Special Issue "Data Analysis and Domain Knowledge" Information Dear Colleagues, Data analysis is one of the application areas of mathematics. Statistical hypothesis testing belongs to the first tasks of data analysis. The goal of exploratory data analysis is using data to suggest hypotheses to test. Data mining and knowledge discovery in data bases have brought new goals to data analysis—to find patterns hidden in given large data, which can be useful for data owners. Fast development of tools for generating and storing data has led to tremendous heterogeneous data sets to be analyzed. It is thus becoming clearer that the domain knowledge, i.e., the knowledge of the field that the data belongs to, must be considered when analyzing data. The goal of this special issue is to present recent developments in applications of domain knowledge in data analysis. We are especially interested in papers describing tools for formalizations of items of domain knowledge such that the formalized items can be used to generate reasonable analytical questions solvable by available tools for data analysis. We are also interested in papers describing approaches when consequences of formalized items of domain knowledge are automatically filtered out from outputs of analytical procedures. Of course, any other interesting aspects of applications of domain knowledge in data analysis are welcomed. Prof. Dr. Jan Rauch Guest Editor For details see https://www.mdpi.com/journal/mathematics/special_issues/data_knowledge