Semantic Social Networks (SSN)
Technically, a semantic social network is two or more connected Samarai brains. We are assuming they are communicating using Havel but it could be any universal graph language.
The underlying idea is simple: Users setup Samarai brains, fill them with information and functionality and connect them to other brains in order to communicate, organize and collaborate.
The brains can run in the cloud, on servers or on personal devices. Where they run is a question of resources, connectivity, practicality and convenience. Each brain has one or multiple functions, maybe information repository, messaging hub, shop, business or community management service, anything really.
The brains connect through different mechanisms. They can be manually mounted as remote brains or information repositories. They can discover each other in a local network. There can be brains that act as connection hubs or "search engines". Peer-to-peer technology can be used.
SSNs that run on internet infrastructure do not have physical boundaries but either semantic or logical ones. They have semantic boundaries if a part of the SSN uses ontologies and grammars another part does not know. They have logical boundaries if access is restricted by security and encryption.
Semantic social networks might very well be Tim Berners-Lee's vision of a truly semantic web, enabled by universal data, graph languages and protocol-free communication. First generation SSNs can be seen as a kind of semantic web with a focus on information exchange, communication and functionality, without all the flashy visual clutter of today's World Wide Web. They will be a reduction to pure information and functionality. In the long run, SSNs have the potential to change the way how people, communities and companies organize themselves, how they communicate amongst each other and how they collaborate with each other.
This post is part of a comprehensive introduction into SRDM, graph languages and Havel.
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