Well designed experiments can be the key to scientific success. We develop methods that are mainly based on the idea of approximate optimal designs. They are intended for the use in virtually any application field that utilizes experimental/observational results, our main areas of interest being ecology, economics, industry, social sciences and computer experiments. Within these fields there are a number of problems, for which particularly optimal design theory for correlated observations could be effectively applied. In the geological sciences, for instance, one could employ those techniques for constructing earthquake monitoring networks. Another area of interest is the geochemical surveying of potentially contaminated land. The corresponding theory differs from classical approaches as often we cannot make use of convexity properties or equivalence theorems. By the better development and propagation of the above described methods a more widespread application of optimal design techniques (and thus more precise experimental results) in many application fields must be expected. This would then lead to new theoretical problems arising and therefore to a mutual fertilization of the respective disciplines. As the developments are predominantly algorithmic an association with the research priority Digital Transformation is most fitting.