This is a data product to support state indicators that are based from groundfish biological data, derived using primary data from surveys undertaken in the Northeast Atlantic between 1983 and 2020. Catch records by taxonomic group and by length category in terms of biomass and numbers of fish standardised to duration (per hour) or to the area swept by the haul. Data are available from multiple surveys using data downloaded from the ICES database of trawl surveys (DATRAS) once quality-controlled and standardised following procedures detailed in Greenstreet and Moriarty 2017. Data file names reflect the OSPAR region sampled, country conducting the sampling, fishing gear and time of years of sampling (as defined by Greenstreet and Moriarty 2017), e.g.: BBICFraBT4 refers to Bay of Biscay and Iberian Coast data from France by a Beam Trawl survey in quarter 4 of the year and GNSIntOT3 refers to Greater North Sea data from International (multiple countries) sampling by an Otter Trawl survey in quarter 3 of the year etc. Greenstreet, S.P.R. and Moriarty, M. (2017) OSPAR Interim Assessment 2107 Fish Indicator Data Manual (Relating to Version 2 of the Groundfish Survey Monitoring and Assessment Data Product). Scottish Marine and Freshwater Science Vol 8 No 17, 83pp. DOI: 10.7489/1985-1 Scientific survey data collected by multiple countries and made available through ICES DATRAS (https://www.ices.dk/data/data-portals/Pages/DATRAS.aspx). Swept-area estimates were generated by ICES 2021ab (ICES. 2021a. Workshop on the production of swept-area estimates for all hauls in DATRAS for biodiversity assessments (WKSAE-DATRAS). ICES Scientific Reports. 3:74. https://doi.org/10.17895/ices.pub.8232; ICES. 2021b. Workshop on the production of abundance estimates for sensitive species (WKABSENS); ICES Scientific Reports. 3:96. https://doi.org/10.17895/ices.pub.8299). ICES Data Centre host the database of trawl surveys (DATRAS) for groundfish and beam trawl data. DATRAS has an integrated quality check utility. All data, before entering the database, have to pass an extensive quality check. Despite this errors and missing data arise, which are subsequently dealt with by the data submitters from the contributing countries as required. However, this screening process was implemented in 2009 for data from 2004 onwards. Since some survey time-series extend back to the 1960s, historic data (unless re-evaluated and re-submitted by contributing countries) may not have been subject to the same level of quality control as these more recent data. Furthermore, the type of information collected, the level of detail and resolution in the data, has gradually evolved over time. In order to derive a single format, quality assured monitoring programme data product covering the entire Northeast Atlantic region inconsistencies in the datasets required resolution. These corrections are detailed in ICES 2021a,b: Biological data for trawl surveys are downloaded directly from DATRAS in raw exchange format (known as “HL data”). Ancillary data were processed by ICES 2021a,b to create the “SweptAreaAssessmentOutput” (which replaces the “HH data”) and these were downloaded from the same location: https://datras.ices.dk/Data _ products/Download/Download _ Data _ public.aspx Data are processed to create a standalone data product to be used for indicator assessments of fish and elasmobranchs. Initially, hauls are subset to determine the Standard Monitoring Programme (i.e. excluding invalid hauls including those of duration shorter than 13 minutes or longer than 66 minutes, following Greenstreet and Moriarty 2017) and these hauls are used to define the Standard Survey Area by excluding areas sampled infrequently over time). Biological data were accepted with ICES SpecVal of 1, 4, 7, 10 (see http://vocab.ices.dk/ for further information on SpecVal categories). Additional QA/QC is made at this step to determine if species identification issues are present in the raw biological data and these were discussed and agreed with the Chief Scientist for each survey.

Maximize your online sales potential with our e-commerce data and analytics solutions. Our comprehensive suite of data sources includes real-time information on market trends, consumer behavior, and product pricing. With our advanced analytics tools, you can unlock the power of data-driven insights to optimize your online sales strategy, improve customer engagement, and drive revenue growth.

Whether you want to identify new opportunities, streamline your operations, or stay ahead of the competition, our e-commerce data and analytics product can help you achieve your goals.

Sources: Cubus Official COS Boozt BIK BOK AS Royal Design Group Holding AB Bagaren och Kocken AB Rum21 Svenskt Tenn Kökets favoriter lannamobler.se KWA Garden furniture Confident Living Stalands Möbler Trendrum AB Svenssons Nordiska Galleriet Jotex Jollyroom Monki New Bubbleroom Sweden AB Wegot KitchenTime AB Lindex NA-KD.com Olsson & Gerthel Nordic Nest Bonprix Nederland Vero Moda Care of Carl Cervera Zoovillage ARKET Kappahl DesignTorget Mio AB Afound

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

Envestnet®| Yodlee®'s Consumer Transaction Data (Aggregate/Row) Panels consist of de-identified, near-real time (T+1) USA credit/debit/ACH transaction level data – offering a wide view of the consumer activity ecosystem. The underlying data is sourced from end users leveraging the aggregation portion of the Envestnet®| Yodlee®'s financial technology platform.

Envestnet | Yodlee Consumer Panels (Aggregate/Row) include data relating to millions of transactions, including ticket size and merchant location. The dataset includes de-identified credit/debit card and bank transactions (such as a payroll deposit, account transfer, or mortgage payment). Our coverage offers insights into areas such as consumer, TMT, energy, REITs, internet, utilities, ecommerce, MBS, CMBS, equities, credit, commodities, FX, and corporate activity. We apply rigorous data science practices to deliver key KPIs daily that are focused, relevant, and ready to put into production.

We offer free trials. Our team is available to provide support for loading, validation, sample scripts, or other services you may need to generate insights from our data.

Investors, corporate researchers, and corporates can use our data to answer some key business questions such as: - How much are consumers spending with specific merchants/brands and how is that changing over time? - Is the share of consumer spend at a specific merchant increasing or decreasing? - How are consumers reacting to new products or services launched by merchants? - For loyal customers, how is the share of spend changing over time? - What is the company’s market share in a region for similar customers? - Is the company’s loyal user base increasing or decreasing? - Is the lifetime customer value increasing or decreasing?

Additional Use Cases: - Use spending data to analyze sales/revenue broadly (sector-wide) or granular (company-specific). Historically, our tracked consumer spend has correlated above 85% with company-reported data from thousands of firms. Users can sort and filter by many metrics and KPIs, such as sales and transaction growth rates and online or offline transactions, as well as view customer behavior within a geographic market at a state or city level. - Reveal cohort consumer behavior to decipher long-term behavioral consumer spending shifts. Measure market share, wallet share, loyalty, consumer lifetime value, retention, demographics, and more.) - Study the effects of inflation rates via such metrics as increased total spend, ticket size, and number of transactions. - Seek out alpha-generating signals or manage your business strategically with essential, aggregated transaction and spending data analytics.

Use Cases Categories (Our data provides an innumerable amount of use cases, and we look forward to working with new ones): 1. Market Research: Company Analysis, Company Valuation, Competitive Intelligence, Competitor Analysis, Competitor Analytics, Competitor Insights, Customer Data Enrichment, Customer Data Insights, Customer Data Intelligence, Demand Forecasting, Ecommerce Intelligence, Employee Pay Strategy, Employment Analytics, Job Income Analysis, Job Market Pricing, Marketing, Marketing Data Enrichment, Marketing Intelligence, Marketing Strategy, Payment History Analytics, Price Analysis, Pricing Analytics, Retail, Retail Analytics, Retail Intelligence, Retail POS Data Analysis, and Salary Benchmarking

1. Investment Research: Financial Services, Hedge Funds, Investing, Mergers & Acquisitions (M&A), Stock Picking, Venture Capital (VC)

2. Consumer Analysis: Consumer Data Enrichment, Consumer Intelligence

3. Market Data: AnalyticsB2C Data Enrichment, Bank Data Enrichment, Behavioral Analytics, Benchmarking, Customer Insights, Customer Intelligence, Data Enhancement, Data Enrichment, Data Intelligence, Data Modeling, Ecommerce Analysis, Ecommerce Data Enrichment, Economic Analysis, Financial Data Enrichment, Financial Intelligence, Local Economic Forecasting, Location-based Analytics, Market Analysis, Market Analytics, Market Intelligence, Market Potential Analysis, Market Research, Market Share Analysis, Sales, Sales Data Enrichment, Sales Enablement, Sales Insights, Sales Intelligence, Spending Analytics, Stock Market Predictions, and Trend Analysis

This clean dataset is a refined version of our company datasets, consisting of 35M+ data records.

It’s an excellent data solution for companies with limited data engineering capabilities and those who want to reduce their time to value. You get filtered, cleaned, unified, and standardized B2B data. After cleaning, this data is also enriched by leveraging a carefully instructed large language model (LLM).

AI-powered data enrichment offers more accurate information in key data fields, such as company descriptions. It also produces over 20 additional data points that are very valuable to B2B businesses. Enhancing and highlighting the most important information in web data contributes to quicker time to value, making data processing much faster and easier.

For your convenience, you can choose from multiple data formats (Parquet, JSON, JSONL, or CSV) and select suitable delivery frequency (quarterly, monthly, or weekly).

Coresignal is a leading public business data provider in the web data sphere with an extensive focus on firmographic data and public employee profiles. More than 3B data records in different categories enable companies to build data-driven products and generate actionable insights. Coresignal is exceptional in terms of data freshness, with 890M+ records updated monthly for unprecedented accuracy and relevance.

The RSS SSM/I Ocean Product Grids Weekly Average from DMSP F14 netCDF dataset is part of the collection of Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager Sounder (SSMIS) data products produced as part of NASA's MEaSUREs Program. Remote Sensing Systems generates SSM/I and SSMIS binary data products using a unified, physically based algorithm to simultaneously retrieve ocean wind speed, water vapor, cloud water, and rain rate. The SSMIS data have been carefully intercalibrated to the brightness temperature level of the previous SSM/I and therefore extend this important time series of ocean winds, vapor, cloud and rain values. This algorithm is a product of 20 years of refinements, improvements, and verifications. The Global Hydrology Resource Center has reformatted the binary data into a netCDF data product for each temporal group for each satellite. The netCDF SSMI/SSMIS collection will be available for F14 for a weekly average.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

Data sets and related data products and services provided by SEDAC managed by the NASA Earth Science Data and Information System (ESDIS) project. SEDAC is one of the Earth Observing System Data and Information System (EOSDIS) Distributed Active Archive Centers (DAACs), part of the ESDIS project.

About SEDAC. http://sedac.ciesin.columbia.edu/about, Retrieved 27 Oct 2020.

SAMSN7L1RAD_CDROM is the gridded Nimbus-7 Stratospheric and Mesospheric Sounder (SAMS) Level 1 Radiance Data Product. The radiances were selected to derive gas concentrations at the wavelength bands 15 (CO2), 25-100 (H2O) 4-5 (CO and NO), and 7.7 (N2O and CH4) microns in the stratosphere and mesosphere, with a resolution of 100 km in the horizontal by 10 km in the vertical at the limb. This product contains radiances in a daily 2.5 degree latitude x 10 degree longitude grid format, gridded temperature profiles at 100, 30, 10, 3, 1, 0.3, 0.1, 0.03, 0.01 and 0.003 hPa, as well as the calibration, apriori and reformatted copies of the original tapes. The data for this product are available from 22 October 1978 through June 9 1983, with a few additional raw radiances to 16 April 1984. The principal investigators for the SAMS experiment were Prof. John T. Houghton and Dr. Fredric W. Taylor from Oxford University. This product was created by the Oxford University's Atmospheric, Oceanic and Planetary Physics (AOPP) group. The data are stored on a set of 53 CD-ROMs in ASCII files of hexadecimal characters, and are available in gzipped Unix tar archive files. The first CD-ROM contains the a-priori temperature profile, monthly mean retrieved temperature profile, pre-launch calibration, housekeeping and instrument subsystem status files. CD-ROMs 2-5 contain the gridded temperature data. CD-ROMs 6-22 contain the radiances from the C-series and G-series tapes, and CD-ROMs 34-53 contain the raw radiance values from the R-series tape. The byte-ordering in the data files follows the DEC convention for 16-bit integers of less significant byte first. Normal 2's complement integer storage is assumed.

DCOTSS-Balloon-Data features the balloon data collected during the Dynamics and Chemistry of the Summer Stratosphere sub-orbital campaign. DCOTSS-Ozone-H2O features balloon flights that include both ozone and water vapor trace gas measurements while DCOTSS-Ozone features balloons with only ozone measurements. Balloons were launched from the following locations: Boulder, CO; Salina, KS: Corpus Christi, TX; and Grand Forks, ND. Data collection for this product is ongoing and currently only features the first deployment. Each summer the North American Monsoon Anticyclone (NAMA) dominates the circulation of the North-Western Hemisphere and acts to partially confine and isolate air from the surrounding atmosphere. Strong convective storms in the NAMA regularly reach altitudes deep into the lower stratosphere, with some ascending above 20 km. These storms carry water and pollutants from the troposphere into the otherwise very dry stratosphere, where they can have a significant impact on radiative and chemical processes, potentially including destruction of stratospheric ozone. The Dynamics and Chemistry of the Summer Stratosphere (DCOTSS) field campaign is a NASA Earth Venture Suborbital research project aimed at investigating these thunderstorms. DCOTSS utilizes NASA’s ER-2 aircraft and conducted two ~8-week science deployments based out of Salina, KS spanning early to late summer.

IDEA Section 618 Data Products: Static Tables Part B Discipline Table 3 Number of children and students ages 3 through 21 served under IDEA, Part B, subject to disciplinary removal by total cumulative number of days removed during school year and state by type of disability.

The Lunar Reconnaissance Orbiter (LRO) Lyman Alpha Mapping Project (LAMP) CODMAC Level 2 Experiment Data Record is a collection of the far ultraviolet photon detections obtained by the LAMP instrument, in raw form. As such, it constitutes the permanent record of the raw LAMP data. These data include both the instrument science and housekeeping data, organized into extensions within files formatted according to the Flexible Image Transport System (FITS) standard, version 2.1b. The LAMP EDR archive enables reprocessing of the raw science data as radiometric and geometric calibration processing routines improve. Investigators interested in applying advanced calibration methods or needing to understand the properties of the raw data will find the EDR products useful. Most investigators, however, will be interested in using either the LAMP data products contained in the CODMAC Level 3 Reduced Data Record, as radiometric and geometric calibration processing has already been done for these products, or the LAMP CODMAC Level 5 far ultraviolet map products.

This zip folder contains data files described in Section 6 of Panopoulou & Lenz (2020) as well as a data usage tutorial written in Python.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

The SWOT Level 2 Radiometer Brightness Temperatures and Troposphere Geophysical Data Record (GDR) dataset produced by the Surface Water and Ocean Topography (SWOT) mission provides atmospheric water vapor and liquid water content from the Advanced Microwave Radiometer (AMR), a Jason-class radiometer that measures sea surface brightness temperatures at three microwave frequencies (18.7, 23.8 and 34 GHz). Brightness temperatures are processed to estimate the wet troposphere content, atmospheric attenuation to backscatter, cloud liquid water, water vapor content, and wind speed coincident with each range measurement from the nadir altimeter and applied to correct for altimeter range delays caused by atmospheric effects. SWOT is a joint mission between NASA and CNES that launched on December 16, 2022 and aims to measure ocean surface topography with unprecedented resolution and accuracy, as well as map inland water bodies globally. This radiometer dataset consists of discrete measurements along two tracks located approximately 30-km to the left and right of the satellite nadir. The data were processed using the Precise Orbit Ephemeris (POE) and analyzed calibrations. The data are available with latency of < 90 days and distributed in netCDF-4 file format.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

Altosight | AI Custom Web Scraping Data

✦ Altosight provides global web scraping data services with AI-powered technology that bypasses CAPTCHAs, blocking mechanisms, and handles dynamic content.

We extract data from marketplaces like Amazon, aggregators, e-commerce, and real estate websites, ensuring comprehensive and accurate results.

✦ Our solution offers free unlimited data points across any project, with no additional setup costs.

We deliver data through flexible methods such as API, CSV, JSON, and FTP, all at no extra charge.

― Key Use Cases ―

➤ Price Monitoring & Repricing Solutions

🔹 Automatic repricing, AI-driven repricing, and custom repricing rules 🔹 Receive price suggestions via API or CSV to stay competitive 🔹 Track competitors in real-time or at scheduled intervals

➤ E-commerce Optimization

🔹 Extract product prices, reviews, ratings, images, and trends 🔹 Identify trending products and enhance your e-commerce strategy 🔹 Build dropshipping tools or marketplace optimization platforms with our data

➤ Product Assortment Analysis

🔹 Extract the entire product catalog from competitor websites 🔹 Analyze product assortment to refine your own offerings and identify gaps 🔹 Understand competitor strategies and optimize your product lineup

➤ Marketplaces & Aggregators

🔹 Crawl entire product categories and track best-sellers 🔹 Monitor position changes across categories 🔹 Identify which eRetailers sell specific brands and which SKUs for better market analysis

➤ Business Website Data

🔹 Extract detailed company profiles, including financial statements, key personnel, industry reports, and market trends, enabling in-depth competitor and market analysis

🔹 Collect customer reviews and ratings from business websites to analyze brand sentiment and product performance, helping businesses refine their strategies

➤ Domain Name Data

🔹 Access comprehensive data, including domain registration details, ownership information, expiration dates, and contact information. Ideal for market research, brand monitoring, lead generation, and cybersecurity efforts

➤ Real Estate Data

🔹 Access property listings, prices, and availability 🔹 Analyze trends and opportunities for investment or sales strategies

― Data Collection & Quality ―

► Publicly Sourced Data: Altosight collects web scraping data from publicly available websites, online platforms, and industry-specific aggregators

► AI-Powered Scraping: Our technology handles dynamic content, JavaScript-heavy sites, and pagination, ensuring complete data extraction

► High Data Quality: We clean and structure unstructured data, ensuring it is reliable, accurate, and delivered in formats such as API, CSV, JSON, and more

► Industry Coverage: We serve industries including e-commerce, real estate, travel, finance, and more. Our solution supports use cases like market research, competitive analysis, and business intelligence

► Bulk Data Extraction: We support large-scale data extraction from multiple websites, allowing you to gather millions of data points across industries in a single project

► Scalable Infrastructure: Our platform is built to scale with your needs, allowing seamless extraction for projects of any size, from small pilot projects to ongoing, large-scale data extraction

― Why Choose Altosight? ―

✔ Unlimited Data Points: Altosight offers unlimited free attributes, meaning you can extract as many data points from a page as you need without extra charges

✔ Proprietary Anti-Blocking Technology: Altosight utilizes proprietary techniques to bypass blocking mechanisms, including CAPTCHAs, Cloudflare, and other obstacles. This ensures uninterrupted access to data, no matter how complex the target websites are

✔ Flexible Across Industries: Our crawlers easily adapt across industries, including e-commerce, real estate, finance, and more. We offer customized data solutions tailored to specific needs

✔ GDPR & CCPA Compliance: Your data is handled securely and ethically, ensuring compliance with GDPR, CCPA and other regulations

✔ No Setup or Infrastructure Costs: Start scraping without worrying about additional costs. We provide a hassle-free experience with fast project deployment

✔ Free Data Delivery Methods: Receive your data via API, CSV, JSON, or FTP at no extra charge. We ensure seamless integration with your systems

✔ Fast Support: Our team is always available via phone and email, resolving over 90% of support tickets within the same day

― Custom Projects & Real-Time Data ―

✦ Tailored Solutions: Every business has unique needs, which is why Altosight offers custom data projects. Contact us for a feasibility analysis, and we’ll design a solution that fits your goals

✦ Real-Time Data: Whether you need real-time data delivery or scheduled updates, we provide the flexibility to receive data when you need it. Track price changes, monitor product trends, or gather...

FLASH_TISA_Terra-NOAA20_Version4B is the Fast Longwave And SHortwave Fluxes (FLASHFlux) Daily Gridded Top-of-Atmosphere (TOA) and Surfaces/Clouds Version 4B data product. This product contains low latency (< 7 days from observations) combined Terra and NOAA-20 FLASHFlux Single Scanner Footprint (SSF) globally gridded TOA and parameterized surface radiative fluxes for applied science uses. Data collection for this product is in progress.FLASHFlux data are a product line of the Clouds and the Earth's Radiant Energy Systems (CERES) project designed to process and release TOA and surface radiative fluxes for applied sciences and education uses. The FLASHFlux data product is a rapid-release product based on the algorithms developed for and data collected by the CERES project. CERES is currently producing world-class climate data products derived from measurements taken aboard NASA's Terra, Aqua, and NOAA-20 spacecraft. While of exceptional fidelity, these data products require considerable processing time to assure quality, verify accuracy, and assess precision. The result is that CERES data are typically released up to six months after acquiring the initial measurements. Such delays are of little consequence for climate studies, especially considering the improved quality of the released data products. Thus, FLASHFlux products are not intended to achieve climate quality. FLASHFlux data products were envisioned as a resource whereby CERES data could be provided to the community within a few days of the initial measurements, with some calibration accuracy requirements relaxed to gain speed. The SSF TOA/Surface Fluxes and Clouds product contains one hour of instantaneous FLASHFlux data for a single CERES scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager, such as Moderate-Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites and meteorological and ozone information from The Goddard Earth Observing System (GEOS) GEOS-5 FP-IT Atmospheric Data Assimilation System (GEOS-5 ADAS). NOAA-20 SSF combines instantaneous CERES data with scene information from the Visible Infrared Imaging Radiometer Suite (VIIRS) with GEOS-5 ADAS. Scene identification and cloud properties are defined at the higher image resolution, and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains Top-of-Atmosphere fluxes in SW, LW, and NET, surface fluxes using the Langley parameterized shortwave and longwave algorithms, and cloud information. CERES is a key Earth Observing System (EOS) program component. The CERES instruments provide radiometric measurements of the Earth's atmosphere from three broadband channels. The CERES mission is a follow-up to the successful Earth Radiation Budget Experiment (ERBE) mission. The first CERES instrument (PFM) was launched on November 27, 1997, as part of the Tropical Rainfall Measuring Mission (TRMM). Two CERES instruments (FM1 and FM2) were launched into polar orbit on board the EOS flagship Terra on December 18, 1999. Two additional CERES instruments (FM3 and FM4) were launched on board EOS Aqua on May 4, 2002. CERES instrument Flight Model 5 (FM5) was launched on board the Suomi National Polar-orbiting Partnership (NPP) satellite and the CERES instrument (FM6) was launched on board NOAA's next generation of polar-orbiting satellites on November 18, 2017.

Elevate your Electric Vehicle (EV) development with Datatorq's comprehensive EV Data. We offer over 250 carefully curated and regularly updated data points, covering essential details like price, features, technical specifications, and dimensions.

Why choose Datatorq's Electric Vehicle (EV) Data? - Electric Vehicle (EV) Insights: Expert-curated data for optimal EV development and pricing. - Evolving Landscape: Stay ahead with in-depth insights. - Accurate Electric Vehicle (EV) Data: Clean, comprehensive, and up-to-date for confident decision-making. - Tailored Solutions: Get the exact Electric Vehicle (EV) data you need. - Monthly Updates: Stay current with the latest trends on the market.

Datatorq's expansive and precise Electric Vehicle (EV) datasets are designed to empower innovation and success in your EV product development and pricing strategies across Europe. Gain a competitive edge in France, UK, Italy, Poland, Netherlands, Spain, Belgium, Germany, Austria, Czechia, Portugal, Romania, Switzerland, Denmark, Norway, Slovenia, Sweden, and Ireland.