100+ datasets found
  1. Commercial Fisheries Database Biological Sample (CFDBS)

    • fisheries.noaa.gov
    • catalog.data.gov
    Updated Jul 11, 2017
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    Northeast Fisheries Science Center (2017). Commercial Fisheries Database Biological Sample (CFDBS) [Dataset]. https://www.fisheries.noaa.gov/inport/item/27401
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    Dataset updated
    Jul 11, 2017
    Dataset provided by
    Northeast Fisheries Science Center
    Time period covered
    1963 - Jul 17, 2125
    Area covered
    Description

    Age and length frequency data for finfish and invertebrate species collected during commercial fishing vessels. Samples are collected by fisheries reporting specialist from fish dealers in ports along the northwest Atlantic Ocean from Maine to North Carolina.

  2. Most popular commercial database management systems worldwide 2024

    • ai-chatbox.pro
    • statista.com
    Updated Jun 12, 2024
    + more versions
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    Statista (2024). Most popular commercial database management systems worldwide 2024 [Dataset]. https://www.ai-chatbox.pro/?_=%2Fstatistics%2F1131597%2Fworldwide-popularity-ranking-database-management-systems-commercial%2F%23XgboD02vawLKoDs%2BT%2BQLIV8B6B4Q9itA
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    Dataset updated
    Jun 12, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jun 2024
    Area covered
    Worldwide
    Description

    As of June 2024, the most popular commercial database management system (DBMS) in the world was Oracle, with a ranking score of 1244. MySQL was the most popular open source DBMS at that time, with a ranking score of 1061.

  3. d

    Assessor - Commercial Valuation Data

    • catalog.data.gov
    • datacatalog.cookcountyil.gov
    • +1more
    Updated Apr 12, 2025
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    datacatalog.cookcountyil.gov (2025). Assessor - Commercial Valuation Data [Dataset]. https://catalog.data.gov/dataset/assessor-commercial-valuation-data
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    Dataset updated
    Apr 12, 2025
    Dataset provided by
    datacatalog.cookcountyil.gov
    Description

    Commercial valuation data collected and maintained by the Cook County Assessor's Office, from 2021 to present. The office uses this data primarily for valuation and reporting. This dataset consolidates the individual Excel workbooks available on the Assessor's website into a single shared format. Properties are valued using similar valuation methods within each model group, per township, per year (in the year the township is reassessed). This dataset has been cleaned minimally, only enough to fit the source Excel workbooks together - because models are updated for each township in the year it is reassessed, users should expect inconsistencies within columns across time and townships. When working with Parcel Index Numbers (PINs) make sure to zero-pad them to 14 digits. Some datasets may lose leading zeros for PINs when downloaded. This data is property-level. Each 14-digit key PIN represents one commercial property. Commercial properties can and often do encompass multiple PINs. Additional notes: Current property class codes, their levels of assessment, and descriptions can be found on the Assessor's website. Note that class codes details can change across time. Data will be updated yearly, once the Assessor has finished mailing first pass values. If users need more up-to-date information they can access it through the Assessor's website. The Assessor's Office reassesses roughly one third of the county (a triad) each year. For commercial valuations, this means each year of data only contain the triad that was reassessed that year. Which triads and their constituent townships have been reassessed recently as well the year of their reassessment can be found in the Assessor's assessment calendar. One KeyPIN is one Commercial Entity. Each KeyPIN (entity) can be comprised of one single PIN (parcel), or multiple PINs as designated in the pins column. Additionally, each KeyPIN might have multiple rows if it is associated with different class codes or model groups. This can occur because many of Cook County's parcels have multiple class codes associated with them if they have multiple uses (such as residential and commercial). Users should not expect this data to be unique by any combination of available columns. Commercial properties are calculated by first determining a property’s use (office, retail, apartments, industrial, etc.), then the property is grouped with similar or like-kind property types. Next, income generated by the property such as rent or incidental income streams like parking or advertising signage is examined. Next, market-level vacancy based on location and property type is examined. In addition, new construction that has not yet been leased is also considered. Finally, expenses such as property taxes, insurance, repair and maintenance costs, property management fees, and service expenditures for professional services are examined. Once a snapshot of a property’s income statement is captured based on market data, a standard valuation metric called a “capitalization rate” to convert income to value is applied. This data was used to produce initial valuations mailed to property owners. It does not incorporate any subsequent changes to a property’s class, characteristics, valuation, or assessed value from appeals.Township codes can be found in the legend of this map. For more information on the sourcing of attached data and the preparation of this datase

  4. d

    Commercial Landings Data monthly summaries (Dealers)

    • catalog.data.gov
    • fisheries.noaa.gov
    Updated Jul 2, 2024
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    (Point of Contact, Custodian) (2024). Commercial Landings Data monthly summaries (Dealers) [Dataset]. https://catalog.data.gov/dataset/commercial-landings-data-monthly-summaries-dealers
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    Dataset updated
    Jul 2, 2024
    Dataset provided by
    (Point of Contact, Custodian)
    Description

    This data set contains pounds and value for all seafood products that are landed and sold by established seafood dealers and brokers in the SE Region of the US mainland. In the US Caribbean, the landings are reported by permitted fishers. These types of data, referred to as the general canvass landings statistics, have been collected by the NOAA Fisheries Service, National Marine Fisheries Service and its predecessor agency, the Bureau of Commercial Fisheries. These data are available on computer since the mid 1920s. The quantities and values that are reported in this data set include monthly landings that were initiated in 1972. Between 1926 and 1971, data were collected annually and not monthly. Mixed annual and monthly data occur from 1972-1976 according to State and year. The general canvass landings include quantities and value for all commercially caught marine species and are identified by species or species group. These data are collected from or reported by every seafood dealer or broker that is licensed by each state in the Southeast Region (North Carolina through Texas). In addition, information on the gear and area of capture is available for most of the landings statistics in the data set except for Florida 1977-1996 and Louisiana 1992-1999. However, because these data are summaries, they do not contain information on the quantities of fishing effort or identifications of the fishermen or vessels that caught the fish or shellfish. In early years, these data were collected by field agents employed by the Southeast Fisheries Science Center and assigned to local fishing ports. These individuals would canvass the seafood dealers and record the quantity and value for each species or species category from the sales receipts maintained by the seafood dealers. Based on their detailed knowledge of the fishing activity in the area, the agents would estimate the type of fishing gear and area where the fishing was likely to have occurred. It should be noted that landings by gear and water body (fishing area) does not reside in the monthly landings data set for Florida for the years, 1977-1995, Louisiana 1990-1999, and Texas (for gear) from 1993 to present (this is subject to change for years 2008 and more recent). Annual landings by gear, water body and distance from shore are available in the Annual General Canvass data for Florida. More detailed information on the caveats associated with these data is provided in the Issues section. In more recent years, the states in the Southeast Region began to implement trip ticket programs that required the licensed seafood dealer/brokers to report the landings of all seafood products. A trip ticket program was initiated in Florida in 1985, in North Carolina in 1994, in Louisiana in 1999, in Alabama in 2000, and in Texas in 2007. In addition to the quantities of these landings, the states require dealers to report the price, the type of gear and the fishing area for each trip. Through cooperative agreements with each of the states, monthly summaries of the states trip ticket programs are provided to the Southeast Fisheries Science Center (SEFSC) and are included in the general canvass landings data set. In addition, summarized data are extracted from the NOAA-SEFSC Gulf Shrimp System for commercial landings of shrimp species that are landed at port in the coastal area of the Gulf of Mexico.

  5. O

    Commercial Parking Lots

    • data.montgomerycountymd.gov
    • datadiscoverystudio.org
    • +2more
    application/rdfxml +5
    Updated Jul 1, 2025
    + more versions
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    Montgomery County, MD (2025). Commercial Parking Lots [Dataset]. https://data.montgomerycountymd.gov/Consumer-Housing/Commercial-Parking-Lots/weic-kzbi
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    csv, xml, tsv, application/rssxml, application/rdfxml, jsonAvailable download formats
    Dataset updated
    Jul 1, 2025
    Dataset authored and provided by
    Montgomery County, MD
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    Names of parking lot owners and inventory Update Frequency: Semi-Annually

  6. C

    Commercial Patent Database Report

    • marketresearchforecast.com
    doc, pdf, ppt
    Updated Feb 21, 2025
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    Market Research Forecast (2025). Commercial Patent Database Report [Dataset]. https://www.marketresearchforecast.com/reports/commercial-patent-database-26415
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    pdf, doc, pptAvailable download formats
    Dataset updated
    Feb 21, 2025
    Dataset authored and provided by
    Market Research Forecast
    License

    https://www.marketresearchforecast.com/privacy-policyhttps://www.marketresearchforecast.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    Market Analysis for Commercial Patent Database The global commercial patent database market size is projected to reach USD XXX million by 2033, exhibiting a CAGR of XX% from 2025 to 2033. Rising demand for patent protection and analysis, coupled with the increasing complexity of patent landscapes, fuels market growth. Additionally, government initiatives and incentives to promote innovation and technological advancements contribute to the industry's expansion. Key market drivers include the growing awareness of intellectual property rights and the need for companies to protect their innovations. The emergence of new technologies, such as artificial intelligence (AI) and machine learning (ML), enhances the accessibility and efficiency of patent searches and analysis, further stimulating market demand. However, factors such as copyright and patent infringement concerns and the high cost of maintaining databases may hinder market expansion. Nevertheless, the continuous evolution of patent laws and regulations and the globalization of the patent system present opportunities for market participants.

  7. r

    MarketScan Commercial Database

    • redivis.com
    • stanford.redivis.com
    Updated Aug 15, 2018
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    (2018). MarketScan Commercial Database [Dataset]. http://doi.org/10.57761/2wqj-ph37
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    Dataset updated
    Aug 15, 2018
    Description

    null This dataset was created on Thu, 26 Oct 2017 04:04:33 GMT.

  8. p

    Commercial Agents in León, Spain - 12 Verified Listings Database

    • poidata.io
    csv, excel, json
    Updated Jul 6, 2025
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    Poidata.io (2025). Commercial Agents in León, Spain - 12 Verified Listings Database [Dataset]. https://www.poidata.io/report/commercial-agent/spain/leon
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    csv, json, excelAvailable download formats
    Dataset updated
    Jul 6, 2025
    Dataset provided by
    Poidata.io
    Area covered
    León, Spain
    Description

    Comprehensive dataset of 12 Commercial agents in León, Spain as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

  9. F

    Commercial Real Estate Prices for United States

    • fred.stlouisfed.org
    json
    Updated Apr 1, 2025
    + more versions
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    (2025). Commercial Real Estate Prices for United States [Dataset]. https://fred.stlouisfed.org/series/COMREPUSQ159N
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    jsonAvailable download formats
    Dataset updated
    Apr 1, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-citation-requiredhttps://fred.stlouisfed.org/legal/#copyright-citation-required

    Area covered
    United States
    Description

    Graph and download economic data for Commercial Real Estate Prices for United States (COMREPUSQ159N) from Q1 2005 to Q3 2024 about real estate, commercial, rate, and USA.

  10. f

    Pair-wise Comparison Matrix for Commercial Database.

    • plos.figshare.com
    xls
    Updated Jun 1, 2023
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    Reza Vaziri; Mehran Mohsenzadeh; Jafar Habibi (2023). Pair-wise Comparison Matrix for Commercial Database. [Dataset]. http://doi.org/10.1371/journal.pone.0154508.t012
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    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Reza Vaziri; Mehran Mohsenzadeh; Jafar Habibi
    License

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

    Description

    Pair-wise Comparison Matrix for Commercial Database.

  11. China CN: Real Estate Investment: Commercial Building: Anhui

    • ceicdata.com
    Updated Feb 15, 2025
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    CEICdata.com (2025). China CN: Real Estate Investment: Commercial Building: Anhui [Dataset]. https://www.ceicdata.com/en/china/real-estate-investment-commercial-building/cn-real-estate-investment-commercial-building-anhui
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    Dataset updated
    Feb 15, 2025
    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    Dec 1, 2012 - Dec 1, 2023
    Area covered
    China
    Variables measured
    Real Estate Investment
    Description

    Real Estate Investment: Commercial Building: Anhui data was reported at 35,627.570 RMB mn in 2023. This records a decrease from the previous number of 51,792.600 RMB mn for 2022. Real Estate Investment: Commercial Building: Anhui data is updated yearly, averaging 26,422.390 RMB mn from Dec 1995 (Median) to 2023, with 28 observations. The data reached an all-time high of 102,586.200 RMB mn in 2015 and a record low of 626.370 RMB mn in 1995. Real Estate Investment: Commercial Building: Anhui data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Real Estate Sector – Table CN.RKA: Real Estate Investment: Commercial Building.

  12. Commercial Reference Building: Warehouse

    • data.openei.org
    • s.cnmilf.com
    • +1more
    data, image_document +1
    Updated Nov 25, 2014
    + more versions
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    Michael Deru; Kristin Field; Daniel Studer; Kyle Benne; Brent Griffith; Paul Torcellini; Bing Liu; Mark Halverson; Dave Winiarski; Michael Rosenberg; Mehry Yazdanian; Joe Huang; Drury Crawley; Michael Deru; Kristin Field; Daniel Studer; Kyle Benne; Brent Griffith; Paul Torcellini; Bing Liu; Mark Halverson; Dave Winiarski; Michael Rosenberg; Mehry Yazdanian; Joe Huang; Drury Crawley (2014). Commercial Reference Building: Warehouse [Dataset]. https://data.openei.org/submissions/171
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    website, data, image_documentAvailable download formats
    Dataset updated
    Nov 25, 2014
    Dataset provided by
    United States Department of Energyhttp://energy.gov/
    Office of Energy Efficiency and Renewable Energyhttp://energy.gov/eere
    National Renewable Energy Laboratory
    Open Energy Data Initiative (OEDI)
    Authors
    Michael Deru; Kristin Field; Daniel Studer; Kyle Benne; Brent Griffith; Paul Torcellini; Bing Liu; Mark Halverson; Dave Winiarski; Michael Rosenberg; Mehry Yazdanian; Joe Huang; Drury Crawley; Michael Deru; Kristin Field; Daniel Studer; Kyle Benne; Brent Griffith; Paul Torcellini; Bing Liu; Mark Halverson; Dave Winiarski; Michael Rosenberg; Mehry Yazdanian; Joe Huang; Drury Crawley
    License

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

    Description

    Commercial reference buildings provide complete descriptions for whole building energy analysis using EnergyPlus (see "About EnergyPlus" resource link) simulation software. Included here is data pertaining to the reference building type "Warehouse" for each of the 16 climate zones described on the Wiki page (see "OpenEI Wiki Page for Commercial Reference Buildings" resource link), and each of three construction categories: new (2004) construction, post-1980 construction existing buildings, and pre-1980 construction existing buildings.

    The dataset includes four key components: building summary, zone summary, location summary and a picture. Building summary includes details about: form, fabric, and HVAC. Zone summary includes details such as: area, volume, lighting, and occupants for all types of zones in the building. Location summary includes key building information as it pertains to each climate zone, including: fabric and HVAC details, utility costs, energy end use, and peak energy demand.

    In total, DOE developed 16 reference building types that represent approximately 70% of commercial buildings in the U.S.; for each type, building models are available for each of the three construction categories. The commercial reference buildings (formerly known as commercial building benchmark models) were developed by the U.S. Department of Energy (DOE), in conjunction with three of its national laboratories.

    Additional data is available directly from DOE's Energy Efficiency & Renewable Energy (EERE) website (see "About Commercial Buildings" resource link), including EnergyPlus software input files (.idf) and results of the EnergyPlus simulations (.html).

    Note: There have been many changes and improvements since this dataset was released. Several revisions have been made to the models and moved to a different approach to representing typical building energy consumption. For current data on building energy consumption please see the ComStock resource below.

  13. d

    USVI commercial fisheries cost data

    • catalog.data.gov
    • s.cnmilf.com
    • +1more
    Updated Apr 1, 2024
    + more versions
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    (Point of Contact, Custodian) (2024). USVI commercial fisheries cost data [Dataset]. https://catalog.data.gov/dataset/usvi-commercial-fisheries-cost-data1
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    Dataset updated
    Apr 1, 2024
    Dataset provided by
    (Point of Contact, Custodian)
    Area covered
    U.S. Virgin Islands
    Description

    To assist the Caribbean Fishery Management Council in managing marine living resources in the United States Virgin Islands, the Southeast Fisheries Science Center (SEFSC) collected economic cost data from commercial fishermen in July 2014. Surveys were administered in-person during the annual registration process. Per-trip and fixed cost estimates are included. This data set includes survey results merged with individual landings from the territorial governments logbook program. Summary results and forms can be found at http://www.sefsc.noaa.gov/socialscience/CrossonUSVI2015.htm

  14. d

    Commercial Permits

    • catalog.data.gov
    • data.montgomerycountymd.gov
    • +2more
    Updated Jun 29, 2025
    + more versions
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    data.montgomerycountymd.gov (2025). Commercial Permits [Dataset]. https://catalog.data.gov/dataset/commercial-permits
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    Dataset updated
    Jun 29, 2025
    Dataset provided by
    data.montgomerycountymd.gov
    Description

    Data for all Commercial Building Permits issued since 2000, including status and work performed. Update Frequency: Daily

  15. d

    Tax Administration's Real Estate - Commercial Data

    • catalog.data.gov
    • data.virginia.gov
    • +3more
    Updated Apr 22, 2023
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    County of Fairfax (2023). Tax Administration's Real Estate - Commercial Data [Dataset]. https://catalog.data.gov/dataset/tax-administrations-real-estate-commercial-data-27d50
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    Dataset updated
    Apr 22, 2023
    Dataset provided by
    County of Fairfax
    Description

    This table contains information about commercial properties including number of stories, elevators, exterior wall type, floor type and roof type for commercial properties within Fairfax County. There is a one to many relationship to the parcel data. Refer to this document for descriptions of the data in the table.

  16. F

    Total Construction Spending: Commercial in the United States

    • fred.stlouisfed.org
    json
    Updated Jul 1, 2025
    + more versions
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    (2025). Total Construction Spending: Commercial in the United States [Dataset]. https://fred.stlouisfed.org/series/TLCOMCONS
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    jsonAvailable download formats
    Dataset updated
    Jul 1, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    United States
    Description

    Graph and download economic data for Total Construction Spending: Commercial in the United States (TLCOMCONS) from Jan 2002 to May 2025 about expenditures, commercial, construction, and USA.

  17. United States Commercial Paper Outstanding: Non Financial: Foreign

    • ceicdata.com
    Updated Apr 1, 2018
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    CEICdata.com (2018). United States Commercial Paper Outstanding: Non Financial: Foreign [Dataset]. https://www.ceicdata.com/en/united-states/commercial-paper-outstanding/commercial-paper-outstanding-non-financial-foreign
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    Dataset updated
    Apr 1, 2018
    Dataset provided by
    CEIC Data
    License

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

    Time period covered
    May 1, 2017 - Apr 1, 2018
    Area covered
    United States
    Variables measured
    Amount of Securities Outstanding
    Description

    United States Commercial Paper Outstanding: Non Financial: Foreign data was reported at 60.289 USD bn in Jun 2018. This records a decrease from the previous number of 71.377 USD bn for May 2018. United States Commercial Paper Outstanding: Non Financial: Foreign data is updated monthly, averaging 33.883 USD bn from Jan 2001 (Median) to Jun 2018, with 210 observations. The data reached an all-time high of 71.377 USD bn in May 2018 and a record low of 11.870 USD bn in Jun 2005. United States Commercial Paper Outstanding: Non Financial: Foreign data remains active status in CEIC and is reported by Federal Reserve Board. The data is categorized under Global Database’s USA – Table US.Z034: Commercial Paper Outstanding.

  18. Commercial (Comm) Radio Occultation (RO) Raw Data Record (RDR) from Spire...

    • catalog.data.gov
    • datasets.ai
    • +1more
    Updated Sep 19, 2023
    + more versions
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    NOAA National Centers for Environmental Information (Point of Contact) (2023). Commercial (Comm) Radio Occultation (RO) Raw Data Record (RDR) from Spire Global Subsidiary [Dataset]. https://catalog.data.gov/dataset/commercial-comm-radio-occultation-ro-raw-data-record-rdr-from-spire-global-subsidiary1
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    Dataset updated
    Sep 19, 2023
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    National Centers for Environmental Informationhttps://www.ncei.noaa.gov/
    Description

    This dataset contains Commercial (Comm) Radio Occultation (RO) raw data from Spire Global Subsidiary, which is an established method for remote sounding of the atmosphere. The technique uses an instrument in low-Earth orbit (LEO) to track radio signals from Global Navigation Satellite System (GNSS) transmitters as they rise or set through the atmosphere. The occulting atmosphere refracts or bends the radio signals, and given the precise positions of both satellites, the bending angle can be deduced from the time delay of the signal. Collecting these measurements for a full occultation through the atmosphere provides a vertical profile of bending angles, from which profiles of physical quantities such as temperature, humidity, and ionospheric electron density can be retrieved. These data primarily feed numerical weather prediction (NWP) models that support weather forecasts, and also support space weather analysis/prediction at NOAA.

  19. d

    DSNY Commercial Waste Zones

    • catalog.data.gov
    • data.cityofnewyork.us
    • +1more
    Updated Jun 29, 2025
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    data.cityofnewyork.us (2025). DSNY Commercial Waste Zones [Dataset]. https://catalog.data.gov/dataset/dsny-planned-commercial-waste-zones
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    Dataset updated
    Jun 29, 2025
    Dataset provided by
    data.cityofnewyork.us
    Description

    While the NYC Department of Sanitation (DSNY) collects trash, recycling, and compostable material from residents, businesses are required to hire private carters to collect their waste. Following significant planning, analysis, and contract development, DSNY is overhauling the City's commercial waste industry mandated under Local Law 199 of 2019 to make our City cleaner and safer. Commercial Waste Zones create a regulatory framework that establishes new safety standards for workers in the commercial carting industry, improving service for businesses, and reducing harmful emissions from waste hauling vehicles. DSNY has broken the five boroughs into 20 Commercial Waste Zones and authorized three carters to offer curbside services in each zone. For more information, see: https://www.nyc.gov/site/dsny/businesses/commercial-waste-zones.page

  20. d

    2014: ECAD Commercial Reported Data

    • catalog.data.gov
    • datahub.austintexas.gov
    • +3more
    Updated Apr 25, 2025
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    data.austintexas.gov (2025). 2014: ECAD Commercial Reported Data [Dataset]. https://catalog.data.gov/dataset/2014-ecad-commercial-reported-data
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    Dataset updated
    Apr 25, 2025
    Dataset provided by
    data.austintexas.gov
    Description

    This report is the result of the Austin City Code 6-7’s Energy Conservation Audit and Disclosure Ordinance approved in November 2008 (amended in April 2011) to improve the energy efficiency of homes and buildings that receive electricity from Austin Energy. The ordinance meets one of the goals of the Austin Climate Protection Plan, which is to offset 800 megawatts of peak energy demand by 2020. This report contains information on commercial facilities that have reported the EPA’s Energy Star Portfolio Manager benchmarking results in 2014 () to the City of Austin, as well as the calculated electric Energy Utilization Index (EUI). For information on ECAD exemptions and other requirements, see Austin City Code Chapter 6-7. Note – () Data reported by Commercial Customers

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Northeast Fisheries Science Center (2017). Commercial Fisheries Database Biological Sample (CFDBS) [Dataset]. https://www.fisheries.noaa.gov/inport/item/27401
Organization logo

Commercial Fisheries Database Biological Sample (CFDBS)

Commercial Fisheries Database Biological Sample (CFDBS)

Explore at:
2 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jul 11, 2017
Dataset provided by
Northeast Fisheries Science Center
Time period covered
1963 - Jul 17, 2125
Area covered
Description

Age and length frequency data for finfish and invertebrate species collected during commercial fishing vessels. Samples are collected by fisheries reporting specialist from fish dealers in ports along the northwest Atlantic Ocean from Maine to North Carolina.

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