Configure Faceted Search

Faceted Search

Faceted Search may be configured by adding or removing custom facets. You can configure this by uploading the Facets Register via the Ingestion API in the Data Pipeline. This process updates the Dashboard accordingly. The processing of the register can be monitored in the Data Pipeline Load Reporting website.

Note: Faceted Search must be enabled for the respective AIM-A environment before the facets can be customized. This service is already enabled for all AIM-A environments.

The Facets Register

The Data Pipeline accepts the facets register in the following csv format:

The column definitions are:

• Name: The class name of the attributes that need to be added or deleted from the available custom facets.

• Type: Allowed values are:

  • tags

  • documents

  • events

  • tasks

  • locations

  • 3dmodels

  • physicalequipment

  • activity

• Action: Allowed values are (to update an existing facet, first delete and then create a new facet):

  • add

  • delete

Ingestion API Request Parameters

Here is the required Ingestion API request body for uploading the facets register:

Semantic Search

The enabling and disabling of Semantic Search for the content of specific documents is performed by uploading a CSV file to the Custom endpoint of the Ingestion API, as follows:

Input File

The Data Pipeline accepts the input file as a csv in the following format (the headers in row 1 are mandatory):

The required columns are:

• DocumentId: This is the full document ID (<ROOTCONTEXT>|DOC|<FileName>) of the document that needs to be added or removed from the list of documents with Semantic Search enabled. For example, C400|CTX|DOC|Document1.

• Action: Allowed values are:

  • add - add the specified document to the list of documents with semantic search enabled

  • remove - removes the specified document from the list of documents with semantic search enabled

Ingestion API Request parameters

The following is an example Ingestion API upload request body for uploading the input csv file:

[{

"target": "Custom",

"configId": "semanticsearch",

"fileName": "Input1.csv"

}]