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Personal knowledge networking

From Wikipedia, the free encyclopedia

Personal knowledge networks are methods for organizations to identify, capture, evaluate, retrieve, and share information. This method was primarily conceived by researchers to facilitate the sharing of personal, informal knowledge between organizations. Instead of focusing on the organizational context, some researchers investigate the intra-firm aspects at the personal level of organizational knowledge networks, where knowledge management (KM) processes both begin and end.[1] Various technologies and behaviors support personal knowledge networking, including wikis, Really Simple Syndication (RSS), and relationship networks. Researchers propose that knowledge management can occur with little explicit governance. This trend is referred to as "grassroots KM" as opposed to traditional, top-down enterprise KM.

Origin

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New models have emerged for the continuous operation of knowledge management. Apart from formal arrangements for official alliances, individuals often know each other and interact beyond their official duties, leading to knowledge flows and learning.[2]

  • Drawbacks of Traditional Knowledge Management
Traditional Knowledge Management focuses more on technology than on social interaction.[3] Organizations should first look at the culture inherent inside, as it significantly affects the social interaction among members involved.
  • Technical Support from Social Network
Social software provides an answer to this previous question. It is a means of giving people what they want in terms of their traditional knowledge management activities, in a way that also benefits the firm.[4]

Comparison between KM and PKN

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Structural Aspect

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  • Content-Centric vs User-Centric
A content-based process is regarded as a major factor leading to the incompatibility of Knowledge Management in the current situation. In contrast, a user-based process focuses on each individual in a learning process, shifting the driving force of knowledge from an organization's content database to the learners themselves. Furthermore, knowledge can only be evaluated or managed by individuals, emphasizing its unique nature.[5]
  • Centralized vs Distributed
In the PKN model, knowledge learning is undertaken with a high consideration of its natural distributed format. In comparison, the centralized feature has been proven to perform well in guiding an organized and structured learning session.[6] However, the well-structured guidance could hardly satisfy the various and timely requirements of today's users.
  • Top-Down vs Bottom-Up
Top-down models and hierarchically controlled structures are the enemies of innovation.[7] In general, learners and knowledge workers love to learn, but they hate not being given the freedom to decide how they learn and work (Cross, 2003).[8] Given this fact, a better way to cope with this system is to let them develop and emerge naturally in a free-form way, which could be abstracted to a bottom-up structure.[9]
  • Enforcement vs Voluntary
Traditional KM mainly adopts a pushing model that passively provides content to users and expects the learning process to happen. This model is not sufficient to improve learners' motivation. Considering the dynamic and flexible nature of the learning process, LM and KM approaches require a shift in emphasis from a knowledge-push to a knowledge-pull model.[10] PKN provides a more attractive platform where users can locate content according to their needs from information repositories.

Application Aspect

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References

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  1. ^ Ismail, S.; Ahmad, M.S.; ‘Emergence of personal knowledge networks in agent-mediated PKM processes: A qualitative analysis in the Malaysian context, Computer & Information Science (ICCIS), 2012 International Conference on Computer & Information Science (ICCIS), 2012 vol. 1, no., pp. 72-78, 12–14 June 2012
  2. ^ F. Huber, “Contextualising the Role of Extra-Firm Personal Networks as a Source of Work-Related Knowledge,” Organisational Learning, Knowledge and Capabilities (OLKC) Conference, Hull, UK, 2011
  3. ^ Delmonte, A.J. and Aronson, J.E. (2004) ‘The relationship between social interaction and knowledge management system success’, Journal of Knowledge Management Practice, Vol. 5.
  4. ^ Penny Edwards, (2009), Role of social software and networks in knowledge management. http://www.headshift.com/our-blog/2009/09/14/role-of-social-software-and-ne/ Retrieved 2012-11-03
  5. ^ Wilson, T.D. (2002) ‘The nonsense of ‘knowledge management’ Archived 2017-12-26 at the Wayback Machine, Information Research, Vol. 8, No. 1, p. 144.
  6. ^ Siemens, G. (2006) Knowing Knowledge Archived 2008-07-04 at the Wayback Machine, Lulu.com, ISBN 978-1-4303-0230-8.
  7. ^ M. A. Chatti, M. Jarke, D. Frosch-Wilke, The future of e-learning: a shift to knowledge networking and social software, International Journal of Knowledge and Learning, Vol. 3, No. 4. (2007)
  8. ^ Cross, J. (2003) ‘Informal learning – the other 80%’, Internet Time Group.
  9. ^ Cross, J. (2005) ‘Educating ourselves at emerging’, Internet Time Blog.
  10. ^ Naeve, A. (2005) ‘The human semantic web – shifting from knowledge push to knowledge pull’, International Journal of Semantic Web and Information Systems (IJSWIS), Vol. 1, No. 3, pp. 1–30.