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Table 2 Summary of the components of the canvas sort activity

From: The Enzyme Portal: a case study in applying user-centred design methods in bioinformatics

Component added by the users to the canvas Description of the component UCD information and useful outputs from the component
Canvas name Users were required to select the name of the canvas and to choose data cards to put onto the canvas. Category names, in the users own words, were useful for the site map, information architecture and for understanding the overarching concepts that were important to the users.
Data card selection Data cards were based on data items extracted from our existing resources and also requests during the interview process such as “enzyme reaction”, “enzyme mechanism” and “chemical compound/ligand”. These were printed in duplicate onto white card and cut out to any reasonable size. Blank cards were also available so users could create their own data items if none of the available were appropriate. After selecting a number of data items users had to democratically vote to keep only six using the dot voting method [as described in [29]). This was the prioritisation task of the exercise. By allowing only 6 items to be collated on one canvas, it forced participants to prioritise which were most valuable to them.
An incidental benefit of this approach was that users’ awareness was raised, regarding the data items we could provide via EMBL-EBI public data resources.
Actions On sticky notes users had to describe what actions they wanted to perform on these data items. Nouns (data items) and verbs (actions) needed to be captured in the workshop in order to translate them into specifications for the Enzyme Portal design.
How to get there? Describe how they could navigate to this canvas. This gave insight into the navigational structure that users required.
Where to go next? Describe where they would want to get after this canvas. This gave insight into the navigational structure that users were after.
  1. The main purpose of the canvas was to identify what data was valuable to users at each point of the workflow and how users wanted to interact with the data. The workflow was also captured by the final two sections, which describe how users got to this canvas and where they would like to go next.