The book proposes a systematic approach to big data collection, documentation and development of analytic procedures that foster collaboration on a large scale. This approach, designated as "data factoring" emphasizes the need to think of each individual dataset developed by an individual project as part of a broader data ecosystem, easily accessible and exploitable by parties not directly involved with data collection and documentation. Furthermore, data factoring uses and encourages pre-analytic operations that add value to big data sets, especially recombining and repurposing.
The book proposes a research-development agenda that can undergird an ideal data factory approach. Several programmatic chapters discuss specialized issues involved in data factoring (documentation, meta-data specification, building flexible, yet comprehensive data ontologies, usability issues involved in collaborative tools, etc.). The book also presents case studies for data factoring and processing that can lead to building better scientific collaboration and data sharing strategies and tools.
Finally, the book presents the teaching utility of data factoring and the ethical and privacy concerns related to it.
Chapter 9 of this book is available open access under a CC BY 4.0 license at link.springer.com
This book is an edited volume of case studies exploring the uptake and use of computer supported collaborative learning in work settings. This book fills a significant gap in the literature. A number of existing works provide empirical research on collaborative work practices (Lave & Wenger, 1987; Davenport, 2005), the sharing of information at work (Brown & Duguid, 2000), and the development of communities of practice in workplace settings (Wenger, 1998). Others examine the munificent variation of information and communication technology use in the work place, including studies of informal social networks, formal information distribution and other socio-technical combinations found in work settings (Gibson & Cohen, 2003).
Another significant thread of prior work is focused on computer supported collaborative learning, much of it investigating the application of computer support for learning in the context of traditional educational institutions, like public schools, private schools, colleges and tutoring organizations. Exciting new theories of how knowledge is constructed by groups (Stahl, 2006), how teachers contribute to collaborative learning (reference to another book in the series) and the application of socio-technical scripts for learning is explicated in book length works on CSCL. Book length empirical work on CSCW is widespread, and CSCL book length works are beginning to emerge with greater frequency.
We distinguish CSCL at Work from prior books written under the aegis of training and development, or human resources more broadly. The book aims to fill a void between existing works in CSCW and CSCL, and will open with a chapter characterizing the emerging application of collaborative learning theories and practices to workplace learning. CSCL and CSCW research each make distinct and important contributions to the construction of collaborative workplace learning.