Nazemi, Kawa; Burkhardt, Dirk; Kaupp, Lukas; Dannewald, Till; Kowald, Matthias; Ginters, Egils
In: Ginters, Egils; Estrada, Mario Arturo Ruiz; Eroles, Miquel Angel Piera (Ed.): ICTE in Transportation and Logistics 2019, pp. 82–89, Springer International Publishing, Cham, 2020, ISBN: 978-3-030-39688-6.
Mobility, transportation and logistics are more and more influenced by a variety of indicators such as new technological developments, ecological and economic changes, political decisions and in particular humans' mobility behavior. These indicators will lead to massive changes in our daily live with regards to mobility, transportation and logistics. New technologies will lead to a different mobility behavior with new constraints. These changes in mobility behavior and logistics require analytical systems to forecast the required information and probably appearing changes. These systems have to consider different perspectives and employ multiple indicators. Visual Analytics provides both, the analytical approaches by including machine learning approaches and interactive visualizations to enable such analytical tasks. In this paper the main indicators for Visual Analytics in the domain of mobility transportation and logistics are discussed and followed by exemplary case studies to illustrate the advantages of such systems. The examples are aimed to demonstrate the benefits of Visual Analytics in mobility.
Nazemi, Kawa; Burkhardt, Dirk
In: Bebis, George; Boyle, Richard; Parvin, Bahram; Koracin, Darko; Ushizima, Daniela; Chai, Sek; Sueda, Shinjiro; Lin, Xin; Lu, Aidong; Thalmann, Daniel; Wang, Chaoli; Xu, Panpan (Ed.): Advances in Visual Computing, pp. 283–294, Springer International Publishing, Cham, 2019, ISBN: 978-3-030-33723-0.
Tags: Artificial Intelligence, Data Analytics, Human Factors, Human-Centered Interfaces, Human-Computer Interaction, Information Visualization, Intelligent Systems, maschine learning, Visual Analytics| | |
Visual Analytics provides with a combination of automated techniques and interactive visualizations huge analysis possibilities in technology and innovation management. Thereby not only the use of machine learning data mining methods plays an important role. Due to the high interaction capabilities, it provides a more user-centered approach, where users are able to manipulate the entire analysis process and get the most valuable information. Existing Visual Analytics systems for Trend Analytics and technology and innovation management do not really make use of this unique feature and almost neglect the human in the analysis process. Outcomes from research in information search, information visualization and technology management can lead to more sophisticated Visual Analytics systems that involved the human in the entire analysis process. We propose in this paper a new interaction approach for Visual Analytics in technology and innovation management with a special focus on technological trend analytics.
Nazemi, Kawa; Burkhardt, Dirk
In: ICTE in Transportation and Logistics 2018 (ICTE 2018), vol. 149, pp. 138-150, 2019, ISSN: 1877-0509.
Mobility, logistics and transportation are emerging fields of research and application. Humans’ mobility behavior plays an increasing role for societal challenges. Beside the societal challenges these areas are strongly related to technologies and innovations. Gathering information about emerging technologies plays an increasing role for the entire research in these areas. Humans’ information processing can be strongly supported by Visual Analytics that combines automatic modelling and interactive visualizations. The juxtapose orchestration of interactive visualization enables gathering more information in a shorter time. We propose in this paper an approach that goes beyond the established methods of dashboarding and enables visualizing different databases, data-sets and sub-sets of data with juxtaposed visual interfaces. Our approach should be seen as an expandable method. Our main contributions are an in-depth analysis of visual task models and an approach for juxtaposing visual layouts as visual dashboards to enable solving complex tasks. We illustrate our main outcome through a case study that investigates the area of mobility and illustrates how complex analytical tasks can be performed easily by combining different visual interfaces.