100+ datasets found
  1. R

    Packaging Project Dataset

    • universe.roboflow.com
    zip
    Updated May 29, 2023
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    Samuel (2023). Packaging Project Dataset [Dataset]. https://universe.roboflow.com/samuel-w694e/packaging-project/dataset/1
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    zipAvailable download formats
    Dataset updated
    May 29, 2023
    Dataset authored and provided by
    Samuel
    License

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

    Variables measured
    Packaging Bounding Boxes
    Description

    Packaging Project

    ## Overview
    
    Packaging Project is a dataset for object detection tasks - it contains Packaging annotations for 606 images.
    
    ## Getting Started
    
    You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
    
      ## License
    
      This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
    
  2. w

    City of Wells Geothermal Project- Data

    • data.wu.ac.at
    • data.amerigeoss.org
    mpk, xlsx, zip
    Updated Jan 30, 2018
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    (2018). City of Wells Geothermal Project- Data [Dataset]. https://data.wu.ac.at/schema/edx_netl_doe_gov/MGUzNDFjNDUtZDE5My00MGI5LTk1ZDMtM2JmOTk1NGVkZjg3
    Explore at:
    xlsx(18321.0), zip(565012932.0), mpk(1140941278.0)Available download formats
    Dataset updated
    Jan 30, 2018
    Description

    This submissions contains datasets and information relevant to work on the City of Wells geothermal project

  3. f

    Overview of best practices in software engineering for scientific software...

    • plos.figshare.com
    • figshare.com
    xls
    Updated Mar 23, 2020
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    Michael Riesch; Tien Dat Nguyen; Christian Jirauschek (2020). Overview of best practices in software engineering for scientific software projects. [Dataset]. http://doi.org/10.1371/journal.pone.0230557.t001
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    xlsAvailable download formats
    Dataset updated
    Mar 23, 2020
    Dataset provided by
    PLOS ONE
    Authors
    Michael Riesch; Tien Dat Nguyen; Christian Jirauschek
    License

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

    Description

    For each best practice, implementation candidates are listed where the selected choice is denoted in bold.

  4. a

    Kendall County Packages

    • hub.arcgis.com
    Updated Oct 27, 2020
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    Kendall County Illinois GIS (2020). Kendall County Packages [Dataset]. https://hub.arcgis.com/content/937085a9708446ab959a3f021d7bba04
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    Dataset updated
    Oct 27, 2020
    Dataset authored and provided by
    Kendall County Illinois GIS
    License

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

    Area covered
    Kendall County
    Description

    This .zip file contains pre-configured files for members of the public to interact with Kendall County's public GIS layers in a desktop environment. Included are:An ArcGIS Pro PackageA QGIS Project FIleArcGIS Pro requires an ESRI license to use. See the ArcGIS Pro product page for more information.QGIS is free, open-source software that is available for a variety of computing environments. See the QGIS Downloads page to select the appropriate installation method.With the appropriate software installed, users can simply open the corresponding file. It may take a minute or two to load, due to the number of layers that need to load. Once loaded, users will have read-only access to all of the major public layers, and can adjust how they are displayed. In a desktop environment, users can also create and interact with other data sources, such as private site plans, annotations, and other public data layers from non-County entities.Please note that the layers included in these packages are the same live data sources found in the web maps. An internet connection is required for these files to function properly.

  5. g

    Straight Fork Road Bridge Construction Project | gimi9.com

    • gimi9.com
    Updated Jun 20, 2024
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    (2024). Straight Fork Road Bridge Construction Project | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_straight-fork-road-bridge-construction-project/
    Explore at:
    Dataset updated
    Jun 20, 2024
    Description

    This data package was created 2024-06-20 11:39:41 by NPSTORET and includes selected project, location, and result data. Data are from monitoring conducted to assess the potential impacts of the Straight Fork Road Bridge Construction Project in Great Smoky Mountains National Park. The Straight Fork road ford was replaced with a bridge in early 2006. The purpose of this project was to determine if the water quality during bridge construction from March 2006 through August 2006 was significantly different than the water quality prior to construction (October 2004 through September 2005). Data contained in Great Smoky Mountains National Park NPSTORET back-end file (GRSM_NPSTORET_BE_20240510.ACCDB) were filtered to include: Organization: - GRSM: Great Smoky Mountains National Park Project: - GRSM_SF: Straight Fork Road Bridge Construction Project Station: - Include Trip QC And All Station Visit Results Value Status: - Accepted or Certified (exported as Final) or Final The data package is organized into five data tables: - Projects.csv - describes the purpose and background of the monitoring efforts - Locations.csv - documents the attributes of the monitoring locations/stations - Results.csv - contains the field measurements, observations, and/or lab analyses for each sample/event/data grouping - HUC12.csv - enumerates the domain of allowed values for 12-digit hydrologic unit codes utilized by the Locations datatable - Characteristics.csv - enumerates the domain of characteristics available in NPSTORET to identify what was sampled, measured or observed in Results Period of record for filtered data is 2004-10-27 to 2004-10-27. This data package is a snapshot in time of one National Park Service project. The most current data for this project, which may be more or less extensive than that in this data package, can be found on the Water Quality Portal at: https://www.waterqualitydata.us/data/Result/search?project=GRSM_SF

  6. Great Smoky Mountains National Park 1993-2023 Parkwide Water Quality Survey...

    • catalog.data.gov
    Updated Jul 11, 2025
    + more versions
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    National Park Service (2025). Great Smoky Mountains National Park 1993-2023 Parkwide Water Quality Survey Data from the GRSM_WQ Project as of 2024-05-10 [Dataset]. https://catalog.data.gov/dataset/great-smoky-mountains-national-park-1993-2023-parkwide-water-quality-survey-data-from-the--3f3a2
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    Dataset updated
    Jul 11, 2025
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Area covered
    Great Smoky Mountains
    Description

    This data package was created 2024-10-17 16:52:40 by NPSTORET and includes selected project, location, and result data. Data contained in the Great Smoky Mountains National Park NPSTORET back-end file (GRSM_NPSTORET_BE_20240510_20240510_1245.ACCDB) were filtered to include: Organization: - GRSM: Great Smoky Mountains National Park Project: - GRSM_WQ: GRSM Parkwide Water Quality Survey Station: - Include Trip QC And All Station Visit Results Value Status: - Accepted or Certified (exported as Final) or Final The data package is organized into five data tables: - Projects.csv - describes the purpose and background of the monitoring efforts - Locations.csv - documents the attributes of the monitoring locations/stations - Results.csv - contains the field measurements, observations, and/or lab analyses for each sample/event/data grouping - HUC.csv - enumerates the domain of allowed values for 8-digit and 12-digit hydrologic unit codes utilized by the Locations data table - Characteristics.csv - enumerates the domain of characteristics available in NPSTORET to identify what was sampled, measured or observed in Results Period of record for filtered data is 1993-10-01 to 2023-11-20. This data package is a snapshot in time of one National Park Service project. The most current data for this project, which may be more or less extensive than that in this data package, can be found on the Water Quality Portal at: https://www.waterqualitydata.us/data/Result/search?project=GRSM_WQ&mimeType=csv&zip=yes&dataProfile=biological&providers=STORET

  7. BMBF KüNO BluEs project: Work package 4.3 by University of Rostock

    • zenodo.org
    zip
    Updated Jul 31, 2024
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    Duy Nghia Pham; Julie Angelina Kopplin; Olaf Dellwig; Eugene P. Sokolov; Inna M. Sokolova; Duy Nghia Pham; Julie Angelina Kopplin; Olaf Dellwig; Eugene P. Sokolov; Inna M. Sokolova (2024). BMBF KüNO BluEs project: Work package 4.3 by University of Rostock [Dataset]. http://doi.org/10.5281/zenodo.7978848
    Explore at:
    zipAvailable download formats
    Dataset updated
    Jul 31, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Duy Nghia Pham; Julie Angelina Kopplin; Olaf Dellwig; Eugene P. Sokolov; Inna M. Sokolova; Duy Nghia Pham; Julie Angelina Kopplin; Olaf Dellwig; Eugene P. Sokolov; Inna M. Sokolova
    License

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

    Area covered
    Rostock
    Description

    Research data from work package 4.3 of the project BluEs (Blue_Estuaries - Developing estuaries as habitable sustainable ecosystem despite climate change and stress), funded by the Federal Ministry of Education and Research of Germany (BMBF), grant number 03F0864B.

  8. Materials Project Data

    • figshare.com
    txt
    Updated May 30, 2023
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    Anubhav Jain; Shyue Ping Ong; Geoffroy Hautier; Wei Chen; William Davidson Richards; Stephen Dacek; Shreyas Cholia; Dan Gunter; David Skinner; Gerbrand Ceder; Kristin Persson; Hacking Materials (2023). Materials Project Data [Dataset]. http://doi.org/10.6084/m9.figshare.7227749.v1
    Explore at:
    txtAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Anubhav Jain; Shyue Ping Ong; Geoffroy Hautier; Wei Chen; William Davidson Richards; Stephen Dacek; Shreyas Cholia; Dan Gunter; David Skinner; Gerbrand Ceder; Kristin Persson; Hacking Materials
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    A complete copy of the Materials Project database as of 10/18/2018. Mp_all files contain structure data for each material while mp_nostruct does not.Available as Monty Encoder encoded JSON and as CSV. Recommended access method for these particular files is with the matminer Python package using the datasets module. Access to the current Materials Project is recommended through their API (good), pymatgen (better), or matminer (best).Note on citations: If you found this dataset useful and would like to cite it in your work, please be sure to cite its original sources below rather than or in addition to this page.Dataset discussed in:A. Jain*, S.P. Ong*, G. Hautier, W. Chen, W.D. Richards, S. Dacek, S. Cholia, D. Gunter, D. Skinner, G. Ceder, K.A. Persson (*=equal contributions) The Materials Project: A materials genome approach to accelerating materials innovation APL Materials, 2013, 1(1), 011002.Dataset sourced from:https://materialsproject.org/Citations for specific material properties available here:https://materialsproject.org/citing

  9. Replication Package for Student Challanges Data in Team Project Course

    • figshare.com
    xlsx
    Updated Jan 16, 2022
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    Arthur-Jozsef Molnar; Simona Motogna; Dan Mircea Suciu (2022). Replication Package for Student Challanges Data in Team Project Course [Dataset]. http://doi.org/10.6084/m9.figshare.18506450.v1
    Explore at:
    xlsxAvailable download formats
    Dataset updated
    Jan 16, 2022
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Arthur-Jozsef Molnar; Simona Motogna; Dan Mircea Suciu
    License

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

    Description

    Replication package consisting of student feedback regarding the challenges encountered in two consecutive iterations of a Team Projects course (2019-2020 on-site, 2020-2021 online due to pandemic-related restrictions).

  10. d

    Project Management

    • catalog.data.gov
    • datasets.ai
    • +2more
    Updated May 2, 2025
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    Office of Project Management (2025). Project Management [Dataset]. https://catalog.data.gov/dataset/project-management
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    Dataset updated
    May 2, 2025
    Dataset provided by
    Office of Project Management
    Description

    the Department of Energy’s Enterprise Project Management Organization (EPMO), providing leadership and assistance in developing and implementing DOE-wide policies, procedures, programs, and management systems pertaining to project management, and independently monitors, assesses, and reports on project execution performance. The office validates project performance baselines–scope, cost and schedule–of the Department’s largest construction and environmental clean-up projects prior to budget request to Congress—an active project portfolio totaling over $30 billion. The office also serves as Executive Secretariat for the Department’s Energy Systems Acquisition Advisory Board (ESAAB) and the Project Management Risk Committee (PMRC). In these capacities, the Director is accountable to the Deputy Secretary.

  11. p

    Dataset from the B-GOOD project, containing data from Tier 1 studies...

    • app.pollinatorhub.eu
    Updated Apr 18, 2025
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    B-GOOD Bee Health Data Portal (2025). Dataset from the B-GOOD project, containing data from Tier 1 studies performed in Work Package 1 in 2020 [Dataset]. https://app.pollinatorhub.eu/dataset-discovery/BGDWP181.0.0
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    Dataset updated
    Apr 18, 2025
    Dataset provided by
    EU Pollinator Hub
    Authors
    B-GOOD Bee Health Data Portal
    License

    Attribution-NonCommercial-NoDerivs 4.0 (CC BY-NC-ND 4.0)https://creativecommons.org/licenses/by-nc-nd/4.0/
    License information was derived automatically

    Description

    Dataset B-GOOD WP1 Tier 1 Data 2020 collects data from Tier 1 studies performed in Work Package 1 in 2020 in Belgium, Switzerland, Germany, France, United Kingdom, the Neterlands, Portugal and Romania. It contains metadata on study sites (locations of apiaries and honey bee colonies), on test beehives (type and…

  12. Replication package for class comment analysis

    • zenodo.org
    zip
    Updated Aug 29, 2022
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    Pooja Rani; Pooja Rani (2022). Replication package for class comment analysis [Dataset]. http://doi.org/10.5281/zenodo.3762776
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    zipAvailable download formats
    Dataset updated
    Aug 29, 2022
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Pooja Rani; Pooja Rani
    License

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

    Description

    This project contains the necessary material to replicate the project. It also contains supplementary data to give better insights into the results.

  13. Add realistic detail to a scene

    • visionzero.geohub.lacity.org
    Updated Jan 31, 2024
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    Esri Tutorials (2024). Add realistic detail to a scene [Dataset]. https://visionzero.geohub.lacity.org/content/629abff38e664eaf97b4197aeae10ca2
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    Dataset updated
    Jan 31, 2024
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri Tutorials
    Description

    Renowned for its natural and man-made beauty, the historic city of Venice spans a series of islands in a shallow lagoon. Venice’s unique geography has a downside, however. Tidal patterns mix with low elevation to cause acqua alta (high water), a periodic flooding that, although not dangerous to human life, impedes transportation and endangers Venice’s priceless architecture.This layer package includes five layers. The Structures layer contains building footprint data. The Canals layer contains Venice's canals. The Landmarks layer contains famous landmarks throughout the city. The Venice 1m and Venice Ground Surface layers are interpolated elevation rasters of Venice. The data was acquired or derived from data acquired from Comune di Venezia - Portale dei servizi in 2014.This project package contains the default ArcGIS Pro project for the tutorial Add realistic detail to a scene. If users did not complete the previous tutorial in the series, they can use this project package.

  14. d

    Data from: Codebook and data collection guidelines of work package 1 on...

    • search.dataone.org
    • dataverse.harvard.edu
    Updated Nov 22, 2023
    + more versions
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    Morales, Laura; Vintila, Daniela; Geese, Lucas; Mügge, Liza; van der Pas, Daphne; van de Ward, Marc (2023). Codebook and data collection guidelines of work package 1 on descriptive political representation in regional parliaments of the project Pathways to Power [Dataset]. http://doi.org/10.7910/DVN/KZMOAM
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    Dataset updated
    Nov 22, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Morales, Laura; Vintila, Daniela; Geese, Lucas; Mügge, Liza; van der Pas, Daphne; van de Ward, Marc
    Description

    Codebook of work package 1 on descriptive political representation in regional parliaments of the project Pathways to Power

  15. Seismic Line Location Map File, Hot Pot Project, Humboldt County, Nevada...

    • data.openei.org
    • gdr.openei.org
    • +4more
    Updated Jan 1, 2010
    + more versions
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    Michael Lane; Michael Lane (2010). Seismic Line Location Map File, Hot Pot Project, Humboldt County, Nevada 2010 [Dataset]. http://doi.org/10.15121/1150325
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    Dataset updated
    Jan 1, 2010
    Dataset provided by
    United States Department of Energyhttp://energy.gov/
    Open Energy Data Initiative (OEDI)
    Oski Energy LLC
    Authors
    Michael Lane; Michael Lane
    License

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

    Area covered
    Humboldt County, Nevada
    Description

    Location of seismic lines carried out under DOE funded project Advanced Seismic Data Analysis Program (The Hot Pot Project). ArcGIS map package containing topographic base map, Township and Range layer, Oski BLM and private leases at time of survey, and locations, with selected shot points, of the five seismic lines.

  16. Visualize 2045: Constrained Element (Data Download)

    • rtdc-mwcog.opendata.arcgis.com
    • hub.arcgis.com
    Updated Jun 20, 2019
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    Metropolitan Washington Council of Governments (2019). Visualize 2045: Constrained Element (Data Download) [Dataset]. https://rtdc-mwcog.opendata.arcgis.com/datasets/54c2682fde8e4a0c9a8a1c0a8e81fef5
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    Dataset updated
    Jun 20, 2019
    Dataset authored and provided by
    Metropolitan Washington Council of Governmentshttp://www.mwcog.org/
    Area covered
    Description

    The financially constrained element of Visualize 2045 identifies all the regionally significant capital improvements to the region’s highway and transit systems that transportation agencies expect to make and to be able to afford through 2045.For more information on Visualize 2045, visit https://www.mwcog.org/visualize2045/.To view the web map, visit https://www.mwcog.org/maps/map-listing/visualize-2045-project-map/.* NOTE: the online map shows projects in the current version of the plan (2022 update); this data download is for the 2018 update to the plan.Adding GIS Data to ArcMap from a Map Package:To load the .mpk file if saved locally: From Windows Explorer1. Browse to the location of the .mpk file. 2. Double-click the file to launch ArcMap and unpack all the data in the package. From ArcCatalog1. Browse to the location of the .mpk file. 2. Right-click the file, and select Unpack. This action launches ArcMap and unpacks the data in the package. The process is the same if you are using ArcCatalog from within ArcMap.Note: The .mpk file cannot be opened within ArcMap.Regardless of where the .mpk file is stored originally, the data within the map package when unpacked saves on your hard drive in the Documents and Settings folder:C:\Documents_and_Settings\MyDocuments\ArcGIS\Packages*.gdb

  17. P

    Fire Drill Anti-Pattern Dataset Dataset

    • paperswithcode.com
    Updated Apr 29, 2021
    + more versions
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    Sebastian Hönel (2021). Fire Drill Anti-Pattern Dataset Dataset [Dataset]. https://paperswithcode.com/dataset/detection-of-the-fire-drill-anti-pattern-nine
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    Dataset updated
    Apr 29, 2021
    Authors
    Sebastian Hönel
    Description

    Fire Drill Anti-Pattern Dataset is a collection of nine real-world software projects for detection of the fire drill anti-pattern with ground truth, issue-tracking data, source code density, models and code. The data is supposed to aid the detection of the presence of the Fire Drill anti-pattern. It includes data, ground truth, code, and notebooks. The data supports two distinct methods of detecting the AP: a) through issue-tracking data, and b) through the underlying source code. Therefore, this package includes the following:

    Fire Drill in issue-tracking data:

    Ground truth for whether and how strong each project exhibits the Fire Drill AP, on a scale from [0,10]. This was determined by two individual raters, who also reached a consensus. Coefficients for indicators for the first method, per project. Detailed issue-tracing data for each project: what occurred and when. Time logs for each project.

    Fire Drill in source-code data:

    Three technical reports that document the developed method of how to translate a description into a detectable pattern, and to use the pattern to detect the presence and to score it (similar to the rating). Also includes a report for how activities were assigned to individual commits. Source code density data (metrics) for each commit in each of the nine projects as a separate dataset. Code: a snapshot of the repository that holds all code, models, notebooks, and pre-computed results, for utmost reproducibility (the code is written in R).

  18. g

    Ontario Raw Point Cloud (Imagery-Derived)

    • geohub.lio.gov.on.ca
    • hub.arcgis.com
    Updated Aug 30, 2019
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    Ontario Ministry of Natural Resources and Forestry (2019). Ontario Raw Point Cloud (Imagery-Derived) [Dataset]. https://geohub.lio.gov.on.ca/maps/08f1a39395e04803ace0225c1fc196a0
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    Dataset updated
    Aug 30, 2019
    Dataset authored and provided by
    Ontario Ministry of Natural Resources and Forestry
    License

    https://www.ontario.ca/page/open-government-licence-ontariohttps://www.ontario.ca/page/open-government-licence-ontario

    Area covered
    Description

    If you are interested in obtaining a copy of this data see LIO Support – Large Data Ordering Instructions. Data can be requested by project or by package within each project. To determine which package contains your area of interest zoom in on the map above and click. You will need to provide a large enough hard drive for the data to be copied onto. Data sizes are listed below.

    The Ontario Raw Point Cloud (Imagery-Derived) was created using a pixel-autocorrelation process based on aerial photography collected by the imagery contractor for the Geospatial Ontario (GEO) imagery program. The dataset consists of overlapping tiles in LAZ format and is 8.29 terabytes in size. Tiles for some projects are overlapping because the pixel-autocorrelation process extracts elevation values from overlapping stereo photo strips. No classification has been applied to the point cloud, however they are encoded with colour (RGB) values from the source photography.

    For more detailed information about this dataset, refer to the associated User Guide.

    For a product in non-overlapping tiles with a ground classification applied see the Ontario Classified Point Cloud (Imagery-Derived).

    Raster derivatives have been created from the point clouds for some imagery projects. These products may meet your needs and are available for direct download. See the Ontario Digital Elevation Model (Imagery-Derived) for a representation of bare earth and the Ontario Digital Surface Model (Imagery-Derived) for a model representing all surface features.

    Additional Documentation OntarioRaw Point Cloud (Imagery-Derived) - User Guide (DOCX) Ontario Raw Point Cloud (Imagery-Derived) - Tile Index (SHP)

    Data Package Sizes SWOOP 2010 - Total - 519 GB SWOOP 2010 - Chatham-Kent - 132 GB SWOOP 2010 - Elgin - 130 GB SWOOP 2010 - Oxford - 133 GB SWOOP 2010 - Perth - 124 GB

    SCOOP 2013 - Total - 1.56 TB SCOOP 2013 - Package A - 275 GB SCOOP 2013 - Package B - 238 GB SCOOP 2013 - Package C - 278 GB SCOOP 2013 - Package D - 350 GB SCOOP 2013 - Package E - 420 GB

    DRAPE 2014 - Total - 2.05 TB DRAPE 2014 - Package A - 504 GB DRAPE 2014 - Package B - 436 GB DRAPE 2014 - Package C - 337 GB DRAPE 2014 - Package D - 348 GB DRAPE 2014 - Package E - 430 GB

    SWOOP 2015 - Total - 2.52 TB SWOOP 2015 - Package A - 235 GB SWOOP 2015 - Package B - 394GB SWOOP 2015 - Package C - 439GB SWOOP 2015 - Package D - 363GB SWOOP 2015 - Package E - 439GB SWOOP 2015 - Package F - 351GB SWOOP 2015 - Package G - 302GB

    Algonquin 2015 - 235 GB SCOOP 2018 - 410 GB DRAPE 2019 - 328 GB SWOOP 2020 - 329 GB COOP 2021 - 451 GB NWOOP 2022 Zone 15 - 118 GB NWOOP 2022 Zone 16 - 271 GB

    Status On going: Data is continually being updated

    Maintenance and Update Frequency As needed: Data is updated as deemed necessary

    Contact Ontario Ministry of Natural Resources - Geospatial Ontario, geospatial@ontario.ca

  19. O

    Bond Project Line

    • data.sanantonio.gov
    • opendata-cosagis.opendata.arcgis.com
    Updated Jun 17, 2025
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    GIS Data (2025). Bond Project Line [Dataset]. https://data.sanantonio.gov/dataset/bond-project-line
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    html, gpkg, gdb, csv, zip, arcgis geoservices rest api, txt, geojson, kml, xlsxAvailable download formats
    Dataset updated
    Jun 17, 2025
    Dataset provided by
    Capital Improvements Management Services Department
    Authors
    GIS Data
    Description

    City of San Antonio Capital Improvements Program project data (spatial). Project limits for horizontal Bond Projects only. Updated construction timelines, budget, and contact information are provided for each project (updated monthly).

  20. Shenandoah National Park - University of Virginia Primary Project Water...

    • catalog.data.gov
    • s.cnmilf.com
    Updated May 11, 2025
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    National Park Service (2025). Shenandoah National Park - University of Virginia Primary Project Water Quality Data from 1979-2023 as of 2025-03-28 [Dataset]. https://catalog.data.gov/dataset/shenandoah-national-park-university-of-virginia-primary-project-water-quality-data-from-1-
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    Dataset updated
    May 11, 2025
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Description

    This data package was created 2025-03-28 10:09:52 by NPSTORET and includes selected project, location, and result data. The included project (SHEN_UVA_Primary) comprises data from the following sources: (1) the Shenandoah Watershed Study (SWAS); (2) quarterly sampling for the Virginia Trout Stream Sensitivity Study (VTSSS); and (3) 1987, 2000, 2010, and 2011 ('decadal') sampling for the Virginia Trout Stream Sensitivity Study. The Shenandoah Water Study (SWAS), initiated in 1979, has both scientific and resource management objectives. The underlying scientific objective of the SWAS program has been to improve understanding of hydro-biogeochemical processes and factors that govern ecosystem conditions in the mountain watersheds of Shenandoah National Park (SHEN). This scientific objective complements a resource management objective that has been defined by the need to document and assess change that is occurring in SHEN ecosystems. Only the data from SWAS and VTSSS collected within SHEN are contained in the SHEN_UVA_Primary project. Other data from these programs collected outside SHEN (e.g., on U.S. Forest Service and other lands) can be obtained from the University of Virginia or the Water Quality Portal under the USFS_UVA_Primary and OTHR_UVA_Primary projects. Data contained in the Shenandoah National Park - University of Virginia NPSTORET back-end file (NPS_UVA_NPSTORET_BE_20250108.ACCDB) were filtered to include: Project: - SHEN_UVA_PRIMARY: University of Virginia's Primary SWAS-VTSSS Program Database Station: - Include Trip QC And All Station Visit Results Park/Unit Code: - SHEN Activity Start Date (>=1/1/1950 and <=12/31/2023) Value Status: - Accepted or Certified (exported as Final) or Final The data package is organized into five data tables: - Projects.csv - describes the purpose and background of the monitoring efforts - Locations.csv - documents the attributes of the monitoring locations/stations - Results.csv - contains the field measurements, observations, and/or lab analyses for each sample/event/data grouping - HUC.csv - enumerates the domain of allowed values for 8-digit and 12-digit hydrologic unit codes utilized by the Locations data table - Characteristics.csv - enumerates the domain of characteristics available in NPSTORET to identify what was sampled, measured or observed in Results Period of record for filtered data is 1979-11-02 to 2023-12-28. This data package is a snapshot in time of one National Park Service project. The most current data for this project, which may be more or less extensive than that in this data package, can be found on the Water Quality Portal at: https://www.waterqualitydata.us/data/Result/search?project=SHEN_UVA_PRIMARY&mimeType=csv&zip=yes&dataProfile=biological&providers=STORET

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Samuel (2023). Packaging Project Dataset [Dataset]. https://universe.roboflow.com/samuel-w694e/packaging-project/dataset/1

Packaging Project Dataset

packaging-project

packaging-project-dataset

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zipAvailable download formats
Dataset updated
May 29, 2023
Dataset authored and provided by
Samuel
License

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

Variables measured
Packaging Bounding Boxes
Description

Packaging Project

## Overview

Packaging Project is a dataset for object detection tasks - it contains Packaging annotations for 606 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
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