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Sci – Bar – Foo etc. Part II – SciFoo – Engaging with the world

17 July 2009 2 Comments

Last Friday afternoon (was it really only a week ago?) about 200 people made their way to the Googleplex in Mountain View for the fourth SciFoo. There are many people who got their blog posts out well before me so I will focus on the sessions which don’t seem to have been heavily discussed and try to draw a few themes out.

For me, the over riding theme that came through was Engagement. Engaging people beyond the narrow confines of the professional research community in real research projects, making science more engaging for students, and engaging in a serious way with both the tools that are available to help us do these things, and increasingly with data generation and dissemination processes that are not under our control.

I was involved in running two sessions. The first with Peter Murray-Rust was on Open Data, focussed on getting feedback on the current form of the Panton Principles and has been blogged in detail by Peter. For me the main message from this was a lack of push-back. Many of the more technical people in the room were bemused that there was a problem. “Just put it on the web” was a common response. Other’s were concerned about where data stops and creative works begin but the main message for me was that “for published data just put it explicitly in the public domain” was seen as the right thing to do by the people in the room. Indeed most were suprised it was even worth discussing.

The second session I ran was on Google Wave in research and this will get a whole post of its own very soon so I won’t discuss it in detail here. Suffice to say that there was excitement, great ideas about what could be done, and concerns about the details of technical implementation. Which to me seems like an excellent mix to make progress with. Engagement for these two sessions was engagement with the data and engagement with the technology for generating, annotating, and sharing that data.

The other sessions I would like to draw a common theme through were more focussed on public engagement and education. The first session I attended on Saturday morning was run by Daniel Glaser called Doing Science in Non-Science Spaces. This was an interesting discussion on many levels but particularly for me because it challenged my ideas about multi-disciplinary working and deploying research projects into an educational setting. Daniel described disciplinary boundaries as fractal and described multidisciplinary projects as requiring as space where people can come together in a safe common space to share ideas, but also a requirement for people to then disperse again and re-intepret the outputs in the context of their own experience and discipline. In this view disciplinary boundaries are important in enabling effective summarisation and communication of outputs. I’ve been kicking myself ever since for not thinking to ask whether that means these boundaries are any less arbitrary than those of us who are interdisciplinary always feel.

Another challenge to my thinking from this session was the need to give up control over the shared collaboration space. In thinking about putting research projects into educational settings I’ve always looked at the process as trying to find a question within the research that can be understood and answered by students. The argument here was that to truly engage students it would be necessary to let them find and answer their own questions. I’m not sure how in practice to think about that in terms of drug discovery or how it maps on the success of projects like Galaxy Zoo but it bears some thinking about.

Also focussed on interactions beyond the professional research community was Ariel Waldman‘s session “Open collaboration between scientists, communities, and the unknown” which followed on from a session of the same title at SciBarCamp which I somehow missed. Here the focus was on problems with sharing research with the wider world, with similar problems to those of sharing between researchers identified,  and potential solutions. Some great projects were discussed and showcased with contributions on a new collaboration site for research into Parkinsons, getting the public to search for surface exposed fossils in high resolution ground images (Louise Leakey, Turkana Basin Institute), and the experience of being the public conduit for a spacecraft from Veronica “Mars PhoenixMcGregor. Once again a major theme was “just get the data out there” so that people can do something with it if they want to. If it isn’t available no-one is going to do anything.

The final session was lead by Joan Peckham on Computational Thinking, the idea that the principles behind good computing design should be taught as a core skill on a par with reading and writing, and that this techniques are widely applicable beyond computing per se. For more on the background to this you can checkout John Udell interviewing Joan on his Interviews with Innovators podcast. The point for me was to try and understand how I can most effectively learn these principles and techniques as it is clear to me that I need a better understanding of good software and system design for the work I would like to do. What was interesting to me was whether my needs mapped onto what would be required for teaching children and whether willing and interested guinea pigs such as myself might be useful in helping to develop educational programmes. Here engagement means effective use of technology and design of systems that will make our work and collaborations efficient.

Scifoo is always challenging, requiring that you re-think and re-examine many of the assumptions that your everyday work is built on. Many smart people with very different perspectives and experiences make a great environment to stress test your ideas, sometimes to destruction. The challenge can be actually applying those insights in the real world with limited resources and time. But it provides some goals to work towards and much food for thought.


  • Anna

    “the argument here was that to truly engage students it would be necessary to let them find and answer their own questions. I’m not sure how in practice to think about that in terms of drug discovery”

    It will be dependent on the level and which questions you ask. We successfully ran a “Dragon’s den” 3 week problem based learning session with our students on what one might badge as drug discovery. The important thing was to have an open-ended (‘real life’) question, but to have a guiding framework. The other really important thing is ‘facilitators’ – preferably PhD students (or even the next peer level up, which we have plans to implement), who are able to just respond ‘why’ to the students (more or less). There are lots of tips on how to include this as part of research-style undergrad practicals and we certainly intend to include more and more. I can give you more details, but the best place to start looking for info on PBL and CBL (in the UK) is: http://www.heacademy.ac.uk/physsci/home/pedagogicthemes/pbl

    Re: computational thinking – I agree. I’ve had an increasing realisation that I really need to take more courses on software design and engineering (and who knows, I might be able to join google in the end :) So if you know anything running directed at our target group, let me know! At the moment I have downloaded a pile of itunesU to look at ‘when I have time’.

  • Anna

    “the argument here was that to truly engage students it would be necessary to let them find and answer their own questions. I’m not sure how in practice to think about that in terms of drug discovery”

    It will be dependent on the level and which questions you ask. We successfully ran a “Dragon’s den” 3 week problem based learning session with our students on what one might badge as drug discovery. The important thing was to have an open-ended (‘real life’) question, but to have a guiding framework. The other really important thing is ‘facilitators’ – preferably PhD students (or even the next peer level up, which we have plans to implement), who are able to just respond ‘why’ to the students (more or less). There are lots of tips on how to include this as part of research-style undergrad practicals and we certainly intend to include more and more. I can give you more details, but the best place to start looking for info on PBL and CBL (in the UK) is: http://www.heacademy.ac.uk/physsci/home/pedagogicthemes/pbl

    Re: computational thinking – I agree. I’ve had an increasing realisation that I really need to take more courses on software design and engineering (and who knows, I might be able to join google in the end :) So if you know anything running directed at our target group, let me know! At the moment I have downloaded a pile of itunesU to look at ‘when I have time’.