At present this is a portal to discussions and resources on open semantic ontologies, folksonomies, taxonomies, vocabularies, dictionaries, databases, knowledge bases, etc.; Read-Write Web (RWW) data structures and protocols like linked-data and RDF; the tools and resources for using them; and ways the commons/p2p community can collaborate on these issues and technologies.
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The P2P collaborative economy, free culture, and new commons movements are creating a lot of digital content. Most is in discursive and narrative form that is time consuming to read. This volume of content includes news, opinion articles and essays, online books, social dialog, history, case studies in a variety of formats (many very informal), business plans, proposals, and presumably many legal documents (charters, agreements, etc.) and many other kinds of content.
I am imagining an ontology (perhaps a hybrid ontology/folksonomy) according to which the key ideas and data of this content could be parsed, tagged, and cross linked to form a distributed knowledge base using linked-data structures. This would help transition the collective knowledge of the research, activist, and social entrepreneurial communities into a machine-readable, cross linked, semantically searchable form.
The P2P Foundation Wiki is an excellent searchable resource on peer-to-peer culture, theory, and the collaborative economy, and perhaps the semantic extensions for the Wikimedia engine could eventually be applied. "A semantic wiki is a wiki that has an underlying model of the knowledge described in its pages. Regular, or syntactic, wikis have structured text and untyped hyperlinks. Semantic wikis, on the other hand, provide the ability to capture or identify information about the data within pages, and the relationships between pages, in ways that can be queried or exported like a database." http://en.wikipedia.org/wiki/Semantic_wiki
A fringe benefit of creating such data structures for existing content would be to provide common templates for future content creation and data collection.