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Context: Organizations are increasingly challenged by dynamic and technical market environments. Traditional product roadmapping practices such as detailed and fixed long-term planning typically fail in such environments. Therefore, companies are actively seeking ways to improve their product roadmapping approach.
Goal: This paper aims at identifying problems and challenges with respect to product roadmapping. In addition, it aims at understanding how companies succeed in improving their roadmapping practices in their respective company contexts.
Method: We conducted semi-structured expert interviews with 15 experts from 13 German companies and conducted athematic data analysis.
Results: The analysis showed that a significant number of companies is still struggling with traditional feature-based product-roadmapping and opinion-based prioritization of features. The most promising areas for improvement are stating the outcomes a company is trying to achieve and making them part of the roadmap, sharing or co-developing the roadmap with stakeholders, and establishing discovery activities.
Regardless of company size or industry sector, a majority of project teams and companies use customized processes that combine different development methods-so-called hybrid development methods. Even though such hybrid development methods are highly individualized, a common understanding of how to systematically construct synergetic practices is missing. Based on 1,467 data points from a large-scale online survey among practitioners, we study the current state of practice in process use to answer the question: What are hybrid development methods made of? Our findings reveal that only eight methods and few practices build the core of modern software development. This small set allows for statistically constructing hybrid development methods.
In dieser Ausarbeitung wird auf Visualisierungsmöglichkeiten von neuronalen Netzen eingegangen. Ein neuronales Netz scheint zuerst nicht von außen einsehbar und ist somit für viele eine Blackbox. Häufig genutzte Python-Bibliotheken, zum Beispiel TensorFlow, werden vorgestellt und deren Stärken wie auch Schwächen präsentiert. Anhand dieser werden bereits bestehende Visualisierungen gezeigt und ihr derzeitiger Einsatz wird erläutert. Durch einen Vergleich soll ersichtlich werden, welche Bibliothek am meisten Daten während des Trainings liefert, damit diese Informationen weiter verarbeitet werden. Diese Daten sollen so visualisiert werden, dass sie bei der Entwicklung eines neuronalen Netzes unterstützend sind. Ziel ist es, auf die Möglichkeiten einzugehen, welche geboten werden können. Durch eine Vereinfachung des Debuggings neuronaler Netze sollen weiterführende Entwicklungen in diese Richtung unterstützt werden.
Formula One races provide a wealth of data worth investigating. Although the time-varying data has a clear structure, it is pretty challenging to analyze it for further properties. Here the focus is on a visual classification for events, drivers, as well as time periods. As a first step, the Formula One data is visually encoded based on a line plot visual metaphor reflecting the dynamic lap times, and finally, a classification of the races based on the visual outcomes gained from these line plots is presented. The visualization tool is web-based and provides several interactively linked views on the data; however, it starts with a calendar-based overview representation. To illustrate the usefulness of the approach, the provided Formula One data from several years is visually explored while the races took place in different locations. The chapter discusses algorithmic, visual, and perceptual limitations that might occur during the visual classification of time-series data such as Formula One races.
In diesem Beitrag wird ein neuer Ansatz vorgestellt, welcher eine schwerkraftreduzierte Navigation innerhalb einer VR-Umgebung erlaubt, wie beispielsweise ein simulierter Mondspaziergang. Zur Navigation in der VR-Umgebung wird der Cyberith Virtualizer ein-gesetzt. Die Schwerkraftsimulation erfolgt mittels eines einstellbaren Gurtsystems, das anelastischen Seilen aufgehängt wird und abgestufte Schwerkraftkompensationen erlaubt. Als Umgebung wurde ein Raumschiffszenario sowie eine Mondoberfläche generiert. Hier sind in der aktuellen Anwendung einfache Interaktionen möglich. In Anlehnung an existierende Gravity Offload Systeme wird die Lösung ViRGOS bezeichnet. ViRGOS wurde bereits bei verschiedenen Besuchsterminen und Hochschulevents eingesetzt, so dass erste Rückmeldungen von Nutzern eingeholt werden konnten.
Vergleichende Analyse des YouTube-Auftritts von privat- und öffentlich-rechtlichen Sendegruppen
(2020)
Lange wurde das Internet als Antagonismus zum Fernsehen gesehen. Es wurde dementsprechend zur Zuschauerrück- bzw. -gewinnung genutzt, was sich allerdings als ineffizient erwies. Inzwischen haben die einzelnen Sendegruppen das Internet jedoch als mediale Erweiterung erkannt und genutzt. Durch diese späte Akzeptanz zeigen sich starke Unterschiede im Umfang und der Vorgehensweise hinsichtlich der Nutzung des Internets als zusätzliches Medium. Am besten lässt sich dies in einem Vergleich in Bezug auf die wichtigste videotechnische Social Media Plattform YouTube darstellen.
In diesem Vergleich sollen die einzelnen Sendegruppen hinsichtlich ihrer wahrgenommenen Vorteile, Nachteile und Attraktivität bezogen auf das Nutzerverhalten und die Nutzermeinung bewertet werden. Die zielgruppenorientierte Optimierung des YouTube-Auftrittes ist von außerordentlich hoher Bedeutung für die zukünftige Marktdurchdringung.
Artificial Intelligence enables innovative applications, and applications based on Artificial Intelligence are increasingly important for all aspects of the Digital Economy. However, the question of how AI resources such as tools and data can be linked to provide an AI-capability and create business value is still open. Therefore, this paper identifies the value-creating mechanisms of connectionist artificial intelligence using a capability-oriented view and points out the connections to different kinds of business value. The analysis supports an agenda that identifies areas that need further research to understand the mechanism of value creation in connectionist artificial intelligence.
Going forward with the requirements of missions to the Moon and further into deep space, the European Space Agency is investigating new methods of astronaut training that can help accelerate learning, increase availability and reduce complexity and cost in comparison to currently used methods. To achieve this, technologies such as virtual reality may be utilized. In this paper, an investigation into the benefits of using virtual reality as a means for extravehicular activity training in comparison to conventional training methods, such as neutral buoyancy pools is given. To help determine the requirements and current uses of virtual reality for extravehicular activity training first hand tests of currently available software as well as expert interviews are utilized. With this knowledge a concept is developed that may be used to further advance training methods in virtual reality. The resulting concept is used as a basis for development of a prototype to showcase user interactions and locomotion in microgravity simulations.
Die Entwicklung eines Medizinproduktes benötigt in der Regel mehrere Jahre. Gesetzliche Vorgaben, wie zum Beispiel das Medizinprodukte Durchführungsgesetz, bestimmen, welche Schritte während der Entwicklung durchgeführt werden müssen. Deren Einhaltung muss in der technischen Dokumentation nachgewiesen werden. Die darin enthaltenen technischen Dokumente entstehen im Verlauf der Entwicklung. Diese bauen aufeinander auf und verweisen sich gegenseitig. Dadurch entstehen heterogene und unübersichtliche Strukturen. Eine Lösung für dieses Problem bietet Traceability. Traceability sorgt dafür, dass die Anforderungen an das Medizinprodukt mit Dokumenten, wie dem Anforderungskatalog, Lastenheft oder der Spezifikation verknüpft werden können. Somit ist jederzeit nachvollziehbar, welche Anforderungen mit welchem Test, welchen Änderungen oder welchen Ergebnissen zusammenhängen. Ein wichtiger Prozess bei der Entwicklung von Medizinprodukten ist zudem das Usability Engineering, wodurch die Sicherheit eines Medizinprodukts sichergestellt und Risiken bei der Anwendung minimiert werden sollen. In diesem Prozess entstehen viele Artefakte, wie zum Beispiel Usability-Berichte. Um den Überblick über alle Usability-Daten behalten zu können, können diese mithilfe von Traceability verknüpft werden. In diesem Artikel wird herausgestellt, welche Voraussetzungen für das Usability Engineering in der Medizintechnik an Traceability gestellt
werden.
Hardly any software development process is used as prescribed by authors or standards. Regardless of company size or industry sector, a majority of project teams and companies use hybrid development methods (short: hybrid methods) that combine different development methods and practices. Even though such hybrid methods are highly individualized, a common understanding of how to systematically construct synergetic practices is missing. In this article, we make a first step towards a statistical construction procedure for hybrid methods. Grounded in 1467 data points from a large‐scale practitioner survey, we study the question: What are hybrid methods made of and how can they be systematically constructed? Our findings show that only eight methods and few practices build the core of modern software development. Using an 85% agreement level in the participants' selections, we provide examples illustrating how hybrid methods can be characterized by the practices they are made of. Furthermore, using this characterization, we develop an initial construction procedure, which allows for defining a method frame and enriching it incrementally to devise a hybrid method using ranked sets of practice.
Facial expressions play a dominant role in facilitating social interactions. We endeavor to develop tactile displays to reinstate facial expression modulated communication. The high spatial and temporal dimensionality of facial movements poses a unique challenge when designing tactile encodings of them. A further challenge is developing encodings that are at-tuned to the perceptual characteristics of our skin. A caveat of using vibrotactile displays is that tactile stimuli have been shown to induce perceptual tactile aftereffects when used on the fingers, arm and face. However, at present, despite the prevalence of waist-worn tactile displays, no such investigations of tactile aftereffects at the waist region exist in the literature, though they are warranted by the unique sensory and perceptual signalling characteristics of this area. Using an adaptation paradigm we investigated the presence of perceptual tactile aftereffects induced by continuous and burst vibrotactile stimuli delivered at the navel, side and spinal regions of the waist. We report evidence that the tactile perception topology of the waist is non-uniform, and specifically that the navel and spine regions are resistant to adaptive aftereffects while side regions are more prone to perceptual adaptations to continuous but not burst stimulations. Results of our current investigations highlight the unique set of challenges posed by designing waist-worn tactile displays. These and future perceptual studies can directly inform more realistic and effective implementations of complex high-dimensional spatiotemporal social cues.
AI technologies such as deep learning provide promising advances in many areas. Using these technologies, enterprises and organizations implement new business models and capabilities. In the beginning, AI-technologies have been deployed in an experimental environment. AI-based applications have been created in an ad-hoc manner and without methodological guidance or engineering approach. Due to the increasing importance of AI-technologies, however, a more structured approach is necessary that enable the methodological engineering of AI-based applications. Therefore, we develop in this paper first steps towards methodological engineering of AI-based applications. First, we identify some important differences between the technological foundations of AI- technologies, in particular deep learning, and traditional information technologies. Then we create a framework that enables to engineer AI-applications using four steps: identification of an AI-application type, sub-type identification, lifecycle phase, and definition of details. The introduced framework considers that AI-applications use an inductive approach to infer knowledge from huge collections and streams of data. It not only enables the rapid development of AI-application but also the efficient sharing of knowledge on AI-applications.
Intraoperative brain deformation, so called brain shift, affects the applicability of preoperative magnetic resonance imaging (MRI) data to assist the procedures of intraoperative ultrasound (iUS) guidance during neurosurgery. This paper proposes a deep learning-based approach for fast and accurate deformable registration of preoperative MRI to iUS images to correct brain shift. Based on the architecture of 3D convolutional neural networks, the proposed deep MRI-iUS registration method has been successfully tested and evaluated on the retrospective evaluation of cerebral tumors (RESECT) dataset. This study showed that our proposed method outperforms other registration methods in previous studies with an average mean squared error (MSE) of 85. Moreover, this method can register three 3D MRI-US pair in less than a second, improving the expected outcomes of brain surgery.
With the expansion of cyber-physical systems (CPSs) across critical and regulated industries, systems must be continuously updated to remain resilient. At the same time, they should be extremely secure and safe to operate and use. The DevOps approach caters to business demands of more speed and smartness in production, but it is extremely challenging to implement DevOps due to the complexity of critical CPSs and requirements from regulatory authorities. In this study, expert opinions from 33 European companies expose the gap in the current state of practice on DevOps-oriented continuous development and maintenance. The study contributes to research and practice by identifying a set of needs. Subsequently, the authors propose a novel approach called Secure DevOps and provide several avenues for further research and development in this area. The study shows that, because security is a cross-cutting property in complex CPSs, its proficient management requires system-wide competencies and capabilities across the CPSs development and operation.
Autonomous driving is becoming the next big digital disruption in the automotive industry. However, the possibility of integrating autonomous driving vehicles into current transportation systems not only involves technological issues but also requires the acceptance and adoption of users. Therefore, this paper develops a conceptual model for user acceptance of autonomous driving vehicles. The corresponding model is tested through a standardized survey of 470 respondents in Germany. Finally, the findings are discussed in relation to the current developments in the automotive industry, and recommendations for further research are given.
The typed graph model
(2020)
In recent years, the Graph Model has become increasingly popular, especially in the application domain of social networks. The model has been semantically augmented with properties and labels attached to the graph elements. It is difficult to ensure data quality for the properties and the data structure because the model does not need a schema. In this paper, we propose a schema bound Typed Graph Model with properties and labels. These enhancements improve not only data quality but also the quality of graph analysis. The power of this model is provided by using hyper-nodes and hyper edges, which allows to present a data structure on different abstraction levels. We demonstrate by example the superiority of this model over the property graph data model of Hidders and other prevalent data models, namely the relational, object-oriented, and XML model.
The tale of 1000 cores: an evaluation of concurrency control on real(ly) large multi-socket hardware
(2020)
In this paper, we set out the goal to revisit the results of “Starring into the Abyss [...] of Concurrency Control with [1000] Cores” and analyse in-memory DBMSs on today’s large hardware. Despite the original assumption of the authors, today we do not see single-socket CPUs with 1000 cores. Instead multi-socket hardware made its way into production data centres. Hence, we follow up on this prior work with an evaluation of the characteristics of concurrency control schemes on real production multi-socket hardware with 1568 cores. To our surprise, we made several interesting findings which we report on in this paper.
The advent of chatbots in customer service solutions received increasing attention by research and practice throughout the last years. However, the relevant dimensions and features for service quality and service performance for chatbots remain quite unclear. Therefore, this research develops and tests a conceptual model for customer service quality and customer service performance in the context of chatbots. Additionally, the impact of the developed service dimensions on different customer relationship metrics is measured across different service channels (hotline versus chatbots). Findings of six independent studies indicate a strong main effect of the conceptualized service dimensions on customer satisfaction, service costs, intention to service reusage, word-of-mouth, and customer loyalty. However, different service dimensions are relevant for chatbots compared to a traditional service hotline.
It is essential for the success of a company to set a strategic direction in which a product offering will be developed over time to achieve the company vision. For this reason, roadmaps are used in practice. in general, roadmaps can be expressed in various forms such as technology roadmaps, product roadmaps or industry roadmaps. From the point of view of industry, the basic purpose of a roadmap is to explore, visualize and communicate the dynamic linkage between markets, products and technology.
Entrepreneurship education is becoming increasingly important in higher education and also drives the development of innovative teaching formats, which can increase student engagement. It does, however, need greater international focus to become more attractive for both domestic and international students. This paper presents the examination and course design of two case studies, which promote entrepreneurship education for domestic and international students. These examples show that entrepreneurship courses are attractive due to their focus on interdisciplinarity, experience-based learning, and project-based work. Following a design-based research approach, this paper provides a practical contribution by offering a detailed overview of course design principles, classroom practice and presents reflections and learnings from an iterative development process.