- Textual information or data annotated with textual information (meta-information) are regular targets of securing or confiscating relevant material in the field of criminal proceedings. In general evaluation of relevant material is complex, especially the manual (re)search in the increasing amount of data as a result of cheaper storage capacity available nowadays therefore the identification of valid relations are enormously complex, error-prone and slow. In addition, the adherence to time limits and data privacy protection make searching even more difficult. The development of an (semi-)automatic high modular solution for exploration of this kind of data using capabilities of computer linguistic methods and technologies is presented in this work. From a scientific perspective, the biggest challenge is the au-tomatic handling of fragmented or defective texts and hidden semantics. A domain-specific language has been defined using the model-driven approach of the Eclipse Modeling Framework for the purpose of developing forensic taxonomies and ontologies. Based on this, role-based editors have been developed to allow the definition of case-based ontologies and taxonomies and the results of manual annotation of texts. The next steps required for further development are going to include comparison of several back-end frameworks, e.g., for indexing, information extraction, querying and the providing of a graphical representation of relations as a knowledge map. Finally, the overall process needs to be optimized and automated.