Data, Knowledge and the Climate

by graydaniels on January 21, 2012 · 2 comments

in KMb Articles,Sustainability Articles

It seems obvious to me now that knowledge mobilization (KMb) is a horizontal concept, but this was not always so. Once upon a time I looked at KMb as many do, as a discipline on its own, something that was often mistaken for communications.

While KMb is certainly an area of academic research it is much more than that. KMb is a tool, like computers and mathematics and it applies everywhere, across many fields, and its guiding principles help filter the data we have to tell useful and valuable stories that will lead to positive action.

Perhaps part of the issue is that the KMb spectrum is poorly defined. To help with this, I refer to KMb research as theoretical KMb and application as applied KMb.

Applied KMb is a broadly useful (and potent) horizontal tool. In fact with the right combo and use of KMb, computer expertise and math I venture that one can tackle any problem or any pool of data and turn it in to a useful solution. This is my interest – mastering those three areas (which I will call the big 3 from now on) and using those tools to find solutions to important problems.

Applied Knowledge Mobilization Project

I’ve certainly made no secret of my love for nature and my desire help solve environmental problems. It is evident that this is an area where the big 3 are extremely important. Recently I started a project through Natural Resources Canada to help develop climate models for specific areas in the Canadian Arctic. This blog will chronicle my work, prep, challenges and journey with 2 goals in mind.

The first goal is to illustrate the deep connection between effective KMb and environmental solutions as well as to highlight the importance of the application of the big 3 tools (again that being computers, math and KMb principles).

The second is goal is much more modest, but no less important; and it is to entertain those who choose to read this blog. So it is my hope that at the end of this blog series you will emerge both entertained, and with a really good idea of the power of the big 3 and how they can be applied to solve not only environmental problems, but problems of all kinds.

I am of course the protagonist of my own story, and as such would like to paint myself of the James Bond of climate analytics. For the readers’ sake I certainly hope my journey contains a lot of excitement so that I can write about it. So with that in mind, let the story begin.

This whole journey began not 3 weeks ago, when I was sitting in the airport in Kelowna, BC coming back from visiting my family for the holidays. It was a sunny warm winter day in the Okanagan. Most people in Canada are not used to those adjectives being used to describe winter days but the Okanagan is certainly a unique place. Arid, warm, and mountainous it exists in stark contrast to anywhere else in Canada. It is easy to see, when driving though the dry desert mountains, how people could feel as if they were in the American southwest.

The Okanagan is the northern tip of the Sonora Desert the runs all the way down to Mexico, Canada’s only desert. It is truly an interesting biotic zone; with sagebrush, cacti, sand and tumbleweed. It was even the site of the western movie Gunless. We in Canada are fortunate to live in a beautiful and diverse country, so for those of you who haven’t been to the Okanagan I highly recommend it.

At this time of course I was dreading returning to the frozen land of Ottawa. I was reading a book on quantum physics to pass the time. In fact, these days I read very little else other than physics or earth sciences, I don’t know why that its; likely a combination of the fact that both of those subjects are of great interest to me, and I am a bit too ADHD for fiction (for those of you interested in retro-engineering dinosaurs from latent bird genes check this out http://dsc.discovery.com/news/2009/03/05/dinosaur-chicken.html. Jurassic Park anyone?).

Upon getting to a point in the text highlighting the math behind solving the Schrodinger equation I had to take a break (it was at that point that I began to redline mentally, check it out if you’d like http://scienceworld.wolfram.com/physics/SchroedingerEquation.html ).

It was Internet surfing time! News, sports, puzzles and weird little factoids, and like 90% of us my surfing lead to Facebook.

My friend Jackie Dohaney, who is a Geologist in New Zealand at the University of Canterbury, had put up an add that she came across detailing how NRCan and their various partners on the project, were looking for someone to help with paleoclimate analytics. For those of you who are unfamiliar with the term, paleoclimatology is just the study of the climate, past and present, of the earth, or to quote Wikipedia, “the study of the changes in climate taken on the scale of the entire history of Earth.”

This sounded right up my alley! Getting a chance to play with climate data, the words SUPER COOL leaped energetically to mind. So I wrote the project lead, detailing my interest and experience with data mining and analytics. To be honest I did not expect a quick response, but she wrote back to me extremely quickly, just as I was boarding the plane in fact. She seemed extremely interested in speaking with me, and so it began… the kick off to 2012.

{ 2 comments… read them below or add one }

david phipps January 21, 2012 at 12:05 pm

Computers, math and KMb: a powerful combination. Computers, analysis and KMb would be widely applicable in a research to action praradigm but adding math refines the combination and creates more power to address complex issues. Good luck with the paleoclimatology, Gray. We often align KMb with social policy but cConnecting research to practice can be equally applied to “hard” science to inform science policy.

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Gray January 22, 2012 at 1:42 pm

Hi David, thanks for the kind words, and I’m glad you think so. I have often thought that mastery of these tools, what I am calling the big three, are the key to working on solving a variety of problems in the data age, from social to hard science. Much like being a builder, if you master the tools you can work with almost any material and to build something great. I am certainly excited about playing with the climate data, and as you will see there is a huge traditional knowledge component in the climate modelling as well. Truly an example of Applied KMb

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