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- 1 2016-03-04T05:03:11-08:00 Florian Wiencek ce1ae876f963bfc3b5cf6c3bbd8f57daf911e67f Quantity Display Florian Wiencek 2 plain 2016-03-04T05:04:53-08:00 Florian Wiencek ce1ae876f963bfc3b5cf6c3bbd8f57daf911e67f
- 1 2016-03-04T05:06:41-08:00 Florian Wiencek ce1ae876f963bfc3b5cf6c3bbd8f57daf911e67f Movability Florian Wiencek 2 plain 2016-03-04T05:13:05-08:00 Florian Wiencek ce1ae876f963bfc3b5cf6c3bbd8f57daf911e67f
- 1 2016-03-04T05:10:10-08:00 Florian Wiencek ce1ae876f963bfc3b5cf6c3bbd8f57daf911e67f Node-Link relationship in textual form Florian Wiencek 2 plain 2016-03-04T05:13:07-08:00 Florian Wiencek ce1ae876f963bfc3b5cf6c3bbd8f57daf911e67f
- 1 2016-03-04T04:57:27-08:00 Florian Wiencek ce1ae876f963bfc3b5cf6c3bbd8f57daf911e67f Color Coding Florian Wiencek 2 plain 2016-03-04T04:59:38-08:00 Florian Wiencek ce1ae876f963bfc3b5cf6c3bbd8f57daf911e67f
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The Entity Mapper—a data visualization tool for Grounded Theory research
by Anne Luther
Atlas.Ti is one of the most prominent software applications for data coding in Grounded Theory research. The approach is based on the aim to detect patterns of the social world we live in through a coding process that leads to a theoretical understanding of concepts in this social field. The tool has visualization features that are not flexible and user-friendly enough in its design to give the researcher the possibility of developing further reaching visual analysis. Visual analysis here refers to an analysis of the data that leads to theory development which is based on the visual comprehension of the data.
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  and force-directed graphs.  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 CodingAs 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 DisplayAs 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.
Node-Link relationship in textual formThe box on the right of the web browser (Figure 4, for a larger image, see video min. 3.08) reacts to the researcher’s interaction with the visual map. Choosing an entity by clicking on it in the web browser displays the textual information within this entity and the linked entities. For example, when one chooses a code family, the codes that are linked to it appear in the right box in text form and are highlighted in the visual map by emphasizing the links with a stronger line thickness. Choosing a code in the visual map by first hovering over it will highlight the code in the visual map with the feature displaying the entire map as more transparent—the link becomes apparent with the textual label. Choosing the code in the map or in the textual box displays the quotations linked to the code and the code family in the text box. The logic of the text box display follows the coding hierarchy/structure. Choosing a code from the scroll-down in the text box shows the entire quotation, which allows a copy and paste for direct quotations in the textual translation of the visual analysis. By clicking on the quotation, the parent of the quotation, or the rtf file from which it is taken, becomes apparent in the text box. The codes displayed below the quotation show how often and to which codes the quotation is linked. This feature allows therefore that the researcher can access the textual data in its full complexity while comparing and interacting with the data visually as well. One does not exclude the other and the data analysis features both, a visual and a textual understanding of the data as a whole network.
MovabilityThe movability of the entities in the visual map (Figure 5) is an important feature that allows the researcher to construct patterns that are not directed by the network structure. The feature initially shows the movability of the entities, the logic being that the strongest entity is directed to the center of the network. The strength of the entity is measured by the quantity of links connected to the node (the more links, the further it is centered). The researcher can nevertheless alter the position of the entity in the visual map by holding the cmd/ctrl key and clicking on the entity/node. The command/control key fixes the node and releases it from the force-directed logic. The nodes can be moved but the links always stay the same. The node-link relationship cannot be rendered in the visual map, but the location of the nodes can be altered. When a node is pinned in a specific location, it can be released to its organic force-directed movability by clicking on it without pressing the command/control key. The release of the node brings it back to the position based on the quantity of links in the network.
Color coding, quantity display, node-link relationship in textual form, and movability are features that the Entity Mapper offers to bring Grounded Theory research into the realm of data visualization and analysis. The understanding of the pre-structured data in a visual way and the construction of a visual argument with the full complexity of the collected and structured data (from the raw language of the field of study to the theoretical concepts) allow both a visual and textual understanding of the data and metadata. The presentation and conclusions drawn on from the visual map are only possible with the described features and extend an established methodology into a current development in qualitative research—namely the integration of intuitive, interactive software tools for qualitative data analysis.
Parts of this article are based on chapters of Anne Luther's PhD thesis from the University of the Arts and Design, London, which will be available in the British Library for reference expected in April 2016.