The General Service Administration's data.json harvest source. This file contains the metadata for the GSA's public data listing shown on data.gov as defined by the Project Open Data

Tracking systems for timeliness and completion for business processes

Gds

## Overview

Gds is a dataset for object detection tasks - it contains Objects annotations for 1,500 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).

The MetOp First Generation (FG) is a European multi-satellite program jointly established by ESA and EUMETSAT, comprising three satellites, MetOp-A, -B and -C. The primary sensor onboard MetOp-FG, the Advanced Very High Resolution Radiometer/3 (AVHRR/3) contributed by NOAA, measures Earth emissions and reflectances in 5 out of 6 available bands (centered at 0.63, 0.83, 1.61, 3.7, 11 and 12 microns), in a swath of 2,600km from an 817km altitude. These data are collected in a Full Resolution Area Coverage (FRAC) mode, with pixel size of 1.1km at nadir. MetOp-A launched on 19 October 2006 is the first in the MetOp-FG series. The NOAA Advanced Clear-Sky Processor for Ocean (ACSPO) Level 2 Preprocessed (L2P) SST product is derived at the full AVHRR FRAC resolution and reported in 10 minute granules in NetCDF4 format, compliant with the GHRSST Data Specification version 2 (GDS2). Subskin SSTs are derived using the regression Nonlinear SST (NLSST) algorithm, which employs three bands (3.7, 11 and 12 microns) at night and two bands (11 and 12 microns) during the day. The ACSPO AVHRR FRAC L2P product is monitored and validated against quality controlled in situ data, provided by the NOAA in situ SST Quality Monitor system (iQuam; Xu and Ignatov, 2014, https://doi.org/10.1175/JTECH-D-13-00121.1 ), in another NOAA system, SST Quality Monitor (SQUAM; Dash et al, 2010, https://doi.org/10.1175/2010JTECHO756.1 ). SST imagery and clear-sky masking are continuously evaluated, and checked for consistency with other sensors and platforms, in the ACSPO Regional Monitor for SST (ARMS) system. MetOp-A orbital characteristics and AVHRR/3 sensor performance are tracked in the NOAA 3S system (He et al., 2016, https://doi.org/10.3390/rs8040346 ).The L2P Near Real Time (NRT) SST files are archived at PO.DAAC with 3-6 hours latency, and then replaced by the Re-ANalysis (RAN) SST after about 2 months later with identical file names. Two features can be used to identify them: different file name time stamps and netCDF global attribute metadata source=NOAA-NCEP-GFS for NRT and source=MERRA-2 for RAN. A reduced size (0.45GB/day), equal-angle gridded (0.02-deg resolution) ACSPO L3U product is available at https://doi.org/10.5067/GHMTA-3US28

Detecting the presence and location of hand written artifacts such as signatures, dates, initials can be critical for scanned (offline)document processing systems. This capability can support multiple downstream tasks such as signature verification, document tagging and categorization. In this work, we present SignverOD, a curated dataset of 2576 scanned document images with 7103 bounding box annotations, across 4 categories (signature, initials, redaction, date). SignverOD cover a diverse set of document types including memos, emails, bank cheques, lease agreements and letters, memos, invoices.

Dataset Source

Images of documents in this dataset are sourced from 4 main locations and then annotated.

Tobacco800

Tobacco800 is a publicly accessible document image collection with realistic scope and complexity is important to the document image analysis and search community. https://www.kaggle.com/sprytte/tobacco-800-dataset.

NIST.gov Special Database

The NIST.gov structured Forms Database consists of 5,590 pages of binary, black-and-white images of synthesized documents. The documents in this database are 12 different tax forms from the IRS 1040 Package X for the year 1988. https://www.nist.gov/srd/nist-special-database-2

Bank Cheques

The bank cheques dataset is a collection of xx colored images of bank checks. They consist of scanned realistic checks as well as examplar signatures with signatures. https://www.kaggle.com/saifkhichi96/bank-checks-signatures-segmentation-dataset

GSA.gov Lease Documents

GSA provides electronic copies of GSA lease documents for general public viewing. The lease documents are sorted by region and contain, for the most part, GSA Lease Forms and Lease Amendments (LA) from selected GSA leases across the nation. https://www.gsa.gov/real-estate/real-estate-services/leasing/executed-lease-documents

Citation

If you use this dataset as part of your work or experiments, please consider citing:

This L3U (Level 3 Uncollated) dataset contains global daily Sea Surface Temperature (SST) on a 0.02 degree grid resolution. It is produced by the National Oceanic and Atmospheric Administration (NOAA) Advanced Clear Sky Processor for Ocean (ACSPO) using L2P (Level 2 Preprocessed) product acquired from the Meteorological Operational satellite B (Metop-B) Advanced Very High Resolution Radiometer 3 (AVHRR/3) (https://podaac.jpl.nasa.gov/dataset/AVHRRF_MB-STAR-L2P-v2.80 ) in Full Resolution Area Coverage (FRAC) mode as input. It is distributed as 10-minute granules in netCDF-4 format, compliant with the Group for High Resolution Sea Surface Temperature (GHRSST) Data Specification version 2 (GDS2). There are 144 granules per 24-hour interval. Fill values are reported in all invalid pixels, including land pixels with >5 km inland. For each valid water pixel (defined as ocean, sea, lake or river), and up to 5 km inland, the following major layers are reported: SSTs and ACSPO clear-sky mask (ACSM; provided in each grid as part of l2p_flags, which also includes day/night, land, ice, twilight, and glint flags). Only input L2P SSTs with QL=5 were gridded, so all valid SSTs are recommended for the users. Per GDS2 specifications, two additional Sensor-Specific Error Statistics layers (SSES bias and standard deviation) are reported in each pixel with valid SST. Ancillary layers include wind speed and ACSPO minus reference Canadian Meteorological Centre (CMC) Level 4 (L4) SST. The ACSPO Metop-B AVHRR FRAC L3U product is monitored and validated against iQuam in situ data (Xu and Ignatov, 2014) in the NOAA SST Quality Monitor (SQUAM) system (Dash et al, 2010). SST imagery and clear-sky mask are evaluated, and checked for consistency with L2P and other satellites/sensors SST products, in the NOAA ACSPO Regional Monitor for SST (ARMS) system. More information about the dataset is found at AVHRRF_MB-STAR-L2P-v2.80 and in (Pryamitsyn et al., 2021).

GSA Enterprise Data Inventory (EDI)

Gsa Tank Bubble

## Overview

Gsa Tank Bubble is a dataset for object detection tasks - it contains Gas Tank Bubble annotations for 697 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).

A Group for High Resolution Sea Surface Temperature (GHRSST) Level 4 sea surface temperature analysis produced daily on an operational basis at the UK Met Office using optimal interpolation (OI) on a global 0.05x0.05 degree grid. The Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) analysis uses satellite data from over 10 unique sensors that include the Advanced Very High Resolution Radiometer (AVHRR), the Spinning Enhanced Visible and Infrared Imager (SEVIRI), the Geostationary Operational Environmental Satellite (GOES) imager, the Infrared Atmospheric Sounding Interferometer (IASI), the Tropical Rainfall Measuring Mission Microwave Imager (TMI) and in situ data from ships, drifting and moored buoys. This analysis was specifically produced to be used as a lower boundary condition in Numerical Weather Prediction (NWP) models. This dataset adheres to the GHRSST Data Processing Specification (GDS) version 2 format specifications and is updated daily with 24-hours nominal latency in a Near Real Time (NRT) mode. UKMO also produces the higher quality reprocessed OSTIA L4 SST using more sensors and data with a biannual latency (https://podaac.jpl.nasa.gov/dataset/OSTIA-UKMO-L4-GLOB-REP-v2.0).

This is an example dataset that comes with a new installation of JKAN

Dataset

This dataset was created by guandongsheng888

Released under Apache 2.0

Contents

Purchases made with the purchase card. Files will be batched quarterly.

This dataset is about books. It has 1 row and is filtered where the author is G. D. S. Beechey. It features 2 columns including publication date.

Pollen, plant macrofossil, charcoal, geochronological, and loss-on-ignition data from sediment core GDS-83-3-22-2017 were generated in support of research on long-term patterns of vegetation, fire, and climate in Great Dismal Swamp National Wildlife Refuge (Willard et al., in review). Raw counts of pollen data are provided. Plant macrofossil data are presented as presence/absence. Macroscopic charcoal was counted in one size class: > 125 micrometers. Uncalibrated radiocarbon dates were obtained and provided for use in development of age models for analyses by Willard et al, in review. Loss-on-ignition data are presented as percent organic matter.

Imports (Fob): Capital Gds - Fixed Equipment For Transportation in Brazil decreased to 20.61 USD Million in January from 24.56 USD Million in December of 2016. This dataset includes a chart with historical data for Brazil Imports of : Capital Gds - Fixed Equipment F.

The Sediment Analysis Network for Decision Support (SANDS) MODIS Geological Survey of AL (GSA) Analysis dataset consists of geoTIFF images were analyzed for sediment redistribution after hurricanes on the Gulf of America. These are seasonal data for storms from September 14, 2000 to September 8, 2008. In addition to the analyzed files, the data files include the ESRI files for zipped bands and/or grids, metadata, and storm temporal information for the sediment analysis images. The Geological Survey of Alabama (GSA) generated this dataset from geoTIFF MODIS images as part of the Sediment Analysis Network for Decision Support (SANDS) project.

This dataset provides values for TRADE BAL CAPITAL GDS MACHINERY OTH CAPITAL reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

A Group for High Resolution Sea Surface Temperature (GHRSST) Level 4 sea surface temperature (SST) analysis produced daily on an operational basis at the Canadian Meteorological Center. This dataset merges infrared satellite SST at varying points in the time series from the (A)TSR series of radiometers from ERS-1, ERS-2 and Envisat, AVHRR from NOAA-16,17,18,19 and METOP-A, and microwave data from TMI, AMSR-E and Windsat in conjunction with in situ observations of SST from drifting buoys and ships from the ICOADS program. It uses the previous days analysis as the background field for the statistical interpolation used to assimilate the satellite and in situ observations. This dataset adheres to the GHRSST Data Processing Specification (GDS) version 2 format specifications.

The dataset contains locations and attributes of GSA owned or leased buildings, created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies. A database provided by GSA identified Federal locations and DC GIS staff geo-processed the data.

The Groundwater Sustainability Plan (GSP) Annual Report (AR) datasets contain the following data submitted by Groundwater Sustainability Agencies (GSA) and Alternative Agencies as part of their GSP AR or Alternative to GSP AR: groundwater extraction, surface water supply, total water use, and change in storage volumes for a given water year. All data was originally submitted to the Department of Water Resources (DWR) through the Sustainable Groundwater Management Act (SGMA) Portal’s AR Modules (https://sgma.water.ca.gov/portal/gspar/submitted and https://sgma.water.ca.gov/portal/alternative/annualreport/submitted). Data records within each dataset correspond to either an entire basin or one of multiple GSP areas which collectively correspond to an entire basin.

The GSP Regulations established the AR data requirements (23 CCR § 356.2) and tasked DWR with developing an online reporting system for GSAs and Alternative Agencies to electronically submit these data (23 CCR § 353.2). The data fields associated with these datasets were created by DWR to ensure GSAs and Alternative Agencies electronically submitted the required AR data to DWR’s online reporting system, the SGMA Portal (https://sgma.water.ca.gov/portal/). For additional information regarding the AR Modules and the AR submittal process, please view the DWR’s AR resources (https://sgma.water.ca.gov/portal/resources).