Lisa Ehrlinger 

Date/Time: cancelled

Location: 

Abstract 

Data is used to make decisions in both personal and business settings, such as selecting appropriate actions to improve production. In the age of artificial intelligence (AI), the amount of data used to make these decisions has grown exponentially. Despite the assumption that quality becomes less important with more data, recent studies show the impact of poor-quality training data on the performance of machine learning models. The recent trend towards data-centric AI also reflects the increasing awareness of data quality in the research community. In this talk, I will motivate the topic of data quality and why we should care about it. I will present our current research on data quality assessment and conclude the talk with an outlook on open challenges.

Bio 

Dr. Lisa Ehrlinger is a senior researcher at the Hasso Plattner Institute, Germany. In the Data & AI Cluster, she conducts research on how to assess data quality in the era of artificial intelligence. Lisa Ehrlinger obtained her PhD on "Automated Continuous Data Quality Measurement" from the Johannes Kepler University in Linz and worked on applied research projects in the field of data quality, data integration, and metadata management for the last 7 years at the Software Competence Center in Austria. Her research interests and publications cover the topics of data quality, databases, metadata management, and semantic technology. In 2023 and 2024, she co-organized the 12th and 13th Quality of Databases (QDB) workshop at the International Conference on Very Large Databases (VLDB) with the aim to provide a discussion platform for data quality researchers. Ehrlinger is also member of the Global Editorial Board of the CDO Magazine and had several talks at the MIT CDOIQ Symposium in Boston, MA, USA.

Link to website: https://hpi.de/naumann/people/dr-lisa-ehrlinger.html