Disruptive Events (DE), such as disasters, virus outbreaks, and military conflicts, are often hugely affecting human life, and works featuring resilience against DE are receiving much attention. A key priority in this regard is the effective monitoring of the affected systems' state after a DE has occurred. Earlier work shows relevant strengths of drone technology for that purpose. In this paper, we take a functional perspective of this technology, for the sake of considering monitoring services and addressing DE. We conceptualize those services and provide explicit insight as it concerns the alignment between user needs and technological (drone-specific) solutions. Further, we zoom in, considering adaptation features, sensing features, and data analytics features accordingly. Finally, we present our general implementation vision that puts drones in a system-of-systems perspective. Since this is work-in-progress, validation is left for future research. @en

Enterprise Information Systems (EIS) are designed to deal with normal variability in their inputs and data. Empowered by CONTEXT-AWARENESS, some EIS even count on sensors and/or data analytics for capturing changes outside of the system. Nevertheless, context-awareness would often fail when EIS are affected by (large-scale) disruptive events, such as disasters, virus outbreaks, or military conflicts. Hence, in the current paper, we take a step forward, by considering context-awareness for disruptive events. We combine context-awareness with risk management techniques, such as FMECA and FTA, that are useful for defining and mitigating risk events. To avoid having to define the likelihood for such very-low-probability disruptive risks, we use CONSEQUENCE-BASED RISK MANAGEMENT rather than traditional risk management. We augment this approach with the context-awareness paradigm, delivering a contribution that is two-fold: (i) We propose context-awareness-related measures and consequence-based-risk-management-related measures, to address disruptive events; (ii) We reflect this in a method featuring the application of context-awareness and risk management for designing robust and resilient EIS.@en

We observe a world of increasing anxiety due to natural and man-made disasters, pandemics, andmilitary conflicts. Such disruptive events lead to decreased infrastructure and personnel availability; still, infrastructure and personnel are essential for keeping society running, and for addressing the effects of disruptions. We argue that drone technology could provide monitoring/logistics services that can help in addressing such needs. This paper focuses on the monitoring function whichcan provide situational awareness to decision makers after such a crisis. Drones are less dependenton nearby area infrastructure and can observe affected regions from above. Those are key advantagescompared to other solutions. Still, drones are dependent on communication services and ground operators. Therefore, we need drone solutions that are less dependent on the availability of local infrastructure and people. Several conceptual solutions to reach this independence, based on recent developments in drone technology, are explicitly discussed in the current paper and confronted with therequirements and boundary conditions posed by disruptive events. Validating such solutions in real emergency situations is left for future work. @en

With regard to context-aware systems: some optimize system-internal processes, based on the context state at hand; others maximize the user-perceived effectiveness of delivered services, by providing different service variants depending on the situation of the user; still others are about offering value-sensitivity when the society demands so. Even though those three perspectives cover a broad range of currently relevant applications there are no widely accepted and commonly used corresponding concepts and terms. This is an obstacle to broadly understand, effectively integrate, and adequately assess such systems. We address this problem, by considering a (component-based) methodological derivation of technical (software) specifications based on underlying enterprise models. That is because context states are about the enterprise environment of a (software) system while the delivery of context-aware services is about technical (software) functionalities; hence, we need a perspective on both. We consider the SDBC (Software Derived from Business Components) approach that brings together enterprise modeling and software specification. On that basis: (a) We deliver a base context-awareness conceptualization; (b) We partially align it to agent technology because adapting behaviors to environments assumes some kind of pro-activity that is only fully covered by agent systems, in our view. We partially illustrate our proposed conceptualization and particularly - the agent technology implications, by means of a case example featuring land border security.

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Networked physical devices, vehicles, home appliances, and other items embedded with electronics, software, sensors, actuators, and connectivity, allow for run-time acquisition of user data. This in turn can enable information systems which capture the “current” user state and act accordingly. The use of this data would result in context-aware applications that get fueled by user data (and environmental data) to adapt their behavior. Yet the use of data is often restricted by privacy regulations and norms; for example, the location of a person cannot be shared without given consent. In this paper we propose a design approach that allows for weaving context-awareness and privacy-by-design into the specification of information systems. This is to be done since the very early stages of the software development, while the enterprise needs are captured (and understood) and the software features are specified on that basis. In addition to taking into account context-awareness and privacy-sensitivity these two aspects will be balanced, especially if they are conflicting. The presented approach extends the “Software Derived from Business Components” (SDBC) approach. We partially demonstrate our proposed way of modeling, by means of a case example featuring land border security. Our proposed way of modeling would allow developers to smoothly reflect context and privacy features in the application design, supported by methodological guidelines that span over the enterprise modeling and software specification. Those features are captured as technology-independent societal demands and are in the end reflected in technology-specific (software) solutions. Traceability between the two is possible as well as re-use of modeling constructs.

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Public values are desires of the general public, that are about properties considered societally valuable, such as respecting the privacy of citizens or prohibiting polluting activities. “Translating” public values into functional solutions is thus an actual challenge. Even though Value-Sensitive Design (VSD) is about weaving public values in the design of (technical) systems, it stays insufficiently concrete as it concerns the alignment between abstract public values and technical (software) solutions. Still, VSD indirectly inspires ideas in that direction as for example the idea to consider business process variants for achieving such an alignment. Nevertheless, this is all about “atomic” public values (encapsulating only one particular behavioral goal) while one would often face public values that are “composite” in the sense that they reflect a particular human attitude rather than just a desired behavioral goal. In the current paper, we propose a value decomposition approach that allows for operationalizing composite public values. We also present experimental results featuring data analytics using self-administrated surveys.

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Current global trends push enterprises to be increasingly efficient and flexible, and at the same time compliant with legislation regarding privacy, security, and transparency. The latest IoT (Internet-of-Things) developments offer opportunities for enterprises but at the same time those developments lead to an increased complexity with regard to the underlying software, this in turn leading to new risks. Hence, more advanced modeling methods and techniques may be necessary, especially in the area of enterprise information systems (often featured currently by enterprise-aligned IoT-enabled software systems), such that both the enterprise needs are captured (and understood) and software features are specified accordingly. We need a common modeling ground for this, allowing us to properly align enterprise modeling and software specification. Such a common ground can be co-created by enterprise engineers and software engineers, featuring: (a) technologyindependent enterprise models rooted in social theories; (b) technology-specific software models rooted in computing paradigms. An approach is needed on top of that because such an integrated enterprise-software modeling requires to be greased by modeling guidelines and notations, such that adequate modeling generations and transformations are possible. This means that taking as input unstructured business information, we should be able to usefully apply a modeling and design process, such that we come through enterprise models and reach as far as the specification and implementation of software. We argue that an existing approach has those capabilities, namely the approach SDBC (Software Derived from Business Components). Hence, we adopt SDBC in the current research. Further, we have opted for an explicit consideration of context-awareness and privacy, claiming their relevance with regard to some current IoT-related demands (mentioned above). Nevertheless, it has not yet been extensively studied how SDBC can be used for modeling software systems with requirements on those properties. For this reason, we aim at enriching the SDBC-rooted enterprise-modeling-driven software specification, by weaving in contextawareness and privacy enforcement. We partially demonstrate our proposed way of modeling, by means of a case example featuring land border security.

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