The Semantic Web is slowly evolving towards its original vision of a Linked Web of Data, in which the machines are able to interpret and exchange knowledge, acting as proxy agents on behalf of human. Even so, the Linked Data Web maintains a large human-driven side, characterized by intensive collaboration, cooperation and knowledge processing activities, that lead to emerging complex social and economical networks. Various knowledge processing techniques are being used to address data portability and Web information discovery problems. Collective intelligence is a key issue to collaboratively share and generate knowledge. Many Web 2.0 (or 3.0) platforms (e.g., blogs and wikis) have been developed to exchange meaningful information and support user-centered tasks on a variety of domains (e.g., e-learning, e-commerce, and e-government). Local knowledge is annotated into a large repositories of content including not only simple documents but also multimedia data. As an example, collaborative tagging (e.g., del.icio.us) still plays an important role in knowledge (or information) sharing between people on social networks. Modeling the dynamics and evolution of such complex networked systems, involving knowledge processing with intelligent information agents acting on behalf of thousands of users, is a promising research area with many practical applications.

The aim of this workshop is to bring together researchers and practitioners in areas of knowledge and intelligence, semantics, agents and grid computing to share their visions, research achievements and solutions as well as to establish worldwide cooperative research and development. At the same time, we want to provide a platform for discussing research topics underlying the concepts of Social Semantics for the Linked Web of Data by inviting members of different communities that share this common interest of social semantic collaborative intelligence on the web:

• Semantic Web researchers developing and using social semantic techniques for modeling collaboration and intelligence on the Web,
• Complex Social Network researchers building static, dynamic and prediction models of complex networks and developing new nature-inspired network analysis methods,
• Linked Data researchers providing means for publishing and using Linked Open Data on the Web, and
• The Intelligent Agents community that develop agents and algorithms for collaboration and intelligence on the Web.

This will give an opportunity to push further the discussion upon the potential of social semantic collaborative intelligence across these communities.