Research

Selected research projects at the University of Mannheim in the field of data science

In our interview series Data Science Insights, we introduce you to one research project in the field of Data Science at the University of Mannheim every month.

Data Science Insights

Interdisciplinary projects and offers

Research Data Center of the Mannheim University Library

The Research Data Center of the University Library provides specialized data sets from the economic and social sciences, in particular company data. Read the DSI interview with Tobias Rettig about the German Research Panel (GIP).

Advancing New Methodological Approaches to Measure Social Decisions: The Case of Eating in a Family Context

The goal of the research project is to further develop and apply a multi-method approach that combines methods from informatics, sociology, and psychology to better understand everyday social decisions, using the example of family food decisions. Developing such externally valid methods that take the social context into account is central to better understand the inequalities in nutrition and health.

BERD@NFDI

BERD@NFDI is a research data infrastructure dedicated to transforming the way Business, Economic, and Related Data are managed. To the DSI-interviews with project staff Renat Shigapov and Andreas Hamann.

Consequences of Artificial Intelligence for Urban Societies (CAIUS)

AI systems help to efficiently allocate scarce public resources and are at the core of many smart city activities. Yet, the same systems may also result in unintended societal consequences, particularly by reinforcing social inequalities. CAIUS will identify and analyze such consequences.

From Data to Insights

The analysis of large amounts of data in order to derive relevant management implications and achieve competitive advantages is a research focus of the Chair of Quantitative Marketing and Consumer Behaviour.

User and data bias in people ranking systems

The project, which is funded by the German Research Foundation (DFG), aims to contribute to the development of systems that adequately take into account the complexity of the assessment of individuals.

Early Stage Diabetes Detection

The goal of the KI-Diabetes Detektion project is to integrate indication data from various sources in a knowledge graph and apply machine learning methods to improve the early stage detection of Diabetes.

Data Analytics

Our group's research focuses on systems and methods for analyzing and mining large datasets as well as their application in practice.

Web Data Mining

The research group looks on using structured and semi-structured web data as background knowledge in data mining problems.

Natural Language Processing and Information Retrieval

The NLP and IR group at DWS conducts research on integrating knowledge from heterogeneous Web sources.

Web-based Systems

The project explores technical and empirical questions concerning the development of global, decentralized information environments.

Artificial Intelligence

The group conducts fundamental and applied research in knowledge representation formalisms with a focus on reasoning techniques for information extraction and integration.

UNICON – Understanding Nutrition Inequalities in Context: Momentary and Persistent Processes

The GRF-funded project investigates how social inequality is reflected in social differences in nutritional behavior and provides clues for the design of behavioral interventions that can effectively reduce social inequalities in nutritional behavior.

Fairness in Automated Decision-Making

The project deals with discrimination and fairness of algorithm-based decision-making processes (Automated Decision-Making, ADM) in the German public sector. To the DSI-interview with project team member Christoph Kern.

Using Machine Learning to Predict Panel Attrition

We use machine learning to identify predictors of participation and nonparticipation in longitudinal surveys.

Combining Passive Mobile Data with Surveys

In several projects, we explore ways of combining passively collected data from smartphones with self-reports from users.

Competence Center for Data Quality in the Social Sciences (KODAQS)

In this project, the University of Mannheim is working together with the LMU Munich and GESIS – Leibniz Institute for the Social Sciences on a learning, research and networking center for the quality-assured use of social science data. Read the DSI-interview with project team member Fiona Draxler.

Language corpora as digital educational technologies

The aim of the working group is to systematise approaches and concepts for the use of long-term available corpus infrastructures in teaching and learning in order to develop appropriate usage scenarios for different teaching contexts and to develop teaching and learning materials. To the DSI interview with project team member Laura Herzberg.