Manual inspection of individual user sessions provides valuable information on how users search within a collection. To support this inspection we present a session visualization tool, Metadata Augmented Graphs for User Sessions (MAGUS), representing sessions in a digital library. We evaluate MAGUS by comparing it with the more widely used table visualization in three representative tasks of increasing complexity performed by 12 professional participants. The perceived workload was a little higher for MAGUS than for the table. However, the answers provided during the tasks using MAGUS were generally more detailed using different types of arguments. These answers focused more on specific search behaviors and the parts of the collection users are interested in, using MAGUS’s visualization of the (bibliographic) metadata of clicked documents and selected facets. MAGUS allows professionals to extract more, valuable information on how users search within a collection.

Information visualization, Search behavior, Digital libraries, Metadata, Log analysis, User study
dx.doi.org/10.1007/978-3-030-54956-5_13
Lecture Notes in Computer Science
International Conference on Theory and Practice of Digital Libraries
Human-centered Data Analysis

Bogaard, T, Wielemaker, J, Hollink, L, Hardman, L, & van Ossenbruggen, J.R. (2020). Understanding user behavior in digital libraries using the MAGUS session visualization tool. In Digital Libraries for Open Knowledge (pp. 171–184). doi:10.1007/978-3-030-54956-5_13