The Origin/Synthesis of Life VRE (Virtual Research Environment)
is under construction. The site will serve two complementary functions:
Users click back and forth between passive and active modes using the Vase (archives) / Faces (collaborative construction) toggle button. The passive mode comprises a knowledge management framework to navigate information resources and archives. The active mode offers process support for invention and collaborative problem-solving.
Passive — Active Coupling. The passive/ active modes are tightly coupled, since each user’s path through the knowledge archives (passive) leaves a “pheromone trail” that feeds into the design of the recommender system for future users of the site.
Navigational Mapping. Site design automated updating reflects preferences of its users.
Knowledge Clusters. Navigational mapping of user paths (passive) and contributions to the site (active) evolves into knowledge clusters that enable site users interested in the creative process of the collective community of origin/ synthesis of life theorists to observe how knowledge clusters form, link to other clusters, or dissipate.
Evolutionary Emergence. The site as a whole is not only intended as a knowledge resource for origin/ synthesis of life researchers, but also as a meta-experiment in evolutionary emergence — bottom up structuring as in evolution, rather than traditional top-down hierarchical control. Research will focus on
This VRE prototype will study
- how people cooperate to build hypotheses in the origin/ synthesis of life domain;
- how new ideas and concepts arise in this domain;
- how to build a system that supports that creative, collaborative process;
- how such a system can adapt and evolve to perform with increasing efficiency;
- how this case study can test the usefulness of such a system and develop a prototype to serve other application domains.
Future research will explore how web mining can harvest patterns in navigational, user-focused, content-structured data. Tools are currently under development for data and knowledge modeling, integration and management for personalization, e.g. personalized taxonomies/ ontologies for particular individuals and user communities; semantic web-mining using the syntactic layer (XML), the vocabulary layer (RDF-Schema) or the logic layer (Description Logics/ OIL). Challenges in developing architectures include the need for semantically-enhanced collaborative filtering techniques, adaptive systems, and hybrid recommender systems.
- knowledge growth and self-organization across projects, disciplines, and through time;
- how process data can be gathered, archived and retrieved by humans and/or intelligent agents;
- how to support cross-disciplinary innovation, collaborative scenario-building, and
- rapid response where collective action by diverse human/ agent teams is needed to address complex problems.