This paper introduces a conceptual framework aiming to broaden the discussion on resilience for the design of public services. From a theoretical point of view, the paper explores service design with a Systems Thinking lens. A multi-contextual perspective aiming to analyze, decompose, and design smart cities services where resilience is an input at the service design level is described and the four diamonds-of-context model for service design (4DocMod) is introduced. This service model accommodates various actors’ contexts in public service design and consists of four design artefacts, the diamonds (See, Recognize, Organize, Do). From a practical point of view, guidelines for the application of the 4DocMod service model extension for resilience are described along with two case studies addressing the recent COVID-19 pandemic that illustrates a clear situation of resilience with insights in multiple contexts. According to the findings of this paper, it is obvious that resilience is not "just" a request. Instead, it plays a higher role within the service system. It is not "just" another Context, either. Instead, it goes through many contexts with different circumstances. In this manner, it is possible to address the qualities through which actors can become resilient, at the service design stage, to ensure continuity of the public services in times of emergency. As our approach using the 4DocMod is proposing, resilience may be is achieved when specific properties are provisioned at information service design level.

Purpose: The COVID-19 pandemic started a new era in understanding the topic of resilience and adaptability. The human society has not faced such a widespread global challenge until now. This paper aims to address a context change influenced by the COVID-19 pandemic, using a case study in high education. While the character of the issues emerging is the same as in any other domain, in high education, the principles and consequences can be more directly studied and analyzed. Design/methodology/approach: This paper describes a framework to evaluate how the context of the tertiary education service has been disrupted and the influence on the adherence of the students to the educational process, via primary quantitative data collection. This paper tackles the problem of distinguishing the change in context and context change and the possibility of system reconfiguration. Findings: To properly face the evolving conditions induced by the pandemic, the education service system must be aligned to the imposed emergency situations, trying to “find” where the changes have emerged, i.e. what kind of reconfiguration is, whether it appears in the goals or in the service system itself. Furthermore, this study discusses how the findings can be valuable and applied to situations beyond the pandemic, in other cases of context disruption to highlight how general the service activities are within our reconfiguration approach. Originality/value: From a theoretical point of view, this work is in line with main assumptions of system thinking, by confirming several insights of service systems’ behavior, even in a logic of B2B interactions (from the offer side); first in terms of openness and adaptation, in addition to readiness to change and – when and how – this change can occur. From a practical point of view, this paper’s contribution is directed toward achieving the more successful change management process, as reached together by motivated partners working hard for a common final goal. Realizing that the pandemic has brought a completely new context of education, managers should focus now on monitoring all aspects of the education business, not only directly affected projects and processes.

This paper presents a digital system that aims to analyze real-time data obtained from sensors installed in a city's water distribution infrastructure. The system’s primary objective is to monitor water quality and generate alerts when necessary. The following water quality metrics are used: Flow, pH, Turbidity, Free Chlorine, Nitrate, and Fluoride. The data gathered from sensors is initially processed by a distributed system, which generates multiple visualizations that synthesize large amounts of information. These visualizations facilitate real-time monitoring of the sensor's status. Additionally, citizens can receive updates on any possible issues in the water distribution network through WhatsApp messages. By addressing the limitations of traditional water quality monitoring methods, this system contributes to a noteworthy enhancement in public water supply services. Consequently, it improves the overall quality of life for the citizens.

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 potential hazardous events. It aims 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 domain expertise through 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 data traceability. A semantic component that manages the TSQA ontology and the SWRL-encoded rules is introduced in the data acquisition module of a Cyber Physical System application for environmental monitoring, to solve a specific problem of data cleaning associated to water resources management. The method is applicable to any time series of measured data.