Using Visual Communication Design To Optimize Exploration of Large Text-Mining Datasets

• Author / Creator

  Montague, John J

• How can the principles and concepts applied by visual communication designers be used to assist in exploring and understanding the massive, complex volumes of data now available to Digital Humanities researchers? One method we might employ to help us more easily comprehend the implications of these large data sets is visualization. While potentially helpful, visualizations can be more effective still if they are constructed in such a way as to allow or even encourage the viewer to interact with them, exploring the data looking for patterns that might lead to new insight. Visual communication designers try to strike a balance between “clarity” and “immediacy”; clarity, meaning the reader’s ability to identify and recognize communicative elements like text and symbols, and immediacy meaning the ease with which the reader can understand the message. This same two-part formula can be applied to visualizations of Big Data relationships. Almost by definition, immediacy (understanding) will be at a premium when displaying massive amounts of complex data. With especially complex new forms of Big Data, “message” might simply involve determining “where more specialized researchers might want to look more closely.” Greater viewer engagement will invariably help promote exploration, more exploration will bring with it a greater likelihood of new insights or questions, and these insights/questions might suggest new research directions in which traditional scholars may want to focus their attentions. This optimized engagement will principally be the result of two things; the purposeful application of visual communication and perception theory, and the creation of opportunities for dynamic interactivity between the user and the data, which will also provide the means of exploration. Dynamic interaction affords a more likely path to successful visualization as defined by Petre & Green, that is, visualization “that makes accessible the particular information the user needs” (56). Visual communication designers are always asking themselves what the user needs and crafting their designs accordingly; data visualization design should involve this same consideration.

• Subjects / Keywords

  • Text mining
  • Exploration
  • Perception
  • Visual communication design
  • Big data
  • Visualization

• Graduation date

  Spring 2016

• Type of Item

  Thesis

• Degree

  Master of Arts

• DOI

  https://doi.org/10.7939/R3Q23RB0S

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.