An Approach to Enable Collective Intelligence in Digital Repositories
A significant amount of digital resources used to support workers and learners in their daily tasks is stored in digital repositories. Metadata about these resources is usually automatically generated or defined by experts or selected users in a centralized, top-down approach according to certain standards and conventions. Enriching the description of these resources with information such as tags, ratings and annotations generated by common users in a social media environment allows the harvesting of collective intelligence and the provision of new services based on these enriched metadata. In this paper, we introduce an infrastructure to plug in social media functionalities in existing repositories, and we provide a case study showing a sample realization by applying the ALOE system in two Learning Resource Repositories: The Ariadne Knowledge Pool and public FM replays.