a future science publishing vision

hi,

I lost sleep lately over the ideas I had on future science publishing. I wrote before that I think an independent publishing platform financed by an international group of public funding organizations would be an answer to several problems in academia of financial nature but also problems with internal academic evaluation systems.

So here is my sleepless-night-concept of how I would construct an archive system that covers many, maybe all, wishes I currently have – it may sound a bit like F1000 here and there, but it is different, I promise. And it doesn’t take any new technology at all, we just need to take what’s out there and mash it together like Jobs did with the iPhone (yes, guys, Apple just mashed technology together that had been invented financed by public funding ;)). My idea has two main components: a publication side and a community side.
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Hi,

the school I did my PhD at did not publish my dissertation for some unknown reason – they are usually pretty good at self-archiving these things. This might have been out of copyright reasons(?). However, I found out that all publishers allow me to self-archive the articles. Thus, I have no problem putting the whole dissertation online (yay!):

Optic Flow in Behavior and Brain Function of the Zebra Finch

Have fun

Dennis

Depth perception in small, flying animals – Introduction

Just recently the last article from my PhD thesis was published by Frontiers in Integrative Neurophysiology! I want to explain to you over the next few posts what my thesis was all about – several posts because I don’t like long posts :P. So, today I start with this brief introduction:

My collaborators and I want to know how small animals can see things during fast flight. Well, it is actually not only about just seeing things. Small animals, especially fast moving ones must be able to quickly realize where all the things around them are and which of those they might collide with if they don’t maneuver around them in time. Imagine you are a little zebra finch, just 12 grams body weight, and you are sitting at the water pond home in Australia minding your own business, taking a sip, washing the dust off your feathers or hopping around looking for grains to eat. And then all of the sudden a warning call! One of your peers has seen a bird of prey approaching! What follows is total chaos – well at least from the perspective of an outsider – everybody, maybe hundreds of fellow zebra finches, rush from the water pond into the bushes and tree tops near by. Flying buddies everywhere, leafs, twigs, branches and you have to be quick! And this is not a made up story, just watch this video!

The question is

Why do zebra finches not crash into each other and into branches?

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early career academics and the fuss about glam

Trying to publish glamorously in a high impact factor journal is not a bad thing if you do it purely by having a great, high quality study to publish that changes the world – or at least influences your field. But reading such ‘glam pubs’ I sometimes feel they were pushed into that journal by just boldly overselling the work’s importance. Scientists are usually very carefull with their statements. So what makes them completely oversell what they did? I think it is the high competition among early career scientists and career path insecurity.
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Barplot Madness

Maybe it is because of the change in fields and scientific environment, but I increasingly doubt data presented in talks, posters and articles. Mostly because I find myself wondering whether the choice of statistical description of the data makes any sense. I am not speaking of advanced statistics at all, just the simplest descriptive techniques and the choice of the right plot for it.

figure 1. X represents spike rates, categories cell types A and B respectively. Whisker indicates standard deviation.
figure 1. X represents spike rates, categories cell types A and B respectively. Whisker indicates standard deviation.

My doubts are usually raised when I see a bar plot as sketched in figure 1. What looks like a rather okay representation of data actually does not really give you an intuitive idea of how the data are distributed.
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Survey: The Ultimate Goal of Neuroscience

I am planning a blog post on what the Ultimate Goal of Neuroscience is. I would like to make a survey first, to hear from all you neuroscientists out there, what you think, is the big goal of neuroscience. I will present the results in this blog and write a commentary on it.

The question is: “Given unlimited ressources (infinite time – yes immortatlity, people, money, technology, everything), what would be the ultimate goal or ultimate application that would crown your neuroscientific work?”

Please write your brief(!) answer in the comments below, or twitter (don’t forget to adress me: @DennisEckmeier)! Please be creative! ‘Duh, everything.’ does not count! And spread the word!

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Cite the shite out of this site. Or better don’t.

I caused a little outrage among the passionate social designers of the future science community, lately. They usually envision a brighter future for science communication, discussing evaluation metrics, funding practices and strongly facilitate open access publishing, open data, science writing, and whatnot. I greatly appreciate this – I convinced my skeptical PhD adviser to publish open access in 2008 and I made suggestions about which online medium would serve best as a publishing platform that has great post-publication review features built in (via Twitter). Still I got called a ‘complete fool’ with an ‘unfortunate, outdated attitude’ by one of them (HHMI Investigator Michael Eisen, via Twitter). Why? Because I don’t see why an article has to mention everybody the author was ever inspired by and I do not think that every source should be ‘cite-able’ – like Twitter (in parts storified by @Hysell).

I made a ‘trollish’ (@sarcastic_f, via Twitter) comment as I entered the general discussion by indirectly responding to ‘We need better culture of citing blog posts, not just papers.’ (Michael Eisen, via Twitter), saying ‘I disagree. I would never quote a blog because most of them are terrible and almost all others are still not worth it.’ (DE, via Twitter). Of course this made a bad first impression. Ironically, what I then received became a collection of tweets directed at me that serves as a great example for why sources like twitter should not be considered cite-able – and I include my own. Because they are not meant to be official statements and people – even scientists – don’t act like professionals when using social media. And such free space is good for us!
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