The interdisciplinary nature of modern science adds to significant gaps in scientists’ performance caused by limited proficiency levels with diverse scientific tools and a lack of common language across different disciplines. Although developers of data intensive science platforms are slowly beginning to move away from function-oriented software engineering approaches and towards to user-centered design approaches, they rarely consider users’ value, and expectations that embrace different user contexts.
Further, there is an absence of research that specifically aims to support the broad range of users from multiple fields of study. Thus, a goal of this research is to investigate scientists’ experiences with interdisciplinary data-intensive knowledge resources and derive design implications for delivering consistent user experiences.
For this work, we examine:
- Implicit and explicit motivations for knowledge sharing
- Predictive models of online human behavior
- Data representation and visualization techniques to match users’ cognitive styles
- Adaptive interfaces that support steep learning curves with powerful & complex scientific software tools
- Jongsoon Park & Joseph L. Gabbard, (2016), “Factors that Affect Scientists' Knowledge Sharing Behavior in Data-intensive Cross-disciplinary Scientific Communities: Differences Between Explicit and Implicit Knowledge”, In review.
- Jongsoon Park & Joseph L. Gabbard (2014). "User Experiences with Open Access Knowledge Sharing Platforms Preliminary User-Centered Design Implications for Complex Data-intensive Domains". Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 58(1), 1496-1500.
- Randi Vita, James A Overton, Jason A Greenbaum, Julia Ponomarenko, Jason D Clark, Jason R Cantrell, Daniel K Wheeler, Joseph L Gabbard, Deborah Hix, Alessandro Sette, Bjoern Peters (2015). "The Immune Epitope Database (IEDB) 3.0". Nucleic Acids Research, 43(D1), D405-D412.
- Alice R. Wattam, Joseph L. Gabbard, Maulik Shukla & Bruno W. Sobral (2014). "Comparative Genomic Analysis at the PATRIC, a Bioinformatic Resource Center". Host-Bacteria Interactions. Springer New York, 2014. 287-308.