With online maps and geovisualizations becoming increasingly available, techniques are needed to facilitate their findability (see e.g. [1]). The aim of this thesis is to propose a model to rank these online maps during information search. The model will be tested through user ratings from a lab-based or online study.
Tasks include:
• Relevance criteria elicitation: compile a list of criteria that matter during relevance assessment of online maps and geovisualizations, based on a focus group discussion.
• Prototype development: implement a user interface to display most relevant online geovisualizations for a given query. The data from [2] will be used as input.
• Relevance model development: collection of user ratings (e.g. DCG) about the visualizations returned by the prototype and development of a model to estimate the relevance of online geovisualizations for given tasks. The model development approach can be inspired from [3]. Its sensitivity to the device type (e.g. Desktop vs Mobile) may be also evaluated.
Literature/references:
Degbelo, A. (2022) ‘FAIR geovisualizations: definitions, challenges, and the road ahead’, International Journal of Geographical Information Science, pp. 1–41. doi: 10.1080/13658816.2021.1983579.
Hüffer, P., Degbelo, A. and Risse, B. (2025) ‘Geovicla: automated classification of interactive web-based geovisualizations’, in. The 13th International Conference on Geographic Information Science (GIScience 2025), Christchurch, New Zealand.
Hu, Y., Janowicz, K., Prasad, S. and Gao, S. (2015) ‘Enabling semantic search and knowledge discovery for ArcGIS online: A linked-data-driven approach’, in Bacao, F., Santos, M. Y., and Painho, M. (eds) AGILE 2015 - Geographic Information Science as an Enabler of Smarter Cities and Communities. Lisbon, Portugal: Springer, Cham, pp. 107–124. doi: 10.1007/978-3-319-16787-9_7.
