Learning a musical instrument requires regular exercise. However, students are often on their own during their practice sessions due to the limited time with their teachers, which increases the likelihood of mislearning playing techniques. To address this issue, we present Let’s Frets - a modular guitar learning system that provides visual indicators and capturing of finger positions on a 3D-printed capacitive guitar fretboard. We based the design of Let’s Frets on requirements collected through in-depth interviews with professional guitarists and teachers. In a user study (N=24), we evaluated the feedback modules of Let’s Frets against fretboard charts. Our results show that visual indicators require the least time to realize new finger positions while a combination of visual indicators and position capturing yielded the highest playing accuracy. We conclude how Let’s Frets enables independent practice sessions that can be translated to other musical instruments.

Scientists are increasingly using the workflow technology as a means for modeling and execution of scientific experiments. Despite being a very powerful paradigm workflows still lack support for trial-and-error modeling, as well as flexibility mechanisms that enable the ad hoc repetition of experiment logic to enable, for example, the convergence of results or to handle errors. In this respect, in our work on enabling multi-scale/field (multi-*) experiments using choreographies of scientific workflows, we contribute a method comprising all necessary steps to conduct the repetition of choreography logic across all workflow instances participating in a multi-* experiment. To realize the method, we contribute i) a formal model representing choreography models and instances, including the re-execute and iterate operations for choreographies, and based on it ii) algorithms for determining the rewinding points, i.e., the activity instances where the rewinding has to stop and iii) enable the actual rewinding to a previous execution state and repetition of the choreography. We present the implementation of our approach in a message-based, service-oriented system that allows scientists to model, control, and execute scientific choreographies as well as perform the rewinding and repeating of choreography logic. We also provide an evaluation of the performance of our approach.

Reuse of service orchestrations or service compositions is extensively studied in the literature of process modeling. Sub-processes, process templates, process variants, and process reference models are employed as reusable elements for these purposes. The concept of process fragments has been previously introduced in order to capture parts of a process model and store them for later reuse. However, similar efforts on facilitating the reuse of processes that cross the boundaries of organizations expressed as service choreographies are not available yet. In this paper, we introduce the concept of choreography fragments as reusable elements for service choreography modeling. Choreography fragments can be extracted from choreography models, adapted, stored, and later inserted into new models. Based on a formal model for choreography fragments, we define methods and algorithms for the extraction and insertion of fragments from and into service choreographies. We then discuss an experimental and proof-of-concept evaluation of our proposal.

Service orientation has significantly facilitated the development of complex distributed systems spanning multiple organizations.However, different application areas approach such systems in domain-specific ways, focusing only on particular aspects relevant for their application types.As a result, we observe a very fragmented landscape of service-oriented systems, which does not enable collaboration across organizations.To address this concern, in this work we introduce the notion of Collaborative, Dynamic and Complex (CDC) systems and position them with respect to existing technologies.In addition, we present how CDC systems are modeled and the steps to provision and execute them.Furthermore, we contribute an architecture and prototypical implementation, which we evaluate by means of a case study in a Cloud-enabled context-aware pervasive application.

Current systems for enacting scientific experiments, and in particular simulation workflows, do not support multi-scale and multi-field problems if they are not coupled on the level of the mathematical model. We present a life cycle that utilizes the notion of choreographies to enable the trial-and-error modeling and execution of multi-scale and/or multi-field simulations. The life cycle exhibits two views reflecting the characteristics of modeling and execution in a top-down and bottom-up manner. It defines techniques for composing data-intensive, scientific workflows in more complex simulations in a generic, domain-independent way, and thus provides scientists with means for collaborative and integrated data management based on the workflow paradigm.