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The aim of the EU FP 7 Large-Scale Integrating Project LarKC is to develop the Large Knowledge Collider (LarKC, for short, pronounced "lark"), a platform for massive distributed incomplete reasoning that will remove the scalability barriers of currently existing reasoning systems for the Semantic Web.

We view Digital Ecosystems to be the digital counterparts of biological ecosystems, exploiting the self-organising properties of biological ecosystems, which are considered to be robust, self-organising and scalable architectures that can automatically solve complex, dynamic problems.

Built on top of Calais and scalably hosted on Amazon's EC2 service, the new site at SemanticProxy.com enters public beta today, and enables anyone to easily generate rich semantic metadata for pages on the open web, simply by passing the URL to SemanticProxy.

Mahout's goal is to build scalable, Apache licensed machine learning libraries. Initially, we are interested in building out the ten machine learning libraries detailed in http://www.cs.stanford.edu/people/ang//papers/nips06-mapreducemulticore.pdf using Hadoop. While these algorithms are our initial focus, we welcome contributions of other machine learning approaches.

CAIDA, the Cooperative Association for Internet Data Analysis, provides tools and analyses promoting the engineering and maintenance of a robust, scalable global Internet infrastructure.

Sensing importance across a sea of dynamic systems with constantly changing data requires the accumulation and persistence of context. (I am using the term persistence here to mean storing/saving what one has observed and learned - in a database for example.)

The Drizzle project is building a database optimized for Cloud and Net applications. It is being designed for massive concurrency on modern multi-cpu/core architecture. The code is originally derived from MySQL.