Description
This hands-on tutorial introduces OpenSemanticLab (OSL) as an integrated OpenSource platform for research data management, combining ELN, LIMS, and workflow support. Participants will learn how to model data using Object-Oriented Linked Data (OO-LD) and build simple linked data applications using Python and LLM integration.
This tutorial is split in 3 parts.
- Part 1: A single Platform as ELN, LIMS, Workflow-, Project- and Terminology Management & more - Using OpenSemanticLab (OSL) for Research Data Management
- Part 2: A custom schema in 5 minutes - Adapting OSL to your need by understanding Object-Oriented Linked Data (OO-LD)
- Part 3: A linked research data app in 50 lines of code - Development with oold-python and its LLM integration
Audience
Researchers, data stewards, and R&D professionals with an interest in research data management and digitalisation in materials science; basic programming experience is helpful but not strictly required.
Pre-requisites
No prior knowledge of semantic technologies is required.
For part 3 basic familiarity with programming concepts (preferably Python) is beneficial
Setup
For part 3 a laptop with a modern web browser and Python (>=3.11, uv package manager) installed or access to a JupyterHub Notebook