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eisti_tool [2019/06/26 10:13]
laumond
eisti_tool [2019/06/26 10:39]
laumond
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 The visual analytics tool Intergraph offers a novel approach to exploring Digital Humanities corpora by means of an iterative search and discovery workflow. Written in javascript, Intergraph runs in a web browser and communicates with a node.js server which queries the data from a Neo4j database. The front-end client renders the graphs using the Three.js graphics library. ​ The visual analytics tool Intergraph offers a novel approach to exploring Digital Humanities corpora by means of an iterative search and discovery workflow. Written in javascript, Intergraph runs in a web browser and communicates with a node.js server which queries the data from a Neo4j database. The front-end client renders the graphs using the Three.js graphics library. ​
  
-Given the size of the histograph dataset, an overall visualization of the corpus is neither suitable nor desirable for exploration. Users are rather interested in creating and inspecting subnetworks with entities relevant to their current research interest. Therefore, the main idea of Intergraph is to begin the exploration from one or more known start nodes. Following the expand-on-demand principle, the user will encounter new relevant nodes and pursue their exploration by conveniently creating additional graphs stemming from the existing ones. This path of exploration yields a sequence of linked sub-graphs. ​Figure 1 shows a global screenshot of the Intergraph interface.+Given the size of the histograph dataset, an overall visualization of the corpus is neither suitable nor desirable for exploration. Users are rather interested in creating and inspecting subnetworks with entities relevant to their current research interest. Therefore, the main idea of Intergraph is to begin the exploration from one or more known start nodes. Following the expand-on-demand principle, the user will encounter new relevant nodes and pursue their exploration by conveniently creating additional graphs stemming from the existing ones. This path of exploration yields a sequence of linked sub-graphs. ​The following figure ​shows a global screenshot of the Intergraph interface. 
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 {{ :​img:​intergraph.png?​800 |}} {{ :​img:​intergraph.png?​800 |}}
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 Graphs can be dynamically added to and deleted from the scene. Following the VisLink approach, they are rendered on free-floating planes which can be arbitrarily translated, oriented and scaled using familiar transformation widgets. Depending on the user tasks and preferences,​ the scene can be viewed in a 2Dor a 3D perspective. ​ Graphs can be dynamically added to and deleted from the scene. Following the VisLink approach, they are rendered on free-floating planes which can be arbitrarily translated, oriented and scaled using familiar transformation widgets. Depending on the user tasks and preferences,​ the scene can be viewed in a 2Dor a 3D perspective. ​
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 After a brief introduction to the functionalities of the platform, users were invited to use Intergraph for themselves and to begin their session with an elementary keyword search for an entity they knew was mentioned in the corpus. From this starting point, they were free to perform more synoptic tasks, such as finding relevant collections and resources, searches for co-appearing entities and comparison of their corresponding networks, in order to get a comprehensive view of how the investigated element is represented,​ positioned and linked in the corpus. Throughout the session, users were encouraged to continuously verbalize their train of thoughts and actions following the thinking aloud approach. ​ After a brief introduction to the functionalities of the platform, users were invited to use Intergraph for themselves and to begin their session with an elementary keyword search for an entity they knew was mentioned in the corpus. From this starting point, they were free to perform more synoptic tasks, such as finding relevant collections and resources, searches for co-appearing entities and comparison of their corresponding networks, in order to get a comprehensive view of how the investigated element is represented,​ positioned and linked in the corpus. Throughout the session, users were encouraged to continuously verbalize their train of thoughts and actions following the thinking aloud approach. ​
  
-Following the 45 minute testing period users were asked to give verbal feedback and to complete a questionnaire. ​ Concerning verbal feedback, users appreciated the ease of navigating through the corpus, the flexibility and freedom to combine different elements, the links across canvases, the management of duplicate entities as well as the ability to drill down to the underlying resources. In the questionnaire,​ users were invited to rate on a scale of 1 to 7 the utility of Intergraph with view to all aspects of the initially defined user story. As a result, ​Figure 2 shows a high general acceptance. In particular, all users declared that for the given user story they would prefer to use Intergaph over the other available tools (CVCE homepage search and CVCE backendsearch).+Following the 45 minute testing period users were asked to give verbal feedback and to complete a questionnaire. ​ Concerning verbal feedback, users appreciated the ease of navigating through the corpus, the flexibility and freedom to combine different elements, the links across canvases, the management of duplicate entities as well as the ability to drill down to the underlying resources. In the questionnaire,​ users were invited to rate on a scale of 1 to 7 the utility of Intergraph with view to all aspects of the initially defined user story. As a result, ​the following figure ​shows a high general acceptance. In particular, all users declared that for the given user story they would prefer to use Intergaph over the other available tools (CVCE homepage search and CVCE backendsearch). 
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 {{ :​img:​intergraph2.png?​400 |}} {{ :​img:​intergraph2.png?​400 |}}