MEDES 2009 on Collective Information and Knowledge Management

In the long standing tradition of Computer Science and Artificial Intelligence, information processing and management as well as knowledge engineering principles and techniques have been envisioned and practiced claiming some kind of intelligence in organization, processing and behavior. Effective memory models and organization have always attracted research and development efforts in an attempt to address the challenges of intelligent behavior in humans and machines. Among the oldest examples are nature inspired models such as cellular automaton conceived by Ulam and von Neumann in the 1940s, which has been investigated as a framework for the understanding of the behavior of complex systems. In spite of the controversial opinions about the degrees of success for understanding and applying intelligence, today's computer impacted culture is characterized by the production and consumption of knowledge and information in an assembly of smaller universes of entities, i.e., people, machines, software, data, computational models rather than truly intelligent systems. In order to adhere to the evolutionary and cultural impact of computer science in society and organizations, we need to re-visit memory and organizational models within a universe of discourse where entity participation and connectionism are of paramount importance. Data, information and knowledge management principles and techniques need to be conceived as contributing to the creation of a huge associative memory, which could enable a collectively, eventually truly, intelligent society and organization. Within such a Collective Intelligence (CI) Universe of Discourse, coping with and harnessing complexity and diversity remains a key challenge, which can be met by conceiving data and knowledge engineering and management as an ecosystem underlying synergy and natural selection processes. In this special issue, we solicited five visionary as well as theoretical and application papers among the best papers submitted and presented to the international conference on Emergent Digital Ecosystems 2009 (MEDES'09). All five papers have been extended of 30% of additional materials and rigorously reviewed by a dedicated peer review. The solicited papers address data and knowledge engineering principles and techniques in a CI Universe of