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).

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

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

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

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

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.

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).

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

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.

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.

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…

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

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.

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

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

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.

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).

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

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

Due to the United States' high rates of obesity and diet-related chronic diseases, this project aims to develop a plan for front of package (FOP) and shelf-labeling systems that identifies healthy choices, develops theory-based approaches that leverage FOP and shelf-labeling systems to promote healthier food purchases by SNAP participants, and identifies further exploration through the implementation and testing of a future pilot study.