This 2010 article focuses on crowd-sourced information and particularly the utility of artificial intelligence (AI) in crowdsourcing workflows.
This 2012 article focuses on crowd-sourced information and particularly the use of crowdsourcing services with geo-spatial and geo-temporal data. The article explores how to improve on the interoperability of Web 2.0 services by providing a single service as a unique entry for searches over several service clients in a single step. The paper demonstrates the usefulness of the Open Geospatial Consortium’s OpenSearch Geospatial and Time specification as an interface for a service that searches and retrieves information available in crowdsourcing services. Citizens are increasing willing to share information, using tools provided by crowdsourcing platforms to describe events that may have a social impact. The potential of crowdsourcing information is increasingly fuelled by location-aware smartphones and tablets, with location-enabled data, allowing users to contribute to crowdsourcing platforms from the field “in real-time” and augmenting their information with geo-location.
This article will be of use to PVE researchers and practitioners interested in crowd sourced information platforms and particularly those that make use of geo-location and geo-spatial/temporal contexts. The authors demonstrate the value and merits of this type of crowd sourced information in complementing other authoritative information, by providing alternative contemporary sources. They demonstrate the interoperability of the system showing the integration of crowd-sourced data in various scenarios.