Chris Colin Baillie

Linking Open Data and the Crowd for Real-Time Passenger Information

The availability of real-time passenger information (RTPI) is a key factor in making public transport both accessible and attractive to users. Unfortunately, rural areas often lack the infrastructure necessary to provide such information, and the cost of deploying and maintaining the required technologies outside of urban areas is seen as prohibitive. In this paper we present the GetThere system developed to overcome such issues and to provide public transport users in rural areas with RTPI. An ontological framework for representing mobility information is described, along with the Linked Data approach used to integrate heterogeneous data from multiple sources including government, transport operators, and the public. To mitigate possible issues with the veracity of this data, a quality assessment framework was developed that utilises data provenance. We also discuss our experiences working with Semantic Web technologies in this domain, and present results from both a user trial and a performance evaluation of the system.

Quality reasoning in the semantic web

Assessing the quality of data published on the Web has been identified as an essential step in selecting reliable information for use in tasks such as decision making. This paper discusses a quality assessment framework based on semantic web technologies and outlines a role for provenance in supporting and documenting such assessments.

QUAL: A Provenance-Aware Quality Model

In this article, we present a model for quality assessment over linked data. This model has been designed to align with emerging standards for provenance on the Web to enable agents to reason about data provenance when performing quality assessment. The model also enables quality assessment provenance to be represented, thus allowing agents to make decisions about reuse of existing assessments. We also discuss the development of an OWL ontology as part of a software framework to support reasoning about data quality and assessment reuse. Finally, we evaluate this framework using two real-world case studies derived from transport and invasive-species monitoring applications.

Quality assessment, provenance, and the web of linked sensor data

This paper presents a quality assessment framework for linked sensor data and discusses a role for provenance in quality assessment.