The Meaning of Data panel at a class on the Rhetoric of Science

Update: Lawrence Souder provided the audio for the presentation and panel questions.

On October 6, 2010 I had the pleasure to participate in a panel discussion at Lawrence Souder's class on the Rhetoric of Science. I gave a brief presentation on "The Meaning of Data" to kick off the discussion. I provided a scientist's perspective of data - with the basic idea that at best data are evidence. Data cannot be treated as irrefutable facts since there is always some uncertainty and many assumptions must be made in their interpretation. I also argued that, although uncertainty cannot be eliminated completely, transparency goes a long way to reducing it.

The students in the class did not have a science background and I think it was informative for them to explore a different perspective from their other exposure to science through popular media or even textbooks. The term "fact" is thrown around a lot in these information sources to simplify but it doesn't reflect how scientists think about data. We discussed how unbelievably wrong the scientific details in movies and TV shows such as NCIS and House can be. Nevertheless, one student pointed out that these shows can be effective in attracting people to science - as long as it was understood that the details were probably incorrect.

Because of market forces we recognized that science portrayed in the popular media would have a strong tendency to be exaggerated or oversimplified resulting in the phenomenon of "hype". A related effect can distort the way scientists communicate with each other, where there is a perception that exposing ambivalence in the form of seemingly contradictory data may not be in the researcher's best interest. This is a strong deterrent to the general adoption of transparency.

We explored the possible evolution of scientific communication as new tools such as blogs and wikis become increasingly used by scientists. Of course the issue of claims of priority was brought up and I discussed how this issue was handled in my own research work.

We debated whether these new forms of communication would alter the language used in scientific communication - even in traditional journals. I think that with the advent of the semantic web many researchers will start to write in a way that is understandable to humans as well as machines, their new target audience. One student remarked that the new generation coming up is very used to texting and that type of succinct communication is certainly in line with machine readability.

The assigned reading for the class involved a study of the language used by the Nobel laureates who discovered the buckyball to describe their research:

"In Praise of Carbon, In Praise of Science - The Epideictic Rhetoric of the 1996 Nobel Lectures in Chemistry by Christian Casper". This paper demonstrates that both personality and the perceived target audience can dramatically affect the language and focus that scientists use to explain their research.

The Meaning of Data

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