SODIC is a research group at TU Chemnitz focused on advancing open and semantic data infrastructures.
We explore how structured, interoperable and spatially linked data can foster innovation, transparency, and collaboration across public administration, science, and civil society.

In a world increasingly driven by data, the accessibility, semantics, and interoperability of Open Data are more important than ever.
SODIC stands at the intersection of technology, governance, and transparency – pushing for intelligent Open Data infrastructures that empower society, science, and administration.

• Florian Hahn ORCID Researcher in Semantic Open Data, Web Technologies & Public Data Infrastructures

• Prof. Dr. Michael Martin ORCID Professor of Data Management – Expert in Linked Data, Semantics, and Data Architectures

SODPUB is a docker based tool for enhancing pre-publication processes for Open Data. It supports CSV input files and produces enhanced CSV file, improvied metadata file and an reproducable publication file, all together ready for semantic interoperability in RDF format. This work is the main focus at the moment and there is not an officially release right now, but you can sneak peak into the architecture level here: 🌐 SODPUB GitHub Repository or an under development website here: 🌐 SODPUB pre-website

SODS is an survey based on DACH region Open Data Portals to gather information about the Open Data Portal state with best practices, standards, interoperability, current work and more. The survey took place in january 2026. All results are published here: 🌐 SODS GitHub Repository

An interactive map-based tool linking Open Data portals to administrative boundaries across Europe.

It contains a small, reproducible example knowledge graph that demonstrates how to model time-scoped organizational structures and thematic assignments for German public-sector actors in the context of Open Government Data. 🌐 SODORG GitHub Repository

This Python-based research tool executes and aggregates data extraction scripts for all 16 German federal states. Each script targets specific Open Data sources (e.g. state portals, ArcGIS endpoints) and parses region-specific datasets. The result is a unified metadata corpus that can be used for further semantic analysis, statistical evaluation, or integration into RDF graphs. 🌐 SODCET GitHub Repository

SODINA is a lightweight introspection layer for SPARQL endpoints, designed to support semantic data exploration by dynamically exposing available classes, properties, datatypes, and value samples. Inspired by GraphQL’s __schema functionality, SODINA lowers the entry barrier for users unfamiliar with the internal vocabulary of RDF-based Open Data portals.

This Node.js-based research tool analyzes the metadata quality of German municipal Open Data portals. Specifically, it evaluates the regional assignability of datasets depending on whether standardized metadata models like DCAT-AP and GeoDCAT-AP are used (typically via CKAN), best practice as a SPARQL endpoint, or non-standard formats (e.g. ArcGIS JSON).

SODBond is a toolkit that bridges Camunda BPMN 2.0 process definitions and runtime instances with RDF knowledge graphs via an ontology-driven approach. It retrieves BPMN models and instance data from Camunda through the REST API and transforms them into semantically rich RDF/OWL representations based on a BPMN-based ontology.

SODPEST is a small, dependency-light CLI tool that derives SPARQL endpoint candidates for Open Data portals and optionally verifies them via real SPARQL protocol checks.

SODDUT ist an interactive timeline to check the corresponding creation and updating process of an Open Data Dataset.

• SODA – Saxony Open Data Assembly (planned)

• Hahn, F. (2026). 'SODPUB: A BPMN-Orchestrated Workflow-as-a-Service for Interoperability-Oriented Pre-publication Quality Improvement in Open Government Data' (ICWE 2026)

• Hahn, F. (2026). 'Measuring Semantic Comparability in Federal Open Data: Evidence from German State Portals.' (DGO 2026)

• Hahn, F. (2026). 'SODS: Surveying Interoperability Readiness in DACH Open Data Portals.' (DGO 2026)

• Hahn, F. (2026). 'From Federal Heterogeneity to Reproducible Analytics: A Provenance-Aware Knowledge Graph for Cross-Portal Comparability of German Open Government Data' (KGCW 2026 at ESWC 2026)

• Hahn, F. (2025). 'Ontology Driven Transformation of Camunda BPMN Instances into RDF Knowledge Graphs' (NFDI4DS 2025)

• Hahn, F. (2025). 'Geographical Provenance of Open Government Datasets: Evaluating Geospatial Metadata in Municipal Open Data Portals' (DCMI 2025)

• Hahn, F. (2025). 'Bridging gaps in the Open Data landscape: A step towards a global atlas' (ICEGOV 2025).

• Hahn, F. (2025). 'Towards an Standardized Dataset Publishing in Open Government Data Ecosystems' (ESWC 2025).

• Semantic Web & Ontologies
• Open Government Data
• Metadata Enrichment & Quality Assessment
• FAIR Data Principles & Data Ecosystems

Faculty of Computer Science, Professorship Data Management, Chemnitz University of Technology, Germany

• Email: florian.hahn@informatik.tu-chemnitz.de
• GitHub: github.com/SODIC-research
• GitHub Page:https://sodic-research.github.io/
• TU Chemnitz Page: https://www.tu-chemnitz.de/informatik/dm/team/fh.php.en

© {year} SODIC Research Group – TU Chemnitz. All rights reserved. Since 01.02.2025