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I am a Lecturer in the Bio-Health Informatics Group at the School of Computer Science, University of Manchester. I am also a member of the Interaction Analysis and Modelling Lab.

CONTACT

markel . vigo at manchester . ac . uk

@markelvigo

+44 (0) 161 275 0143

2.32 Kilburn Building

School of Computer Science

M13 9PL, Manchester (UK)

PROFILE

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TEAM

Aitor Apaolaza (Post-doc)

Deemah Alqahtani (PhD student, Y2)

He Yu (PhD student, Y1)

Co-supervised PhD students

Julio Vega, Y4

Olu Matthews, Y3

Alaa Alahmadi, Y2

a cat

markel vigo

A picture of myself

I'm interested in understanding and modeling user behaviour in interactive complex systems. My research takes two complementary approaches:

  1. We build systems to facilitate the collection and analysis of user interaction data by removing barriers to data wrangling and pattern mining;
  2. We seek proxies that derive from user interaction and are indicators of search strategies, attention, usability problems and knowledge acquisition.

I'm currently working in three main spaces: in the health domain I explore how medication safety dashboards, EPRs, patient portals and health tracking apps are used by clinicians and patients; in the software engineering domain I examine how engineers construct knowledge artefacts (i.e. ontologies) and task models; and, finally, on learning systems, I'm working in finding navigation activities that are proxies of usability problems and knowledge acquisition.

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:

LATEST NEWS

December 2018 — A paper describing the MOVING platform was published in IEEE Multimedia.

We argue how the MOVING EU H2020 Project addresses the need of interactive learning platforms that enable open innovation. We describe how our approach relies on the Big Data paradigm for content indexing and learner interaction analytics. The paper will be published in the Special Issue on 'Multimedia Big Data Analytics in Technology Enhanced Learning'.

September 2018 — A paper describing three studies we ran to identify ontology authoring workflows in a data-driven fashion was accepted to the Journal of Web Semantics.

Automaton displaying the core workflow which is common to all settings

We run three studies with ontology authors addressing the continuum of expertise (from intermediate to expert users), the type of tasks (whether they are free-form or prescriptive) and the effect of the location (laboratory, tutorial or on their own) and how the studies are administered (whether or not there is a close supervision). While there are activity workflows that are particular to settings, the results indicate a number of core workflows that are common to all of them.