In short:

My research focuses on the development of trustworthy personal information systems that are able to explain themselves, and the design and engineering principles for developing systems with such capabilities.

In a few more words:

The ability to explain reasoning processes and results can substantially affect the usability and acceptance of a software system. Explanation, trust, and transparency are concepts strongly associated with information systems.

Within the field of knowledge-based systems, explanations are considered as an important link between humans and machines. Their main purpose is to increase the confidence of the user in system results (persuasion) or the system as a whole (satisfaction), by providing evidence of how the solution was derived (transparency) and where the information came from (knowledge provenance). Explanations are part of human understanding processes and part of most dialogues, and, therefore, need to be engineered into system interactions to improve interactive decision-making processes and, thus, making such systems more robust and dependable. Systems that justify their means may increase the user’s sense of control, further increasing acceptance.

Eventually, changes of the knowledge base and changes of the system‘s environment directly lead to the problem of knowledge maintenance, which I already addressed in several projects and which I will be dealing with more in the future.

The Semantic Web pursues the goal of making web content and databases accessible to software systems, e.g., agents using semi-structured data and ontologies. This goal is an enormous challenge as well as a good opportunity, especially for AI methods and techniques. Interoperability and semantics are the watchwords here. (➠ my work during the EU project MedCIRCLE on quality assurance of medical information on the Web and NEPOMUK–The Social Semantic Desktop where the use of personas and low-tech video prototypes were crucial to its success.)

Semantic Web research mainly focusses on logic-based methods, which often do not allow adequately representing reality. Case-based reasoning (CBR) methods are a good way to address uncertainty and vagueness. The development of the open source tool myCBR, based on the Protégé ontology editor, was a first step in that direction. myCBR features explanation capabilities for supporting the user in similarity measure modelling and in better understanding retrieval results.

The Semantic Web / Web 2.0 provides the technical and conceptual platform for my research and system development.  My overall goal is to address the sketched problems of giving personal information systems proper explanation capabilities conceptually and practically, using the methods, skills, and technologies I acquired in many projects as software developer, technical consultant, quality manager, and researcher.

Teaching undergraduate as well as graduate students, and directing post-graduate activities such as a doctoral colloquium at the knowledge management department of DFKI already accompanied my research. Practical courses and exercises accompanying my lectures proved to me being a successful way of attracting and preparing students for my research project work, and as a way of directly including them in such work.

Particular Interests