@article{christensen_bae_watson_talamadupula_spjut_joines_2019, title={UIBK: User Interactions for Building Knowledge}, DOI={10.1145/3308557.3313122}, abstractNote={This half-day workshop seeks to bring together practitioners and academics interested in the challenges of structuring interactions for subject matter experts (SMEs) who are providing knowledge and/or feedback to an AI system, but are not well-versed in the underlying algorithms. Since the information provided by SMEs directly effects the efficacy of the final system, collecting the correct data is a problem that navigates issues ranging from curating data that may be tainted to structuring data collection tasks in such a way as to mitigate user boredom. The goal of this workshop is to discuss methods and new paradigms for productively interacting with users while collecting knowledge.}, journal={PROCEEDINGS OF THE 24TH INTERNATIONAL CONFERENCE ON INTELLIGENT USER INTERFACES: COMPANION (IUI 2019)}, author={Christensen, Johanne and Bae, Juhee and Watson, Benjamin and Talamadupula, Kartik and Spjut, Josef and Joines, Stacy}, year={2019}, pages={131–132} }
 @article{bae_watson_2014, title={Reinforcing Visual Grouping Cues to Communicate Complex Informational Structure}, volume={20}, ISSN={["1941-0506"]}, DOI={10.1109/tvcg.2014.2346998}, abstractNote={In his book Multimedia Learning [7], Richard Mayer asserts that viewers learn best from imagery that provides them with cues to help them organize new information into the correct knowledge structures. Designers have long been exploiting the Gestalt laws of visual grouping to deliver viewers those cues using visual hierarchy, often communicating structures much more complex than the simple organizations studied in psychological research. Unfortunately, designers are largely practical in their work, and have not paused to build a complex theory of structural communication. If we are to build a tool to help novices create effective and well structured visuals, we need a better understanding of how to create them. Our work takes a first step toward addressing this lack, studying how five of the many grouping cues (proximity, color similarity, common region, connectivity, and alignment) can be effectively combined to communicate structured text and imagery from real world examples. To measure the effectiveness of this structural communication, we applied a digital version of card sorting, a method widely used in anthropology and cognitive science to extract cognitive structures. We then used tree edit distance to measure the difference between perceived and communicated structures. Our most significant findings are: 1) with careful design, complex structure can be communicated clearly; 2) communicating complex structure is best done with multiple reinforcing grouping cues; 3) common region (use of containers such as boxes) is particularly effective at communicating structure; and 4) alignment is a weak structural communicator.}, number={12}, journal={IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS}, author={Bae, Juhee and Watson, Benjamin}, year={2014}, month={Dec}, pages={1973–1982} }
 @article{bezerianos_dragicevic_fekete_bae_watson_2010, title={GeneaQuilts: A System for Exploring Large Genealogies}, volume={16}, ISSN={["1941-0506"]}, DOI={10.1109/tvcg.2010.159}, abstractNote={GeneaQuilts is a new visualization technique for representing large genealogies of up to several thousand individuals. The visualization takes the form of a diagonally-filled matrix, where rows are individuals and columns are nuclear families. After identifying the major tasks performed in genealogical research and the limits of current software, we present an interactive genealogy exploration system based on GeneaQuilts. The system includes an overview, a timeline, search and filtering components, and a new interaction technique called Bring & Slide that allows fluid navigation in very large genealogies. We report on preliminary feedback from domain experts and show how our system supports a number of their tasks.}, number={6}, journal={IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS}, author={Bezerianos, Anastasia and Dragicevic, Pierre and Fekete, Jean-Daniel and Bae, Juhee and Watson, Ben}, year={2010}, pages={1073–1081} }