Create and manage a dataset

Datasets let you upload geospatial data from a local file or from Google Cloud Storage to the Google Maps Platform. You can then associate a dataset with one or more map styles in the Cloud Console. After associating the dataset with a maps style, use the data-driven styling API to dynamically style your maps application.

You can also use a REST API to upload your geospatial data to a dataset. For more information, see Maps Datasets API

Configure roles

To create and manage datasets in a Google Cloud project, you must hold either the Owner or Editor IAM role on the project.

Alternatively, you can assign the following IAM roles to a user account or service account that you use to manage datasets:

  • The Maps Platform Datasets Admin role grants the user or services account read/write access to datasets in the project. This role lets the user perform all operations on a dataset.
  • The Maps Platform Datasets Viewer role grants read-only access to datasets in the project. This role lets you perform a list, get, or download operation on a dataset.

For more information, see Grant an IAM role by using the Google Cloud console.

Data source for a dataset

After you create a dataset, upload the data to the dataset from Google Cloud Storage or from a local file.
  • When uploading data from Cloud Storage, specify the file path to the resource containing the data in Cloud Storage. This path is in the form gs://GCS_BUCKET/FILE.

    The user making the request requires the Storage Object Viewer role, or any other role that includes the storage.objects.get permission. For more information about managing access to Cloud Storage, see Overview of access control.

  • When uploading data from a local file, specify the path to the GeoJSON, KML, or CSV file containing the data to upload.


When creating a dataset:

  • Display names must be unique within your Google Cloud project.
  • Display names must be less than 64 bytes (Because these characters are represented in UTF-8, in some languages each character can be represented by multiple bytes).
  • Descriptions must be less than 1000 bytes.

When uploading data:

  • The supported file types are CSV, GeoJSON, and KML.
  • The maximum supported file size is 350 MB.
  • Attribute column names cannot begin with the string "?_".
  • Three-dimensional geometries are not supported. This includes the "Z" suffix in the WKT format, and the altitude coordinate in the GeoJSON format.

Data preparation best practices

If your source data is complex or large, such as dense points, long linestrings or polygons (often source file sizes larger than 50 MB fall into this category), consider simplifying your data before uploading to achieve the best performance in a visual map.

Here are some best practices for preparing your data:

  1. Minimize feature properties. Only keep feature properties needed to style your map, for example "id" and "category". You can join additional properties to a feature in a client application using data-driven styles on a unique identifier key. For example, see See your data in real time with Data-driven styling.
  2. Use simple data types for property objects where possible, such as integers, to minimize tile size and improve map performance.
  3. Simplify complex geometries prior to uploading a file. You can do this in a geospatial tool of your choice, such as the open source utility, or in BigQuery using ST_Simplify on complex polygon geometries.
  4. Cluster very dense points prior to uploading a file. You can do this in a geospatial tool of your choice, such as the open source turf.js cluster functions, or in BigQuery using ST_CLUSTERDBSCAN on dense point geometries.

See additional guidance about datasets best practices in Visualize your data with Datasets and BigQuery.

GeoJSON requirements

Maps JavaScript API supports the current GeoJSON specification. Maps JavaScript API also support GeoJSON files that contain any of the following object types:

  • Geometry objects. A geometry object is a spatial shape, described as a union of points, lines, and polygons with optional holes.
  • Feature objects. A feature object contains a geometry plus additional name/value pairs, whose meaning is application-specific.
  • Feature collections. A feature collection is a set of feature objects.

Maps JavaScript API does not support GeoJSON files that have data in a coordinate reference system (CRS) other than WGS84.

For more information on GeoJSON, see RFC 7946 compliant.

KML requirements

Maps JavaScript API has the following requirements:

  • All URLs must be local (or relative) to the file itself.
  • Point, line, and polygon geometries supported.
  • All data attributes are considered strings.
The following KML features are not supported:
  • Icons or <styleUrl> defined outside of the file.
  • Network links, such as <NetworkLink>
  • Ground overlays, such as <GroundOverlay>
  • 3D geometries or any altitude-related tags such as <altitudeMode>
  • Camera specifications such as <LookAt>
  • Styles defined inside the KML file.

CSV requirements

For CSV files, the supported column names are listed below in order of priority:

  • latitude, longitude
  • lat, long
  • x, y
  • wkt (Well-Known Text)
  • address, city, state, zip
  • address
  • A single column containing all address information, such as 1600 Amphitheatre Parkway Mountain View, CA 94043

For example, your file contains columns named x, y, and wkt. Because x and y have a higher priority, as determined by the order of supported column names in the list above, the values in the x and y columns are used and the wkt column is ignored.

In addition:

  • Each column name must belong to a single column. That is, you cannot have a column named xy that contains both x and y coordinate data. The x and y coordinates must be in separate columns.
  • Column names are case-insensitive.
  • The order of the column names does not matter. For example, if your CSV file contains lat and long columns, they can occur in any order.

Handle data upload errors

When uploading data to a dataset, you might experience one of the common errors described in this section.

GeoJSON errors

Common GeoJSON errors include:

  • Missing type field, or the type is not a string. The uploaded GeoJSON data file must contain a string field named type as part of each Feature object and Geometry object definition.

KML errors

Common KML errors include:

  • The data file must not contain any of the unsupported KML features listed above, otherwise the data import might fail.

CSV errors

Common CSV errors include:

  • Some rows are missing values for a geometry column. All rows in a CSV file must contain non-empty values for the geometry columns. The geometry columns include:
    • latitude, longitude
    • lat, long
    • x, y
    • wkt
    • address, city, state, zip
    • address
    • A single column containing all address information, such as 1600 Amphitheatre Parkway Mountain View, CA 94043
  • If x and y are your geometry columns, ensure that the units are longitude and latitude. Some public datasets use different coordinate systems under the headers x and y. If the wrong units are used, the dataset might import successfully, but the rendered data can show the dataset points in unexpected locations.

Create a dataset

To create a dataset:

  1. In the Google Cloud Console, go to the Datasets page.
  2. Click Create Dataset.
  3. Enter the dataset name. The name must be unique among all datasets.
  4. Optionally enter a dataset Description.
  5. Click Continue. The Import data page appears.
  6. Select the Upload source of the data used to populate the dataset as Desktop, meaning a local file on your system, or Google Cloud Storage bucket.
    • For Desktop, click Browse and then select the file from the file chooser.
    • For Google Cloud Storage bucket, click Browse and select the bucket and file containing the data.
  7. Select the File format.
  8. Click Continue to review your settings.
  9. Click Create. The Datasets page appears showing your new dataset. The status should be Processing.
  10. Wait until your dataset has a status of Completed.

View or modify a dataset

After you create a dataset successfully, its status appears as Completed. You can then examine the details of the dataset.

To view or modify the dataset:

  1. In the Google Cloud Console, go to the Datasets page.
  2. Click the name of the dataset. The Dataset details page appears.
    1. Click the Details tab to see information about the dataset. On this tab you can also edit the dataset name and description.
    2. Click the Preview tab to see your dataset on a map.
    3. Click the Table Data tab to see all attributes of the dataset. These are the attributes that you can use to style the dataset on the map.
    4. Click the Download button to download the data to a local file.
    5. Click the Delete button to delete the dataset.
    6. Click the Import Data File button to upload new data to the dataset.

      Uploading new data to the dataset creates a new version of the dataset. If the new data uploads successfully:

      • The status of the new version of the dataset is set to COMPLETED.
      • The new version becomes the "active" version and is the version used by your app.

      If there is an error in the upload:

      • The status of the new dataset version is set to a status other than COMPLETED. For example, if there is a previous "active" version, the status of the dataset is set to REVERTED.
      • The previously "active" dataset version stays as the "active" version and is the version used by your app.