The Entity Mapper—a data visualization tool for Grounded Theory research
Grounded Theory research can be described as a process that builds relationships between the collected qualitative data (for example the interview or spoken word), the transcript, quotations that are extracted and tagged in the transcript, codes that summarize these quotations, and code families or concepts that elevate the coding process to a theoretical understanding of the data. Figure 1 visualizes this node-link network.
Using software such as Atlas.Ti, we can detect patterns in the transcript, based on the language the members of the field are using (quotes) and elevate those to theoretical concepts. Atlas.Ti is mentioned here specifically because the Entity Mapper currently only allows the export format [XML] of Atlas.Ti for the visualization of this node-link network shown in figure 1. The instant visualization of the network shows patterns the researcher textually pre-structured in Atlas.Ti. The Entity Mapper was developed to show visualizations of the node-link network shown in Figure 1 as circle packing [14] and force-directed graphs. [15] The hierarchy of the entities (nodes) are differentiated by color and furthermore the size of the nodes shows the quantity of the links connected; and the location of the nodes is also based on the quantity of links (it is built as a force-directed graph—the more links, the more centered the nodes become).
A comparison of the differences and commonalities in colors, shapes, location, and textual information can visually represent hierarchies (node-link hierarchies as described above), providing an argument structure for the visual analysis and the quantitative structure of the coded data (more links/less links in one topic area). Comparing these features visually explains how the researcher can use the metadata that these features provide in the visual analysis by constructing a visual map accordingly. The following features of the Entity Mapper allow the researcher an interaction that leads to a visual understanding of the data coding process and analysis. The description of these features is also explained in the video which corresponds to the explanation of the features:
Color Coding
As shown in Figure 2, the different entity types (text, quotation, code, code family, and memo) are colored differently to immediately show the researcher the significance and hierarchy of the entity in the visual network. The researcher can change the colors of each entity (node) type in the editing feature of the software. The hierarchy colors are not binding and can be changed individually by each researcher. In the video example red corresponds to the concept/code family node, green to code, grey to quotes, and yellow to the transcript location.
Quantity Display
As it is visible in Figure 3, both the number of quotations in relation to the codes and the quantity of codes in relation to the code families is displayed with the size of the nodes in the Entity Mapper. The bigger the node, the higher the quantity of connections. The quantity display can show that one aspect, material, or concept was mentioned more often than others. Quantity can show that the researcher needs to follow-up on the displayed topic or that the focus in the qualitative data [for example interviews] need to shift because although the quantity display of a certain topic is more, the relevance of a less mentioned (smaller node) needs to be focused on instead. The quantity display allows an instant comparison of the focus of some concepts in a study. The researcher can make decisions on further research actions based on this comparison.
