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How to Structure Data for Humanitarian Learning
Abstract
How should we structure data describing global change? How can we achieve humanitarian development by support of structured data? To answer this question, a fresh view on “learning” is provided from an interdisciplinary viewpoint. The underlying conceptual model of a network society combined with empirical research on long-term civilisational and economic evolution allows to generally understand data structures and IT as facilitators of a multi-perspectivist and multi-disciplinary construction of world views (m:n type of science). Such a synopsis of education, structural evolution, social spaces, and institutional change provides insight into data science's strategic role of facilitating consensus building and constructing common world views that can socially converge isolated cultures of understanding. The interdisciplinary discipline of geography is here seen as a provider of world views that emerge from communicative action. The presented cases span both geographic locations as well as constructed cultures of understanding.
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