http://opendatacommons.org/licenses/dbcl/1.0/http://opendatacommons.org/licenses/dbcl/1.0/
Adapted from Wikipedia: OpenStreetMap (OSM) is a collaborative project to create a free editable map of the world. Created in 2004, it was inspired by the success of Wikipedia and more than two million registered users who can add data by manual survey, GPS devices, aerial photography, and other free sources.
To aid researchers, data scientists, and analysts in the effort to combat COVID-19, Google is making a hosted repository of public datasets including OpenStreetMap data, free to access. To facilitate the Kaggle community to access the BigQuery dataset, it is onboarded to Kaggle platform which allows querying it without a linked GCP account. Please note that due to the large size of the dataset, Kaggle applies a quota of 5 TB of data scanned per user per 30-days.
This is the OpenStreetMap (OSM) planet-wide dataset loaded to BigQuery.
Tables:
- history_*
tables: full history of OSM objects.
- planet_*
tables: snapshot of current OSM objects as of Nov 2019.
The history_*
and planet_*
table groups are composed of node, way, relation, and changeset tables. These contain the primary OSM data types and an additional changeset corresponding to OSM edits for convenient access. These objects are encoded using the BigQuery GEOGRAPHY data type so that they can be operated upon with the built-in geography functions to perform geometry and feature selection, additional processing.
You can read more about OSM elements on the OSM Wiki. This dataset uses BigQuery GEOGRAPHY datatype which supports a set of functions that can be used to analyze geographical data, determine spatial relationships between geographical features, and construct or manipulate GEOGRAPHYs.
Open Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
License information was derived automatically
Adapted from Wikipedia: OpenStreetMap (OSM) is a collaborative project to create a free editable map of the world. Created in 2004, it was inspired by the success of Wikipedia and more than two million registered users who can add data by manual survey, GPS devices, aerial photography, and other free sources. We've made available a number of tables (explained in detail below): history_* tables: full history of OSM objects planet_* tables: snapshot of current OSM objects as of Nov 2019 The history_* and planet_* table groups are composed of node, way, relation, and changeset tables. These contain the primary OSM data types and an additional changeset corresponding to OSM edits for convenient access. These objects are encoded using the BigQuery GEOGRAPHY data type so that they can be operated upon with the built-in geography functions to perform geometry and feature selection, additional processing. Example analyses are given below. This dataset is part of a larger effort to make data available in BigQuery through the Google Cloud Public Datasets program . OSM itself is produced as a public good by volunteers, and there are no guarantees about data quality. Interested in learning more about how these data were brought into BigQuery and how you can use them? Check out the sample queries below to get started. 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 .
Attribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
License information was derived automatically
ChEMBL is maintained by the European Bioinformatics Institute (EBI), of the European Molecular Biology Laboratory (EMBL), based at the Wellcome Trust Genome Campus, Hinxton, UK.
ChEMBL is a manually curated database of bioactive molecules with drug-like properties used in drug discovery, including information about existing patented drugs.
Schema: http://ftp.ebi.ac.uk/pub/databases/chembl/ChEMBLdb/releases/chembl_23/chembl_23_schema.png
Documentation: http://ftp.ebi.ac.uk/pub/databases/chembl/ChEMBLdb/releases/chembl_23/schema_documentation.html
Fork this notebook to get started on accessing data in the BigQuery dataset using the BQhelper package to write SQL queries.
“ChEMBL” by the European Bioinformatics Institute (EMBL-EBI), used under CC BY-SA 3.0. Modifications have been made to add normalized publication numbers.
Data Origin: https://bigquery.cloud.google.com/dataset/patents-public-data:ebi_chembl
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http://opendatacommons.org/licenses/dbcl/1.0/http://opendatacommons.org/licenses/dbcl/1.0/
Adapted from Wikipedia: OpenStreetMap (OSM) is a collaborative project to create a free editable map of the world. Created in 2004, it was inspired by the success of Wikipedia and more than two million registered users who can add data by manual survey, GPS devices, aerial photography, and other free sources.
To aid researchers, data scientists, and analysts in the effort to combat COVID-19, Google is making a hosted repository of public datasets including OpenStreetMap data, free to access. To facilitate the Kaggle community to access the BigQuery dataset, it is onboarded to Kaggle platform which allows querying it without a linked GCP account. Please note that due to the large size of the dataset, Kaggle applies a quota of 5 TB of data scanned per user per 30-days.
This is the OpenStreetMap (OSM) planet-wide dataset loaded to BigQuery.
Tables:
- history_*
tables: full history of OSM objects.
- planet_*
tables: snapshot of current OSM objects as of Nov 2019.
The history_*
and planet_*
table groups are composed of node, way, relation, and changeset tables. These contain the primary OSM data types and an additional changeset corresponding to OSM edits for convenient access. These objects are encoded using the BigQuery GEOGRAPHY data type so that they can be operated upon with the built-in geography functions to perform geometry and feature selection, additional processing.
You can read more about OSM elements on the OSM Wiki. This dataset uses BigQuery GEOGRAPHY datatype which supports a set of functions that can be used to analyze geographical data, determine spatial relationships between geographical features, and construct or manipulate GEOGRAPHYs.