Researchers coming from the qualitative area are familiar with the situation that a lot of effort and resources are needed to create a dataset for answering specific research questions. Once these questions are answered, the full potential of the data is often not tapped since the dataset is usually not used for further analyses. Therefore the following questions appear:
How can qualitative data be used for various problems in a reliable way as it is common praxis with quantitative data? How can different datasets be matched in order to answer further research questions? How can scope and usefulness of qualitative data be increased and be used in a more efficient way?
Solving these problems seems to be possible by consistent coding of the verbal data based on its semantic structure. This type of coding is the basic element for analyzing data with GABEK®, which is a method that allows for analyzing unordered linguistic texts in a way that provides a comprehensive view of their entity.
When subdividing verbal data into brief, self-contained and intrinsically comprehensible statements, which - by themselves and not considering any context - are 'true', these statements can be linked with statements of similar content using representative key words.
Thus, it is also possible to connect different datasets through these key words. It is through these connections that questions become answerable that had not been intended to be addressed by the original datasets involved.
Additionally, basal statistical criteria and socio-demographic indicators such as sex, age or occupation can be collected easily and may be used to create specific subgroups in order to tailor the combined dataset to the new research questions.