Data interpretation

Data has literally no meaning, it is just data – researchers interpret data and attribute meaning to it to answer a research question. In content analysis and any other empirical research (e.g., ethnography and surveys), interpretation is based on systematic work with data and theory to produce results and draw conclusions, which are backed by an empirically grounded systematic analysis according to a category scheme. Interpretation cannot be standardized. However, we can provide practical guidance for the interpretation process. In this chapter, we start the interpretation journey with a simple interpretation exercise and then use more data to provide you with ideas about what interpretation basically is. The practical examples will help you understand that interpretations are part of different stages of the research process. To elaborate how theory can support interpretation, we present three types of theories: concept, proposition and comparison, and typology. In the second part of this chapter, to overcome interpretation Angst by doing interpretation, we suggest strategies for the interpretation process, for example, for how to deal with a large quantity of data and meaning.