In recent years, data visualization has been used as a tool to understand and analyse data and metadata in both qualitative and quantitative research. Established methodologies such as Grounded Theory or Discourse Analysis promote the use of prominent software tools such as Atlas Ti, NVivo, and MaxQDA for qualitative data analysis.  These software allow one to structure qualitative data such as interviews, debates, research diaries, or field notes in a database system according to established methodological processes. In these tools, the visualization of the structured data in graphs or networks ultimately focuses on quantified metadata rather than the process of the analysis, and the metadata (how many words were used in the interviews, how often they were used, which codes were used how often, etc.) is often restricted by the static nature of the graphs, word clouds, or network views. The usability and interface of most integrated visualization tools in these popular software for qualitative data analysis do not integrate current trends in data visualization design and UX. 
The Entity Mapper , introduced in the following paragraphs, extends the established methodology of Grounded Theory  to a contemporary understanding of digital data and brings the use of technology in qualitative data visualization to a current state of interdisciplinary research.
The two main problems with popular contemporary visualization tools, like Atlas Ti, NVivo and MaxQDA—the static representation of metadata and the lack in usability and interface design—were the driving forces for the development of The Entity Mapper visualization tool which allows researchers to understand their data analysis in an intuitive and interactive, visual way. The Entity Mapper software was developed in 2013/14 at Parsons Institute for Information Mapping by the author. It is an open-source software  that was built by the programmer Noah Pedrini with AngularJS, D3, and Bootstrap, based on the research and development of the author.