GeostoreDataSourceProto

GeostoreLocal SEO

GoogleApi.ContentWarehouse.V1.Model.GeostoreDataSourceProto

4
out of 10
Low
SEO Impact
Every data source used to construct a data repository has an associated feature that provides more information about it. The standard feature properties have the following interpretations: bound - The bounds must includes all features that refer to this data source, so that bucketing MapReduce passes work correctly. name - The provider name associated with this data source. It is expected to remain constant from release to release, and between datasets. address - should be empty. point, polyline, polygon - should be empty. source_info - should not be set. child - should be empty.

SEO Analysis

AI Generated

Part of Google's geographic data infrastructure (Geostore). This system stores and processes geographic information that powers Google Maps, local search, and location-based search features. For local SEO, these geographic signals determine how businesses and locations appear in local search results and map packs.

Actionable Insights for SEOs

  • Optimize Google Business Profile with accurate location data
  • Ensure NAP (Name, Address, Phone) consistency across the web
  • Build local citations and location-relevant content

Attributes

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Default: nilFull type: list(GoogleApi.ContentWarehouse.V1.Model.GeostoreUrlProto.t

This is the URL of a website representing this DataSource as a whole. If this DataSource feature is specific to a particular dataset or product, the page may contain information relevant to that dataset or product or may be the main page of the organization.

copyrightOwnerstring
Default: nilFull type: String.t

A UTF8 string that will be inserted in copyright messages to refer to this copyright owner, e.g. "Tele Atlas".

copyrightYearinteger(
Default: nil

The copyright year of this data (which may be different than the year of the release date), e.g. 2005.

descriptionstring
Default: nilFull type: String.t

A free-form description of this data source. Ideally the description should include: - Where the data was obtained (URL, company name, individual, etc). - Where to find detailed documentation. - A brief summary of the licensing terms. - As much internal and external contact information as possible (e.g. who to ask about licensing questions, interpreting the data, updating the data, fixing bugs in the importer, etc).

importerBuildInfostring
Default: nilFull type: String.t

The build information of the importer binary used to generate this data source.

importerBuildTargetstring
Default: nilFull type: String.t

The build target of the importer binary used to generate this data source.

importerClientInfostring
Default: nilFull type: String.t

The Perforce client information of the importer binary used to generate this data source.

importerMpmVersionstring
Default: nilFull type: String.t

If the importer was built as an MPM, the version number can be stored in this field. As with build_info, this can be useful when tracking down issues that may be due to the use of a particular binary.

importerTimestampstring
Default: nilFull type: String.t

The timestamp of the importer binary used to generate this data source.

providerstring
Default: nilFull type: String.t

The provider type of this data source.

Default: nilFull type: list(GoogleApi.ContentWarehouse.V1.Model.GeostoreRawMetadataProto.t

For every key that is used in raw_data from this source, there must be a corresponding entry in raw_metadata that describes this key.

releasestring
Default: nilFull type: String.t

A release string that doesn't have to be a date. This is provided so that we can preserve provider release strings that aren't based on dates. If you don't set it, the release_date will get formatted into this field for debugging purposes.

Default: nilFull type: GoogleApi.ContentWarehouse.V1.Model.GeostoreDateTimeProto.t

The release date of this data.

sourceDatasetstring
Default: nilFull type: String.t

A data provider defined string describing the source dataset from which the features of this data source were generated. For example, the MultiNet "fra" dataset produces features for both France and Monaco.