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# Data integration and metadata annotation
# DIMA: Data Integration and Metadata Annotation
DIMA (Data Integration and Metadata Annotation) is a Python package, developed for the Lab of Atmospheric Chemistry that supports integration of multi-instrument data in HDF5 format, collected across a wide range of experimental campaigns, from beamtimes and kinetic flowtube studies to smog chamber studies and field campaigns.
creation of semiformat descriptions using
. This repository is a Python package, consisting of modules data integration, metadata annotation, data manipulation, and visualization of experimental campaign data in HDF5 files.
provides tools and workflows for efficient data integration and metadata management, particularly for experimental campaign data stored in the HDF5 file format.
Repository for integrating data in HDF5 from various sources and managing metadata updates in the integrated files.
Includes tools and workflows for comprehensive data integration and automated metadata review processes.
## Overview
DIMA is a collection of reusable data operation modules and high-level workflows designed to streamline the following tasks:
- **Data Integration Pipeline**: Harmonizes and integrates diverse data sources into a unified HDF5 format.
- **Metadata Revision Workflow**: Updates and refines metadata to ensure consistency and accuracy for experimental campaigns.
## Repository Structure
![Software Architecture](docs/software_architecture_diagram.svg)
## Installation
Follow these steps to install and set up the project: