I am interested in how individuals interact with data-intensive, complex and critical information artefacts such as medical dashboards, engineering tools for safety critical systems and knowledge artefacts. Little is known about how to make these interfaces easy to use, mainly because the activities users carry out are not well understood. Conceiving and applying empirical methods to better understand the difficulties of the users, identifying the strategies employed to overcome these problems and discovering the activity patterns is the focus of my research.
I received a PhD in Computer Science from the University of the Basque Country about web accessibility assessment, evaluation and measurement. I keep active in the accessibility field and publish papers about
- Scoping and defining web accessibility;
- The perception of web accessibility by proffessionals;
- The limitations of automated accessibility evaluation tools;
- The role of expectations on user testing;
- and more recently we empirically analysed the relationship between user experience and web accessibility.
markel . vigo at manchester . ac . uk
+44 (0) 161 275 0143
2.32 Kilburn Building
School of Computer Science
M13 9PL, Manchester (UK)
January 2017 — Paper accepted to the International Journal of Human-Computer Studies: Real-Time Detection of Navigation Problems on the World 'Wild' Web.
We propose (and empirically validate in the field) a set of algorithms to detect Web navigation problems in real time. This approach is ground-breaking in that existing approaches are applied on a post hoc basis, which are resource consuming and prevent a prompt intervention to repair the cause of problems. Our work opens up new avenues to real time delivery of support and adaptive web interventions to alleviate the detected problems.
September 2016 — Paper accepted to EKAW: "Making Entailment Set Changes Explicit Improves the Understanding of Consequences of Ontology Authoring Actions".
When authoring ontologies, one single authoring action can have a number of implicit consequences that are difficult to grasp. This is a known problem for those who build ontologies. In this paper we address this problem by engineering a tool, the 'Inference Inspector' that makes this implicit changes not only explicit, but also understandable and actionable. We empirically suggest the effectiveness of our approach in two experiments with ontology authors.