The quality of paleoecological research depends strongly on site selection. If a researcher is asking a specific question (‘What was the effect of Holocene climate change on the position of treelines in the coastal mountains of BC?’) then they choose sites that are meaningful – sites at or near treeline in the coastal mountains of BC. The current network of paleoecological sample sites (I’m just going to use pollen sites here, but I recognize there are different kinds of sites!) reflects almost 100 years (has it been that long von Post?!) of site selection by researchers for specific research questions. Continue reading The quality of paleoecological research
We had a lab meeting this week where we talked a bit about some of the issues surrounding blogging, in particular we talked about trolls and their annoying trolling. I should be careful here, the term ‘troll’ has evolved a bit over the last few years. My understanding of a troll was generally someone who posted contentious material (inflammatory or offensive) for the purpose of getting a rise out of people or derailing a conversation. The most important part of the early definition was that the person was posting for the purpose of derailing the conversation, and often they did not believe what they were saying. As we move toward what I think of as the newer definition, it’s basically anyone posting inflammatory comments, whether they believe them or not. I’m going to use my second definition of the term troll from now on. Continue reading Thinking about trolls
I’ve just uploaded a version of a very large data set to our project wiki. We have been using dokuwiki to share our data, R code and ideas/meeting notes/biographies/general stuff and we’re getting to the point where a lot of data has been processed and finalized.
Going from ‘me’ code, which is messy, has digressions and is generally lightly commented, to ‘you’ code is a scary thing. Some of the data I use is bound by data sharing agreements, some of my collaborators aren’t useRs, some of my collaborators are very good useRs (which is a bit daunting as well). So how do you balance user needs, code requirements, and reproducibility? Continue reading Versioning R code
This is just a quick post, with a neat little trick.
I use Linux (Ubuntu) at home and Windows in the lab, which can be frustrating for coding in R since I like to keep my work in nicely sorted working directories. I used to have to have two ‘setwd’ commands at the head of every R file, one for Windows and one for linux, and I would just accept that I’d get an error thrown. No big deal.
Check this out:
That’s right friends, you know what part of my directory tree looks like. It tests whether I am in a ‘unix’ type system, and if I’m not, it gives me a Windows directory. Rad!
While I’m at it, Watch the Throne is a pretty decent album isn’t it?
EDIT; For the sake of posterity I’m going to keep this post up, but I would like to direct readers to this amazing resource (The R Inferno, should be required reading!) that goes into many of the issues surrounding vectorization in a really fantastic way.
James Brown talks about the Big Payback.
(they put an ad in front of that song, the soul-less bastards!)
But I’d like to talk about the big payback in another sense. As researchers we’re always looking for the payback. Our research funding is no payback for all the time we’ve put into reading papers that no one else has read, writing papers that no one else will read (maybe that’s just me) and all the administrative hoops we have to jump through (although pity those administrators who have to put up with us!). . .