Contribution to Geocomp 2017 Keynote

One of the Geocomputation keynotes is going to be crowdsourced.  This is the first time that this has happened at Geocomputation.  The brave souls pulling this together are:  Dr Adam Dennett and Dr Dianna Smith.  I’ve added my thoughts/musing – copied below (please note these were written off the top of my head).  Do get involved and give your opinions on the subject, you will be credited on the keynote – go here.

Thoughts / questions / musings / predictions / observations and things that are getting you all excited about the future of GeoComputation as a sub-discipline

“As I’m from Yorkshire, I can’t just post ‘excited’ things about Geocomputation – I have to start with some whinging to get comfortable. My area of Geocomputation, individual-based modelling, has several very important methodological issues to overcome; understanding patterns in spatio-temporal data, simulating (human) behaviour and most importantly robustly calibrating and validating simulation models. With the heralding of ‘big data’, we have a real opportunity to use new forms of micro data to both improve the realism of our models, but also to give the rigor to calibration and validation. However, this hasn’t happened? Why? Personally I think that researchers have got distracted from the big issues in IBM (and Geocomp more broadly) through both these new forms of data and the easy DIY IBM frameworks that are abundantly available. I feel that IDEs (e.g. Netlogo, perhaps not so much Repast) that allow ABMs to be rapidly thrown together are having a negative effect. Journals are full of models that have little engagement with theory and are poorly calibrated and validated. Why is this important? Well, as academics we want our work to have a positive societal impact and be taken up by policymakers. There are innumerable challenges that now face us e.g. dealing with an ageing population, creating smart and sustainable cities etc etc. Technologies such as IBM can provide valuable insight that can help policy-makers etc in solving some of these issues. But without robust calibration and validation of these approaches (comparable to that found in climate models), these models remain academic playthings. IBM, especially ABM is a bit of an anomaly as its developed rapidly in several silo’s over the past 20 years – there is no centrally held ‘best’ practice and the discipline certainly needs input from other areas such as maths (error quantification), physics (handling non-linearity and complexity), computing (large simulations), sociology, human geography and psychology (behavioural frameworks and theory) to progress. To move ABM forward, the community needs to work together – but where to start?
Geocomputation is a rapidly moving subject and I feel the definition is very dynamic, changing with the current fad e.g. most people would associated ABM with Geocomp rather than other approaches e.g Bayesian. However, if we strip it back to basics, its as Andy Evans describes “the art of solving complex problems with computers” – increasing computer power, technology (sharing and dissemination platforms) and more data give us the opportunity to solve (and contribute to) these problems, and this is possibly the most exciting part of Geocomputation. But as a community will we ever get our act together and realise this potential?”

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