Besides that sporting event taking place in some city, there’s been plenty to chew on over the last few days on the Open Science circuit. First up is a video I stumbled across on Open Notebook Science. It’s presented by Jean-Claude Bradley at the University of British Columbia School of Libraries. The talk covered several topics, including the implications of Open Notebook Science for storing and retrieving scientific information through the use of wikis:
- Publishing in the Era of Open Science part one and part two
- Altmetrics and the future of Bibliometrics
- Interview with Ivan Oransky of Retraction Watch
- Footprints and Shadows: Assessing the academic’s presence in the digital world
- Geneticists eye the potential of arXiv
- How and Why the RCUK Open Access Policy Needs to be Revised
- Open Access Mandates and the “Fair Dealing” Button
- Wikipedia and Geology
Image of the Day:
One of the emerging dangers we’re seeing is the rise of predatory open access journals. The website, Scholarly Open Access, has a list of these dubious publishers based on a relatively comprehensive criteria and it’s also where I discovered the above journal. The Journal of Buffalo Science is a funny example of this problem, but I imagine predatory journals are something that’s going to become persistently more problematic as the open access movement continues to gain traction.
Arbitrary Olympic Mention of the Day:
You didn’t think I would finish this blog post without mentioning the Olympics? It appears that everyone is finding some way to mention the Olympics, irrespective of whether or not they actually have something interesting to say. Thankfully, Markus Gesmann, of the brilliant R-Bloggers, is firmly on the side of interesting: he posted a simple log-linear model of the men’s 100m sprint final (predicting a winning time of 9.68s with a prediction interval from 9.39s to 9.97s). As most of us probably know, Bolt came through in a winning time of 9.63s, which is less than a 1% difference from his prediction (see Markus’ graph which I reproduced in RStudio below). It’s relatively simplistic for a number of reasons (some of which Markus highlights) and, if I were to try and improve the model, then we’d need to account for the fact that Olympic times aren’t going to continue to decrease in a linear-like fashion: there’s an obvious physical limitation on what the human body can achieve.
Of course, we could always allow for the Cheetah model fixing algorithm.