Ulrich ReimerProf. Dr. Ulrich Reimer received his PhD in Computer and Information Science at the University of Konstanz with a thesis on formal ontologies for natural language understanding. In 1992 he obtained his venia legendi at the University of Konstanz. From 1991 to 2002 Ulrich Reimer was head of the IT R&D group of Swiss Life in Zurich. During that time his group was responsible for various research and application projects in the areas of Semantic Web, Knowledge management, Data Mining and E-Tutoring, some of them having been funded by the EU. His main areas of expertise are currently the utilization of semantic technologies in knowledge management und e-health applications as well as domain-specific languages.
|1992||Habilitation at the University of Konstanz, Germany|
|1987||Doctoral thesis on knowledge representation for automatic text understanding and abstracting|
|1981||Diploma in Computer Science at Technical University Darmstadt, Germany|
|since 2005||Institute for Information and Process Management|
University of Applied Sciences, St. Gallen, Switzerland
|2002 – 2005||Senior Consultant and responsible for Business Development and Research at Business Operation Systems, Kreuzlingen, Switzerland|
|1991 – 2002||Head of IT Research & Development at Swiss Life, Zurich, Switzerland|
|1987 – 1991||Assistant Professor at the Dept. of Information Science of the University of Konstanz, Germany|
|1982 – 1987||Scientific Researcher at the Dept. of Information Science of the University of Konstanz, Germany|
Behaviour Change Support Systems:
A current research area is dealing with how to support people to change their behaviour to improve their health. To this end we have developed the SABA framework which facilitates the development of behaviour change support systems. SABA comprises components to accommodate user preferences and to adapt system interventions to individual users. User adaptation is realized by means of user modeling and collaborative filtering, resulting in a self-learning application that changes in line with a user’s progress and takes a user’s current situation into account. We expect our approach to enhance user acceptance and increase and sustain people’s motivation for behavioral change.
Making sense of sensors:
With the proliferation of body sensors on the market it has become quite easy to collect a wide variety of vital data as well as behavioural data indicating physical exercise. To make sense of all the collected data we employ data mining techniques to derive insights which then again lead to personalised advice, e.g. on how to change one’s behavior to improve sleep quality, or how to avoid stress. Since giving personalised advice can contribute considerably to behavioural change, sensor data analysis combines nicely with behavioural change support systems.
Application of Semantic Web technologies to various application areas such as knowledge management, e-health, e-government, and e-participation, for example to support personalised information access for patients, to enable clustering and categorisation of contributions to discussion forums, and extracting the key terminology from a text collection.
Domain-Specific Modelling Languages (DSLs):
Domain-specific modelling languages (DSLs) are focused on supporting the creation of models within a certain application domain. They typically comprise predefined domain-specific concepts as well as specialised language constructs that make it easier to create a model in the associated domain. In our current research we are applying DSLs and meta-modelling in the application domain of e-health, e.g. to help developing and configuring toolboxes of IT-based components for various medical interventions.
see a short description of my projects here: http://www.ulrichreimer.net/home/projects
|-||Information extraction from texts|
|-||WM2015: Professionelles Wissensmanagement: March 2015, Dresden|
|-||Modellierung 2014: 19-21 March 2014, Vienna|
|-||GI Fachgruppe Wissensmanagement|
|-||Querschnittsfachausschuss Modellierung der GI|