The Diagramed Model Query Language (DMQL) is a structural query language that operates on process models and related kinds of models, e.g., data models. In this article, we explain how DMQL works and report on DMQL's research process, which includes intermediate developments. The idea of a new model query language came from observations in industry projects, where it was necessary to deal with a variety of modeling languages, complex query requirements and the need for pinpointing the query results.
Constraint-logic object-oriented programming is useful in the integrated development of business software that occasionally solves constraint-logic problems. So far, work in constraint-logic objectoriented programming was limited to considering constraints that only involve logic variables of primitive types; in particular, boolean, integer, and floating-point numbers. However, the availability of object-oriented features calls for the option to use logic variables in lieu of objects as well. Therefore, support for reference-type logic variables (or free objects) is required.
Data Science: Machine Learning and Data Engineering
ERCIS Headquarters
Fabian Gieseke is head of the Machine Learning and Data Engineering Group of the Department of Information Systems. The group's research focus is on the development of efficient and scalable implementations for modern machine learning models. The resulting frameworks are also used to address real-world applications from a variety of domains. For instance, the team is involved in the development of machine learning models to detect and monitor changes visible in satellite time series data and in the application of corresponding models in the context of smart grids and smart cities (e.g.
