Collaborative Semantic Tables

Abstract. The scenario defined by current Web architectures and paradigms (such as Cloud Computing), poses challenges and opportunities to users. On the one hand, they have to manage huge amounts of digital resources handled by different applications in spite of their possibly related content; on the other hand, they are enabled to share knowledge and participate to content creation. The interaction of these two aspects provided a great impulse to collaborative resource management: in this paper we present T++, an environment that ex-ploits semantic knowledge about digital resources in order to face these chal-lenges, by providing an integrated and smart management of heterogeneous in-formation objects

I learn. You learn. We learn? An experiment in collaborative concept mapping.

International audienc

An Integrated Support to Collaborative Semantic Annotation

Everybody experiences every day the need to manage a huge amount of heterogeneous shared resources, causing information overload and fragmentation problems. Collaborative annotation tools are the most common way to address these issues, but collaboratively tagging resources is usually perceived as a boring and time consuming activity and a possible source of conflicts. To face this challenge, collaborative systems should effectively support users in the resource annotation activity and in the definition of a shared view. The main contribution of this paper is the presentation and the evaluation of a set of mechanisms (personal annotations over shared resources and tag suggestions) that provide users with the mentioned support. The goal of the evaluation was to (1) assess the improvement with respect to the situation without support; (2) evaluate the satisfaction of the users, with respect to both the final choice of annotations and possible conflicts; (3) evaluate the usefulness of the support mechanisms in terms of actual usage and user perception. The experiment consisted in a simulated collaborative work scenario, where small groups of users annotated a few resources and then answered a questionnaire. The evaluation results demonstrate that the proposed support mechanisms can reduce both overload and possible disagreement