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Science 2.0 – introduction and perspectives for Poland

This is more-or-less transcript of Science 2.0 based on a presentation I gave on conference on open science organized in Warsaw earlier this month. Please remember that it’s not meant to be a general introduction to S2.0 – it was prepared for mixed audience and focused on perspectives for Poland.

Science 2.0 is a concept describing new forms of communication between scientists. Communication has been the essence of science; research become meaningful only after confronting results with the scientific community. So far it was thought that peer-reviewed publication is the best communication channel we had so far. New internet technologies had changed this picture – not by replacing the “best” channel, but by showing that the concept of “the best” covers only small part of a communication spectrum. We knew that already, but we keep forgetting: people didn’t stop calling each other after email had appeared – these two services complement each other. And in the same way many of new communication channels complement peer-reviewed publication.

Collaboration, exchanging information and confronting research results in 2.0 era have two important attributes in which they differ from traditional models: openness and communication time. Exploration towards increased openness and shorter communication time happens already in publishing industry (via Open Access movement and experiments with alternative/shorter ways of peer-review). However I wanted to say few words about experiments that go little or quite a lot beyond publication.

I have chosen My Experiment as an example of an important step towards openness because it’s probably the least radical idea you can find in modern Science 2.0 world. This service provides a virtual research environment in which the main focus is put on sharing scientific workflows. One of the use cases may be sharing a precise diagram of the “methods” sections from experimental (including bioinformatics analyses) publications. Small step towards openness towards other scientists – we can make it easier for others to understand what we did in a particular paper.

And while we can open towards other scientists we can also open towards non-experts. FoldIt is a game in which people from all over the world compete in improving structural models of proteins. There’s no deep knowledge required – a brief tutorial contains essential introduction to the topic and exercises testing if user understands some basic concepts. Playing the game does not contribute directly to the science, but helps in improving protein structure prediction software and in understanding protein folding. Two other examples of non-expert participation in science are Annotathon and Spectral Game. These are servers that combine “required” and “useful”, that is combine teaching and data annotation. Both servers aim at enhancing learning process and at the same time use crowdsourcing approach to curate data – metagenome sequences in first case and chemistry spectra in the second.

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What about shorter communication time? The image above combines various data visualization techniques based on the Second Life platform. While Second Life was first sold to scientists as a conference platform, it turned out it’s not very useful for such purpose – but scientists stayed for SL’s very good visualization capabilities. How many times instead of explaining via email/phone some concept to a colleague, you said “come here, I’ll show you”? SL allows to prepare interactive visualizations of chemical structures, genomes, proteins or multidimensional data and as such, to communicate some difficult concepts faster than via other channels.

Last year’s ISMB conference became a major step towards new approaches in conference reporting. A few scientists that happened to be bloggers and users of a life streaming service called FriendFeed decided to report in real time from the conference. Their effort was followed by a number of people, including even the ones that were already on the conference. I’ve seen my colleagues creating an account on FriendFeed (which they sadly abandoned shortly after) only to follow this report. It is still available in permanent, searchable archive over at FriendFeed and resulted in an interesting publication. Life streaming service wasn’t designed strictly for conference reporting and similarly, virtual world platform wasn’t designed strictly for data visualization. But it obviously doesn’t matter to us, as long as it works. slajd13

But you may ask: where is “science” in “science 2.0″, as these examples are not necessarily about doing research. And while I could provide some examples of using new communication channels in day-to-day work, I think it’s more important to tell you about people who test boundary conditions of communication spectrum in their research. In 2006 Jean-Claude Bradley coined a phrase “open notebook science” which means conducting research using publicly available, immediately updated laboratory notebook. Despite obvious disadvantages of such approach (competition, scooping etc.) he is quite successful in terms of getting grants, publishing his results and so on. A number of people followed his approach with smaller or bigger modifications and it is argued that ONS enables more effective collaboration and more effective (no repeated experiments) science. Is that true? Quite probably, but it’s important to recognize that Science 2.0 is not only about better communication. As Jean-Claude mentions is his talks, all these experiments are parts of a bigger process, a change in a way science is done. The outcome of Science 2.0 is not going to be limited to complementary channels to peer-reviewed publications – the more important part will be rules, formats and standards for communication between machines, not scientists. Those who think that removing scientists from scientific process is not going to happen all that soon, I would like to point to a recent publication in Nature presenting Adam, a robot that independently discovers scientific knowledge. While Adam seems to be an equivalent of a junior lab assistant (or a postdoc as some say) and is definitely too expensive to consider as your cheap lab workforce replacement, it’s a quite significant step towards automatising of many elements of scientific process.

There’s another aspect of Science 2.0 that is usually skipped in many articles. A screenshot I’ve shown you contains my conversation with Cameron Neylon over at FriendFeed in April 2008 and was presented in many talks on open science since then. The reason was clear – FriendFeed wasn’t designed to start scientific collaborations and this was the first example of such kind. However what is usually not said is the fact that I wouldn’t answer anonymous request. The reason I did a model for Cameron’s grant was that I subscribed to his feed before so I actually could see the request. However, I didn’t subscribe to Cameron because I knew his professional profile – I didn’t even know his affiliation then (and barely remember today). The reason I subscribed to Cameron was that I somehow “knew” him, this is I read his blog, I commented on it and he commented on mine, etc.

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An important part of Science 2.0 is the fact that it has human face. In other words, through participation in online communities we become living persons, instead of anonymous scientists hiding behind publication list.

Why does it matter? Looking at Science 2.0 from perspective of a young scientists working in Poland, this aspect of Science 2.0 becomes a game changer. Poland has ca. 30 times less money in available grants than UK (according to calculation of the UK research budget by Duncan Hull). In biology, which is a very expensive field, it simply means that we have a hard time competing with other countries. And while that fact matters less on the country scale, it matters a lot at a level of individual researchers, because it closes many career opportunities.slajd20

This is not an example, this is a comparison of two real people I know, that finished their PhDs about the same time. The first was from a major Polish institute, the second from a major European one. And while impact factor is a poor measure of their research outcome, it’s exactly what a head of a lab both would apply to will see: few publications, not that impressive vs lots of publications, all in good journals. With research budget Poland has it’s hard to compete with Western Europe and even the EU money will not change that situation in a matter of days, because we also lack experience in spending money. While the system slowly transforms, young Polish scientists have already a way to fill this gap – by Science 2.0, or more precisely by participation in online scientific conversations. There’s no currently easier way to show that poor publication record does not equal poor skills.

And the last aspect of Science 2.0 I want to talk about today comes from the fact that I’ve just became a lecturer at the University of Warsaw. There’s another gap we must fill, this is between current research and lectures we give today. It is a hard task as the amount of knowledge doubles faster and faster. To adopt to such speed the structure of the university courses must change – or instead, we let the students to take care of the gaps. They can easily follow current research and decide what is important to learn by having an access to real-time scientific conversation, by participation in Science 2.0. It’s not an easy road, but at least it will allow them to learn important concepts long before we come up with an idea to teach these concepts.

Consider such example: a group of students from Department of Biology of University of Warsaw participated in 2008 in IGEM, International Genetically Engineered Machine competition. This is a part of a new field, called synthetic biology. This field is fresh and somehow still controversial and these are not the only reasons why not all universities in world have synthetic biology courses. University of Warsaw doesn’t have it either – but it didn’t stop these students, and they plan to participate in IGEM again this year. However, synthetic biology, as many emerging fields today, is done in the open. Scientific conversations are open. Ideas and thoughts are open. And students can learn from it before we organize these thoughts into textbooks.

The last slide shows a community of life scientists I’m a part of. These are not only scientists – there are librarians, science communicators, editors from scientific journals, people working in biotech industry or even people without direct connection to science. These people with diverse skills and background create a 24h a day, all year long online conference. Ability to interact with them and to learn from them was among biggest privileges I had in recent years. And even if this is the least visible aspect of Science 2.0, it’s the most important one and the main reason for my participation in online communities. Thank you.

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Posted by on May 18, 2009 in Community

 

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The Life Scientists room over at FriendFeed

It’s one of the slides prepared for “Open Science in Poland” conference. I captured screenshots of subscribers to The Life Scientists room over at FriendFeed (however, as you’ll notice, with uneven number of rows, so not all of subscribers did fit). I hesitated to share it at a high quality, but new FriendFeed layout does not look anywhere as pretty as the old one (and has much smaller number of avatars per page), so here it is.  The Life Scientists

The Life Scientists slide – PowerPoint format, PNG format.

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Posted by on May 3, 2009 in Community

 

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What would you (do you) teach your kids?

KTurtle
Image via Wikipedia

This post is inspired by a question Iddo posted over at FriendFeed, in The Life Scientists room:

Teaching my 7 year old Logo (using kturtle). Any ideas for a good programming book for kids?

Other than programming, what would you (or do you) teach your kids? What kind of skills science geeks consider important, that aren’t really tought in schools (at least not at the level you’d want schools to teach them)?

My first thoughts were about remixing digital media, 3D modelling and printing (I believe 3D printers will become quite cheap in few years) and technical side of photography but I didn’t really spend much time on this topic (it’s obvious from this list). What’s your opinion?

UPDATE: Feel free to comment on this post’s FriendFeed thread.

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Posted by on March 8, 2009 in Comments

 

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Microblogging in PLoS

I don’t usually repost news, as my FriendFeed stream (also available from the sidebar of this blog)  is a more efficient way to let you know about interesting things, but this one deserves a special mention. Recent coverage of ISMB 2008 conference over at FriendFeed ended up as a publication in PLoS Computational Biology:

Saunders, N., Beltrão, P., Jensen, LJ, Jurczak, D., Krause, R., Kuhn, M. and Wu, S. (2009).
Microblogging the ISMB: A New Approach to Conference Reporting.
PLoS Comput Biol 5(1): e1000263
doi:10.1371/journal.pcbi.1000263

This is very exciting, but it also has some interesting implications. Of course it means that more and more people will participate in our community and finally BioGang projects will start to take off (hopefully), but I think also about something else. Do you remember Neil’s post about why you should have online presence? I think there’s one more thing to add to this list. Authors of this publication and lots of others scientists over at FriendFeed will sooner or later climb to to a PI-equivalent positions, where they can decide about hiring somebody. And strong online presence will be for them an important asset in CV. Much more important than you’d think today ;).

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Posted by on January 30, 2009 in Community

 

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Timestamped FriendFeed activity – really public “profile”

Accidentaly, I have found a simple way for obtaining a time stamp for each entry and comment any person with publicly available lifestream makes on FriendFeed (except “Likes”, which do not seem to be timestamped at all). Activity of semi-randomly choosen person during the day (summarized over couple of weeks (!))  is shown below:

FriendFeed usage during 24 hours, summarized over couple of days.

FriendFeed usage during 24 hours, summarized over couple of days.

While relation between AM and PM periods is correct, time-zone is manually shifted, so it’s more difficult to guess who’s this activity is (but it’s not Robert Scoble if you want to ask). What does it tell? Basically, this person does not close FriendFeed window for the most of the day. Additionally, there’s a period of the day in which “catching-up” has place. Nothing interesting so far? Original data has much more details. It is possible for example to collect information when during the day particular person usually watches videos on YouTube. Guess – is that during working hours? :)

Ability to get that data for couple of weeks back without any trouble (I didn’t need to track this person’s activity for such period) was kind of disturbing. I knew it’s very simple to start tracking my habits, but I wasn’t aware of the fact that it’s also easy to see what I was doing over the last three weeks. Do you think it makes a difference?

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Posted by on January 29, 2009 in Comments, Visualization

 

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Photography is not a hobby. Updated CV and feedback request.

Visual resumeYesterday I asked over at FriendFeed for the feedback on my early attempt of making visual CV (big thanks to all who commented). Here’s a revised version that hopefully looks much better. The key to read the image above (click to see larger version) is as follows: Y-axis represents time (with dotted line indicating more or less the present moment); areas of interest are along X-axis; color of the phrases indicates my confidence level; font size denotes amount of time I spent on the topic (so in this case I have spent lots of time using perl, but I still don’t feel very confident about it); placement of the phrases denotes which areas of interest particular project/phrase spans; area below the dotted line shows my approximate plans and hopes for the future.

The first version had “Photography” area instead of “Visualization”, but I needed to change that since it was confusing everybody and raised questions why I put a hobby on a professional CV. Photography (or visual arts) is not my hobby. My hobby is choir singing (which I do for over 14 years already, currently singing jazz and gospel). Visualization/Photography is there to indicate that I consider data visualization one of the most important elements of scientific method. What I’m trying to figure out is what kind of presentation can help us in understanding really complex systems, such as human (genetic, to make it easier) diseases. And when we understand them curing is going to be much easier. At least I hope it will.

Anyway, the true reason to post it is to ask my readers for feedback on missing elements of my plans. So far my ideas for the future research projects split into a few paths. First path is to work further on bacterial systems (or subsystems, such as secretion systems etc.). This work would translate later on into something I call Synthetic Biology Framework, which would be a tool helping in designing new biological systems, and maybe later would result in creating a programming language for a cell. My first ideas about the framework were to design engineered bacteria producing some important compounds, maybe drugs, but now I think the cooler use for the framework would be to design bionano machines. The second path is about modelling of human diseases, with important milestone which is analysis of human genome and metagenome (genobiome as I call it) – if the data will be available. Because I don’t think I could do better here than thousands of scientists if I were using the same information, here’s a moment where synthetic biology comes into play again – I hope that I could design nanomachines that would server as quick diagnostic tools or would be reporting the body state in some mostly non-invasive way (aiming at issue of “how is my cholesterol level building up”). The third path is mostly empty and concerns visualization methods. So far I have no clear idea how to build a system that would visually assist in understanding how cells work. I plan to experiment with 3D printing and 3D visualization of biological networks, but I have no clear idea where this will lead me.

So if you have some opinion, comment, idea how to connect some dots, how to jump from one area to another (for example I have no yet idea how to approach pharmacogenomics), or if you think that it doesn’t make sense at all feel free to comment.

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Posted by on November 18, 2008 in Career, Research

 

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How far one can push online collaboration in research?

History comparison reports highlight the chang...Image via Wikipedia

A week or so ago I’ve asked on the FriendFeed if there’s an interest in writing a cyclic publication on the status of Science 2.0. I thought that summarizing every year advancements in openness of science would be a good idea. During discussion it turned out that there’s a need to write a first major publication on Science 2.0 concepts because there isn’t one published in the life sciences field. The final conclusion of interested people was to meet face to face on the upcoming conference and discuss things in detail.

And this made me think.

I started to wonder why people who live, breathe and do research online still need to meet in person to plan and discuss some stuff. The very obvious explanation is that the conference was only two weeks ahead, so there was nothing more than that, but some patterns (brainstorm online, then meet in person, then finish online) repeat so often that I started to believe an online collaboration can only go to a certain point.

The excuse is not in the tools, especially given how fast the new ones appear.  As an examples may serve recently launched Adobe Acrobat site, which contains online editor and live collaboration suite (contains screen sharing, notes, chat, audio, video) or its analog for programmers: Assembla (svn, git, trac, wiki, milestones).

My feeling is that what makes a difference is not a quality of interaction while working on a certain project, but the possibility of discussing things not directly related to this project. Online collaboration is usually very focused. When editing a document online it’s usually hard to side-track it, so at the end it’s about something else than it was planned. Calls or videoconferences have usually a schedule. No place for non-related stuff. No place for a beer/coffee/glass of water and a chat about how life was good in old times. No place for discussions on random things and coming to the main project from a different angle and with completely new ideas.

I’ve been trying for quite a long to work online with other people on some projects from my home office (which is in the middle of nowhere). As you can guess, it works to a certain point and majority of them were improved upon meeting face to face. And this left me wondering how far can I push online collaborations. It isn’t usually an issue in IT field, but so far it doesn’t look very promising in research.

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Posted by on August 27, 2008 in Comments, Community, Research

 

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One year of blogging – plans for ten years

Ethos Roundtable at Bob Doyle's Home - July 18...Image by Pathfinder Linden via Flickr

Following BioBarCamp I missed one year anniversary of this blog. With sixty something posts I cannot say I’m very productive blogger, but I didn’t aim at being one, as probably all other science-types. My goal was to be engaged in the conversation and I have reached it much faster than I expected. I got lots of help and encouragement from people I wouldn’t even dear to email a year ago. I know much more than I did on things outside of my research area. While it sounds all pathetic, advantages of being part of this community are hard to overestimate – I wrote about it couple of times already (and Neils did a great job summarizing why you should have a web presence).

Where is “Freelancing science” heading? That’s a question I asked myself pretty often during last 12 months. At first, I just blogged about interesting stuff around bioinformatics. Then I made a jump into freelancing as scientists (and this experiment goes pretty well). Statistics on keywords people are using to find this blog clearly show that there’s some interest within bioinformatics community in following this path. But the idea for this blog I have right now is not about freelancing anymore. Or rather it’s about freelancing on the next level, because today I think about starting a non-profit institute.

I believe that small research groups formed as a non-profit organizations will have enourmous impact on science within next ten, twenty years (more about it in upcoming post about the future of scientists). In spirit of freelancing they will jump from one project to another (see Deepak’s post about bursty work and follow-ups), developing solutions and making discoveries much faster (or cheaper) than it is possible in beaurocratic environment. We do have tools for effective collaboration online, we have new generation scientists that do not feel attached to academic system and we have science which starts to evolve about undestanding data, not performing experiments. Is it time to try such approach?

So, watch this space to see how the idea develops. I’m also interested in your opinions and experiences with starting and cooperating with non-profits if you have any.

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Posted by on August 11, 2008 in Career, Community, Research

 

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By any measure I’m average at most

Nature, Science and PNASImage via Wikipedia

As you have probably noticed, yesterday’s BioBarCamp was covered in depth over at FriendFeed and additionally Cameron was streaming video live from the event (it’s still available under the same address). One particular session drawed my attention, because it was about measuring impact of scientists. It’s something I have very strong opinion about since couple of weeks, so forgive me this rant.

Peter Binfield (PLoS) and Pedro Beltrao did a great job on presenting current status of the issue and presented potential way to measure impact of a publication (quoting after Shirley“your article received x citations, viewed x times, received x comments, bookmarked x times, rated x by experts, discussed on x respected blogs, appeared in x news media, etc etc” – instead of single “your article was published in journal with IF of X”). And while two months ago I was really interested in such discussions and willing to help, today I simply don’t care. The reason is simple and is presented in the post title: by any measure, I’m average at most.

That’s absolutely obvious that majority of scientists is at most average by any standard or measure. And that is not going to change, at least not much. Those who are at the top by Impact Factor today, will be at the top by other measure. Those who do some not-that-important stuff like me, will be still pretty average by other measure. One of the reasons may be all kinds of issues with normalization of the field size (there’s too much problems with biological ontologies to believe that dividing science space into fields is going to work much better). Another thing may be relative importance of the field (that’s something different from field size) – human research will always draw more attention than electrochemistry. And I could go on and on – all these issues aren’t novel and have been described and discussed in thousands of blog posts. The point is that even if such new ideal measure is going to be fair, it will not change life of majority of scientists. Not only because some of us do average things, but also because some of us have average money (BTW, I haven’t found much discussion on including in the measure research budget, which surprises me given the fact that amount of money spent on a project correlates pretty much with the IF of the journal it is published in afterwards).

So, I don’t really care if IF stays or not (although people working on improving measuring get my deep respect). Reputation-wise I’m going to be in the middle unless I will make something extraordinary. But honestly to make a scientific breakthrough the last thing I need is a number describing quality of my thinking.

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Posted by on August 8, 2008 in Career, Comments, Research

 

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FriendFeed: where the conversation happens

The start of this post (see the image above) may be a good reason for many people for not to join FriendFeed :) . It shows what happened to number of visitors to this blog after I joined FF – it had dropped by half (actual numbers aren’t relevant, graph shows monthly statistics). The reason is pretty obvious for any long-time blogger – no posts, no visitors. I don’t post as often as before for a good reason – sharing news, interesting links and the whole conversation around these happens on the FriendFeed. While I didn’t set up a dream system I wanted to (see my comment on previous post on the FF), I don’t have any issues with so-called “information overload“. Actually, I don’t believe in any information overload – we are just pretty bad at managing incoming information – but that’s a story for another post.

Rooms are neat feature of FriendFeed – they act a filter and keep the conversation focused. Instead of looking at a stream of titles ranging from linux hacks, through hardcore programming stuff and other bioinformatics-related topics, up to cancer research and science philosophy, I can just go into one of the rooms and see only items related to a particular topic. Yesterday Deepak wrote on the new rooms at FF (for Python, Ruby and R for Bioinformatics) that were created by people from life-science community. There is also a room for Science 2.0 and Open Science, DIYBiology and even a room which collects links to a must-read material – BioGang classics (since I started this post, Ricardo had created OpenWetWare FriendFeed room).

Rooms help in keeping the flow of links under control, but the conversation is the key point of using FriendFeed. Almost every single item posted into The-Life-Scientists room generates comments, sometimes turning into pretty long discussion. Because FF aggregates Twitter updates, majority of “Dear Lazyweb” Twitter requests result in FriendFeed based conversations. And there’s more and more people participating (The Life Scientists room has over 200 members). As usual, there’s a catch – focus and depth are not good sides of FF comments (for example, compare reaction to the recently posted very nice essay by Michael Nielsen on The Future of Science: number of comments on his blog and on the FF are comparable, although discussion/arguing with the essay points happened mostly on the blog). But that’s not a problem – it’s just a result of a speed with which items appear and disappear on the FriendFeed (some of you have seen that tracking real-time stream from concurrent sessions on the recent ISMB conference).

Even such shallow and quick interactions with people on the FriendFeed generate some level of trust, and that I think will lead to couple of interesting things:

  • more people will try how does the online collaboration work (for example, in reflection after recent Cameron’s talk Brian Kelly from UKOLN wants to write his article online)
  • PI-level scientists will join FF to participate in the discussion (we see that already, although so far there’s only very few of them)
  • there will be serious articles why FriendFeed, Twitter and online collaboration are bad for scientists and how these can break their academic career, in similar way as there were for blogs (see recent Pedro’s post)
  • we will see (and read, since it’s going to be open-access) first peer-reviewed publication from an idea that originated at FF/Twitter

Is FriendFeed going to be a hub for science? I don’t really think so. At the time, when mainstream science will pick up FriendFeed I think we are going to be already somewhere else, because there will be more interesting and more useful platforms for scientific collaborations (like for example cyn.in – looks promising, although it’s not yet optimized product). But the time spent at FF will give us an advantage: connections, collaborations, wide spectrum of information and advice from smart people.

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Posted by on July 28, 2008 in Comments, Community

 

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