I am a doctoral student / assistant at the DDIS group at the Institute of Informatics. Before that I studied Wirtschaftsinformatik at the University of Zurich and worked for SAP as a Project Manager and NORWEL AG as a Software Engineer.
Semantic Web Enabled Software Analysis
The goal of software analysis is (among others) a reduced number of errors and an easier manageability of a software system. One particular field is the investigation of the history of a software system (source code, version and bug information) to derive future trends. For example, the monitoring of the code's complexity can help a project manager to identify and plan the need of reeingeering tasks. Semantic technologies can contribute to those analyses by providing an extendible and open representation format for software engineering related data. Due to the vast availability of off-the-shelf tools, those analyses reduce, compared to classic approaches, the implementation and preprocessing effort. For more information see also EvoOnt.
Temporal extensions to Semantic Web Technologies
Semantic technologies, such as RDF and OWL, let a user define a data model similar to a relational database system. Nevertheless, there is no support for change and evolution of neither the data model nor the data itself. Work-around solutions include the storage of data-snapshots according to a schedule (e.g. daily snapshot) or the attempt to cover evolution by the data model itself (by adding timestamp information to changing information). A more sophisticated way is the usage of a 4-dimensional approach enabling the annotation of each information atom (triple) with a start and end time of its validity. This method can reduce the amount and complexity of the stored information having a positive effect on comprehension and execution time.