data-harmonization

Parse multiple Antimicrobial Resistance Analysis Reports into a common data structure

The Harmony Python library: a research tool for psychologists to harmonise data and questionnaire items. Open source.

A python framework for microbial natural products data mining by integrating genomics and metabolomics data

A toolkit for biomedical data integration and harmonization

Python implementation of Combat for data harmonisation, allowing also to remove unwanted effects

Python library for intelligent data stewardship using Large Language Model (LLM) embeddings

This is the DataHarmonizer spreadsheet web application bundled with pathogen genomics data entry and validation templates

Self-hostable, open-source engine for reproducible data harmonization, dataset building & exploration

ADHTEB - Alzheimers Disease Harmonization Text Embedding Benchmark

Harmonize longitudinal BRFSS survey data across years and datasets (CDC national & state-restricted files). A tidycensus-style workflow to resolve variable drift, response code shifts, and REAL-D demographic arrays into tidy tibbles.

Code and sample data for McGregor et al., 2024

⛳️ PASS: Salesforce Certified Data Cloud Consultant by learning based on our Questions & Answers (Q&A) Practice Tests Exams.

Example Jupyter notebook and R scripts using Harmony in real research problems

A data stewardship tool for semi-automatic semantic mapping and harmonization of data dictionaries using standardized vocabularies and ontologies.

Harmonizes battery test datasets into one canonical schema.

A MATLAB-based domain adaptation toolbox for medical data analysis. It supports synthetic data generation for rapid validation and benchmarking, and includes a collection of popular, lightweight domain adaptation algorithms. The toolbox also provides image-level domain adaptation (harmonization) methods for medical imaging applications.

This is the source code for the Harmony project REST API

A semi-automated reference data and standardization service for global projects. This service handles common reference dimensions (marital status, education, nationality, etc.) by semantically matching new raw values, routing them to reviewers for approval, and adding them to a central mapping