An examination of the uses of data within a changing knowledge infrastructure, offering analysis and case studies from the sciences, social sciences, and humanities.
"Big Data" is on the covers of Science, Nature, the Economist, and Wired magazines, on the front pages of the Wall Street Journal and the New York Times. But despite the media hyperbole, as Christine Borgman points out in this examination of data and scholarly research, having the right data is usually better than having more data; little data can be just as valuable as big data. In many cases, there are no data-because relevant data don't exist, cannot be found, or are not available. Moreover, data sharing is difficult, incentives to do so are minimal, and data practices vary widely across disciplines.
Borgman, an often-cited authority on scholarly communication, argues that data have no value or meaning in isolation; they exist within a knowledge infrastructure-an ecology of people, practices, technologies, institutions, material objects, and relationships. After laying out the premises of her investigation-six "provocations" meant to inspire discussion about the uses of data in scholarship-Borgman offers case studies of data practices in the sciences, the social sciences, and the humanities, and then considers the implications of her findings for scholarly practice and research policy. To manage and exploit data over the long term, Borgman argues, requires massive investment in knowledge infrastructures; at stake is the future of scholarship.
Publisher: MIT Press Ltd
Number of pages: 416
Weight: 567 g
Dimensions: 229 x 152 x 17 mm
This reading might be of enormous value to interdisciplinary scholars, seeking to test or adapt different data methods, but also for students, that need to get introduced to them. Without holding back, I would recommend this book, for its clarity, well-organised arguments and throughout approach as a university handbook in the area. It is more than enough to get known to status, practices and procedures concerning any type of data in different research field areas.
Big Data, Little Data, No Data is no mere bibliography or literature review, nor is it a how-to-do-it manual on data curation. It is an extended thought-piece, firmly grounded in the author's extensive experience with all-things data, and her knowledge of the work and writings of hundreds of other scholars over time.
-Journal of the Association for Information Science and Technology