This is an archival copy of my PhD blog, which was active between 2009–2015. I'm publishing it again as a personal time capsule, but also because I think it's an interesting documentation of the PhD process itself, which might be useful to someone, somewhere. – Chris Marmo, January 2026

Not all rangers have beards

This week I went to a seminar that focused on communicating research. It was a pre-requisite for entering the 3-minute thesis competition, which seems like a mini-TED for research students with a time limit. I don’t know if I’ll enter the competition (although there’s some impressive cash amounts up for grabs), but I’ll definitely be using some lessons from the seminar in my writing. The main thing I took away from it was the importance of having a story around the research, and allowing people to feel an emotional connection to it. This post is my attempt to add that story.

The story of National Parks

People love national parks – they are places families go, where summers are spent, and where kids grow up. They provide an escape from architected office buildings, armpits on crowded trains and suburban peak hour traffic. The air is fresh, and the landscape is rejuvenating.

When such a place is ravaged by fire, those that have developed a connection to it feel violated – it’s as if their house has been burgled. An uninvited stranger crashes through, sweeping away the things they feel that connection with and leaving a shell. Like being burgled, it’s not just the memory of absent things that lingers – it’s the thought that the once unquestionably secure destination is no longer so. We never feel completely at home again.

On top of this, fire is devastating for the ecology of a park. When controlled, it is a necessary part of managing the landscape. When unplanned, it can permanently damage the land and the lives of the creatures that inhabit it.

It’s important that we do all we can to manage the risks of unplanned fire.

Some rangers live in the city, and not all of them have beards.

Luckily, there are people whose job it is to do this. Parks rangers are often based in the same park for many years, and over this time they learn to recognise signs in the environment that warn them that a fire may get beyond control. They have sensors that tell them about fuel levels and soil moisture, but, like most of us, they also rely on their instinct, or their tacit knowledge.

At the same time, back in the city, there are people who don’t wear khaki shorts who play just as important a role in the park. These people keep track of ecological research about parks, plan studies to discover populations of rodents, and keep tabs on the regrowth of native scrub. They also coordinate external groups of volunteers and researchers who contribute information back to the organisation, and provide those “on the ground” with the data they need to make decisions.

Both types of park ranger contribute to keeping the ecological balance necessary for healthy parks, and healthy people. However, both are struggling under the sheer weight of data available to them. Relevant scientific studies get lost in filing cabinets, and even when they are accessible they are not easily integrated into management plans. Similarly, rich, tacit knowledge is not accessible to other staff, and is lost completely when rangers retire or move on.

So on one hand, they need help dealing with the sheer quantity of data available to them. On the other, there’s a need to capture the rich, experiential knowledge that can help bridge the gap between the numbers, the park and the people in it.

A consensus of interpretation

The one common element to all of this data, information and knowledge is location. Reports are about regions in a park, rangers visit specific points and extrapolate their assessment to broader areas, and remote sensors are scattered in the park, forming a virtual topography of data on top of the natural environment.

Given the located and situated aspect of park management, it makes sense to give rangers tools to view information through the lens of location. It makes even more sense to give them tools through which they can record, interpret and use information about these places in the places themselves.

There are bodies of research that indicate that information makes more sense to us, and is more useful, when presented in the same context in which it is to be used. Facilitating the exploration of information in the places they are about can lead to the generation of better quality understandings of this information.

Similarly, we want to allow rangers to add their own meaning on top of this raw information, and to share and evolve that with other rangers. There’s also research, and indeed entire disciplines, that focus on computer supported collaborative work and show that the shared interpretation of data leads to better outcomes.

In the cloud

What this research plans to do is allow rangers to explore and interpret data about places, through mobile technology, in those very same places. Similarly, we want to allow rangers to share their interpretations of data with other rangers. By interacting with information and each other through mobile technology, rangers will ultimately form a human filtered and rich-in-quality body of knowledge that lives “in the clouds” above parks.

By giving rangers better access to the most important knowledge about parks, and particularly knowledge around fire management, they will be better equipped to manage and prevent unplanned fires. Uninterrupted, families can continue to form memories tinged with green, native flora and fauna can continue to flourish, and rangers can continue living in the country or in the city and with full freedom of choice around facial hair.

/eom

Well, that’s my first shot at adding some kind of narrative around what I’m doing. I’m in the process of applying to a doctoral consortium, and think this will really help me add context and reason to the more academic details. Thanks Inger!

Context: awareness vs sensitivity

I’ve been doing a lot of reading and writing around context awareness the past couple of months – so much so that I changed the subtitle of this site to include it. It’s safe to say that the notion of this kind of awareness completely captured my imagination, or at the very least, led me to line up a whole stack of journal articles and books on the topic.

With the plethora of location-based applications appearing on various mobile platforms, the ubiquitous nature of geo-tagged data and the popular medias seemingly undying thirst for the latest tech-innovation, location enjoyed a pretty good ride in 2010. Starting at location as a focus of research (as I did), it’s not long before you realise that a coordinate is just one piece of metadata that can describe context, and it seems like a natural progression to begin thinking about broader notions of the term.

The next thing you realise after reading all about the current attempts at context-awareness is that, well, they suck fail to be all that useful.

There are many very intelligent systems-based frameworks for building an architecture of sensors that can detect where and what you’re doing, and very detailed examples of software implementations that aim to interpret this sensor-based data to assist their users. It’s not that these frameworks and implementations are poor or under-thought, it’s simply that the technology isn’t there yet, and our expectations are too high.

Great Expectations

This isn’t our fault though – the term “aware” is loaded with expectation. It immediately conjures notions of Asimov-type robots that basically act and understand as we do – of computational uber-humans superior to us in every way – and ones that we will either grow to love or fear completely.

The problem is hinted at above – in the interpretation. Whilst we might have sensors that can pinpoint you on a map, know who you’re with, whether you’re talking or not, walking or not, whether you’re standing, sitting, or lying down, the problem lies in the translation of this sensorial information into meaningful, and accurate interpretations for software to use.

The optimist and sci-fi fan in me thinks that, one day, we will see a convergence of sensor technology and artificial intelligence that will provide useful scenarios to people. You might argue this happens already – a pilot’s cockpit springs to mind. But the fact remains that the detection of meaningful, dynamic and social context is a long way off.

Context is socially constructed

I’m working on a longer article on this at the moment, so I won’t go into too much detail. It is worth noting however, that whilst the cockpit of a plane is a highly controlled environment where all variables are know, much of what we would define as context is socially constructed. That is, its existence is fleeting, and only arises out of interaction between people, objects and the environment.

Whilst we may be able to detect your location fairly accurately, the context to your presence there is very difficult to detect. Test this next time you’re in a cafe – note all the different activities that are taking place there. The animated conversations, the quiet reading, the anxious waiting, the scurrying (or bored?) staff. For each of these actors, the place holds a completely different meaning for them – and hence, a different context.

Context Sensitivity

So if we can’t rely on technology to sense and interpret that kind of context, then what can we do? Well, I’m not sure I have any answers to this, but I would suggest that we first lower the expectations of and burden on our technology. When compared to “awareness”, a word like “sensitivity” seems much more realistic. We can’t do Bicentennial Man just yet, but what we can do is make intelligent assumptions about when, where and how our technology might be used, and we can selectively use sensed data to inform the design of our applications.

That is, I believe it is the role of design to augment the technology – instead of relying on technology to give us context awareness, we should rely on design to give us context sensitivity.

A synopsis

Inspired by a few different factors (Tricia Wang’s research overview, Patrick Dunleavy’s excellent “Authoring a PhD“, and this tweet – thanks Vicki!) I spent today going over my abstract and ended up writing a slightly more detailed synopsis of my thesis. Like everything on this site, the plan is to keep changing and updating this as thinking progresses.

In the meantime, I once again invite you to visit the abstract page – a brand new 600 words await.

Reference Piles


Completing a PhD is meant to show that you are able to stick at a complex topic and explore it in a disciplined and systematic way, paying attention to existing literature and eventually, after some years, adding your bit to the vast pool of human knowledge.

Research questions are the core around which you conduct these activities, and serve to focus your efforts when it comes to researching and exploring the vast amounts of information out there. Recently though, I find myself growing an increasing list of references in things that I’d really love to get a handle on, but seem to not have the time to digest fully. As a bit of fear of not remaining focus has crept in recently, I thought I’d consolidate some of my current and extra research interests. Inspired in a round about way by challenge piles, here are my Reference Piles representing the broad topics I’m interested in, and what questions I want to find answers to inside those.

Pile #1: Knowledge

I spent a long time trying to answer the question: “What is knowledge?”. It’s a lot harder than it sounds! I guess in 2.5 years time I will have taken a stance on it, but for now I’m going to remain deliberately vague and instead talk about what I think I need to know more about:

  • What I can learn from the more business-management style frameworks around knowledge, particularly tacit knowledge, or “know how”.
  • The more sociological side of things, revolving around communities of practice and the theories that discuss how we learn from each other, rather than what it is we actually learn. This should inform the design of a broader sense-making framework.

Pile #2: Visualisation

This is what I’ve written the most on in papers, etc to date and what I’m most comfortable talking about. I feel I’ve got a good handle on how we make sense of images, why they help us, and what makes a good one. Still, I’d like to find out more about:

  • Social objects, and how the actual artefact of a visualisation can be used to reach shared understandings. That is, how a visualisation can help groups of people understand versus just an individual.
  • Types and variations of geovisualisations and how I might be able to apply them

Pile #3: Location Based Services (LBS)

I’m positioning this research as exploring LBS in relation to a national park, but the reality is it is more context aware than location based as such. I’ve sort of started fresh with this in the last few weeks, so here is what I’m hoping to uncover:

  • Frameworks for talking about location types and the contexts that are applicable to them
  • An understanding of the technologies involved in provided context-aware applications. Particular the technical side of phone networks and GPS.
  • Definitions, studies and examples of LBS, mobile-based systems and ubiquitous computing, particular those that have a mix of intelligent information collection and delivery, coupled with a more traditional “desk bound” visualisation and sense-making interface

Pile #4: Parks Management and Ecology

Obviously one of the most important areas of a PhD dealing with natural environments – despite approaching it from a HCI/Technology perspective, I will basically have to become as close to a park ranger as I can. Further, I will need to understand:

  • What’s important when making decisions around park management, particularly when it comes to fire prevention
  • Even before that; What decisions are being made?
  • What is likely to be effective in assisting them?

Pile #5: Research Methods

As a user experience practitioner, I’ve been involved in a number of qualitative data research projects. For my PhD however, I want to:

  • Gain a deeper understanding of the methods available, when to use them and what results to expect
  • The opportunity to use some more experimental methods and report on their effectiveness
  • The opportunity to explore qualitative research papers and get to understand, from a research students perspective, what has and has not worked for other deep, PhD level studies.

Knowledge pathways

Knowledge Paths
A diagram showing the connections between people in a national park, and highlighting some of the knowledge that passes between them

I’ve spent the last few days making sense of the discussions and observations made during the Affective Atlas team’s visit to Wilson’s Prom. Discussions centered firmly around the acquisition and dissemination of knowledge and how collaborative and social technologies can help connect various people in and around a national park. Whilst simplistic, the diagram above is a representation of the connections between the two main groups: Parks Victoria staff, and park visitors.

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Wilson’s Prom visit

Looking over Squeaky Beach
Looking over Squeaky Beach

Last week the Affective Atlas team went to visit Wilson’s Promontory National Park. Myself and the other PhD student spent 3 days at the park – giving presentations on our progress to date (for me: not much), being shown areas of the park not usually accessible to the public, and touring the on-site offices.

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BurnMap Conversations

I thought it might be a good idea to note down some of the ideas inspired by speaking to members of the Affective Atlas team about the BurnMap project.

I found the process very helpful, especially at such an early stage in my PhD. It really got me into the right frame of mind to start thinking about what types of questions I’d like to explore and (possibly) answer. It’s also given me a great start in understanding the context in which I’ll be working, which will be a major part of the research I undertake.

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