Biblio

In a socio-technically connected environment, self-adaptive systems need to cooperate with others to collect information to provide context-dependent functionalities to users. A key component of ensuring safe and secure cooperation is finding trustworthy information and its providers. Trust is an emerging quality attribute that represents the level of belief in the cooperative environments and serves as a promising solution in this regard. In this research, we will focus on analyzing trust characteristics and defining trust-aware models through the trust-aware goal model and the provenance model. The trust-aware goal model is designed to represent the trust-related requirements and their relationships. The provenance model is analyzed as trust evidence to be used for the trust evaluation. The proposed approach contributes to build a comprehensive understanding of trust and design a trust-aware self-adaptive system. In order to show the feasibility of the proposed approach, we will conduct a case study with the crowd navigation system for an unmanned vehicle system.

The Sensor Web is evolving into a complex information space, where large volumes of sensor observation data are often consumed by complex applications. Provenance has become an important issue in the Sensor Web, since it allows applications to answer “what”, “when”, “where”, “who”, “why”, and “how” queries related to observations and consumption processes, which helps determine the usability and reliability of data products. This paper investigates characteristics and requirements of provenance in the Sensor Web and proposes an interoperable approach to building a provenance model for the Sensor Web. Our provenance model extends the W3C PROV Data Model with Sensor Web domain vocabularies. It is developed using Semantic Web technologies and thus allows provenance information of sensor observations to be exposed in the Web of Data using the Linked Data approach. A use case illustrates the applicability of the approach.