- Series: MIT Press
- Hardcover: 416 pages
- Publisher: The MIT Press (January 2, 2015)
- Language: English
- ISBN-10: 0262028565
- ISBN-13: 978-0262028561
- Product Dimensions: 6 x 0.7 x 9 inches
- Shipping Weight: 1.4 pounds (View shipping rates and policies)
- Average Customer Review: 5 customer reviews
- Amazon Best Sellers Rank: #1,745,359 in Books (See Top 100 in Books)
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Big Data, Little Data, No Data: Scholarship in the Networked World (MIT Press) Hardcover – January 2, 2015
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Once again, Borgman hits it out of the park. She moves beyond the trendy discussion of 'big data' to focus on the real issue: data, the very concept of which differs among scholarly communities. The challenges to successful data sharing are legion, and she spells them out in detail. Those who follow her insights will save a lot of time and money.(John Leslie King, W. W. Bishop Professor of Information, University of Michigan)
We live amidst a sea of data. In Big Data, Little Data, No Data, Christine Borgman explores the depths and swells of that data and how they connect with scholarship and, more broadly, systems of knowledge. The result is an invaluable guide to harnessing the power of data, while remaining sensitive to its misuses.(Jonathan Zittrain, Professor of Law and Computer Science, Harvard University; Co-founder, Berkman Center for Internet & Society; Director, Harvard Law School Library)
Data by itself has no value. It's the ever-changing ecosystem surrounding data that gives it meaning. Borgman gets all of this and much more. Big Data, Little Data, No Data is filled with thoughtful discussion, examples, and case studies that provide a foundation for the much-needed conversations and decisions to be made about research data. This book is a primer for anyone trying to understand data relevancy in scholarship today.(Gregg Gordon, President and CEO, Social Science Research Network)
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.(Leonardo)
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)
About the Author
Christine L. Borgman is Professor and Presidential Chair in Information Studies at the University of California, Los Angeles. She is the author of From Gutenberg to the Global Information Infrastructure and Scholarship in the Digital Age (both winners of the "Best Information Science Book" award from ASIS&T), published by the MIT Press.
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Those who have read any of her previously published works – notably Scholarship in the Digital Age: Information, Infrastructure, and the Internet (2007) and From Gutenberg to the Global Information Infrastructure: Access to Information in the Networked World (2000), both also published by MIT Press — already know that she thinks with exceptional rigor and writes with uncommon eloquence. Non-scholars such as I also appreciate her ability to explain complicated relationships (e.g. disciplinary knowledge infrastructures) without dumbing down their unique significance. Here’s a brief sample of her style and grace in the first paragraph of her preface:
“Big data begets big attention these days, but little data are equally essential to scholarly inquiry. As the absolute volume of data increases, the ability to inspect individual observation decreases. The observer must step ever further away from the phenomena of interest. New tools and new perspectives are required. However, big data is not necessarily better data. The father the observer is from the point of origin, the more difficult it can be to determine what those observations mean — how they were collected; how they were handled, reduced, and transformed; and with what assumptions and purposes in mind. Scholars often prefer smaller amounts of data that they can inspect closely. When data are undiscovered or undiscoverable, scholars may have no data.” See what I mean?
These are among the several dozen passages of greatest interest and value to me, also listed to suggest the scope of Borgman’s coverage:
o Data management (Pages xviii-xix)
o Data definition (4-5 and 18-29)
o Provocations (13-15)
o Digital data collections (21-26)
o Knowledge infrastructures (32-35)
o Open access to research (39-42)
o Open technologies (45-47)
o Metadata (65-70 and 79-80)
o Common resources in astronomy (71-76)
o Ethics (77-79)
o Research Methods and data practices, and, Sensor-networked science and technology (84-85 and 106-113)
o Knowledge infrastructures (94-100)
o COMPLETE survey (102-106)
o Internet surveys (128-143)
o Internet survey (128-143)
o Twitter (130-133, 138-141, and 157-158(
o Pisa Clark/CLAROS project (179-185)
o Collecting Data, Analyzing Data, and Publishing Findings (181-184)
o Buddhist studies 186-200)
o Data citation (241-268)
o Negotiating authorship credit (253-256)
o Personal names (258-261)
o Citation metrics (266-209)
o Access to data (279-283)
Obviously, no brief commentary such as mine can possibly do full justice to the abundance of valuable information, insights, and counsel that Borgmnan provides but I hope I have at least indicated why I think so highly of her and this work.
Every day, we create 2.5 quintillion bytes of data — so much that 90% of the data in the world today has been created in the last two years alone. I agree with Christine Borgman: “The challenge is to make data discoverable, usable, assessable, intelligible, and interpretable, and do so for extended periods of time…To restate the premise of this book, the value of data lies in their use. Unless stakeholders can agree on what to keep and why, and invest in the invisible work necessary to sustain knowledge infrastructures, big data and little data alike will become no data.” That is the peril and, yes, the opportunity that await in months and years to come.