VOLUNTEERED GEOGRAPHIC SERVICES: DEVELOPING A LINKED DATA DRIVEN LOCATION-BASED SERVICE Alexander Savelyev 1, Krzysztof Janowicz 2, Jim Thatcher 3, Sen.

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VOLUNTEERED GEOGRAPHIC SERVICES: DEVELOPING A LINKED DATA DRIVEN LOCATION-BASED SERVICE Alexander Savelyev 1, Krzysztof Janowicz 2, Jim Thatcher 3, Sen Xu 4, Christoph Mulligann 5, Wei Luo 6 1, 4, 6 The Pennsylvania State University, 2 UC Santa Barbara, 3 Clark University, 5 University of Munster

VGS at Work

Related Work Crowdsourcing in the wild Everyday applications (Airbnb, Avego, Yelp) Emergency management (CrisisCommons, Ushahidi) Volunteered Geographic Information One of the many applications of crowdsourcing Focus on collaborative data creation and management Shift towards analysis of social interaction Volunteer effort in Haiti Role in the events of Arab Spring

Motivation for VGS Focus on collaboration instead of data collection In traditional VGI, volunteers collect and share data, whereas only sanctioned, authoritative parties formulate and address specific tasks. Linked Data adopted as the main paradigm Flexibility is the recipe for success. Generic request-offer messaging bus aims to address diverse user communities. Explicit support for mobile applications The Mobile Semantic Web is in its early stage of development. Established APIs, ontologies, and best practice guidelines for mobile applications are lacking.

Prototype Implementation A prototype VGS system implemented in four steps: 1. Design of a Linked Data model Generic model for handling of the key VGS concepts. 2. Implementation of a VGS Service Bus Server-side mechanisms for storage and query of data. 3. Implementation of Triploid API Client-side application for transparent processing of RDF statements. 4. Implementation of a VGS Client Android-based VGS application.

Linked Data Model RequestOffer Request – Need help! – Me too! – Need help! – Will do. Offer – Can help. – Please do! – Can help. – Me too.

Implementation: Service Bus Service Bus* goals: 1. Collect, store, and organize Actions. 2. Support spatial, temporal and thematic queries. 3. Provide auxiliary services. * service as in helpful act

Implementation: Client

Limitations and Future Work Technical problems to be solved: 1. Support for ontologies on the go is still in the works 2. GeoSPARQL standard is yet to be released Research problems to be investigated: 1. Vulnerability to spam and fraud 2. Location-aware trust and reputation model Code is available at: