More thoughts about data and extending science

Some of the most expensive data that we collect is qualitative and/or observational data. Making these data available to other researchers so that they can ask other types of questions or re-analyze data seems like an especially good idea.

There is one good example of this at the U of Illinois that begins to open up these data. This project is called the "Ethnography of the University." Faculty and students have agreed to share their data, publications, etc. in a common space. This allows more students to have access to the data, extend the questions, develop new ideas and exchange information.

Students who are interested in various topics about student life among university students have the opportunity to view multiple perspectives on this topic. Students interested in learning more about how scientists create ethnographies can see science in action.

Scholarship in the Digital Age by C. Borgmann

In this book, Christine Borgmann writes about all the ways in which scholarship among academics is changing and is likely to change as a result of digital publication.

The parts of this book that are especially interesting to me are about the social side of this technological change. For example, she writes:

Collaboration, especially over distance, has high overhead costs. (p. 29)

Much remains to be learned about the factors that make collaboration more or less successful, and the circumstances under which it is most likely to be worth the effort (See Cummings and Kiesler for more examples of this problem). (p. 29)

datebases and scholarly communication

The primary way in which scholars have communicated new scientific knowledge and to the advancement of science has been through the publication of research findings. (this ignores theoretical contributions, but that matters also.)

It seems to me that the vast increase in the ability to store large amounts of information affords the opportunity to ask the question what other ways might scientific scholarship be advanced in addition to publishing findings.

One idea that intrigues me is the sharing of data sets with others and developing interactive data analytic tools to explore these databases. Here is one nice example. The KidsCount Data Center keeps track of over 100 child and family indicators of well-being. At the data center you can select indicators, create comparision's and compare data in a variety of other ways. By making the data available in this fashion, other researchers or even the public at-large can answer questions using this data. No one is going to make scientific breakthroughs with this data, but all of us can find answers to questions that may be of interest to us: Are the trends in teen pregnancy in my state above the average in the US? Are children's reading scores improving? What has happened to teen drinking in the US?

With more powerful tools it would be possible to look at correlations, compare whether differences between counties or states were statistically significant, and so forth.

Imagine if more specialized data collected by scientists were routinely available to other researchers and the general public, wouldn't this advance science all the more quickly?