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on February 4, 2012
This is a wonderful account of how the digital environment is changing how we work - in this case how science is done, and who can do science. The first half of the book is the best as it uses a number of case to illustrate Big Data projects and the positive potential of 'Big' open data. For anyone interested in the implications of open data this is a great resource. He elaborates how the digital environment allows us to connect the right person with the right knowledge to the right situation - helping to restructure expert/knowledge attention.

He provides the foundation - the cases for understanding that the wisdom of crowds is in fact a way of social computing.

The second half of the book is focused more on the policy implications necessary to democratize science, accelerate discovery, improve access to the results of science, reshape how we incentivize scientist to share their data to create open data and enable how new ways of asking questions and finding answers. He challenges the hold that old methods of science journals have and how it was once the key to spreading knowledge but has become a throttle today.

This is an important topic today - if only our politician understood these issues to help in shaping our 21st century infrastructure. Highly recommend this book.
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on July 21, 2015
The author points to new approaches of creating knowledge based on open science and mass collaboration among researchers, including: real-time posting of ideas and lab results, software for tapping collective intelligence, crafting of data webs and open access to speed up the creation of new knowledge. The author illustrates these concepts with specific examples such as Polymath Project, Galaxy Zoo, HapMap, Genbank, Innocentive, PLoS, and Foldit. In the author's words, "the division of labor is changing, with some people specializing in building the experimental apparatus and collecting data, while others specialize in analyzing the data from those experiments.' The promise of this 'new era' of science is the potential for tackling both increasing complex problems and more elaborate models of explanation (i.e. behaviour of simulation models rather than single mathematical equations or universal laws).

Nielsen is critical of these approaches, noting they favor modular participation in fields of inquiry where a shared praxis exists, which facilitates a dynamic division of labor via manageable subtasks. The implication is that such approaches are more relevant for fields with a high degree of agreement on problems and methods (such as bioinformatics, chemistry, econometrics) and less immediately relevant for fields marked by pluralism (such as public policy). Additionally, the trends towards 'networked science' are countered the 'publish or perish' incentive: the competitive pressure on professional scientists to allocate their time to "the kinds of activities that lead to jobs, grants, and promotion".

Yet this book has two interrelated weaknesses. First is the author's wide ambition, which means the book covers a lot of material somewhat superficially, almost inundating the reader in jargon or 'hot topics'. Second, the author sometimes follows spurious non-topics, such as pondering the distinction between simple vs complex explanation, or ideas vs models, rather than the nature of intelligence and explanation. Consider language translation, both human and machine approaches 'work'. Whereas human translation is based on in depth knowledge of causality (how people use and understand messages), machine translation is more correlation (which word in one language has a high probability of being represented by another given the frequency of word pairs in a database of billions of texts). There is a deeper philosophy of science here regarding how do we know what we know that belies the variety of methods for asking and answering questions.

It is precisely this potential that ultimately remains unexplored in this otherwise impressive book. Nielsen eludes to Homer-Dixon's 'ingenuity gap' between the complexity of the problems faced by a society and that society''s capacity to solve such problems. Yet this is also left largely unexplored in the book, with the author merely suggesting that bridging this gap requires changing the institutions that shape 'who funds research', 'how science informs policy', and 'who can be a scientist''.

In short, a good introduction to the topic and survey of emerging topics, yet readers already familiar with research policy and some of these approaches will be left wanting more.
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