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This paper introduces a unified representation for collaborative development of complex services in public safety to explain the infusion of digital technologies into the design of the community resilience processes with respect to the potential hazardous events. It aims at helping to understand how ICT-based knowledge may help stakeholders situated in various positions inside society to participate collaboratively to service development actions. It presents a roadmap to conceive, design, and operationalize the creation of digital artefacts to compound its supporting systems, including the digital one. This representation includes a way of describing the domain of interest to conceive complex services employing human-oriented development, a way of reasoning on the resilience processes complexity, using semantic reasoning along with the time series quality assurance (TSQA) solution ontology, and a way of developing data processing components as internal (technical) services in enterprise information systems to support the design of novel environmental monitoring digital services. A unified semantic reasoning-based approach to evaluate data quality in cyber-physical systems is described to exemplify the creation of a complex public service ecosystem that promotes collaborative knowledge sharing to formalize the domain expertise through the information intensive services. The TSQA ontology integrates knowledge from other domain-specific ontologies to define and share concepts designating observations acquired from sensors, quality issues, methods for detecting quality issues and correcting data, and tags applied to data objects to assure the data traceability. A semantic component that manages the TSQA ontology and the SWRL-encoded rules are introduced in the data acquisition module of a cyber-physical system application for environmental monitoring to solve a specific problem of data cleaning associated with the water resources management. This method is applicable to any time series of measured data.

The development of mobile computing systems is an inherently collaborative activity, and the nature of the collaboration likely affects systems success. Collaboration can lead to faster development of systems and increased creativity, but it may also adversely affect the quality of systems. As one of the most popular and active Web services for developing open source software, Github has been a place of origin of many novel mobile computing systems with the Internet of Things, such as OpenEdge and CloudSim. Meanwhile, Github provides a place for people to collaborate with each other on developing novel mobile service computing systems. In this paper, we explore the effects of collaboration in developing systems hosted by Github and use a model of collaboration to detect bugs of systems aiming to enhance their quality. We conduct an at-scale study of more than five million projects on GitHub to reveal collaboration's effects on the popularity of software systems and speed of development. We find that having more collaborators results in higher popularity but slower development. Projects that use Objective-C are at an even more significant risk for lower development speeds than other projects. We define collaboration networks and co-commit networks, which capture the projects' collaboration patterns and use structural features of these networks to identify files within commits with bugs. By examining 18 large popular projects, we find that involving these features statistically significantly improves bug detection by 6.7% on average.