Presenting Mental Models of User Interaction at the BIR Conference in Italy

The 22nd International Conference on Perspectives in Business Informatics Research (BIR 2023) was hosted by the University of Camerino in Italy. The conference offered a diverse range of talks covering topics related to business informatics such as open data, process mining, digital twins, knowledge graphs, and IT governance.


Dagoberto Herrera(ESR 2) attended the event and presented the manuscript titled “User Interaction Mining: Discovering the Gap Between the Conceptual Model of a Geospatial Search Engine and Its Corresponding User Mental Model”. This research was the result of collaboration between the Universidad Zaragoza and the National Geographic Institute of Spain (IGN), where Dagoberto completed his industrial secondment. The full proceedings have been published in the Lecture Notes in Computer Science (LNCS).


The agenda included the opening session by Bastiaan van Loenen, associate professor of Geoinformation Science at Delft University of Technology and scientific coordinator of the EU project Towards a Sustainable Open Data Ecosystem (ODECO). This keynote focused on discussing the value that open data can have for businesses and featured contributions from Maria Elena Reyes (ESR 6) and Ashraf Shaharudin (ESR 15). In the field of open data, the presentations “Analyzing Open Government High-Value Datasets” by Maria Ioanna Maratsi (ESR 7), “Open Government Data in educational programs curriculum” by Georgios Papageorgiou (ESR 9) and “Predicting Patterns of Firms’ Vulnerability to Economic Crises Using Open Data” by Mohsan Ali (ESR 5) also stood out.



The presentation of Dagoberto Herrera (ESR 2) “User interaction mining: discovering the gap between the conceptual model of a geospatial search engine and its corresponding user mental model” described a case study conducted at the IGN. In this research, twenty-one participants, including novice and expert users, performed a search task with a new geospatial search engine. Their interactions were recorded as event logs and analysed using process mining techniques. The results helped to identify areas for improvement in product design that stem from understanding the differences between the conceptual design of the interface and the mental model of the users. This case study illustrates the potential that user interaction mining can add to the design and evaluation of future user interfaces, ultimately improving the discovery of open data.



The presentation slides can be viewed at the following link.