The effective acquisition of (semantic) metadata is crucial for many present day applications. Games with a purpose address this issue by transforming computational problems into computer games. The authors present a novel approach to metadata acquisition via Little Search Game (LSG) – a competitive web search game, whose purpose is the creation of a term relationship network. From a player perspective, the goal is to reduce the number of search results returned for a given search term by adding negative search terms to a query. The authors describe specific aspects of the game’s design, including player motivation and anti-cheating issues. The authors have performed a series of experiments with Little Search Game, acquired real-world player input, gathered qualitative feedback from the players, constructed and evaluated term relationship network from the game logs and examined the types of created relationships.

Effective access to and navigation in information stored in deep Web ontological repositories or relational databases has yet to be realized due to issues with usability of user interfaces and the overall scope and complexity of information as well as the nature of exploratory user tasks. We propose the integration and adaptation of novel navigation and visualization approaches to faceted browsing such as visual depiction of facets and restrictions, visual navigation in (clusters of) search results and graph like exploration of individual search results' properties.

Open information spaces have several unique characteristics such as their changeability, large size, complexity and diverse user base. These result in novel challenges during user navigation, information retrieval and data visualization in open information spaces.We propose a method of navigation in open information spaces based on an enhanced faceted browser with support for dynamic facet generation and adaptation based on user characteristics.