Harmonizing Complex RWD to a Custom Data Model

The goal of this project is to demonstrate, end to end, that Rhino Federated Computing's Data Harmonization Engine (DHE) can transform a complex, multimodal real-world oncology dataset into a standardized target schema entirely at the data source. Using the publicly accessible AACR GENIE BPC BrCa v1.0-public release — twelve source files spanning patient demographics, cancer diagnoses, treatment regimens, imaging, pathology, tumor markers, and somatic variant calls — the project produces a complete, field-level mapping to the GENIE Data Model (GDM v1.0.1), covering 11 output tables across the Core GENIE and Extended GDM layers.

Beyond the harmonized output itself, the project aims to establish a reusable reference pattern: a documented lineage from source to staging to target, a controlled-vocabulary mapping layer, and a phased execution plan that separates Code Object pre-processing from DHE syntactic mapping, and an auditable specification a partner site can inspect and re-run. In doing so, it shows how any GENIE-contributing center can conform local clinico-genomic data to a shared model in place — making the data federation-ready for multi-institutional cohort discovery and analysis without ever moving patient records across institutional boundaries.

Overview

The figure below represents and overview of the process involved in transforming the real-world data into the custom data model:

While the process could be run end-to-end by an AI agent, having a human in the loop with subject matter expertise is recommended to ensure that the output is of high quality. The four components visible in the diagram are reference below in their own isolated section.

Create Custom Data Model in Rhino

1. Create a new Rhino project for the data transformation

2. Generate Rhino Data Schema Objects to reflect the custom data model (GENIE data model)

3. In Claude, upload the data dictionary representing the GENIE data model and an example Rhino Data Schema with the following prompt:

Build Custom Data Model on the Rhino FCP

1. Create a Data Schema for each target table by uploading the generated CSVs into your project.

1. Create Custom Vocabularies for the code sets required by the custom data model

Register Source Data

1. Register source data (BrCa BPC) on Rhino client by creating Datasets

2. Export auto-generated Rhino Data Schema Objects (CSVs) from the Rhino platform and save them locally.

3. Enhance data schemas by incorporating information from the data dictionary (GENIE BPC Analytic Data Guide BrCa v1.0-public)

4. Upload the data dictionary to Claude with the following prompt:

Ingest Source Data Dictionary

1. Upload the auto-generated Rhino Data Schema objects (CSVs) into Claude with the following prompt:

Enrich Rhino FCP Data Schemas With Source Data Context

1. Re-register the source data by creating Datasets while selecting the updated enriched Data Schema objects.

Generate Semantic Mappings

1. Paste the following prompt into Claude or another LLM connected to the Rhino MCP:

Identify and Generate Required Semantic Mappings

Generate and Execute Syntactic Mappings

1. Paste the following prompt into Claude or another LLM connected to the Rhino MCP:

Identify and Generate Required Syntactic Mappings

1. Review the newly created syntactic mappings on the Rhino dashboard for accuracy and click 'Save' if all of the transformations appear accurate.

2. Navigate to the 'Code' page and click 'Run' on the newly created Data Harmonization Code Object.