Federated knowledge synthesis
- Part of: Discourse Modeling
- Contributors
Knowledge production starts with the work of individuals and teams. Such contributions are then refined and synthesized in topical communities, disciplines, and other higher-level organizational structures. A big challenge at each move to a higher organizational level is the divergent jargon and terminology of the lower-level entities that wish to join forces. Sometimes there is one dominant entity that ends up imposing its choices. This is arguably not the best way to proceed, and not even an option in more egalitarian settings. Common vocabulary (including semantics in formal systems) can only emerge by consensus, a process that is poorly supported by digital knowledge management tools.
One idea for supporting collaboration in spite of divergence, and ultimately consensus formation, is federation. The general idea is to establish "informational meeting points" where each entity exposes its vocabulary in a structured fashion, making divergent definitions explicit and easy to find and compare. Participants can then switch to someone else's definition if they consider it more appropriate, making a step towards consensus (which however may never be complete).
The goals of this project (perhaps better called a meta-project) are:
- Identify existing technology (tools, data models and formats, protocols, ...) that look promising to support a federated mode of knowledge synthesis. Examples: Fedwiki, anagora
- Support projects that improve and extend existing technology. Such support includes providing feedback on each other's work, testing each other's tools, etc. In short: apply the federation idea to develop better infrastructure for federated knowledge synthesis, in a multi-disciplinary setting.
- Think about the social structures that are desirable for consensus formation, and ensure that the technological infrastructure supports them (never forget Conway's law!)