Reinventing Discovery - Michael Nielsen [115]
Data-driven science: One of the first people to understand and clearly articulate the value of data-driven science was Jim Gray, of Microsoft Research. Many of his ideas are summarized in the essay [83], which I also mentioned above. That essay is part of a stimulating book of essays entitled The Fourth Paradigm [94]. The book is freely downloadable from the web, and gives a good overview of many parts of data-driven science. Another thought-provoking article is “The Unreasonable Effectiveness of Data” [88], by Alon Halevy, Peter Norvig, and Fernando Pereira. All three of the authors work for Google, which has perhaps the most data-driven culture of any organization in the world, and the article conveys well the radical shift in perspective that comes from thinking in a data-driven way. If you have a background in programming, I also recommend Norvig’s terrific short essay [157] on how to write a (data-driven, naturally!) spelling corrector in just 21 lines of code. There are many, many texts and papers on topics related to data-driven intelligence. (Note, though, that most don’t use the term.) A good practical introduction is Toby Segaran’s Programming Collective Intelligence [191].
The democratization of science and citizen science: The democratization of science has analogs in the business world, in phenomena such as user-generated innovation, and open innovation models for business. See, for example, Eric von Hippel’s book Democratizing Innovation [233], whose title inspired the title of chapter 7, and Henry Chesbrough’s Open Innovation [36]. The point of view developed in chapter 7 also owes a great deal to Clay Shirky’s notion that our society has a cognitive surplus [195, 194; see also 196] which can be used in the service of new forms of collective action.
Open science: My analysis of open science is strongly influenced by the work of Mancur Olson [161] on collective action, and by the work of Elinor Ostrom [165] on the management of common pool resources such as fisheries and forests. Both these works have many more implications for open science than I have described. In particular, I only briefly touched on many of the detailed principles that Ostrom identifies for the management of common pool resources. Many of those principles can be fruitfully applied or adapted to open science. I have also been stimulated by the work of Robert Axelrod [9] on the conditions under which parties will cooperate; the problem of large-scale cooperation is an example of a collective action problem. On the early history of open science, I’ve been stimulated by many sources, but especially by Paul David [49], Elizabeth Eisenstein [61], and Mary Boas Hall [89].
One thing that pained me while writing this book is that narrative constraints meant that I’ve had to omit nearly all the thousands of open science projects now going on. Fortunately, there are many excellent sources for keeping track of what’s going on in open science today. Let me mention just a few. One of the most valuable is Peter Suber’s website (http://www.earlham.edu/~peters/hometoc.htm), which is a tremendous resource on all aspects of open science, but especially open access publishing. Suber’s superb blog (http://www.earlham.edu/~peters/fos/fosblog.html) is no longer updated, but remains a valuable historical resource. And Suber’s ongoing Open Access Newsletter (http://www.earlham.edu/~peters/fos/newsletter/archive.htm) is essential. Another excellent source