Custom Data Models
Overview
The RhinoDHE allows you to harmonize data to a custom data model rather than a predefined standard such as OMOP. This is useful when your project has a only requires a specific subset or structure of data and performing a full mapping to a standard data model would be unnecessary.
For example, you may want to prepare a dataset for a machine learning model that expects a specific set of fields, create a standardized research dataset containing only the variables needed for an analysis, or transform data into a common ontology agreed upon by multiple collaborators.
Prerequisites
You must have the "Manage Data Mappings" permission.
Before you begin:
The source data you want to use should already be available in Rhino FCP.
The schema for this will be auto-generated if you do not explicitly define it.
Determine which fields you want to include in your custom data model.
Determine how you want to transform your fields from source to target.
Steps
To define the structure of your custom data model, you first create a Data Schema specifying the fields, data types, and other properties that the resulting dataset should contain. You then create a Syntactic Mapping that defines how data from your source dataset should be transformed to match that schema.
Create the syntactic mapping
Create a new Syntactic Mapping by following instructions in Syntactic Mapping.
Make sure that the target data model is Custom.
Select the new schema that you created in the previous steps for the Target field.
Last updated
Was this helpful?