This dataset contains two tables: creative_stats and removed_creative_stats. The creative_stats table contains information about advertisers that served ads in the European Economic Area or Turkey: their legal name, verification status, disclosed name, and location. It also includes ad specific information: impression ranges per region (including aggregate impressions for the European Economic Area), first shown and last shown dates, which criteria were used in audience selection, the format of the ad, the ad topic and whether the ad is funded by Google Ad Grants program. A link to the ad in the Google Ads Transparency Center is also provided. The removed_creative_stats table contains information about ads that served in the European Economic Area that Google removed: where and why they were removed and per-region information on when they served. The removed_creative_stats table also contains a link to the Google Ads Transparency Center for the removed ad. Data for both tables updates periodically and may be delayed from what appears on the Google Ads Transparency Center website. About BigQuery This data is hosted in Google BigQuery for users to easily query using SQL. Note that to use BigQuery, users must have a Google account and create a GCP project. This public dataset is included in BigQuery's 1TB/mo of free tier processing. Each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery . Download Dataset This public dataset is also hosted in Google Cloud Storage here and available free to use. Use this quick start guide to quickly learn how to access public datasets on Google Cloud Storage. We provide the raw data in JSON format, sharded across multiple files to support easier download of the large dataset. A README file which describes the data structure and our Terms of Service (also listed below) is included with the dataset. You can also download the results from a custom query. See here for options and instructions. Signed out users can download the full dataset by using the gCloud CLI. Follow the instructions here to download and install the gCloud CLI. To remove the login requirement, run "$ gcloud config set auth/disable_credentials True" To download the dataset, run "$ gcloud storage cp gs://ads-transparency-center/* . -R" This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery .

The AlphaFold Protein Structure Database is a collection of protein structure predictions made using the machine learning model AlphaFold. AlphaFold was developed by DeepMind , and this database was created in partnership with EMBL-EBI . For information on how to interpret, download and query the data, as well as on which proteins are included / excluded, and change log, please see our main dataset guide and FAQs . To interactively view individual entries or to download proteomes / Swiss-Prot please visit https://alphafold.ebi.ac.uk/ . The current release aims to cover most of the over 200M sequences in UniProt (a commonly used reference set of annotated proteins). The files provided for each entry include the structure plus two model confidence metrics (pLDDT and PAE). The files can be found in the Google Cloud Storage bucket gs://public-datasets-deepmind-alphafold-v4 with metadata in the BigQuery table bigquery-public-data.deepmind_alphafold.metadata . If you use this data, please cite: Jumper, J et al. Highly accurate protein structure prediction with AlphaFold. Nature (2021) Varadi, M et al. AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models. Nucleic Acids Research (2021) This public dataset is hosted in Google Cloud Storage and is available free to use. Use this quick start guide to quickly learn how to access public datasets on Google Cloud Storage.

The Metropolitan Museum of Art, better known as the Met, provides a public domain dataset with over 200,000 objects including metadata and images. In early 2017, the Met debuted their Open Access policy to make part of their collection freely available for unrestricted use under the Creative Commons Zero designation and their own terms and conditions. This dataset provides a new view to one of the world’s premier collections of fine art. The data includes both image in Google Cloud Storage, and associated structured data in two BigQuery two tables, objects and images (1:N). Locations to images on both The Met’s website and in Google Cloud Storage are available in the BigQuery table. The meta data for this public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery . The image data for this public dataset is hosted in Google Cloud Storage and available free to use. Use this quick start guide to quickly learn how to access public datasets on Google Cloud Storage.

The High-Resolution Rapid Refresh (HRRR) is a NOAA real-time 3-km resolution, hourly updated, cloud-resolving, convection-allowing atmospheric model, initialized by 3km grids with 3km radar assimilation. Radar data is assimilated in the HRRR every 15 min over a 1-h period adding further detail to that provided by the hourly data assimilation from the 13km radar-enhanced Rapid Refresh. For more information, see the HRRR Info Page from NOAA ESRL. In addition to the real-time data that is continuously updated, archived data is now available for HRRR forecasts. This data dates back as far as 2014, and is one of the most complete publicly-available archives of HRRR data. This dataset includes a Pub/Sub topic you can subscribe to in order to be notified of updates. Subscribe to the topic 'projects/gcp-public-data-weather/topics/gcp-public-data-hrrr'. Use the Pub/Sub Quickstarts guide to learn more. This public dataset is hosted in Google Cloud Storage and available free to use. Use this quick start guide to quickly learn how to access public datasets on Google Cloud Storage.

This dataset includes raw submitted files, and the Variant Calling Format (VCF) files for SARS-CoV-2. The VCFs are a product of the NCBI SARS-CoV-2 Variant Calling Pipeline. Sequence data includes Coronaviridae (CoV) content identified by a kmer-based approach to organismal content identification using SRA Taxonomy Analysis Tool This public dataset is hosted in Google Cloud Storage and available free to use. Use this quick start guide to learn how to access public datasets on Google Cloud Storage. NCBI has also made SRA data available in BigQuery via the annotated variations table to find programmatically find datasets . This public dataset is hosted in BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery .

GOES-17 (Geostationary Operational Environmental Satellite) is the second in the GOES-R series that promises significant upgrades in observing environmental phenomena. It provides images of weather patterns and severe storms as frequently as every 30 seconds, which supports more accurate and reliable weather forecasts and severe weather outlooks. The dataset includes a feed of the Advanced Baseline Imager (ABI) radiance data (Level 1b) and Cloud and Moisture Imager (CMI) products (Level 2). The NOAA Big Data Project (BDP) is an experimental collaboration between NOAA and infrastructure-as-a-service (IaaS) providers to explore methods of expanding the accessibility of NOAA’s data to facilitate innovation and collaboration. The goal is to help form new lines of business and facilitate economic growth while making NOAA's data more easily discoverable for the American public. This public dataset is hosted in Google Cloud Storage and available free to use. Click the "view dataset" button at the top to access the raw NetCDF files in Cloud Storage. Check out this quick start guide to learn how to access public datasets on Google Cloud Storage. This dataset includes a Pub/Sub topic you can subscribe to in order to be notified of updates. Subscribe to the topic 'projects/gcp-public-data---goes-17/topics/gcp-public-data-goes-17'. Use the Pub/Sub Quickstarts guide to learn more.