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The evolution of selves by open citizen science

This post summarizes my current focus in area of open science. Whether concepts presented here could make their way into practice, that’s still to be seen. So, consider this a work in progress. I’m happy to be proven wrong, change my opinion or get myself sold into other ideas.

On (open) science

Science (like almost everything else in the world) needs a major transformation, as it no longer serves its purpose in the most efficient manner. For that reason I was attracted to open science several years ago – openness is the mode of the future in science. However the adoption rate for open science turned out to be rather low. One thing is that scientists from some point of their careers are like CEOs – they believe they have the ability to make good decisions, and not amount of facts/data/reports/suggestions is going to make them change their mind (Thomas Kuhn had described that phenomenon more precisely, but I find this analogy a bit better suited for modern times). But there’s also another layer – organization of science is a cultural artifact, and we are all culturally conditioned to accept certain approaches to research. “It’s always been that way” is the reason why we don’t have a “fooling around” grant, to explore different areas without being bound by providing results, for scientists with proven track record. It’s the reason why principal investigator of a grant cannot be a team (such as Polymath Project; after all some teams of great-but-not-geniuses can outperform the ones led by a genius). It’s the reason we massively subscribe to beauty contests such as Nobel Prize (or any other ranking system). Cultural conditioning goes even further – we are conditioned to accept or reject certain scientific questions (for example, fishing expeditions such as metagenomics studies would have hard time to gain acceptance in this part of the world before they became hot in the West, as Central and Eastern European researchers usually start with the hypothesis, not data; on the other hand proposals for really complex studies are often turned down in the West). So, in practice only results of research (assertions) are trans-cultural (concept borrowed from Gregory Lent) – the rest is a cultural artifact.

On the OAI7 conference there was an open science breakout session. Among other things, we divided ourselves into groups and each group had to come up with a single action that was supposed to move openness in science forward. Not surprisingly, 3 out of 4 groups proposed some kind of incentive. Carrots are one way of changing this cultural construct. Another way is adjusting a stick in a form of a mandate or change the processes (such as publishing) in a such way that they require certain amount of openness. Interestingly, we don’t need to take care of sustaining cultural change – once certain mode is adopted, scientists will develop sustaining arguments and procedures by themselves.

Tranformation, growth, evolution

We (scientists in general) do not talk about “personal growth” or anything remotely similar. It’s personal, it’s about growth (and assumes something about us is not OK) and by all means it’s something stupid related to banging one’s own chest and believing everything is possible. However, when you ask people if they think that all the problems we have in science could be solved in a short time provided scientist would grow up, you get definite “yes” almost each time. You can look at this in a slightly different way. On the very same open science session at OAI7 I mentioned above, we were asked to provide one keyword/phrase that describes open science. We got a collection of 30-40 keyword and rarely anything repeated. Surprisingly (or not), about one third of them were actually describing science, as it is “supposed” to be, but apparently is not. Open science as a moral transformation movement? Growing up? Come on. This is not the thing reasonable people talk about, right?

While I’m not going to start a new religion, I want you to re-frame the concept of “growth” into something more scientific. The basis for such framework might be the work of the father of so called positive psychology, Mihaly Csikszentmihalyi. He is most known for the book “Flow” about a state of full immersing in the task and conditions required to achieve it. In the next book, “The Evolving Self” he started to look at patterns of “flow” across the history and showed several examples how “flow” was the basis for substantial shifts in the communities across centuries. He also traced how our “self” evolved over millenia. His main point is that large transformations that happened in the past required a complex self and a laser focus of psychic energy, and to deal with several issues of the present, we need more of the same. He argues that the best idea would be to form a creative minority, called “evolutionary cell” that by its special design (more on that in a minute) will allow its members to transcendent their “selves”.

While it may sound a bit abstract (not surprisingly – the issue is quite complex and it’s hard to simplify), let’s look at an example, El Sistema program in Venezuela. It differs quite substantially from most of other music schools systems all over the world. There’s unprecedented amount of working in groups. Kids play together or form orchestras from very early stages. Because they work together, “flow” is achievable much easier than when playing alone. Because music is relatively neutral topic, participants face no resistance from their own communities which helps them to grow out of social conditioning of their communities (studies notice improvements in school attendance and declines in juvenile delinquency among El Sistema participants). And almost by the way, these kids at the end of the day form one of the best 5 youth orchestras in the world.

Fellowship for the future

I think that carefully designed open citizen science projects are our fellowship for the future, as Csikszentmihalyi calls these future oriented creative minorities. And here’s what I understand by careful design:

  • It’s a group effort (there are plenty of venues for individual performance elsewhere – here only the “orchestra” matters).
  • It has a clear goal, that is ideologically neutral (a participant avoids heated discussion about the project in his/her local community) and attacks it from many different perspectives (systems thinking). Scientific questions fit perfectly, as long they are not in the area of climate change, sociology or GMO.
  • The goal has to be large, difficult and open (in a sense that the group invents new solution to the problem). While it’s the easiest to grab people’s attention for short amount of time, there must be an element of long journey in the process.
  • The project should be hands-on – there has to be real contact with the issue (it can be even abstracted in the lab but not virtual- cyber-science doesn’t work here).
  • Difficulty of the tasks follows the skills of participants – you cannot do the same thing for 8 months and expect enthusiasm or “flow” (unless you are given some space to introduce changes).
  • The group has a natural leader (scientists/teacher) but nevertheless is built on the basis of meritocracy (you don’t want participants to compete for alpha position, but you don’t want to entirely obey either).
  • There must be a close and relatively frequent contact with the leader, therefore groups have to be small and local.
  • It should teach logical and creative thinking, but at the same time integrity, accountability interconnectedness and systems thinking. In other words, let’s do interesting science, let’s report it well, and let’s make sure we understand different sides of the problem.

In essence, the project allows participants to have their own “hero’s journey” (the basic pattern of narratives from all over the world, also called monomyth; coined by Joseph Campbell). The journey allows the hero to destroy the old self and build the new one. While it sounds dramatic (some call it “tragic” mode of self-development), it’s actually not. It all happens almost transparently, because this process is not the main purpose of the journey – the main purpose is to kill the dragon or to solve the scientific issue.

It’s not a religion in disguise – it’s an idea to transform science and society, to increase wisdom level just a little bit.

What next?

This approach definitely needs more work. I’m not yet sure how to avoid common mistakes, such as pseudoteaching or shallowness. I’m not yet sure if within so short time (between 1 and 3 years per cycle) I would manage to convey the basics of scientific and systems thinking (it took me a while to get it). The project will present big challenge to participants on many different levels. It’s also relatively easy to attack the project and hard to defend it – especially easy critique is little results vs large investment (the project requires by design relatively low ratio of scientists to participants – and not all of the participants will be willing to lead next iterations; obviously project has no appeal short term).

However, such idealistic stance (framed in different words) is going to repeatedly come back into science. Have a look at the couple of links below (most are quite recent) – the framework is appearing again and again. But it’s not going to be easy to defend it or implement it. Depending on the angle, it’s going to be seen as dangerous ideology bordering on cybercommunism, nice societal idea disconnected from the reality or something that produces completely unwanted results. But systems thinking (kind of pre-requisite for becoming responsible adult) is the skill of the future, and we need to teach it, in whatever form.

One step closer to open science

You know the news already:

The Howard Hughes Medical Institute, the Max Planck Society and the Wellcome Trust announced today that they are to support a new, top-tier, open access journal for biomedical and life sciences research. The three organisations aim to establish a new journal that will attract and define the very best research publications from across these fields. All research published in the journal will make highly significant contributions that will extend the boundaries of scientific knowledge.

Cameron has already commented on the issue, but I would like to add a few more thoughts. The concept of “top-tier journal” obviously resulted in some negative comments from the open science community, with which I fundamentally agree. However in practical terms, it is actually a step in a right direction – it will create an direct and indirect incentives to publish in open journals. As nobody expects scientists to grow up (well, I do, but that’s a topic for another post), we need more carrots to shift the system towards openness.

But that’s not the end of the story. As I have written last year, we needed some large scale experiment in Open Science – not to make some significant change, but to significantly change dynamics of the system. Launching new OA journal by science funders might have directly several positive outcomes but at the same time it is going to spark some interesting discussions on obvious topics such as sustainability of OA, future of journals, marketing costs, quality filtering, impact of publications, etc. However, given that these areas aren’t unexplored (OA publishing isn’t something exotic or new and PLoS has been heavily experimenting in OA for the last couple of years), I look forward to discussions outside of the topic of publishing narratives of research. As people acknowledge OA and try to think about the next step, open data or open notebook science will get a way more attention than they receive at the moment.

Homeschoolers and open citizen science

I’ve recently attended a meeting of Polish homeschoolers. Homeschooling is not that popular in Poland as for example in US. One of the reasons is that it’s basically illegal in here to teach kids at home and a waiver is given only in special cases. Nevertheless there were ca. hundred parents there and I’m sure that number is going to grow for the next few years (unfortunately to understand the discrepancy between illegality of homeschooling and it’s growing popularity you should live here for quite a while – we’ve been saying “Pole can” ages before presidential campaign of Obama).

My presentation was largely about citizen science. I was arguing that all three approaches to answering a question in a traditional education (recalling, guessing and cheating) are almost always preferred to deducting the answer or making an experiment to find out. And the easiest way to avoid that trap is to ask a question that nobody has answer for, that is the scientific question. Then I went on to describe various open citizen science projects and their different levels of participation.

My talk was after another one on open educational resources. Obviously that other presentation received more attention from the parents and resulted in many more questions than mine, but still the concept of citizen science rang a bell with a few of participants.

However, what I realized was that home schooling parents are the best allies open science advocates have within the general public. Open citizen science might play a huge role in early education – not only in teaching how to think, but also how to work together/cooperate. Obviously, parents will be interested – but only if we can give them access to resources (publications, data) that is equal to the access we have.

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Ten commandments of open science

No, this is not “Ten simple rules of open science” (although it could be nice if we could write such article and publish it at PLoS Computational Biology) – this is the list of TEN COMMANDMENTS of open science:

1. You shall give everything away free (do not over-protect your research); do not patent – sell your expertise.

Release source code under open source license, publish OA articles and do not abuse intellectual property rights.

2. You shall change the world, not just sell things.

Seek for making contribution to the scientific knowledge; do not choose trendy research topics if results may contribute a little.

3. You shall be sharing, aware of social responsibility.

Explain your work in simple language.

4. You shall be creative.

Do not repeat someone’s old experiments using new technology.

5. You shall tell all: have no secrets, endorse transparency and the free flow of information; all scientists should collaborate and interact.

Follow the practice of Open Notebook Science.

6. You shall not work: have no fixed 9 to 5 job, but engage in smart, dynamic, flexible communication.

Get familiar with bursty work and “just-in-time” research – do not let your research fall into any schema.

7. You shall return to school: engage in permanent education.

No step of scientific career should prevent you from asking stupid questions.

8. You shall act as an enzyme: work not only on the research, but trigger new forms of scientific collaboration.

Any kind of communication channel is a potential way of collaboration.

9. You shall leave research silently.

Do not make yourself impossible to replace.

10. You shall be the state: companies should be in partnership with the state.

Be independent – do not endorse technology transfer centers.

Sounds nice isn’t it? Now, let’s re-label things. These ten commandments above are almost exact copy (the original list is to found for example here) of Olivier Malnuit’s ten commandments for the liberal communist. In isolation, many of the above are quite reasonable. All of them together, stamped as “commandments for the liberal communist”, trigger violent or at least negative responses in many places.

Why did I put it in here? Because the label of “liberal communism” or “cyber-communism” is used to describe Open Access initiative here in Poland. Not frequently, not so visibly, but you can guess how difficult is to get through such label.

I will write my comments in another post, but I’m of course interested in yours.

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Data science: cost of mistakes

Michael Nielsen some other day shared a story on how researchers are using Twitter to predict stock market movements. The idea wasn’t actually that new – there were other attempts to use Twitter (and not only that) to predict stock prices. And actually it’s fairly easy to come up with another source of signal that will nicely correlate with the market (if you don’t believe that, look for performance figures of astrology-based trading – numbers are quite amazing). However, one of the key issues of algorithmic trading is not how good the method is, but how costly mistakes are. And I believe this is also the key issue in majority of real-life applications of data science projects.

If overprediction in a diagnostics procedure makes somebody loose her/his kidney, that’s not that good procedure. If a trading system makes you loose more money every 10th trade than you earned in previous 9, it’s not a good system either. Assessment of false positives and false negatives (type I and type II errors) is a standard element of statistical hypothesis testing, but real-life applications require weighting mistakes to understand if the algorithm is actually usable.

Systems Institute is officially supporting FigShare (backstage story)

You may or may not know that I’m the head of Systems Institute, non-profit research organization founded in 2009 in Poland. The Institute is located in Poland, but is operating internationally. There’s not much you can learn about this initiative, as we haven’t put up a real website yet (although there’s a placeholder). There was a reason to that lack of online presence – instead of wasting time on hyping our vision, we decided to start working, and brag about results once we have it.

Today FigShare created by Mark Hahnel went beta and as of today, Systems Institute is officially supporting FigShare’s operations. In other words, there’s a real effort to keep FigShare alive for indefinite period of time. Mark is making sure your figures and data are searchable, citable or whatever else is going to be implemented in a near future. We are making sure the service is operating and your figures are backed-up.

There’re few lessons to learn from Mark’s great work on FigShare and other services he has started within last half a year (especially on doing vs talking ratio). But I will share another one, related to our cooperation. Being a head of any institution means one has a decisive power. It’s something online communities don’t have. Let me explain. I was paying attention to Mark’s work on FigShare from the very beginning, because it was an implementation of ideas on nanopublishing I heard from Fabiana and others at Science Online 2010. It’s great to see this finally materialized. But when certain performance or features of FigShare required some investment, there was an issue how to cover that (without stretching too much Mark’s PhD-student budget) and we had discussion or two on FriendFeed on this issue. In my view, microfinancing of such projects is not going to work – at least not in a near future. Given the importance of the FigShare (really, it’s very important to have such service), I’ve decided to step in and offer support from Systems Institute. No online community could provide financial support in a long term. Which is why Systems Institute was started and why I’ve recently complained that too few people try to institutionalize their work. Beautiful and brilliant things emerge from online collaborations. But to make them sustainable, we need supporting institution, even as virtual as SI is.

Now, go to FigShare and upload some data or never-to-be-published figures. But at the end of the day, please think long term about our ideas we discuss online and about work we do everyday. And read again Deepak’s post on Abundance.