Big Data, Little Data, No Data: Scholarship in the Networked World (MIT Press)
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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
- Publisher : The MIT Press (January 2, 2015)
- Language : English
- Hardcover : 416 pages
- ISBN-10 : 0262028565
- ISBN-13 : 978-0262028561
- Reading age : 18 years and up
- Item Weight : 1.5 pounds
- Dimensions : 6 x 0.69 x 9 inches
- Best Sellers Rank: #2,144,168 in Books (See Top 100 in Books)
- Customer Reviews:
Top reviews from the United States
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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.
Top reviews from other countries
It is a readable account of data in all their forms, sources and usages (1), generated in the sciences, social sciences and the humanities. This book is aimed at scholars (2), but I think it would be useful to anyone who is responsible for data, giving them a wider perspective. This book is not a manual on the technical techniques of handling extra-large data sets that are becoming more common nor is it a discussion of where the emergence of these extra-large data sets will lead us.
The author's reason for writing this book can be found on page 14. It also provides a representative example of the writing style used throughout. This style avoids academic jargon, but is very inclusive: ".... data is a far more complex subject than suggested by the popular press or by policy pronouncements. It remains large and unwieldy, even when constrained to research and scholarship. Although the literature on research data is growing rapidly, each journal article, conference paper, white paper, report, and manifesto addresses but one part of the elephantine problem. This book is the first monograph to assess the whole elephant of data from social, technical, and policy perspectives, drawing on examples from across the academic disciplines. It picks up where the more general exploration of scholarship in the digital age left off ( Borgman 2007 ), addressing the radical expansion of interest in data in the interim ...".
The author then defines "six provocations". These are intended to frame the book's "narrative" and provoke discussion. I expected these key points to be briefly named, but each was several sentences long and had a slippery definition. The last two, on knowledge Infrastructures, seemed to me to be describing the same thing. As far as I can tell, these provocations concerned: data re-use; data transfer by discipline and over time; differentiating data from academic writings; the consequences of open access; and knowledge infrastructures evolving over time.
The book has 287 pages of text, divided into three parts: Part I Data and Scholarship; Part II Case Studies in Data Scholarship; Part III Data Policy and Practice. As would be expected of a book aimed at academics it has extensive References (72 pages) and it is well-indexed (23 pages).
There are six case studies, two from the sciences, two from the social sciences and two from the humanities. Each case study is discussed within the same framework, consisting of: Size Matters; Sources and Processes; Knowledge Infrastructure; External Influences; and Conducting Research in the case study area. Conduction Research is divided into: Research Questions; Collecting Data; Analyzing Data; Publishing Findings; Curating, Sharing and Reusing Data. Thus using these examples the reader can compare and contrast their own area of study within the framework provided.
(1) I am trying to follow this book's consistent and correct use of the word data as a plural. However, I find it very hard to do. I have never come across the singular, datum, and the word data always seems to imply to me a data set, which is singular.
(2) The author uses the terms scholar, scholarship and research throughout, for which I read academic.