From Ignorance Map to Informing PKM4E Framework: Personal Knowledge Management for Empowerment
The proposed Personal Knowledge Management (PKM) for Empowerment (PKM4E) Framework expands on the notions of the Ignorance Map and Matrix to support the educational and informing concept of a PKM system-in-progress.
The accelerating information abundance is depleting the very attention our cognitive capabilities are able to master, contributing to widening individual and collective opportunity divides. Support is urgently needed to benefit Knowledge Workers irrespective of space (developed/developing countries), time (study or career phase), discipline (natural or social science), or role (student, professional, leader).
The Design Science Research (DSR) project conceptualizing the PKM System (PKMS) aims to support a scenario of a ‘Decentralizing KM Revolution’ giving more power and autonomy to individuals and self-organized groups.
The informing-science-related approach synthesizes and visualizes concepts related to ignorance and entropy, learning and innovation, chance discovery and abduction to inform diverse audiences and potential beneficiaries.
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The PKM4E learning cycles and workflows apply ‘cumulative synthesis’, a concept which convincingly couples the activities of researchers and entrepreneurs and assists users to advance their capability endowments via applied learning.
In substituting document-centric with meme-based knowledge bases, the PKMS approach merges distinctive voluntarily shared knowledge objects/assets of diverse disciplines into a single unified digital knowledge repository and provides the means for advancing current metrics and reputation systems.
The PKMS features provide the means to tackle the widening opportunity divides by affording knowledge workers with continuous life-long support from trainee, student, novice, or mentee towards professional, expert, mentor, or leader.
After completing the test phase of the PKMS prototype, its transformation into a viable PKM system and cloud-based server based on a rapid development platform and a noSQL-database is estimated to take 12 months.