Dr. Tanja Auge

My interests include a variety of subjects, such as

• provenance, in particular data provenance,
• research data management,
• Chase algorithm,
• schema evolution and data updates, and.
• data provenance for AI.

For me, access to data and its analysis in science and society is the cornerstone of free and sound research. The open, FAIR and privacy-compliant provision of this data is therefore one of our most important basic obligations. My goal in provenance research is to ensure the traceability of a (published) result throughout the entire data science life cycle back to its (possibly physical) source. Especially for machine-generated analysis results, it is particularly important to know where the data used comes from, as it is often (pre-)processed in several stages and may originate from unclear sources. Data from the internet or social media in particular often has a very short half-life and is then no longer traceable. Possible boundary conditions that must be taken into account here include the evolution of the databases at schema and data level, the database type and compliance with privacy aspects. Areas of application for this include research data management and various data engineering, data science or AI applications. With my research, I would like to contribute to making scientific, but also economic processes and evaluations more transparent and thus reduce or prevent errors in data processing as well as ambiguities in their interpretation, hallucinations (of LLMs) and the like.