated Apr 1, 2025
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    nasa.gov (2025). NAAMES C-130 Aircraft Merge Data Files [Dataset]. https://data.nasa.gov/dataset/naames-c-130-aircraft-merge-data-files-16771
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    Dataset updated
    Apr 1, 2025
    Dataset provided by
    NASAhttp://nasa.gov/
    Description

    NAAMES_Merge_Data is the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES) pre-generated aircraft merge data files created using data collected during the NAAMES campaign. NAAMES was a NASA funded Earth-Venture Suborbital (EVS) mission with 4 deployments occurring from 2015-2018. Data collection is complete.The NASA North Atlantic Aerosols and Marine Ecosystems Study (NAAMES) project was the first NASA Earth Venture – Suborbital mission focused on studying the coupled ocean ecosystem and atmosphere. NAAMES utilizes a combination of ship-based, airborne, autonomous sensor, and remote sensing measurements that directly link ocean ecosystem processes, emissions of ocean-generated aerosols and precursor gases, and subsequent atmospheric evolution and processing. Four deployments coincide with the seasonal cycle of phytoplankton in the North Atlantic Ocean: the Winter Transition (November 5 – December 2, 2015), the Bloom Climax (May 11 – June 5, 2016), the Deceleration Phase (August 30 – September 24, 2017), and the Acceleration Phase (March 20 – April 13, 2018). Ship-based measurements were conducted from the Woods Hole Oceanographic Institution Research Vessel Atlantis in the middle of the North Atlantic Ocean, while airborne measurements were conducted on a NASA Wallops Flight Facility C-130 Hercules that was based at St. John's International Airport, Newfoundland, Canada. Data products in the ASDC archive focus on the NAAMES atmospheric aerosol, cloud, and trace gas data from the ship and aircraft, as well as related satellite and model data subsets. While a few ocean-remote sensing data products (e.g., from the high-spectral resolution lidar) are also included in the ASDC archive, most ocean data products reside in a companion archive at SeaBass.

  9. c

    Parcels To Join

    • s.cnmilf.com
    • data.nola.gov
    • +1more
    Updated Jun 28, 2025
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    data.nola.gov (2025). Parcels To Join [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/parcels-to-join
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    Dataset updated
    Jun 28, 2025
    Dataset provided by
    data.nola.gov
    Description

    This dataset is updated monthly based on the Assessor data of GEOPIN and TAXBILL. It is a full polygon dataset of the parcels with both GEOPIN and TAXBILL attached. This allows users to join to tabular data based on either field.

  10. Dataset of merge conflicts collected from GitHub repositories

    • zenodo.org
    • explore.openaire.eu
    • +1more
    application/gzip
    Updated Apr 16, 2020
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    Victor Cacciari Miraldo; Victor Cacciari Miraldo (2020). Dataset of merge conflicts collected from GitHub repositories [Dataset]. http://doi.org/10.5281/zenodo.3751038
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    application/gzipAvailable download formats
    Dataset updated
    Apr 16, 2020
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Victor Cacciari Miraldo; Victor Cacciari Miraldo
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Within each nested folder of the archive you will find files A,O,B and M. They each represent a conflict where file O was altered in two different ways, resulting in A and B. Finally, a developer solved the merge conflict committing M as the solution.

    We have selected these by manually searching for a programming language on GitHub and selecting those repositories that had a large number of forks, commits and contributors.

  11. o

    form to join the golden list - Dataset - Open Government Data

    • opendata.gov.jo
    Updated May 16, 2023
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    (2023). form to join the golden list - Dataset - Open Government Data [Dataset]. https://opendata.gov.jo/dataset/form-to-join-the-golden-list-2243-2023
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    Dataset updated
    May 16, 2023
    License

    Attribution-NonCommercial 2.0 (CC BY-NC 2.0)https://creativecommons.org/licenses/by-nc/2.0/
    License information was derived automatically

    Description

    form to join the golden list

  12. h

    noisy-join-mixed-asr

    • huggingface.co
    Updated Jun 7, 2023
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    Mesolitica (2023). noisy-join-mixed-asr [Dataset]. https://huggingface.co/datasets/mesolitica/noisy-join-mixed-asr
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jun 7, 2023
    Dataset authored and provided by
    Mesolitica
    Description

    Noisy join mixed ASR

    Problem with common ASR dataset, each audio sample is a monolanguage, but we can generate an audio sample with multilanguage using ASR and Force Alignment models. Notebooks at https://github.com/huseinzol05/malaya-speech/tree/master/data/noisy-join-mixed-asr Figure like below, Generated samples ~601 hours.

  13. DLR Falcon 1 Minute Data Merge

    • data.ucar.edu
    ascii
    Updated Dec 26, 2024
    + more versions
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    Gao Chen; Jennifer R. Olson; Michael Shook (2024). DLR Falcon 1 Minute Data Merge [Dataset]. http://doi.org/10.26023/SZ09-F2G3-7X0V
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    asciiAvailable download formats
    Dataset updated
    Dec 26, 2024
    Dataset provided by
    University Corporation for Atmospheric Research
    Authors
    Gao Chen; Jennifer R. Olson; Michael Shook
    Time period covered
    May 29, 2012 - Jun 14, 2012
    Area covered
    Description

    This data set contains DLR Falcon 1 Minute Data Merge data collected during the Deep Convective Clouds and Chemistry Experiment (DC3) from 29 May 2012 through 14 June 2012. These merges were created using data in the NASA DC3 archive as of September 25, 2013. In most cases, variable names have been kept identical to those submitted in the raw data files. However, in some cases, names have been changed (e.g., to eliminate duplication). Units have been standardized throughout the merge. In addition, a "grand merge" has been provided. This includes data from all the individual merged flights throughout the mission. This grand merge will follow the following naming convention: "dc3-mrg06-falcon_merge_YYYYMMdd_R2_thruYYYYMMdd.ict" (with the comment "_thruYYYYMMdd" indicating the last flight date included). This data set is in ICARTT format. Please see the header portion of the data files for details on instruments, parameters, quality assurance, quality control, contact information, and data set comments.

  14. TRACE-A Merge Data

    • s.cnmilf.com
    • gimi9.com
    • +3more
    Updated Jun 28, 2025
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    NASA/LARC/SD/ASDC (2025). TRACE-A Merge Data [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/trace-a-merge-data-204e5
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    Dataset updated
    Jun 28, 2025
    Dataset provided by
    NASAhttp://nasa.gov/
    Description

    TRACE-A_Merge_Data is merge data files created from data collected onboard the DC-8 aircraft during the Transport and Atmospheric Chemistry near the Equator - Atlantic (TRACE-A) suborbital campaign. Data collection for this product is complete.The TRACE-A mission was a part of NASA’s Global Tropospheric Experiment (GTE) – an assemblage of missions conducted from 1983-2001 with various research goals and objectives. TRACE-A was conducted in the Atlantic from September 21 to October 24, 1992. TRACE-A had the objective of determining the cause and source of the high concentrations of ozone that accumulated over the Atlantic Ocean between southern Africa and South America from August to October. NASA partnered with the Brazilian Space Agency (INPE) to accomplish this goal.  The NASA DC-8 aircraft and ozonesondes were utilized during TRACE-A to collect the necessary data. The DC-8 was equipped with 19 instruments. A few instruments on the DC-8 include the Differential Absorption Lidar (DIAL), the Laser-Induced Fluorescence, the O3-NO Ethylene/Forward Scattering Spectrometer, the Modified Licor, and the DACOM IR Laser Spectrometer. The DIAL was responsible for a variety of measurements, which include Nadir IR aerosols, Nadir UV aerosols, Zenith IR aerosols, Zenith VS aerosols, ozone, and ozone column. The Laser-Induced Fluorescence instrument collected measurements on NxOy in the atmosphere. Measurements of ozone were recorded by the O3-NO Ethylene/Forward Scattering Spectrometer while the Modified Licor recorded CO2. Finally, the DACOM IR Laser Spectrometer gathered an assortment of data points, including CO, O3, N2O, CH4, and CO2. Ozonesondes played a role in data collection for TRACE-A along with the DC-8 aircraft. The sondes were dropped from the DC-8 aircraft in order to gather data on ozone, temperature, and atmospheric pressure.

  15. NASA DC-8 1 Second Data Merge

    • data.ucar.edu
    ascii
    Updated Dec 26, 2024
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    Gao Chen; Jennifer R. Olson; Langley Research Center (LaRC), NASA (2024). NASA DC-8 1 Second Data Merge [Dataset]. http://doi.org/10.5065/D6SF2TXB
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    asciiAvailable download formats
    Dataset updated
    Dec 26, 2024
    Dataset provided by
    University Corporation for Atmospheric Research
    Authors
    Gao Chen; Jennifer R. Olson; Langley Research Center (LaRC), NASA
    Time period covered
    May 18, 2012 - Jun 22, 2012
    Area covered
    Description

    This data set contains NASA DC-8 1 Second Data Merge data collected during the Deep Convective Clouds and Chemistry Experiment (DC3) from 18 May 2012 through 22 June 2012. These merges are an updated version that were provided by NASA. In most cases, variable names have been kept identical to those submitted in the raw data files. However, in some cases, names have been changed (e.g., to eliminate duplication). Units have been standardized throughout the merge. No "grand merge" has been provided for the 1-second data on the DC8 aircraft due to its prohibitive size (~1.5GB). In most cases, downloading the individual merge files for each day and simply concatenating them should suffice. This data set is in ICARTT format. Please see the header portion of the data files for details on instruments, parameters, quality assurance, quality control, contact information, and data set comments. For more information on the updates to this dataset, please see the readme file.

  16. NASA DC-8 WAS Data Merge

    • data.ucar.edu
    ascii
    Updated Dec 26, 2024
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    Gao Chen; Jennifer R. Olson; Michael Shook (2024). NASA DC-8 WAS Data Merge [Dataset]. http://doi.org/10.26023/TS5C-4X1T-G901
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    asciiAvailable download formats
    Dataset updated
    Dec 26, 2024
    Dataset provided by
    University Corporation for Atmospheric Research
    Authors
    Gao Chen; Jennifer R. Olson; Michael Shook
    Time period covered
    May 18, 2012 - Jun 22, 2012
    Area covered
    Description

    This data set contains NASA DC-8 WAS Data Merge data collected during the Deep Convective Clouds and Chemistry Experiment (DC3) from 18 May 2012 through 22 June 2012. These are updated merges from the NASA DC3 archive. In most cases, variable names have been kept identical to those submitted in the raw data files. However, in some cases, names have been changed (e.g., to eliminate duplication). Units have been standardized throughout the merge. In addition, a "grand merge" has been provided. This includes data from all the individual merged flights throughout the mission. This grand merge will follow the following naming convention: "dc3-mrgWAS-dc8_merge_YYYYMMdd_R5_thruYYYYMMdd.ict" (with the comment "_thruYYYYMMdd" indicating the last flight date included). This data set is in ICARTT format. Please see the header portion of the data files for details on instruments, parameters, quality assurance, quality control, contact information, and data set comments.

  17. Data for executing merge tools

    • zenodo.org
    csv
    Updated Oct 10, 2024
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    Name Author; Name Author (2024). Data for executing merge tools [Dataset]. http://doi.org/10.5281/zenodo.13881318
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    csvAvailable download formats
    Dataset updated
    Oct 10, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Name Author; Name Author
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Oct 2024
    Description

    Data used by scripts applied for analyzing merging tools.

  18. Data from: ORACLES Merge Data Files

    • s.cnmilf.com
    Updated Jun 28, 2025
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    NASA/LARC/SD/ASDC (2025). ORACLES Merge Data Files [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/oracles-merge-data-files
    Explore at:
    Dataset updated
    Jun 28, 2025
    Dataset provided by
    NASAhttp://nasa.gov/
    Description

    ORACLES_Merge_Data are pre-generated aircraft merge data files created utilizing data collected during the ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) campaign. These measurements were collected from August 19, 2016 – October 27, 2016, August 1, 2017 – September 4, 2017 and September 21, 2018 – October 27, 2018. ORACLES provides multi-year airborne observations over the complete vertical column of key parameters that drive aerosol-cloud interactions in the southeast Atlantic, an area with some of the largest inter-model differences in aerosol forcing assessments on the planet. The P-3 Orion aircraft was utilized as a low-flying platform for simultaneous in situ and remote sensing measurements of aerosols and clouds and was supplemented by ER-2 remote sensing during the 2016 campaign. Data collection for this product is complete.Southern Africa produces almost one-third of the Earth’s biomass burning aerosol particles. The ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) experiment was a five year investigation with three intensive observation periods (August 19, 2016 – October 27, 2016; August 1, 2017 – September 4, 2017; September 21, 2018 – October 27, 2018) and was designed to study key processes that determine the climate impacts of African biomass burning aerosols. ORACLES provided multi-year airborne observations over the complete vertical column of the key parameters that drive aerosol-cloud interactions in the southeast Atlantic, an area with some of the largest inter-model differences in aerosol forcing assessments. These inter-model differences in aerosol and cloud distributions, as well as their combined climatic effects in the SE Atlantic are partly due to the persistence of aerosols above clouds. The varying separation of cloud and aerosol layers sampled during ORACLES allow for a process-oriented understanding of how variations in radiative heating profiles impact cloud properties, which is expected to improve model simulations for other remote regions experience long-range aerosol transport above clouds. ORACLES utilized two NASA aircraft, the P-3 and ER-2. The P-3 was used as a low-flying platform for simultaneous in situ and remote sensing measurements of aerosols and clouds in all three campaigns, supplemented by ER-2 remote sensing in 2016. ER-2 observations will be used to enhance satellite-based remote sensing by resolving variability within a particular scene, and by guiding the development of new and improved remote sensing techniques.

  19. N

    Combine, TX Age Group Population Dataset: A Complete Breakdown of Combine...

    • neilsberg.com
    csv, json
    Updated Feb 22, 2025
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    Neilsberg Research (2025). Combine, TX Age Group Population Dataset: A Complete Breakdown of Combine Age Demographics from 0 to 85 Years and Over, Distributed Across 18 Age Groups // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/combine-tx-population-by-age/
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    csv, jsonAvailable download formats
    Dataset updated
    Feb 22, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Combine, Texas
    Variables measured
    Population Under 5 Years, Population over 85 years, Population Between 5 and 9 years, Population Between 10 and 14 years, Population Between 15 and 19 years, Population Between 20 and 24 years, Population Between 25 and 29 years, Population Between 30 and 34 years, Population Between 35 and 39 years, Population Between 40 and 44 years, and 9 more
    Measurement technique
    The data presented in this dataset is derived from the latest U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. To measure the two variables, namely (a) population and (b) population as a percentage of the total population, we initially analyzed and categorized the data for each of the age groups. For age groups we divided it into roughly a 5 year bucket for ages between 0 and 85. For over 85, we aggregated data into a single group for all ages. For further information regarding these estimates, please feel free to reach out to us via email at research@neilsberg.com.
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset tabulates the Combine population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Combine. The dataset can be utilized to understand the population distribution of Combine by age. For example, using this dataset, we can identify the largest age group in Combine.

    Key observations

    The largest age group in Combine, TX was for the group of age 5 to 9 years years with a population of 311 (11.19%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Combine, TX was the 85 years and over years with a population of 6 (0.22%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

    Age groups:

    • Under 5 years
    • 5 to 9 years
    • 10 to 14 years
    • 15 to 19 years
    • 20 to 24 years
    • 25 to 29 years
    • 30 to 34 years
    • 35 to 39 years
    • 40 to 44 years
    • 45 to 49 years
    • 50 to 54 years
    • 55 to 59 years
    • 60 to 64 years
    • 65 to 69 years
    • 70 to 74 years
    • 75 to 79 years
    • 80 to 84 years
    • 85 years and over

    Variables / Data Columns

    • Age Group: This column displays the age group in consideration
    • Population: The population for the specific age group in the Combine is shown in this column.
    • % of Total Population: This column displays the population of each age group as a proportion of Combine total population. Please note that the sum of all percentages may not equal one due to rounding of values.

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for Combine Population by Age. You can refer the same here

  20. P

    Data from: Wasserstein Distances, Geodesics and Barycenters of Merge Trees...

    • paperswithcode.com
    • opendatalab.com
    Updated Jul 15, 2021
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    Mathieu Pont; Jules Vidal; Julie Delon; Julien Tierny (2021). Wasserstein Distances, Geodesics and Barycenters of Merge Trees Dataset [Dataset]. https://paperswithcode.com/dataset/wasserstein-distances-geodesics-and
    Explore at:
    Dataset updated
    Jul 15, 2021
    Authors
    Mathieu Pont; Jules Vidal; Julie Delon; Julien Tierny
    Description

    This repository contains all the ensemble datasets (along with their meta-data) used in the manuscript "Wasserstein Distances, Geodesics and Barycenters of Merge Trees".

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data.wa.gov (2025). (TEST) Join Data 4 [Dataset]. https://catalog.data.gov/dataset/test-join-data-4

(TEST) Join Data 4

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Dataset updated
May 10, 2025
Dataset provided by
data.wa.gov
Description

This is a test of the Publishing API metadata update.

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