<back to Home>       


Scientific Collaboration

Knowledge Visualization

Algorithm Visualization

Intelligence Visualization


¡@

Visualization Tool for Group Knowledge Formation

        Design of the next-generation Internet-based services has been an active research topic, which is aimed to actuate a social activity that generates and distributes Web contents itself. Development of a knowledge portal is an implementation towards this perspective for scientific collaboration. In comparison with conventional websites, knowledge portals have three features: (1) The contents are contributed by all the portal members, not just by the web design community. Accordingly, the contents of a knowledge portal can be regarded as group knowledge, which aggregates all the intelligent assets from the userbase; (2) Except an axiom ontology given by the portal designer, no detailed sitemaps or blueprints are prepared to outline the contents in advance, i.e., the contents of the website grow in an unplanned and unpredictable manner; (3) The developed knowledge objects are associated with conceptual elements defined within the ontology of the knowledge portal. This fact implies that we can construct the sitemap of the portal site by adopting the notion of a concept map.

      In consideration of the above three aspects, we developed a visualization tool in our previous work for constructing a Site-And-Concept (SAC) map to improve the quality of a knowledge portal. This map allows the members to examine the current status of group knowledge structure by visualization. Figure 1 shows that the SAC map generator supports both the learner- and expert-modes to allow them to interact with the knowledge portal efficiently. Users not only can learn from but also can contribute to the group knowledge through the SAC map.

Fig. 1. Showcases of the SAC map: (a) Right-click k-NN function, (b) the learner-mode extending the map by adding k nearest neighbors, and (c) the expert-mode increasing new knowledge objects and relations

        In our practice platform, the OpenCPS portal members have contributed more than 200 problem objects to the website for the present. Figure 2 is the complete map of these knowledge concepts, where we do not apply any filtering or layout processes. This picture simulates the image of human cognition without concept map supports. This shows a rather messy situation. We can hardly make out any of the concept relations, much less to examine or learn from this knowledge portal. In comparison with the situation shown in Fig. 1, the SAC map generator appears to properly enhance the performance of a knowledge portal.

 Fig. 2. Complete map of current problem objects. We do not apply any filtering and layout process so that this picture may simulate the image of human cognition without concept map supports.

        The SAC map generator can display the sitemap of the OpenCPS portal and observe the concept map of group knowledge. Meanwhile, the knowledge relations inside the OpenCPS are recorded by other hard-coded objects according to rigorous mathematical proofs. Development of the SAC map generator is thus comparatively easy and may limit the practice value in general. Our current research upgrading the map generator plans to construct the knowledge relation map automatically on basis of common references. Accordingly, the generated map is renamed as the ¡§Reference-based Knowledge Relation (RKR)¡¨ map. Figure 3 depicts four design issues of this map generator, i.e., (1) how to assign main references to a particular knowledge object; (2) how to extend the reference list according to the assigned main references; (3) how to assess knowledge relations and display the links; and (4) how to extend the knowledge relation map based on the currently discovered part.

Fig. 3. Design Issues of the RKR map generator -- A hierarchy structure of a citation network and Four design issues of the RKR map.

        We still use the OpenCPS as the platform for current experiments; however, the RKR map generator is potentially useful in other research scopes because getting rid of hard-coded relation objects. We can simply adjust its reference assignment mechanism to cohere to the knowledge objects in any particular environments. In the near future, we will make out a configurable product for other portal to embed the RKR map generator for constructing the concept map that reflects the formation of the group knowledge. The future work also includes the incorporation with data mining techniques. We consider developing a recommender system that calculates the confidence of ¡§association relationship¡¨ from a knowledge mining viewpoint. Additionally, to cluster knowledge objects on the map is also an attractive research direction.

¡@

¡@

¡@

¡@

¡@

¡@