Beki Grinter

Posts Tagged ‘empirical studies’

Growth of ICT4D research

In ICT4D, research on February 13, 2010 at 4:45 pm

Richard Heeks recently posted data showing the growth of ICT4D research.

I find this interesting.

I am sure that you can produce similar data about Biomedical Informatics research. Easily. That would not peek my interest as much.

Because there’s an important difference between Biomedical Informatics and ICT4D, a battle for legitimacy. From what I understand the history of Biomedical Informatics, in addition to being a history of growth is one of finding a name. Biomedical Informatics appears to supersede Health Informatics (although that’s still very much used). It’s also meant to imply more than Bioinformatics. And then there’s a history of different names being used in North America and Europe (I think that’s some of the difference between Health and Medical Informatics). But, things do largely seem to be converging on Biomedical Informatics as the right name for the discipline, with specialities in all sorts of things such as public health informatics, clinical informatics, bioinformatics, and so forth.

But, that’s the name… and the name has been changed and discussed to reflect what should be included in the field. (I have my own opinions of course, which turn on doing the thing that I find myself frequently doing, which is to inspect assumptions… that’s how the idea of Wellness Informatics started, as a means to organize that type of inspection… and I still don’t know where it stands, but I have and continue to enjoy the conversations and people that that process has facilitated).

By contrast, ICT4D has been growing while the people doing the research have been discussing what the research is in the field. That, at least to me, seems quite unusual. To have sustained growth and increased commitment to a field of research for which the case for the research in the field is not clear, even to some of those who do work in the field.

Now that’s interesting. There seems to be a collective “gut sense” that this is an area with rich possibility even though the nature of that possibility is hard to pin down. I wonder whether some of it can be explained by the low morale in CS, and what I see as some of the differences that this area supports… But I don’t know.

All I do know is that smart people, and increasing numbers of them, are putting their bets on ICT4D. And perhaps that’s as it should be. Some of my management are fond of the idea that high risk equals high reward. Well I’d say it’s pretty risky to take on things that the research reward is not clearly understood.

Lucky Physicists and the Devolution of Computer Science

In academia, computer science, discipline on May 26, 2009 at 9:43 pm

There are two types of books one can read about academia.  One genre is the academic “how to” book.  I’ve just written about an example in that genre that I found particularly insightful.  The second is a genre that studies academia itself.  It’s in this second genre that I conclude that Physicists are lucky people indeed.

Many years ago I read Sharon Traweek’s Beam Times and Life Times.  It certainly explained the person I was dating—a High Energy Particle Physicist. But, to the book. The book was a multi-sited ethnography of the way that Physicists work. The division of work differs from computing, and those differences emerge at the graduate school level. Working in teams is the simplest way to describe it, hierarchical teams composed of theorists and experimentalists. Traweek’s book did a marvelous job of explaining how these teams produce the science of physics.

And yesterday I started reading another book about Physicists. This is a longitudinal ethnography, following 55 Physicists over some years, understanding how their career evolves over time and as they climb through the ranks of Assistant, Associate and finally Full Professor. I’ve only just started it, but already I’m finding it quite instructive in thinking how an academic career evolves, and what that might me for me.  (It also makes me think that I should assign the two books as an example of how ethnography is not just one thing, but a methodology that consists of numerous approaches to data collection and analysis. If you add in Latour and Woolgar’s Laboratory Life, you have a third approach to studying scientists and the doing of science).

Computer Scientists by contrast have been woefully neglected in study. There are some books about engineering in practice (Kunda, Bucciarelli for example). But not in the academic context. And this is a shame, because Computer Science is in an interesting transitional period, and one with particular implications for the organisation of the academy. (It almost certainly has other implications but lets begin here for now).

Computer Science is in a period of devolution. Devolution into entities that will be the intellectual home for an increasingly divergent number of research problems and pursuits that go under the banner of Computer Science. One can view this devolution as entirely pragmatic. The field is still fairly young and has enjoyed explosive growth and rapid change (both can be attributed to not just the increased presence of computing technologies, but also the radical transformations that they’ve undergone in terms of size, power, form factor, that fuels a series of alternate possibilities, there are certainly other reasons, these just strike me as some obvious ones). In response to this explosive growth and rapid change, so Computer Science has expanded to accommodate the new research problems and domains made possible. And, here’s the really pragmatic part, the organization of Computer Science as a discipline is now stretched, well it seems to be. Perhaps it’s because no-one wants to have faculty meetings with 100 people that you see an increasing devolution of previously single, monolithic Computer Science entities (such as the College of Computing at Georgia Tech, or the Information and Computer Sciences School at Irvine into a series of smaller organizational entities). (There’s more to say about Computer Science organized inside Engineering and the rise of the ISchool movement, and perhaps I will at some future date).

These smaller entities interest me greatly. Again comparing GT and UCI, we see three different sub structures: Computer Science, Informatics, and Statistics at Irvine, while Georgia Tech has Computational Sciences and Engineering, Computer Science, and Interactive Computing. Do the names matter. Yes, I think so. For many other departments these names are the names of their disciplines (such as finding Physics, Chemistry, Civil Engineering departments that characterise what goes on in them and with what disciplinary entity that research work is associated).

So, lets take a case of a particular speciality in Computer Science, Software Engineering. At GT you’ll find it in Computer Science, but at Irvine it shows up in Informatics. What implications does that have for the practice of Software Engineering? Right now, I don’t know. But will it, that’s what I wonder. When will what we have become institutionally become what we do, our community of practice professionally.  Then there’s a question of contested turf. The name Computer Science is not without problems, particularly when applied to one piece of the organization. Is the implication that what is not within Computer Science is not Computer Science research?  If my boss read my blog, I think he’d groan about this particular comment, one way I have experienced this is rather personally (yes, I certainly do research that’s unusual in Computer Science, I thought that that’s what taking risk meant, but I have always taken the risk identifying myself and my purpose as being invested in the future of Computer Science research).

But there’s far more on the table here than my own ego (big as that is). I think what might be on the table is institutional legitimacy and disciplinary organization and discourse. If an organization is structured to make something possible, it simultaneously hinders other things. What is organizationally near (i.e., in the same organization, sharing a common reporting structure, the more the better) is far easier to accomplish than what requires crossing organizational divides. So, we can view the organization of Computer Science as a set of bets, bets about what will happen if we put some things in the same place and separate others.  I wonder how to place those bets, but that’s because I find organizations absolutely fascinating. At the same time there’s an undercurrent—a suggestion—of a separation that might result in a smaller discipline of Computer Science, and something larger that encompasses the full span of activities that formerly used to be Computer Science (and a question of what that larger entity is, what it’s project is, what space does it occupy at the national level). Transition can be difficult, graduate school is a preparation for a career of identity management and assessment (my vita speaks volumes about Computer Science research, and says nothing about Physics research, not just in content, but also in the mechanisms used to produce that content like whether I choose to write books, journals or conference papers). The Institutional legitimacy I think turns on this somewhat, that identity is not just what we do, but what is given back to us by our ability to affiliate with a particular research discipline.

So, I wish someone had studied us. I wish I could pick up a multi-sited ethnography, preferably also longitudinal, to get some ideas about what if anything my colleagues are doing about the devolution of Computer Science. How they handle identity and legitimacy. What organizations are being created and how that gives rise to new areas of research, and what it might potentially close off. Lucky Physicists as their field evolves they have a series of guides to stimulate and frame questions. But, perhaps we are lucky enough even despite not having these studies because what we have an abundance of right now is opportunity. Opportunity to rethink it all, if we are quick, thoughtful, and open to devolution.