INSEMTIVES · Incentives for Semantics

Creating a critical mass of semantic content is a fundamental challenge that has received considerable attention in the past decade. The result is a maturing inventory of techniques and tools which primarily aim at the automation of the semantic content creation task as a means to lower costs and improve productivity. Whilst the quality of such automated approaches has consistently improved, it is still far from outweighing the required invested manual effort. This holds in particular for the creation of multimedia annotations, or the development of shared ontologies, tasks which are human-driven through their very nature. The aim of INSEMTIVES is to bridge the gap between human and computational intelligence in the current semantic content authoring R&D landscape. We will develop methodologies for the creation of semantic metadata for different types of Web resources, jointly exploiting human intelligence, community effects and machine processing. We will investigate applicable social and economic incentives, notably in the areas of ontology engineering, and the semantic annotation of media and Web services, to motivate user participation in these inherently human-driven tasks. A generic open source platform, including models for representing user-generated semantic content, and methods for supporting their lifecycles, as well as incentive-driven end-user tools, will resultantly bring semantic content to a level where it can be meaningfully used in various application scenarios. Three case studies will apply the developed technology in the sectors of telecommunications, online marketplaces, and virtual worlds. INSEMTIVES will impact the semantic technologies community by demonstrating how user participation can solve the main bottleneck in the uptake of the Semantic Web: i.e., the lack of a critical mass of semantic content required for applications to provide an immediate added value to end-users and businesses to encourage them to adopt semantic technologies.