TY - JOUR
T1 - QueryCrumbs Search History Visualization
T2 - Usability, Transparency and Long-term Usage
AU - Schlötterer, Jörg
AU - Seifert, Christin
AU - Satchell, Christopher
AU - Granitzer, Michael
N1 - Funding Information:
Part of the work was developed within the East-Bavarian Centre of Internet Competence, Big and Open Data Analytics for Small and Medium-sized Enterprises (BODA), funded by the Bavarian Ministry of Economic Affairs and Media, Energy and Technology. Part of the work was developed within the EEXCESS project funded by the European Union Seventh Framework Programme FP7/2007-2013 under grant agreement number 600601.
Publisher Copyright:
© 2020 Elsevier Ltd
PY - 2020/4
Y1 - 2020/4
N2 - Models of human information seeking reveal that search, in particular ad-hoc retrieval, is non-linear and iterative. Despite these findings, today’s search user interfaces do not support non-linear navigation, like for example backtracking in time. We propose QueryCrumbs, a compact and easy-to-understand visualization for navigating the search query history supporting iterative query refinement. We apply a multi-layered interface design to support novices and first-time users as well as intermediate and expert users. The visualization is evaluated with novice users in a formative user study, with experts in a think aloud test and its usage in a long-term study with software logging. The formative evaluation showed that the interactions can be easily performed, and the visual encodings were well understood without instructions. Results indicate that QueryCrumbs can support users when searching for information in an iterative manner. The evaluation with experts showed that expert users can gain valuable insights into the back-end search engine by identifying specific patterns in the visualization. In a long-term usage study, we observed an uptake of the visualization, indicating that users deem QueryCrumbs beneficial for their search interactions.
AB - Models of human information seeking reveal that search, in particular ad-hoc retrieval, is non-linear and iterative. Despite these findings, today’s search user interfaces do not support non-linear navigation, like for example backtracking in time. We propose QueryCrumbs, a compact and easy-to-understand visualization for navigating the search query history supporting iterative query refinement. We apply a multi-layered interface design to support novices and first-time users as well as intermediate and expert users. The visualization is evaluated with novice users in a formative user study, with experts in a think aloud test and its usage in a long-term study with software logging. The formative evaluation showed that the interactions can be easily performed, and the visual encodings were well understood without instructions. Results indicate that QueryCrumbs can support users when searching for information in an iterative manner. The evaluation with experts showed that expert users can gain valuable insights into the back-end search engine by identifying specific patterns in the visualization. In a long-term usage study, we observed an uptake of the visualization, indicating that users deem QueryCrumbs beneficial for their search interactions.
KW - n/a OA procedure
U2 - 10.1016/j.cola.2020.100941
DO - 10.1016/j.cola.2020.100941
M3 - Article
SN - 2665-9182
VL - 57
JO - Journal of Computer Languages
JF - Journal of Computer Languages
M1 - 100941
ER -