Blog 1 – The Edge of Chaos. Reading, Presenting, & Revisions

So after roughly 3 months into my research PhD, there’s a lot to talk about!

My continued place on the PhD is subject to the submission of a revised proposal which was submitted at the beginning of the month, so fingers crossed!

My first few weeks had me reading and writing a lot (something I’m going to have to get used to again!)

My initial research was looking into how data could be used in games to create interactive data visualisation games for citizen science projects.

During these weeks, my focus was upon data visualisation, and data uses in games.  My key sources were Information Visualization, by Colin Ware and The Visual Display of Quantitative Information, by Edward Tufte. My reading of this area was in part to gain a better understanding of how data is represented in other forms, to assess the standards utilised within the visualisation of data, and also some semblance of where interactive data visualisation lays. It seems that there are a wide array of different ideals when it comes to data visualisation, but the main rules float around data accuracy and readability. Even within these, there are various different approaches. Tufte is a strong advocate of creating minimalist visualisations, utilising what he calls the “data-ink-ratio” to the best of one’s advantage. He also does not really agree with the use of elements which aim to prettify the data (vignettes, colours, patterns, etc…) which he refers to as chartjunk, stating that if it does not make the information more legible or clear, then it should be removed. [9] Research material on data uses in games was a difficult area to investigate, as there are very few games that use large datasets (or so I’ve found,) and the games/companies that do use them do not reveal very much about how the data is used. I also began looking at citizen science games.

One of the Citizen Science games I explored is called Forgotten Island. This game is less about using data as it is about gathering it. Forgotten Island was created to identify specie of moth. The game itself feels fairly contrived. A fair amount of work has been put into aspects of it, but there are many issues in its gameplay, story and integration. The science aspect also feels quite tacked on. I did not enjoy the experience of playing, but I think the task of making a moth identification fun and attractive is not a very simple one. I do take my hat off to the developers for the work put in! [8]

So, I had a couple talks lined up for February. One of which (the first one) was in Glasgow, where I would present my findings so far. The unconference was entitled “Game Think”. A week prior to the talk, I had quite a lot to discuss for it, but my supervisory meeting immediately prior changed my direction a substantial amount! I realised that I was diverging away from my original idea, which was about emergence and meaning in games using complex data! I had been reading a lot about data visualisation, when really I should have been reading about complex adaptive systems, chaos theory, and emergence… (doh!) I had to change my slides the night before the talk, to reflect my new (old) direction. The talk turned out fine, and the other talks were very engaging! From video games ecology, to indie game business marketability! I was quite impressed with the work, and the ideas! I also spoke to a few people who were quite interested in my research, but unfortunately I hadn’t moved on much (it was only a month in at that point! Plus I’d just switched my focus onto emergence and complex data.) I do hope you can forgive me interested people! (I will have some interesting things later on, I promise! 🙂 ) My next talk was on 9.03m (Video Trailer) a game that I designed and developed for my Honours project at Abertay University, and later took to Space Budgie for completion. This workshop was a combined effort between Abertay University and the National Theatre of Scotland. Entitled Play Dundee Development Week, the workshop focused upon specific terms, functions and elements of both theatre and games, and explored the similarities and differences between them. My talk, which preceded the awesome talk of Ana Ines Jabares Pita (a theatre designer, whose fabulous work can be found here: http://anainesjabarespita.blogspot.co.uk) was about environment and space in game design, and in relation to 9.03m. The talk (which was roughly an hour in length) was the longest talk I’ve had to give before, and I was pleasantly surprised at how well it went.

So since that talk, my focus has been to look at emergence, and complex adaptive systems. One of the books I have been reading is Complexity: The Emerging Science at the Edge of Order and Chaos By Mitchell Waldrop. Within the first few pages, Waldrop talks about the edge of chaos which  he defines as being the point at which a complex system is in “balance”, showing the highest levels of complexity without turning chaotic. [10] I followed the trail to the origin of the term, and found that the term itself was coined by Doyne Farmer, a physicist, but that the phenomena he was describing was discovered by Christopher Langton, who in his research into cellular automata found that systems do not jump between different states, rather they phased between them. He created a diagram that depicts this, and in the centre is an area labelled “complex”, this is what is otherwise known as the edge of chaos. [5]

CA Rule Space
Figure 1: CA Rule Space by Langton, illustrated by theory.org – Schematic drawing of CA Rule Space

From this term, I realised my research title: Playing on the Edge of Chaos.

I also read a book entitled How Nature Works by Per Bak. He talks about his discovery of self-organised criticality, but also discusses complex adaptive systems. This almost compounds the idea of the edge of chaos in systems – in how systems are in a constant state of turbulence. [1]

I’m still getting to grips with some of the models, theories, and area concerning complex adaptive systems, but so far it’s quite exciting – even getting the chance to read about chaos theory in any depth!

Beyond this research, I’ve also been looking at games and how they are using data. The most notable (and recent) example I have looked at is Elite: Dangerous [2]. Not only is it an extremely interesting, immersive, and fun game, but it also uses over 160,000 real star system data we have here on earth! [3] You can fly your ship to star systems that you’ve been looking at through your telescope, and have a dog fight with a bandit around their collapsing star. Being stuck for free time, I have not had the ability to play it in any depth, but from what I have played the game is pretty good! On a more topical note, the data they use of star systems is not used to create emergent properties, nor would I say it does so. The data is used for simulation purposes. This is where I began looking at different types of games in terms of their data uses. What I’ve found so far is that there are 4 different types of “game” related uses for data. These are Simulation; Citizen Science; Expression; Tools and Technology. So far I’ve only found one example of a game in the expression category, so I’ll wait until the next blog post before I discuss the games (plus this post is getting quite long), after I’ve tried to build up a more vibrant list.

So anyway, back to reading now – I’ve included some of my reading list below for you to look into if you so wish. Feel free to leave a comment, or get in touch!

Until next time.

Karl Inglott

Reading list

[1] BAK, P. (1997). How nature works. New York, NY, USA: Copernicus.

[2] FRONTIER DEVELOPMENTS. (2014) Elite: Dangerous. [DOWNLOAD] PC. Cambridge: Frontier Developments.

[3] HOGARTY, S. (2015). Every star in the night sky exists in Elite: Dangerous — Braben on recreating a galaxy all over again. [online] PCGamesN. Available at: http://www.pcgamesn.com/elite-dangerous/every-single-star-in-our-night-sky-is-in-elite-dangerous-david-braben-on-re-creating-a-galaxy-all-over-again [Accessed 27 Jan. 2015].

[4] HOLLAND, J. (1998). Emergence. Reading, Mass.: Addison-Wesley.

[5] LANGTON, C. (1992). Artificial life II. Redwood City, Calif.: Addison-Wesley.

[6] LANGTON, C. (2000). CA Rule Space by Langton, illustrated by Avnet – Schematic drawing of CA Rule Space. [image] Available at: https://theory.org/complexity/cdpt/html/img101.png [Accessed 24 Feb. 2015].

[7] PEITGEN, H. AND RICHTER, P. (1986). The beauty of fractals. Berlin: Springer-Verlag.

[8] PRESTOPNIK, N. AND CROWSTON, K. (2011). Exploring Collective Intelligence Games With Design Science: A Citizen Science Design Case. [pdf] Available at: http://crowston.syr.edu/sites/crowston.syr.edu/files/designing%20citizen%20science%20games.pdf [Accessed 27 Jan. 2015].

[9] Tufte, E. (2011). The visual display of quantitative information. 2nd ed. Cheshire, Conn. (Box 430, Cheshire 06410): Graphics Press.

[10] WALDROP, M. (1994). Complexity: The Emerging Science at the Edge of Order and Chaos. London: Penguin Group, pp.9-13, 152.

[11] Ware, C. (2013). Information visualization. Waltham, Mass.: Morgan Kaufmann.

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