
In today’s complex, rapidly evolving world, vast amounts of data exist in isolated silos, shared for corporate gain through polarizing algorithms. It is a democratic imperative to make this data become interoperable technically, and more importantly, culturally. Community-driven knowledge networks emerge as a solution, yet face unique social hurdles, particularly when tackling politically charged topics or crossing disciplinary boundaries.
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