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Rugg, Gordon; Rigby, Colin; Gerrard, Sue; Martin, Amy; Skillen, Jennifer; Bonfiglio, Emma; Gardner, Allison; Guo, Yuxin; Minocha, Shailey and Taylor, Gavin
(2022).
DOI: https://doi.org/10.14236/ewic/hci2022.20
Abstract
In this article, we outline the concept of knowledge infrastructure and describe how it differs from Information Technology (IT) infrastructure, with particular regard to the implications for education theory, practice and policy. We examine the inherent limits to growth for attempts to handle knowledge, as opposed to information, via the types of software and hardware likely to be available in the next few decades. We show how a simple process model can be used to identify pinch points where knowledge, as opposed to information, is a bottleneck. We also show how a simple model of knowledge types and knowledge locations can be combined with the process model to remove those bottlenecks via existing low-cost technology and a more efficient use of existing human expertise. We conclude that a minimal investment in knowledge infrastructure would provide significant human, social and economic benefits, by creating major added value from existing digital and organisational infrastructure.
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About
- Item ORO ID
- 86565
- Item Type
- Conference or Workshop Item
- Keywords
- tacit knowledge; semi-tacit knowledge; information; knowledge; sociotechnical
- Academic Unit or School
-
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM) - Copyright Holders
- © 2022 Rugg et al. Published by BCS Learning & Development. Proceedings of the 35th British HCI and Doctoral Consortium
- SWORD Depositor
- Jisc Publications-Router
- Depositing User
- Shailey Minocha