# Tag: Science

It was quite a bit that I wanted to have a go to play with the ipython notebook, but I wanted to do it with something that was quite interesting and useful.

The IPython Notebook is a web-based interactive computational environment where you can combine code execution, text, mathematics, plots and rich media into a single document

– from the docs

This means that you can document your process and or exploration using Markdown, which is than beautiful rendered in html, and have also python code executed, with the graphs that are going to be embedded and will stay in the document.

I think it’s a very valuable tool, in particular when you are doing exploratory work, because the process of discovery can be documented and written down, and it a great way to write interactive tutorials.

For example, in this notebook, I’ve plotted the Probability Density Function of several statistical distributions, to have an idea how they are shaped, and which one to pick as base when creating new bayesian model.

You can see how it looks like on nbviewer

A photo posted by Michele Mattioni (@mattions) on

The path is unknown and full of surprise

It’s a bit of time that I have this post in mind, where I would like to compare the process of building a startup with the process of doing a PhD.

This of course will be based on my experience, therefore the analogies and the difference which I can find between building the SustainableSouk and doing my PhD at the EBI.

The object of a PhD is very broad, and it takes different shape and form. While you do a PhD, you need to have some hypothesis, which you are going to test in a scientific manner to assess if they can be accepted or they need to be thrown away.

Given the fact that I’m a fan of the Lean Startup method, I’ve applied this method also to the ssouk (shorthand for the SustainableSouk), where the inital idea has been launched tested, and now we are pivoting to a new direction.

so here it is the first similarity: Make hypothesis, test them on the ground and act accordingly.

Another important similarity, which is a direct consequences of this is: don’t give up. It takes a lot of time to create, test and analyse the results, and most of the time you will get that the first idea/hypothesis was not good enough and it will not bring you anywhere.

It is also interesting to note that there is a very different pace between the two: in a startup you have to go out there to test the market, and then see how this respond and how you can make it work. And you have to do it fast. While doing science instead, you usually go to conference and present your work, and it tends to take ages to write a paper, to get it out. You still have to do it fast, if it’s possible, however the publishing wheel is very slow turning.

So this is of course a not exhaustive list between the two, but I just wanted to give you a sense of what I have noticed so far and share it.

Lately there has been a clear movement to move science towards a more open way to make research.

I’m not talking about Open Acess Publishing, which is still important, but to the real art and sweat to do science.

Science has always been very collaborative, however the dimension of this collaborative effort has always been restricted to a small group. This is not the case when general problems seems to be tackle.

For example, when the problem is the definition of a standard, like NeuroML or SBML, the development of it is a community driven project, where the community works as a whole to achieve a standard which is backed by the biggest number of people interested, so can be easily adopted.

The beneficial impact of standard is not the topic of this post, and for the sake of brevity I just want to point out that a well-coded model in a well-recognised standard gives the possibility to share the work of a modeller (in this instance) and make the model be re-used by other people.

On the same line OpenWetWare wanted to share the protocols used in the lab as soon they were established, and actually even before that as ‘Work in progress’.

The ability of a scientist to be a part of a community is not taken in account at all, due to the Publish or Perish system which is right now up and running. This model does not encourage collaboration, and actually create groups of people which are competing on the same topic to scoop each other. This is a broken system.

It’s so broken that some people even decide to leave academia, and that is only one of the cases. A lot of letters are also available in Nature and this article from the Economist got quite famous as well.

Therefore I watched with a lot of interest the new way proposed by Dall’Olio  which consist in collaborative editing of papers.

So far, if I didn’t miss any, at least two papers with this approach have been written, which is very interesting and shed a bright light for the future.

Still the number of places available in academia and the way the recruitment is organized uses the current model, which does not fit the market, and it’s prone to discard talented people very easily. There should be at least a live debate on how to fix this problem, and move science to a super collaborative discipline.

Happier scientists and better science sounds good to me.

Great video about science and a way of thinking.

Best quotes:

Plait:
Teach a man to reason
And he’ll think for a lifetime

Randi:
Enjoy the fantasy, the fun, the stories
But make sure that there’s a clear sharp line
Drawn on the floor
To do otherwise is to embrace madness

See you in London, next Sat.

If you need to understand why, read the arguments.

I would like that something like this will happen also in Italy…

Scientific data must be open. Everyone should be able to check them, reuse them. More over they should be always available in a easy way.

That’s why the panthon principle have been launched:

## For science to effectively function, and for society to reap the full benefits from scientific endeavours, it is crucial that science data be made open.

Data is not code and data is not artistic work. This means all the classic licence that we love and we always use like the GNU Public Licence or the Creative Commons (except CCZero) are not good enough for data. Data does not belong to anybody in particular but belongs to everybody. That’s why it’s really important to use the right license. A list is available here .

It seems that I’m not the only one dealing with neurons in the GNOME Community. Well I mean, I never thought I was the only one, but I also didn’t expect to find a blog post on the gnome planet about the first publication.

Let me just say well done ðŸ™‚

So just two words about the ustream website and my experience for the mortal immortal symposium.

First of all I want to say it worked like a charm. I used a mac and a firewire cable to connect the camera with the computer. For the technical point of view, we took the video from the camera and the audio from the auditorium system and plugged that into the mac.

The quality of the sound it’s really good. The quality of the video is good enough I think.

More over you can watch or download the video from the channel url

We had 60 unique visitors, 88 total viewers with the mean of 19.3. Below the statics.

Mortal Immortal live streaming stats

At the BioSysBio Conference which I have attended in London this April there was a lot of things going on. An interesting bit was the workshop on Openscience notebook, on which I am really interested and thrilled. I’ve touched this subject in the past, however I will blog about this later on.

At the social dinner there was an exhibition from some artists and designers from the London Royal College of Art.

Image source

That’s how I knew Tommaso and we started to speak about it. I gave my “scientific” point of view, mainly answering what is possible now, what will be possible in future and what, according to the accepted paradigma and the availability of informations is not possible at all.

The topic was trying to think about new concept ideas grounding them on a scientific point of view.

To be honest I always saw this kind of contamination between the two realities with a lot of interest.

I am quite convinced that a scientist discovers something not when he/she is in the lab, but when he/she is outside the lab. Of course the ability to test the idea and grounding it on the science bases with model,measures and a theory happens in the lab and research work, but the original concept, the main idea is a sum of some different stimuli coming from different sources where art play a really big part.

These projects seems to demonstrate that also the other way is possible and science can influence art and design in a really intriguing and prolific way.

Maybe the difference between humanistic subjects and scientific subjects is only a matter of language and convention, and the holy war that usually it’s on between this two fields it’s just a matter of misunderstanding.

It’s time to move foward and trying to rethink the association between the two fields. Also from a teaching point of view.