Representing user perspectives in IT systems

Taking into account user perspectives when designing technology means that the technology should fit around their concerns and perceptions. This process is generally called “user-centered design” (see for example: Why is this important? It can lead to more simplicity, fewer errors and more satisfied users. There are other advantages that go deeper – such as gaining new insights into what users really require.

The key components of a perspective can be described as follows:

Concepts: how do we describe and visualise the world?  For example, when we prepare documents online, we think of objects such as text and diagrams. These are the concepts. They also include applicable operations (create, edit, save etc.) and the workflow of producing a document. Similarly, when we look up an online map, the concepts include streets, buildings, green spaces etc. Going shopping among physical shops also involves a workflow with applicable operations.

Concerns: what kind of things are important? (including goals, values etc). For example, academics are often concerned about collaborative documents being easy to produce and manage, as well as meeting paper submission deadlines. A user with low literacy may be concerned about completing an online form correctly without assistance. Differing concerns cause key concepts also to differ. For people with mobility restriction, concepts such as “easy walking area” or “slow traffic” on a map may be key, while drivers with busy schedules might look for “fast traffic”.

Representing user perspectives in IT goes way beyond usability or UX (although that is important). In my view, it should satisfy the following requirements:

1. It should be about the actual actions of the IT infrastructure the user is depending on to satisfy their goals. To what extent are the user concerns actually guiding the infrastructure resource allocation and priorities? This is particularly an issue with healthcare systems and privacy.

2. The infrastructure that the user depends on should be transparent and accountable. The visibility should be adjustable depending on the perspective of the particular user.

3. It’s not just about end-users or customers, but also about staff roles within an organisation. For example, a system administrator will have different concepts and concerns from those of a software developer (although both roles now increasingly interact together in the field of “DevOps”). So “the things that matter” then include: “does this help me to do my job effectively? does it cause more complexity and stress? does it reduce errors or create more potential for errors? does it support creativity?”

4. It’s not just about design; it’s also about models based on a user’s perspective. Models allow automated decision-making and prediction. Examples include statistical predictions based on user preferences. These could be said to represent some aspects of a user’s perspective. But I am thinking here particularly about qualitative models. These are models that represent the user’s concepts and concerns in a symbolic language. The language must be human-readable and machine-readable. These topics take us into the field of knowledge-based systems, which I will talk about in a later post.

Smart Assistance for Lifestyle Decisions

Smart assistance technology helps users to achieve goals using informative messages such as recommendations or reminders. To be “smart” the messages need to be sensitive to the user’s changing context, including their current knowledge and perceptions, their mood and environment.

Right now, I’m starting to explore the feasibility of a “smart assistance” app to support users with everyday decisions, for example with food, shopping, finance or time-management. When stressed and overloaded with information, we tend to be influenced easily towards decisions we would disagree with if we had the right information and time to think. Although goals may be set, they are pushed aside by other pressures that are more short-term. Poor decisions cause poor health (and also poor mental health and other negative outcomes).

The project is funded by an UnLtd small grant through the University of Manchester Social Enterprise innovation initiative:

Why is this new?

There are lots of apps out there (see for example, but most are targeted towards individuals as “consumers”, and do not address the more challenging psychological and social problems. Usually they are just addressing a single issue in isolation, such as exercise. Although Google and Apple have started to develop “health platforms” ( they are mostly concerned with integrated sensors and tracking of physical health, not with psychological health.

Some initial requirements

These are the broad requirements that I am starting with:

  1. Citizen led: the users should be in control of both the technology and the process by which they improve their decisions and action.
  2. Promoting reflection and reasoning: reflection and reasoning are high-level cognitive processes that can put the user in control because they involve awareness, deliberate goal setting and planning. This contrasts with behavioural “nudging” which affects decisions unconsciously and have been criticised as unethical ( For this reason I think the app should be called a “cognitive assistance” app.
  3. Promoting social support: Decisions are influenced by the wider social context. Therefore the app should not just be helping individuals in isolation, but must take account of their social environment and promote social support.

Some technical and research challenges

One way to help people resist pressures to make bad decisions is to raise awareness of significant and relevant information (such as why the original goals were set in the first place) and to encourage reasoning. In particular, this might include the following:

  • Smart prompts and reminders – sensitive to the person’s mood and circumstances. Users could also be prompted to send encouragement to others when they may need it.
  • Visualisations to draw attention to the important things, when a user is overloaded with information and options.
  • A kind of dialogue system to help with reasoning (not necessarily using text)

Getting these right is extremely challenging. In particular, the app must be sensitive towards the user’s state of mind and changing context. Smart sensor technology can help with this. (See for example, the MindTech project at The challenge that particularly interests me is the modelling of the user’s mental attitudes so that the reminders are not disruptive or insensitive. To support reasoning, some principles of online Cognitive Behavioural Therapy ( may be applied. In future posts I will discuss the role of theories and models, as well as the participatory software design process.

Ownership of Health Data

I’ve been thinking about ideas for the upcoming HealthHack ( In addition to participatory design (see last post), I’m also interested in transparency and accountability of eHealth infrastructure. Health apps and devices often record real-time data.  Examples include “ecological momentary interventions” that ask patients how they are feeling, and smart sensing devices that transmit data on activity or physiological states.

If I am using a device that produces real-time data, I would like an app that can provide the following information:
(a) What is happening to the data produced by the device? Where does it go, and where is it stored? Which service providers are involved? What are the estimated risks to integrity and privacy in each case?
(b) Which humans can see the data and why? What decisions can they make?
(c) How is the data processed? What algorithms are applied to the data and why? E.g. visualisation, decision support. In each case, what are the risks of error?

Some important points:
1. This is not only about data, but also about processes and organisations.
2. It’s not just about privacy, but also about integrity and reliability.
3. The client or patient need not understand the information in detail, but they may consult an independent expert who can understand it – just as with open source software.
4. Ideally we need modelling on multiple levels of abstraction (e.g. a component can be a secure wireless connection, or it can be an algorithm).

Although this requires some challenging modelling, I think we can start to make the first steps by tracking the data, showing where it is going, and what algorithms or organisations are using it. The next challenge would be ensuring that only acceptable things are happening. More on this later…

Some explorations in Javascript

To get familiar with javascript best practices, I started a small project to improve user control of a web experience. I often get annoyed at the way some websites assume a certain cognitive style and don’t let me change anything (apart from maybe the font size for the whole page). So I put some code on GitHub at: This is currently very simple; it provides some hotkeys for changing the font size or colour of a section of text. For example, a user might want to mark some part of the text as important, or minimise/delete another section as irrelevant.

As a longer term aim, I support the idea of helping users to participate in the design and personalisation of their web or mobile experience. This is not just about the surface “look and feel”, but also about the underlying architecture: what kind of information is considered important, and how is it presented? An example might be a health advice application that adapts to the concepts and experiences of the patient. This is the idea behind “Health 2.0” which I have recently started to find out more about.