This topic explains how to create and approve a semantic mapping. This feature streamlines the process of mapping your data’s locally defined names for procedures, conditions, and other items into clinical data-sharing standards like Observational Medical Outcomes Partnership (OMOP) or a specific standard vocabulary like Systematized Nomenclature of Medicine (SNOMED).
| Note: For the current version, only semantic mapping to OMOP and to Custom Vocabularies are supported. |
Prerequisites
- You must have Manage Data Mappings permission.
- The dataset that you want to use must have been imported into FCP.
- Optional: The project must have K-Anonymization set larger than 1 if stricter privacy protections are needed.
What You'll Learn
In this topic, you will learn about:
Accessing the Semantic Mapping Page
To access the Semantic Mapping page, complete the following steps.
- Select Data Mappings from the Main Menu. The Data Mappings page appears.
- Select the Semantic Mappings link. The Semantic Mappings page appears.
The table below defines each field in this page.
| Field | Description |
| Semantic Mapping Name | Name of the semantic mapping, such as "Procedure", "Condition", or "Drug." |
| Description | Description of the mapping. |
| Version | Version of the semantic mapping. This increments each time you make a change to the semantic mapping. |
| Information Icon (on hover) | The information icon shows a summary of the semantic mapping information. Information shown includes the Dataset, Field, Target, Status, Mapping Coverage and Creator. It also includes the number of unique values and approved mappings, as well as the percentage of approved mappings and mapping coverage. |
| Dataset | Name of the original dataset. |
| Field | Name of the field to map in the original dataset. |
| Target | Name of the Target Vocabulary to map to. For OMOP, it will also list the target Domain (e.g., OMOP Person). |
| Status |
Status of the recommendation and approval part of the process. Statuses are:
|
| Mapping Coverage | Percent of values mapped, calculated as the number of non-empty values that have an approved mapping divided by the number of non-empty values. If there are < K non-empty values, this percent will be omitted. K is set by the K-Anonymization param at the project level. |
| Creator | Name of the person who created the mapping. |
| Three-Dot Menu | The three-dot menu (also known as the “meatballs menu”) provides access to two other options: Edit Data Mapping and Delete Data Mapping. |
Creating a Semantic Mapping
To create a Semantic Mapping, complete the following steps.
- In the Data Mapping > Semantic Mapping page, select the Create Semantic Mapping button.
- The Create Semantic Mapping page appears.
- Enter the following information.
- Name of the semantic mapping.
- Description of the semantic mapping.
- Dataset that has the field you need. The dataset should have already been imported into FCP.
- Select Field to Map. This is the field that you want create the semantic mapping for.
-
Target vocabulary that you want to map the field to. Options are:
- OMOP v5.4
- Custom Vocabulary
- Target Domain within OMOP v5.4 to map the field to. This option is not available for Custom Vocabulary mapping.
- When complete, select Create Data Mapping. The page closes and the Semantic Mappings page is displayed again, with an entry for the mapping you just created. Here is what happens next.
- The software calculates the unique terms within the source dataset field, and for each term suggests five mapping recommendations to the selected target vocabulary and domain.
- The proposed recommendations include target concept names and target concept IDs.
- The automatic generation of the proposed mappings runs on-prem on the Rhino Client, where the dataset is stored.
- If during this process, any queries are required to a Rhino service that isn’t hosted on that Rhino Client, only source values that appear at least K times in the field can be sent to this external service so as to preserve K-Anonymity.
- The status changes to “Processing”. The amount of processing time depends on the number of terms to map. For example, a small vocabulary might take a few minutes, but a large one could take several hours.
- The number of times the source value appears in the field is calculated.
- The confidence of the model recommendation for each of the top 5 recommended mapping values is calculated.
- Once processing is complete, the mapping suggestions are ready for review.
- The software calculates the unique terms within the source dataset field, and for each term suggests five mapping recommendations to the selected target vocabulary and domain.
Next Steps
After you complete these steps, go to the Reviewing and Editing Semantic Mapping topic to learn how to review and approve semantic mapping recommendations.