Fraunhofer-Institut für Angewandte Informationstechnik FIT

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  • Publication
    Information Systems Engineering with Digital Shadows. Concept and Case Studies
    ( 2020)
    Liebenberg, Martin
    ;
    Jarke, Matthias
    The production sector has faced many difficulties in taking full advantage of opportunities found in other web application domains. Production research has focused on sophisticated mathematical models ranging from molecular materials modeling to efficient production control to inter-company supply network logistics. Often, these models have no closed-form solutions; this led to intense simulation research for individual modeling viewpoints, often labeled ""Digital Twins"". However, the complexity of the overall system precludes Digital Twins covering more than just a few system perspectives, especially if near-realtime performance is required. Moreover, the wide variety of individual situations and behaviors is usually captured only as statistical uncertainty. In order to achieve better performance and more context adaptation, the interdisciplinary research cluster ""Internet of Production"" at RWTH Aachen University is exploring the concept of ""Digital Shadows"". Digital Shadows can be understood as compact views on dynamic processes, usually combining condensed measurement data with highly efficient simplified mathematical models. In this exploratory paper, we argue based on a couple of initial case studies that Digital Shadows are not just valuable carriers of deep engineering knowledge but due to their small size also help in reducing network congestion and enabling edge computing. These properties could make Digital Shadows an interesting solution to address resilience in other information-intensive dynamic systems.
  • Publication
    Blu: What GUIs are made of
    ( 2020)
    Sermuga Pandian, Vinoth Pandian
    ;
    Suleri, Sarah
    ;
    Jarke, Matthias
    UI designers look for inspirational examples from existing UI designs during the prototyping process. However, they have to reconstruct these example UI designs from scratch to edit content or apply styling. The existing solution attempts to make UI screens into editable vector graphics using image segmentation techniques. In this research, we aim to use deep learning and gestalt laws-based algorithms to convert UI screens to editable blueprints by identifying the constituent UI element categories, their location, dimension, text content, and layout hierarchy. In this paper, we present a proof-of-concept web application that uses the UI screens and annotations from the RICO dataset and generates an editable blueprint vector graphic, and a UI layout tree. With this research, we aim to support UX designers in reconstructing UI screens and communicating UI layout information to developers.
  • Publication
    Syn: Synthetic Dataset for Training UI Element Detector from Lo-Fi Sketches
    ( 2020)
    Pandian, Vinoth
    ;
    Pandian, Sermuga
    ;
    Suleri, Sarah
    ;
    Jarke, Matthias
    User Interface design is an iterative process that progresses through low-, medium-, and high-fidelity prototypes. A few research projects use deep learning to automate this process by transforming low fidelity (lo-fi) sketches into front-end code. However, these research projects lack a large scale dataset of lo-fi sketches to train detection models. As a solution, we created Syn, a synthetic dataset containing 125,000 lo-fi sketches. These lo-fi sketches were synthetically generated using our UISketch dataset containing 5,917 sketches of 19 UI elements drawn by 350 participants. To realize the usage of Syn, we used it to train a UI element detector, Meta-Morph. It detects UI elements from a lo-fi sketch with 84.9% mAP and 72.7% AR. This work aims to support future research on UI element sketch detection and automating prototype fidelity transformation.
  • Publication
    Digital Energy. Keynote
    ( 2020)
    Jarke, Matthias
    In the presence of climate change, the need for less carbon-intensive renewable energy is obvious, equally for households and energy-intensive industries. At the same time, the growth of solar and wind energy implies much more temporal and geographic fluctuation and volatility between electrical energy supply and demand. Local balancing can reduce the need for expensive and controversial long-range high voltage lines, but the huge growth of small and medium energy prosumers also places high demand on flexible and scalable planning and control, as well as revised business models. The need for multiple kinds of digital solutions ranging from modeling and simulation, to sensing, communication and control software is obvious and under active investigation. However, neither network operators nor individual players will rely on simulations along, yet real large-scale experiments testing how realistic the simulations are hard to conduct in the fully connected electricity networks. And, of course, digitization of this critical infrastructure creates new hazards in terms of IT security that must be mitigated. Last not least, experience not just in the current Corona crisis has shown how tricky the design of stable business and public support models for renewable can be. While most of these issues individually have been subject to quite a bit of research, we see a need to bring the required cross-disciplinary competencies together in a coherent strategic setting. The recently founded Fraunhofer Center Digital Energy at RWTH Aachen University brings together leading researchers in the theory and practice of renewable electrity networks, software support for smart grid and energy-saving strategies in home and factories, IT security, and business administration in order to investigate seamless solutions from the business model and process level all the way down to physical electricity networks. The talk will illustrate these issues by a number of recent projects, including e.g. flexibilization of industrial demand, blockchain solutions for small-scale energy trading, protection of digitized networks against hacker attacks, and others.
  • Publication
    Direwolf Model Academy: An Extensible Collaborative Modeling Framework on the Web
    ( 2020)
    Koren, István
    ;
    Klamma, Ralf
    ;
    Jarke, Matthias
    Conceptual modeling in Industry 4.0 scenarios enables orchestrating production processes and planning data flows. Since diverse stakeholder groups are involved, collaboration features are particularly important. Common web-based tools are available; however, they focus on either modeling or collaboration. Based on our experiences with these two aspects, we present Direwolf Model Academy, a metamodel framework for creating feature-rich modeling environments on the web. It is based on modern standards like SVG and Web Components; it uses object-oriented programming principles enabled by the latest generation of JavaScript. We already employ tool instances in the areas of user interface generation from service description languages as well as conceptual modeling with iStar 2.0. In this article, we discuss the latter implementation and present the underlying technological foundation. Our framework is available open source on https://github.com/direwolf where we welcome contributions.
  • Publication
    Data Sovereignty and the Internet of Production
    ( 2020)
    Jarke, Matthias
    While the privacy of personal data has captured great attention in the public debate, resulting, e.g., in the European GDPR guideline, the sovereignty of knowledge-intensive small and medium enterprises concerning the usage of their own data in the presence of dominant data-hungry players in the Internet needs more investigation. In Europe, even the legal concept of data ownership is unclear. We reflect on requirements analyses, reference architectures and solution concepts pursued by the International Data Spaces Initiative to address these issues. The second part will more deeply explore our current interdisciplinary research in a visionary ""Internet of Production"" with 27 research groups from production and materials engineering, computer science, business and social sciences. In this setting, massive amounts of heterogeneous data must be exchanged and analyzed across organizational and disciplinary boundaries, throughout the lifecycle from (re-)engineering, to production, usage and recycling, under hard resource and time constraints. A shared metaphor, borrowed from Plato's famous Cave Allegory, serves as the core modeling and data management approach from conceptual, logical, physical, and business perspectives.
  • Publication
    Information System Development for Seamless Mobility
    ( 2019)
    Beutel, Markus
    ;
    Gökay, Sevket
    ;
    Jakobs, Eva-Maria
    ;
    Jarke, Matthias
    ;
    Kasugai, Kai
    ;
    Krempels, Karl-Heinz
    ;
    Ohler, Fabian
    ;
    Samsel, Christian
    ;
    Schwinger, Felix
    ;
    Terwelp, Christoph
    ;
    Thulke, David
    ;
    Vogelsang, Sara
    ;
    Ziefle, Martina
    Today, combining diverse mobility services during a single itinerary across different regions is still bristled with obstacles. Although developments concerning Mobility as a Service (MaaS) concepts, Advanced Travel Information Systems (ATIS) or Mobility Service Platforms (MSP) fostered integration, there are still various limitations. Manifold reasons, ranging from technical problems like heterogeneous system landscapes up to strategic business considerations, cause barriers on different levels. Within this work, we present a high level methodology to develop an integrated travel information system to overcome some of these barriers. We describe the practical applications as well as the method evolution in two German research projects. One project developed an IT platform to realize the interoperability of mobility services, whereas the second project focuses on the generalization of the approach by defining a reference framework. In addition, we discuss the lessons learned from half a decade of mobility and information systems research to suggest implications for future research.
  • Publication
    Designing a multi-sided data platform: Findings from the international data spaces case
    ( 2019)
    Otto, Boris
    ;
    Jarke, Matthias
    The paper presents the findings from a 3-year single-case study conducted in connection with the International Data Spaces (IDS) initiative. The IDS represents a multi-sided platform (MSP) for secure and trusted data exchange, which is governed by an institutionalized alliance of different stakeholder organizations. The paper delivers insights gained during the early stages of the platform's lifecycle (i.e. the platform design process). More specifically, it provides answers to three research questions, namely how alliance-driven MSPs come into existence and evolve, how different stakeholder groups use certain governance mechanisms during the platform design process, and how this process is influenced by regulatory instruments. By contrasting the case of an alliance-driven MSP with the more common approach of the keystone-driven MSP, the results of the case study suggest that different evolutionary paths can be pursued during the early stages of an MSP's lifecycle. Furthermore, the IDS initiative considers trust and data sovereignty more relevant regulatory instruments compared to pricing, for example. Finally, the study advances the body of scientific knowledge with regard to data being a boundary resource on MSPs.
  • Publication
    Data Sovereignty and Data Space Ecosystems
    ( 2019)
    Jarke, Matthias
    ;
    Otto, Boris
    ;
    Ram, Sudha