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Information System designers report increasing difficulties applying User-Centred Design (UCD) techniques effectively due to the growing complexity of the domains in which they work and the techniques’ prescriptive nature. The rapid growth of “Big Data” and associated analytical tools thus demands closer investigation of UCD activities and processes within the complex and rapidly-changing work domains in which they are designed, developed and used. This thesis reports a longitudinal case study from inside a commercial organisation, through a six-year Action Research collaboration to introduce and embed UCD techniques in the design of health informatics tools in the UK. An assessment of the initial modus operandi is followed by the development of personas with data from interviews, user-generated screen captures and database server log files; these informed the redesign, evaluation and testing of the organisation’s flagship product. Finally, stakeholder interviews explore the wider impact of UCD techniques. In so doing, this thesis shows the value of auto-ethnographic documentation, based on being embedded in a design team and collaborative reflection, for practice-led research; it found the organisation’s culture around UCD was dynamic and design practices can change this culture through, for example, training opportunities and fostering customer relations. Individuals and extrinsic factors played strikingly key roles in reshaping the organisation’s culture; the commitment and resilience of individuals was important for sustaining UCD activities across several reorganisations and changes in business strategy. Finally, this thesis comprehensively presents and evaluates an innovative approach for grounding personas in database server and user-generated content. These findings concern both research and practice by informing the scope of the designer’s role, educational programmes and Action Research collaborations. They call for further attention on the compatibility of design and development processes and suggest that design practice can not only be tailored to organisations, but organisations can be fitted to design practice with the reassessment of the value of some UCD activities. Finally, this thesis can inform approaches to practice-led research, and more effective and efficient strategies for the introduction of UCD techniques to other organisations from the base of their hierarchy.

Spatial data collection, processing, distribution and understanding have traditionally been handled by professionals. However, as technology advances, non-experts can now collect Geographic Information (GI), create spatial databases and distribute GI through web applications. This Volunteered Geographic Information (VGI), as it is called, seems to be a promising spatial data source. However, the most concerning issue is its unknown and heterogeneous quality, which cannot be handled by traditional quality measurement methods; the quality elements that these methods measure were standardised long before the appearance of VGI and they assume uniform quality behaviour. The lack of a suitable quality evaluation framework with an appropriate level of automation, which would enable the repetition of the quality assessment when VGI is updated, renders the choice of using it difficult or risky for potential users. This thesis proposes a framework for quality evaluation of linear VGI datasets, used to represent networks. The suggested automated methodology is based on a comparison of a VGI dataset with a dataset of known quality. The heterogeneity issue is handled by producing individual results for small areal units, using a tessellation grid. The quality elements measured are data completeness, attribute and positional accuracy, considered as most important for VGI. Compared to previous research, this thesis includes an automated data matching procedure, specifically designed for VGI. It combines geometric and thematic constraints, shifting the scale of importance from geometry to non-spatial attributes, depending on their existence in the VGI dataset. Based on the data matching results, all quality elements are then measured for corresponding objects, providing a more accurate quality assessment. The method is tested on three case studies. Data matching proves to be quite efficient, leading to more accurate quality results. The data completeness approach also tackles VGI over-completeness, which broadens the method usage for data fusion purposes.