Publications

104 entries « ‹ 1 of 5 › »

2021
104.	Kawa Nazemi; Lukas Kaupp; Dirk Burkhardt; Nicola Below Datenvisualisierung Book Chapter Markus Putnings; Heike Neuroth; Janna Neumann (Ed.): Praxishandbuch Forschungsdatenmanagement, Chapter 5.4, pp. 477-502, De Gruyter, Berlin/Boston, 2021, ISBN: 978-3-11-065365-6. Abstract \| Links \| BibTeX \| Tags: Data Visualization @inbook{Nazemi2021, title = {Datenvisualisierung}, author = {Kawa Nazemi and Lukas Kaupp and Dirk Burkhardt and Nicola Below}, editor = {Markus Putnings and Heike Neuroth and Janna Neumann}, doi = {10.1515/9783110657807-026}, isbn = {978-3-11-065365-6}, year = {2021}, date = {2021-01-18}, booktitle = {Praxishandbuch Forschungsdatenmanagement}, pages = {477-502}, publisher = {De Gruyter}, address = {Berlin/Boston}, chapter = {5.4}, abstract = {Die visuelle Projektion von heterogenen (z. B. Forschungs-)Daten auf einer 2-dimensionalen Fläche, wie etwa einem Bildschirm, wird als Datenvisualisierung bezeichnet. Datenvisualisierung ist ein Oberbegriff für verschiedene Arten der visuellen Projektion. In diesem Kapitel wird zunächst der Begriff definiert und abgegrenzt. Der Fokus des Kapitels liegt auf Informationsvisualisierung und Visual Analytics. In diesem Kontext wird der Prozess der visuellen Transformation vorgestellt. Es soll als Grundlage für eine wissenschaftlich valide Generierung von Visualisierungen dienen, die auch visuelle Aufgaben umfassen. Anwendungsszenarien stellen den Mehrwert der hier vorgestellten Konzepte in der Praxis vor. Der wissenschaftliche Beitrag liegt in einer formalen Definition des visuellen Mappings.}, keywords = {Data Visualization}, pubstate = {published}, tppubtype = {inbook} } Close Die visuelle Projektion von heterogenen (z. B. Forschungs-)Daten auf einer 2-dimensionalen Fläche, wie etwa einem Bildschirm, wird als Datenvisualisierung bezeichnet. Datenvisualisierung ist ein Oberbegriff für verschiedene Arten der visuellen Projektion. In diesem Kapitel wird zunächst der Begriff definiert und abgegrenzt. Der Fokus des Kapitels liegt auf Informationsvisualisierung und Visual Analytics. In diesem Kontext wird der Prozess der visuellen Transformation vorgestellt. Es soll als Grundlage für eine wissenschaftlich valide Generierung von Visualisierungen dienen, die auch visuelle Aufgaben umfassen. Anwendungsszenarien stellen den Mehrwert der hier vorgestellten Konzepte in der Praxis vor. Der wissenschaftliche Beitrag liegt in einer formalen Definition des visuellen Mappings. Close doi:10.1515/9783110657807-026 Close
103.	Dirk Burkhardt Nicola Below Kawa Nazemi Lukas Kaupp Datenvisualisierung Incollection Jana Neumann Markus Putnings Heike Neuroth (Ed.): Praxishandbuch Forschungsdatenmanagement, pp. 477–502, De Gruyter, 2021, ISBN: 978-3-11-065365-6. Abstract \| Links \| BibTeX \| Tags: @incollection{Nazemi2021a, title = {Datenvisualisierung}, author = {Dirk Burkhardt Nicola Below Kawa Nazemi Lukas Kaupp}, editor = {Jana Neumann Markus Putnings Heike Neuroth}, url = {https://doi.org/10.1515/9783110657807-026}, doi = {10.1515/9783110657807-026}, isbn = {978-3-11-065365-6}, year = {2021}, date = {2021-01-01}, booktitle = {Praxishandbuch Forschungsdatenmanagement}, pages = {477--502}, publisher = {De Gruyter}, chapter = {5.4}, abstract = {Die visuelle Projektion von heterogenen (z. B. Forschungs-)Daten auf einer 2-dimensionalen Fläche, wie etwa einem Bildschirm, wird als Datenvisualisierung bezeichnet. Datenvisualisierung ist ein Oberbegriff für verschiedene Arten der visuellen Projektion. In diesem Kapitel wird zunächst der Begriff definiert und abgegrenzt. Der Fokus des Kapitels liegt auf Informationsvisualisierung und Visual Analytics. In diesem Kontext wird der Prozess der visuellen Transformation vorgestellt. Es soll als Grundlage für eine wissenschaftlich valide Generierung von Visualisierungen dienen, die auch visuelle Aufgaben umfassen. Anwendungsszenarien stellen den Mehrwert der hier vorgestellten Konzepte in der Praxis vor. Der wissenschaftliche Beitrag liegt in einer formalen Definition des visuellen Mappings.}, keywords = {}, pubstate = {published}, tppubtype = {incollection} } Close Die visuelle Projektion von heterogenen (z. B. Forschungs-)Daten auf einer 2-dimensionalen Fläche, wie etwa einem Bildschirm, wird als Datenvisualisierung bezeichnet. Datenvisualisierung ist ein Oberbegriff für verschiedene Arten der visuellen Projektion. In diesem Kapitel wird zunächst der Begriff definiert und abgegrenzt. Der Fokus des Kapitels liegt auf Informationsvisualisierung und Visual Analytics. In diesem Kontext wird der Prozess der visuellen Transformation vorgestellt. Es soll als Grundlage für eine wissenschaftlich valide Generierung von Visualisierungen dienen, die auch visuelle Aufgaben umfassen. Anwendungsszenarien stellen den Mehrwert der hier vorgestellten Konzepte in der Praxis vor. Der wissenschaftliche Beitrag liegt in einer formalen Definition des visuellen Mappings. Close https://doi.org/10.1515/9783110657807-026 doi:10.1515/9783110657807-026 Close
2020
102.	Dirk Burkhardt; Kawa Nazemi; Egils Ginters Innovations in Mobility and Logistics: Assistance of Complex Analytical Processes in Visual Trend Analytics Inproceedings Janis Grabis; Andrejs Romanovs; Galina Kulesova (Ed.): 2020 61st International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS), pp. 1-6, IEEE, 2020, ISBN: 978-1-7281-9105-8. Abstract \| Links \| BibTeX \| Tags: Adaptive Visualization, logistics, Process Mining, Transportation, Trend Analytics, Visual analytics @inproceedings{Burkhardt2020c, title = {Innovations in Mobility and Logistics: Assistance of Complex Analytical Processes in Visual Trend Analytics}, author = {Dirk Burkhardt and Kawa Nazemi and Egils Ginters}, editor = {Janis Grabis and Andrejs Romanovs and Galina Kulesova}, doi = {10.1109/ITMS51158.2020.9259309}, isbn = {978-1-7281-9105-8}, year = {2020}, date = {2020-11-19}, booktitle = {2020 61st International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS)}, pages = {1-6}, publisher = {IEEE}, abstract = {A variety of new technologies and ideas for businesses are arising in the domain of logistics and mobility. It can be differentiated between fundamental new approaches, e.g. central packaging stations or deliveries via drones and minor technological advancements that aim on more ecologically and economic transportation. The need for analytical systems that enable identifying new technologies, innovations, business models etc. and give also the opportunity to rate those in perspective of business relevance is growing. The users’ behavior is commonly investigated in adaptive systems, which is considering the induvial preferences of users, but neglecting often the tasks and goals of the analysis. A process-related supports could assist to solve an analytical task in a more efficient and effective way. We introduce in this paper an approach that enables non-professionals to perform visual trend analysis through an advanced process assistance based on process mining and visual adaptation. This allows generating a process model based on events, which is the baseline for process support feature calculation. These features in form of visual adaptations and the process model enable assisting non-experts in complex analytical tasks.}, keywords = {Adaptive Visualization, logistics, Process Mining, Transportation, Trend Analytics, Visual analytics}, pubstate = {published}, tppubtype = {inproceedings} } Close A variety of new technologies and ideas for businesses are arising in the domain of logistics and mobility. It can be differentiated between fundamental new approaches, e.g. central packaging stations or deliveries via drones and minor technological advancements that aim on more ecologically and economic transportation. The need for analytical systems that enable identifying new technologies, innovations, business models etc. and give also the opportunity to rate those in perspective of business relevance is growing. The users’ behavior is commonly investigated in adaptive systems, which is considering the induvial preferences of users, but neglecting often the tasks and goals of the analysis. A process-related supports could assist to solve an analytical task in a more efficient and effective way. We introduce in this paper an approach that enables non-professionals to perform visual trend analysis through an advanced process assistance based on process mining and visual adaptation. This allows generating a process model based on events, which is the baseline for process support feature calculation. These features in form of visual adaptations and the process model enable assisting non-experts in complex analytical tasks. Close doi:10.1109/ITMS51158.2020.9259309 Close
101.	Artis Aizstrauts; Dirk Burkhardt; Egils Ginters; Kawa Nazemi On Microservice Architecture Based Communication Environment for Cycling Map Developing and Maintenance Simulator Inproceedings Janis Grabis; Andrejs Romanovs; Galina Kulesova (Ed.): 2020 61st International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS), pp. 1-4, IEEE, 2020, ISBN: 978-1-7281-9105-8. Abstract \| Links \| BibTeX \| Tags: Easy Communication Environment, microservice architecture, Simulation @inproceedings{Aizstrauts2020c, title = {On Microservice Architecture Based Communication Environment for Cycling Map Developing and Maintenance Simulator}, author = {Artis Aizstrauts and Dirk Burkhardt and Egils Ginters and Kawa Nazemi}, editor = {Janis Grabis and Andrejs Romanovs and Galina Kulesova}, doi = {10.1109/ITMS51158.2020.9259299}, isbn = {978-1-7281-9105-8}, year = {2020}, date = {2020-11-19}, booktitle = {2020 61st International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS)}, pages = {1-4}, publisher = {IEEE}, abstract = {Urban transport infrastructure nowadays involves environmentally friendly modes of transport, the most democratic of which is cycling. Citizens will use bicycles if a reasonably designed cycle path scheme will be provided. Cyclists also need to know the characteristics and load of the planned route before the trip. Prediction can be provided by simulation, but it is often necessary to use heterogeneous and distributed models that require a specific communication environment to ensure interaction. The article describes the easy communication environment that is used to provide microservices communication and data exchange in a bicycle route design and maintenance multi-level simulator.}, keywords = {Easy Communication Environment, microservice architecture, Simulation}, pubstate = {published}, tppubtype = {inproceedings} } Close Urban transport infrastructure nowadays involves environmentally friendly modes of transport, the most democratic of which is cycling. Citizens will use bicycles if a reasonably designed cycle path scheme will be provided. Cyclists also need to know the characteristics and load of the planned route before the trip. Prediction can be provided by simulation, but it is often necessary to use heterogeneous and distributed models that require a specific communication environment to ensure interaction. The article describes the easy communication environment that is used to provide microservices communication and data exchange in a bicycle route design and maintenance multi-level simulator. Close doi:10.1109/ITMS51158.2020.9259299 Close
100.	Kawa Nazemi; Matthias Kowald; Till Dannewald; Dirk Burkhardt; Egils Ginters Visual Analytics Indicators for Mobility and Transportation Inproceedings Janis Grabis; Andrejs Romanovs; Galina Kulesova (Ed.): 2020 61st International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS), pp. 1-6, IEEE, 2020, ISBN: 978-1-7281-9105-8. Abstract \| Links \| BibTeX \| Tags: mobility analytics, mobility behaviour, mobility indicators for visual analytics, Visual analytics @inproceedings{Nazemi2020c, title = {Visual Analytics Indicators for Mobility and Transportation}, author = {Kawa Nazemi and Matthias Kowald and Till Dannewald and Dirk Burkhardt and Egils Ginters}, editor = {Janis Grabis and Andrejs Romanovs and Galina Kulesova}, doi = {10.1109/ITMS51158.2020.9259321}, isbn = {978-1-7281-9105-8}, year = {2020}, date = {2020-11-19}, booktitle = {2020 61st International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS)}, pages = {1-6}, publisher = {IEEE}, abstract = {Visual Analytics enables a deep analysis of complex and multivariate data by applying machine learning methods and interactive visualization. These complex analyses lead to gain insights and knowledge for a variety of analytics tasks to enable the decision-making process. The enablement of decision-making processes is essential for managing and planning mobility and transportation. These are influenced by a variety of indicators such as new technological developments, ecological and economic changes, political decisions and in particular humans’ mobility behaviour. New technologies will lead to a different mobility behaviour with other constraints. These changes in mobility behaviour require analytical systems to forecast the required information and probably appearing changes. These systems must consider different perspectives and employ multiple indicators. Visual Analytics enable such analytical tasks. We introduce in this paper the main indicators for Visual Analytics for mobility and transportation that are exemplary explained through two case studies.}, keywords = {mobility analytics, mobility behaviour, mobility indicators for visual analytics, Visual analytics}, pubstate = {published}, tppubtype = {inproceedings} } Close Visual Analytics enables a deep analysis of complex and multivariate data by applying machine learning methods and interactive visualization. These complex analyses lead to gain insights and knowledge for a variety of analytics tasks to enable the decision-making process. The enablement of decision-making processes is essential for managing and planning mobility and transportation. These are influenced by a variety of indicators such as new technological developments, ecological and economic changes, political decisions and in particular humans’ mobility behaviour. New technologies will lead to a different mobility behaviour with other constraints. These changes in mobility behaviour require analytical systems to forecast the required information and probably appearing changes. These systems must consider different perspectives and employ multiple indicators. Visual Analytics enable such analytical tasks. We introduce in this paper the main indicators for Visual Analytics for mobility and transportation that are exemplary explained through two case studies. Close doi:10.1109/ITMS51158.2020.9259321 Close
99.	Artis Aizstrauts; Egils Ginters; Dirk Burkhardt; Kawa Nazemi Bicycle Path Network Designing and Exploitation Simulation as a Microservice Architecture Inproceedings Egils Ginters; Mario Arturo Ruiz Estrada; Miquel Angel Piera Eroles (Ed.): ICTE in Transportation and Logistics 2019, pp. 344–351, Springer International Publishing, Cham, 2020, ISBN: 978-3-030-39688-6. Abstract \| Links \| BibTeX \| Tags: Bicycle path network planning, Easy Communication Environment, Sociotechnical systems simulation @inproceedings{Aizstrauts2020, title = {Bicycle Path Network Designing and Exploitation Simulation as a Microservice Architecture}, author = {Artis Aizstrauts and Egils Ginters and Dirk Burkhardt and Kawa Nazemi}, editor = {Egils Ginters and Mario Arturo Ruiz Estrada and Miquel Angel Piera Eroles}, doi = {10.1007/978-3-030-39688-6_43}, isbn = {978-3-030-39688-6}, year = {2020}, date = {2020-01-31}, booktitle = {ICTE in Transportation and Logistics 2019}, pages = {344--351}, publisher = {Springer International Publishing}, address = {Cham}, abstract = {Simulation is recognized as a suitable tool for sociotechnical systems research. But the variety and complexity of sociotechnical systems often leads to the need for distributed simulation solutions to understand them. Models that are built for infrastructure planning are typical examples. They combine different domains and involve variety of simulation approaches. This article proposes an easy management environment that is used for VeloRouter software -- a multi agent-based bicycle path network and exploitation simulator that is built as a microservice architecture where each domain simulation is executed as a different microservice.}, keywords = {Bicycle path network planning, Easy Communication Environment, Sociotechnical systems simulation}, pubstate = {published}, tppubtype = {inproceedings} } Close Simulation is recognized as a suitable tool for sociotechnical systems research. But the variety and complexity of sociotechnical systems often leads to the need for distributed simulation solutions to understand them. Models that are built for infrastructure planning are typical examples. They combine different domains and involve variety of simulation approaches. This article proposes an easy management environment that is used for VeloRouter software -- a multi agent-based bicycle path network and exploitation simulator that is built as a microservice architecture where each domain simulation is executed as a different microservice. Close doi:10.1007/978-3-030-39688-6_43 Close
98.	Kawa Nazemi; Dirk Burkhardt; Lukas Kaupp; Till Dannewald; Matthias Kowald; Egils Ginters Visual Analytics in Mobility, Transportation and Logistics Inproceedings Egils Ginters; Mario Arturo Ruiz Estrada; Miquel Angel Piera Eroles (Ed.): ICTE in Transportation and Logistics 2019, pp. 82–89, Springer International Publishing, Cham, 2020, ISBN: 978-3-030-39688-6. Abstract \| Links \| BibTeX \| Tags: Data Analytics, Mobility Behavior, Visual analytics @inproceedings{Nazemi2020, title = {Visual Analytics in Mobility, Transportation and Logistics}, author = {Kawa Nazemi and Dirk Burkhardt and Lukas Kaupp and Till Dannewald and Matthias Kowald and Egils Ginters}, editor = {Egils Ginters and Mario Arturo Ruiz Estrada and Miquel Angel Piera Eroles}, doi = {10.1007/978-3-030-39688-6_12}, isbn = {978-3-030-39688-6}, year = {2020}, date = {2020-01-01}, booktitle = {ICTE in Transportation and Logistics 2019}, pages = {82--89}, publisher = {Springer International Publishing}, address = {Cham}, abstract = {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.}, keywords = {Data Analytics, Mobility Behavior, Visual analytics}, pubstate = {published}, tppubtype = {inproceedings} } Close 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. Close doi:10.1007/978-3-030-39688-6_12 Close
97.	Dirk Burkhardt; Kawa Nazemi; Egils Ginters Process Support and Visual Adaptation to Assist Visual Trend Analytics in Managing Transportation Innovations Inproceedings Egils Ginters; Mario Arturo Ruiz Estrada; Miquel Angel Piera Eroles (Ed.): ICTE in Transportation and Logistics 2019, pp. 319–327, Springer International Publishing, Cham, 2020, ISBN: 978-3-030-39688-6. Abstract \| Links \| BibTeX \| Tags: Adaptive Visualization, Process Mining, Transportation and Logistics @inproceedings{Burkhardt2020, title = {Process Support and Visual Adaptation to Assist Visual Trend Analytics in Managing Transportation Innovations}, author = {Dirk Burkhardt and Kawa Nazemi and Egils Ginters}, editor = {Egils Ginters and Mario Arturo Ruiz Estrada and Miquel Angel Piera Eroles}, doi = {10.1007/978-3-030-39688-6_40}, isbn = {978-3-030-39688-6}, year = {2020}, date = {2020-01-01}, booktitle = {ICTE in Transportation and Logistics 2019}, pages = {319--327}, publisher = {Springer International Publishing}, address = {Cham}, abstract = {In the domain of mobility and logistics, a variety of new technologies and business ideas are arising. Beside technologies that aim on ecologically and economic transportation, such as electric engines, there are also fundamental different approaches like central packaging stations or deliveries via drones. Yet, there is a growing need for analytical systems that enable identifying new technologies, innovations, business models etc. and give also the opportunity to rate those in perspective of business relevance. Commonly adaptive systems investigate only the users' behavior, while a process-related supports could assist to solve an analytical task more efficient and effective. In this article an approach that enables non-experts to perform visual trend analysis through an advanced process support based on process mining is described. This allow us to calculate a process model based on events, which is the baseline for process support feature calculation. These features and the process model enable to assist non-expert users in complex analytical tasks.}, keywords = {Adaptive Visualization, Process Mining, Transportation and Logistics}, pubstate = {published}, tppubtype = {inproceedings} } Close In the domain of mobility and logistics, a variety of new technologies and business ideas are arising. Beside technologies that aim on ecologically and economic transportation, such as electric engines, there are also fundamental different approaches like central packaging stations or deliveries via drones. Yet, there is a growing need for analytical systems that enable identifying new technologies, innovations, business models etc. and give also the opportunity to rate those in perspective of business relevance. Commonly adaptive systems investigate only the users' behavior, while a process-related supports could assist to solve an analytical task more efficient and effective. In this article an approach that enables non-experts to perform visual trend analysis through an advanced process support based on process mining is described. This allow us to calculate a process model based on events, which is the baseline for process support feature calculation. These features and the process model enable to assist non-expert users in complex analytical tasks. Close doi:10.1007/978-3-030-39688-6_40 Close
2019
96.	Kawa Nazemi; Dirk Burkhardt Advanced Visual Analytical Reasoning for Technology and Innovation Management (AVARTIM) Miscellaneous Forschungstag 2019 der Hessischen Hochschulen für Angewandte Wissenschaften (HAW), Frankfurt, Germany, 2019. Abstract \| Links \| BibTeX \| Tags: Innovation Management, Technology Management, Trend Analytics, Visual Analytical Reasoning, Visual analytics @misc{Nazemi2019db, title = {Advanced Visual Analytical Reasoning for Technology and Innovation Management (AVARTIM)}, author = {Kawa Nazemi and Dirk Burkhardt}, url = {https://www.hessen.de/presse/veranstaltung/forschungstag-2019-der-hessischen-hochschulen-fuer-angewandte-wissenschaften, Event Website}, doi = {10.5281/zenodo.3517296}, year = {2019}, date = {2019-10-29}, abstract = {Im Rahmen des Vorhabens soll mit „AVARTIM“ ein softwaregestützter Prozess zum Erkennen und Bewerten von Trends, Markt- und Technologiesignalen entwickelt werden, um den Prozess des Innovations- und Technologiemanagements nachhaltig zu unterstützen. Dabei soll im Rahmen des Vorhabens eine Infrastruktur an der Hochschule Darmstadt aufgebaut werden, die modular ist und somit auf technologische Veränderungen schnell reagieren kann. Die zu entwickelnde Infrastruktur dient hierbei als Vorlaufforschung und Ausgangstechnologie sowohl für den industriellen Einsatz durch und mit den KMU Partnern als auch zur Beantragung von Verbundvorhaben.}, howpublished = {Forschungstag 2019 der Hessischen Hochschulen für Angewandte Wissenschaften (HAW), Frankfurt, Germany}, keywords = {Innovation Management, Technology Management, Trend Analytics, Visual Analytical Reasoning, Visual analytics}, pubstate = {published}, tppubtype = {misc} } Close Im Rahmen des Vorhabens soll mit „AVARTIM“ ein softwaregestützter Prozess zum Erkennen und Bewerten von Trends, Markt- und Technologiesignalen entwickelt werden, um den Prozess des Innovations- und Technologiemanagements nachhaltig zu unterstützen. Dabei soll im Rahmen des Vorhabens eine Infrastruktur an der Hochschule Darmstadt aufgebaut werden, die modular ist und somit auf technologische Veränderungen schnell reagieren kann. Die zu entwickelnde Infrastruktur dient hierbei als Vorlaufforschung und Ausgangstechnologie sowohl für den industriellen Einsatz durch und mit den KMU Partnern als auch zur Beantragung von Verbundvorhaben. Close Event Website doi:10.5281/zenodo.3517296 Close
95.	Kawa Nazemi; Dirk Burkhardt A Visual Analytics Approach for Analyzing Technological Trends in Technology and Innovation Management Inproceedings George Bebis; Richard Boyle; Bahram Parvin; Darko Koracin; Daniela Ushizima; Sek Chai; Shinjiro Sueda; Xin Lin; Aidong Lu; Daniel Thalmann; Chaoli Wang; Panpan Xu (Ed.): Advances in Visual Computing, pp. 283–294, Springer International Publishing, Cham, 2019, ISBN: 978-3-030-33723-0. Abstract \| Links \| BibTeX \| Tags: Artificial Intelligence, Data Analytics, Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, Intelligent Systems, maschine learning, Visual analytics @inproceedings{Nazemi_ISVC2019, title = {A Visual Analytics Approach for Analyzing Technological Trends in Technology and Innovation Management}, author = {Kawa Nazemi and Dirk Burkhardt}, editor = {George Bebis and Richard Boyle and Bahram Parvin and Darko Koracin and Daniela Ushizima and Sek Chai and Shinjiro Sueda and Xin Lin and Aidong Lu and Daniel Thalmann and Chaoli Wang and Panpan Xu}, url = {https://rd.springer.com/chapter/10.1007/978-3-030-33723-0_23, Springer LNCS https://dx.doi.org/10.5281/zenodo.3473065, doi:10.5281/zenodo.3473065 (Poster)}, doi = {10.1007/978-3-030-33723-0_23}, isbn = {978-3-030-33723-0}, year = {2019}, date = {2019-10-09}, booktitle = {Advances in Visual Computing}, pages = {283--294}, publisher = {Springer International Publishing}, address = {Cham}, abstract = {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.}, keywords = {Artificial Intelligence, Data Analytics, Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, Intelligent Systems, maschine learning, Visual analytics}, pubstate = {published}, tppubtype = {inproceedings} } Close 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. Close Springer LNCS doi:10.5281/zenodo.3473065 (Poster) doi:10.1007/978-3-030-33723-0_23 Close
94.	Dirk Burkhardt; Kawa Nazemi; Arjan Kuijper; Egils Ginters A Mobile Visual Analytics Approach for Instant Trend Analysis in Mobile Contexts Inproceedings 5th International Conference of the Virtual and Augmented Reality in Education (VARE2019), pp. 11–19, CAL-TEK SRL, Rende, Italy, 2019, ISBN: 978-88-85741-41-6, (Nominated for Best Paper Award). Abstract \| Links \| BibTeX \| Tags: Business Analytics, Decision Support Systems, Human-Computer Interaction, Information visualization, Mobile Devices, Mobile Visual Analytics, Visual Trend Analysis @inproceedings{Burkhardt2019b, title = {A Mobile Visual Analytics Approach for Instant Trend Analysis in Mobile Contexts}, author = {Dirk Burkhardt and Kawa Nazemi and Arjan Kuijper and Egils Ginters}, doi = {10.5281/zenodo.3473041}, isbn = {978-88-85741-41-6}, year = {2019}, date = {2019-09-18}, booktitle = {5th International Conference of the Virtual and Augmented Reality in Education (VARE2019)}, pages = {11--19}, publisher = {CAL-TEK SRL}, address = {Rende, Italy}, abstract = {The awareness of market trends becomes relevant for a broad number of market branches, in particular the more they are challenged by the digitalization. Trend analysis solutions help business executives identifying upcoming trends early. But solid market analysis takes their time and are often not available on consulting or strategy discussions. This circumstance often leads to unproductive debates where no clear strategy, technology etc. could be identified. Therefore, we propose a mobile visual trend analysis approach that enables a quick trend analysis to identify at least the most relevant and irrelevant aspects to focus debates on the relevant options. To enable an analysis like this, the exhausting analysis on powerful workstations with large screens has to adopted to mobile devices within a mobile behavior. Our main contribution is the therefore a new approach of a mobile knowledge cockpit, which provides different analytical visualizations within and intuitive interaction design.}, note = {Nominated for Best Paper Award}, keywords = {Business Analytics, Decision Support Systems, Human-Computer Interaction, Information visualization, Mobile Devices, Mobile Visual Analytics, Visual Trend Analysis}, pubstate = {published}, tppubtype = {inproceedings} } Close The awareness of market trends becomes relevant for a broad number of market branches, in particular the more they are challenged by the digitalization. Trend analysis solutions help business executives identifying upcoming trends early. But solid market analysis takes their time and are often not available on consulting or strategy discussions. This circumstance often leads to unproductive debates where no clear strategy, technology etc. could be identified. Therefore, we propose a mobile visual trend analysis approach that enables a quick trend analysis to identify at least the most relevant and irrelevant aspects to focus debates on the relevant options. To enable an analysis like this, the exhausting analysis on powerful workstations with large screens has to adopted to mobile devices within a mobile behavior. Our main contribution is the therefore a new approach of a mobile knowledge cockpit, which provides different analytical visualizations within and intuitive interaction design. Close doi:10.5281/zenodo.3473041 Close
93.	Egils Ginters; Dirk Burkhardt; Kawa Nazemi; Yuri Merkuryev The Concept of Augmented Reality Application for Putting Alignment in Golf Inproceedings 5th International Conference of the Virtual and Augmented Reality in Education (VARE 2019), pp. 20–27, CAL-TEK SRL, Rende, Italy, 2019, ISBN: 978-88-85741-41-6. Abstract \| Links \| BibTeX \| Tags: Android, Augmented Reality, Intelligent Training, Object Tracking, Objects Recognition @inproceedings{Ginters2019, title = {The Concept of Augmented Reality Application for Putting Alignment in Golf}, author = {Egils Ginters and Dirk Burkhardt and Kawa Nazemi and Yuri Merkuryev}, url = {http://www.msc-les.org/proceedings/vare/2019/VARE2019.pdf, Proceedings as PDF}, isbn = {978-88-85741-41-6}, year = {2019}, date = {2019-09-18}, booktitle = {5th International Conference of the Virtual and Augmented Reality in Education (VARE 2019)}, pages = {20--27}, publisher = {CAL-TEK SRL}, address = {Rende, Italy}, abstract = {Virtual and augmented reality (VR / AR) applications have successfully overcome the critical part of the Gartner curve. Investments are made and new products entering the economy. However, a very small percentage of society have also heard about AR glasses, mainly linking these with potential identity threats and personal data breaches. The authors dealt with the design of application of AR to improve golf skills by improving the putting technique. The above solution is complicated by requiring complex object recognition, tracking and advanced AR software designing.}, keywords = {Android, Augmented Reality, Intelligent Training, Object Tracking, Objects Recognition}, pubstate = {published}, tppubtype = {inproceedings} } Close Virtual and augmented reality (VR / AR) applications have successfully overcome the critical part of the Gartner curve. Investments are made and new products entering the economy. However, a very small percentage of society have also heard about AR glasses, mainly linking these with potential identity threats and personal data breaches. The authors dealt with the design of application of AR to improve golf skills by improving the putting technique. The above solution is complicated by requiring complex object recognition, tracking and advanced AR software designing. Close Proceedings as PDF Close
92.	Kawa Nazemi; Dirk Burkhardt Visual Text Analytics for Technology and Innovation Management Miscellaneous Presented at OpenRheinMain Conference (ORM2019), 13 September 2019, Darmstadt, Germany, 2019. Abstract \| Links \| BibTeX \| Tags: Business Analytics, Innovation Management, Technology Management, Text Analysis, Trend Analytics, Visual Text Analytics @misc{Nazemi2019c, title = {Visual Text Analytics for Technology and Innovation Management}, author = {Kawa Nazemi and Dirk Burkhardt}, url = {https://www.openrheinmain.org/2019/presentations/visual_text_analytics_for_technology_and_innovation_management.pdf, Presentation as PDF}, doi = {10.5281/zenodo.3408391}, year = {2019}, date = {2019-09-13}, abstract = {Through coupling of Data Mining, Visual Analytics and Business Analytics techniques, we created a novel solution for strategic market analysis with focus on early trend recognition. As fundament, we are able to consider a variety of text data, as for instance research publications available from a number of (open access) digital libraries, reports and other data from companies, web data about markets as well as news from companies or social media data etc. In an advanced and unified processing pipeline, the information is extracted and mined for a variety of analytical purposes. Via an interactive analysis user-interface, domain experts are able to analysis strong and weak signals in perspective of upcoming trends.}, howpublished = {Presented at OpenRheinMain Conference (ORM2019), 13 September 2019, Darmstadt, Germany}, keywords = {Business Analytics, Innovation Management, Technology Management, Text Analysis, Trend Analytics, Visual Text Analytics}, pubstate = {published}, tppubtype = {misc} } Close Through coupling of Data Mining, Visual Analytics and Business Analytics techniques, we created a novel solution for strategic market analysis with focus on early trend recognition. As fundament, we are able to consider a variety of text data, as for instance research publications available from a number of (open access) digital libraries, reports and other data from companies, web data about markets as well as news from companies or social media data etc. In an advanced and unified processing pipeline, the information is extracted and mined for a variety of analytical purposes. Via an interactive analysis user-interface, domain experts are able to analysis strong and weak signals in perspective of upcoming trends. Close Presentation as PDF doi:10.5281/zenodo.3408391 Close
91.	Kawa Nazemi; Dirk Burkhardt Visual Analytics for Analyzing Technological Trends from Text Inproceedings 2019 23rd International Conference Information Visualisation (IV), pp. 191-200, 2019, ISSN: 2375-0138, (Best Paper Award). Abstract \| Links \| BibTeX \| Tags: Data Mining, Data Models, Data Visualization, emerging trend identification, Hidden Markov models, Information visualization, Market research, Patents, Trend Analytics, Visual analytics, visual business analytics, Visualization @inproceedings{Nazemi2019d, title = {Visual Analytics for Analyzing Technological Trends from Text}, author = {Kawa Nazemi and Dirk Burkhardt}, doi = {10.1109/IV.2019.00041}, issn = {2375-0138}, year = {2019}, date = {2019-07-01}, booktitle = {2019 23rd International Conference Information Visualisation (IV)}, pages = {191-200}, abstract = {The awareness of emerging technologies is essential for strategic decision making in enterprises. Emerging and decreasing technological trends could lead to strengthening the competitiveness and market positioning. The exploration, detection and identification of such trends can be essentially supported through information visualization, trend mining and in particular through the combination of those. Commonly, trends appear first in science and scientific documents. However, those documents do not provide sufficient information for analyzing and identifying emerging trends. It is necessary to enrich data, extract information from the integrated data, measure the gradient of trends over time and provide effective interactive visualizations. We introduce in this paper an approach for integrating, enriching, mining, analyzing, identifying and visualizing emerging trends from scientific documents. Our approach enhances the state of the art in visual trend analytics by investigating the entire analysis process and providing an approach for enabling human to explore undetected potentially emerging trends.}, note = {Best Paper Award}, keywords = {Data Mining, Data Models, Data Visualization, emerging trend identification, Hidden Markov models, Information visualization, Market research, Patents, Trend Analytics, Visual analytics, visual business analytics, Visualization}, pubstate = {published}, tppubtype = {inproceedings} } Close The awareness of emerging technologies is essential for strategic decision making in enterprises. Emerging and decreasing technological trends could lead to strengthening the competitiveness and market positioning. The exploration, detection and identification of such trends can be essentially supported through information visualization, trend mining and in particular through the combination of those. Commonly, trends appear first in science and scientific documents. However, those documents do not provide sufficient information for analyzing and identifying emerging trends. It is necessary to enrich data, extract information from the integrated data, measure the gradient of trends over time and provide effective interactive visualizations. We introduce in this paper an approach for integrating, enriching, mining, analyzing, identifying and visualizing emerging trends from scientific documents. Our approach enhances the state of the art in visual trend analytics by investigating the entire analysis process and providing an approach for enabling human to explore undetected potentially emerging trends. Close doi:10.1109/IV.2019.00041 Close
90.	Kawa Nazemi Visual Trend Analytics in Digital Libraries Miscellaneous Contribution at ASIS&T European Chapter Seminar on Information Science Trends: Search Engines and Information Retrieval., 2019. Abstract \| Links \| BibTeX \| Tags: Information visualization, Trend analysis, Trend Analytics, Visual analytics @misc{Naz19ASIST, title = {Visual Trend Analytics in Digital Libraries}, author = {Kawa Nazemi}, url = {https://zenodo.org/record/3264801#.XSBcMo_gpaR, Zenodo Open Access}, doi = {10.5281/zenodo.3264801}, year = {2019}, date = {2019-04-26}, abstract = {The early awareness of upcoming trends in technology enables a more goal-directed and efficient way for deciding future strategic directions in enterprises and research. Possible sources for this valuable information are ubiquitously and freely available in the Web, e.g. news services, companies’ reports, social media platforms and blog infrastructures. To support users in handling these information sources and to keep track of the newest developments, current information systems make intensively use of information retrieval methods that extract relevant information out of the mass amount of data. The related information systems are commonly focused on providing users with easy access to information of their interest and deal with the access to information items and resources [1], but they neither provide an overview of the content nor enable the exploration of emerging or decreasing trends for inferring possible future innovations. The gathering and analysis of this continuously increasing knowledge pool is a very tedious and time-consuming task and borders on the limits of manual feasibility. The interactive overview on data, the continuous changes in data, and the ability to explore data and gain insights are sufficiently supported by Visual Analytics and information visualization approaches, whereas the appliance of such approach in combination with trend analysis are rarely propagated. In fact, these so-called early signals require not only an analysis through machine learning techniques to identify emerging trends, but also human interaction and intervention to adapt the parameters used to their own needs [2]. There are two main aspects to consider in the analysis process: 1) which data reveal very early trends and 2) how can human be involved in the analysis process [3].}, howpublished = {Contribution at ASIS&T European Chapter Seminar on Information Science Trends: Search Engines and Information Retrieval.}, keywords = {Information visualization, Trend analysis, Trend Analytics, Visual analytics}, pubstate = {published}, tppubtype = {misc} } Close The early awareness of upcoming trends in technology enables a more goal-directed and efficient way for deciding future strategic directions in enterprises and research. Possible sources for this valuable information are ubiquitously and freely available in the Web, e.g. news services, companies’ reports, social media platforms and blog infrastructures. To support users in handling these information sources and to keep track of the newest developments, current information systems make intensively use of information retrieval methods that extract relevant information out of the mass amount of data. The related information systems are commonly focused on providing users with easy access to information of their interest and deal with the access to information items and resources [1], but they neither provide an overview of the content nor enable the exploration of emerging or decreasing trends for inferring possible future innovations. The gathering and analysis of this continuously increasing knowledge pool is a very tedious and time-consuming task and borders on the limits of manual feasibility. The interactive overview on data, the continuous changes in data, and the ability to explore data and gain insights are sufficiently supported by Visual Analytics and information visualization approaches, whereas the appliance of such approach in combination with trend analysis are rarely propagated. In fact, these so-called early signals require not only an analysis through machine learning techniques to identify emerging trends, but also human interaction and intervention to adapt the parameters used to their own needs [2]. There are two main aspects to consider in the analysis process: 1) which data reveal very early trends and 2) how can human be involved in the analysis process [3]. Close Zenodo Open Access doi:10.5281/zenodo.3264801 Close
89.	Udo Bleimann; Dirk Burkhardt; Bernhard Humm; Robert Loew; Stefanie Regier; Ingo Stengel; Paul Walsh (Ed.) Proceedings of the 5th Collaborative European Research Conference (CERC 2019) Proceeding CEUR-WS, Aachen, Vol. 2348 , 2019, ISSN: 1613-0073, (urn:nbn:de:0074-2348-5). Abstract \| Links \| BibTeX \| Tags: @proceedings{CERC2019, title = {Proceedings of the 5th Collaborative European Research Conference (CERC 2019)}, editor = {Udo Bleimann and Dirk Burkhardt and Bernhard Humm and Robert Loew and Stefanie Regier and Ingo Stengel and Paul Walsh}, url = {http://ceur-ws.org/Vol-2348/, Proceedings on CEUR-WS}, issn = {1613-0073}, year = {2019}, date = {2019-04-19}, booktitle = {CERC2019 Proceedings}, volume = {Vol. 2348}, publisher = {CEUR-WS}, address = {Aachen}, series = {CEUR Workshop Proceedings}, abstract = {In today's world, which has recently seen fractures and isolation forming among states, international and interdisciplinary collaboration is an increasingly important source of progress. Collaboration is a rich source of innovation and growth. It is the goal of the Collaborative European Research Conference (CERC 2019) to foster collaboration among friends and colleagues across disciplines and nations within Europe. CERC emerged from a long-standing cooperation between the Cork Institute of Technology, Ireland and Hochschule Darmstadt - University of Applied Sciences, Germany. CERC has grown to include more well-established partners in Germany (Hochschule Karlsruhe and Fernuniversität Hagen), United Kingdom, Greece, Spain, Italy, and many more. CERC is truly interdisciplinary, bringing together new and experienced researchers from science, engineering, business, humanities, and the arts. At CERC researchers not only present their findings as published in their research papers. They are also challenged to collaboratively work out joint aspects of their research during conference sessions and informal social events and gatherings. To organize such an event involves the hard work of many people. Thanks go to the international program committee and my fellow program chairs, particularly to Prof Udo Bleimann and Prof Ingo Stengel for supporting me in the review process. Dirk Burkhardt and Dr Robert Loew put a great effort into setting up the website and conference management system and preparing the conference programme and proceedings. Many of my colleagues from Hochschule Darmstadt were invaluable for local organization. Thanks also to Hochschule Darmstadt and the Research Center for Applied Informatics (FZAI) for financial support.}, note = {urn:nbn:de:0074-2348-5}, keywords = {}, pubstate = {published}, tppubtype = {proceedings} } Close In today's world, which has recently seen fractures and isolation forming among states, international and interdisciplinary collaboration is an increasingly important source of progress. Collaboration is a rich source of innovation and growth. It is the goal of the Collaborative European Research Conference (CERC 2019) to foster collaboration among friends and colleagues across disciplines and nations within Europe. CERC emerged from a long-standing cooperation between the Cork Institute of Technology, Ireland and Hochschule Darmstadt - University of Applied Sciences, Germany. CERC has grown to include more well-established partners in Germany (Hochschule Karlsruhe and Fernuniversität Hagen), United Kingdom, Greece, Spain, Italy, and many more. CERC is truly interdisciplinary, bringing together new and experienced researchers from science, engineering, business, humanities, and the arts. At CERC researchers not only present their findings as published in their research papers. They are also challenged to collaboratively work out joint aspects of their research during conference sessions and informal social events and gatherings. To organize such an event involves the hard work of many people. Thanks go to the international program committee and my fellow program chairs, particularly to Prof Udo Bleimann and Prof Ingo Stengel for supporting me in the review process. Dirk Burkhardt and Dr Robert Loew put a great effort into setting up the website and conference management system and preparing the conference programme and proceedings. Many of my colleagues from Hochschule Darmstadt were invaluable for local organization. Thanks also to Hochschule Darmstadt and the Research Center for Applied Informatics (FZAI) for financial support. Close Proceedings on CEUR-WS Close
88.	Kawa Nazemi; Dirk Burkhardt Visual analytical dashboards for comparative analytical tasks – a case study on mobility and transportation Journal Article ICTE in Transportation and Logistics 2018 (ICTE 2018), 149 , pp. 138-150, 2019, ISSN: 1877-0509. Abstract \| Links \| BibTeX \| Tags: Data Analytics, Information visualization, Mobility, Prediction, Transportation, Visual analytics, Visual Interfaces, Visual Tasks @article{Nazemi2019, title = {Visual analytical dashboards for comparative analytical tasks – a case study on mobility and transportation}, author = {Kawa Nazemi and Dirk Burkhardt}, url = {http://www.sciencedirect.com/science/article/pii/S1877050919301243, Link to Publisher}, doi = {10.1016/j.procs.2019.01.117}, issn = {1877-0509}, year = {2019}, date = {2019-01-01}, journal = {ICTE in Transportation and Logistics 2018 (ICTE 2018)}, volume = {149}, pages = {138-150}, series = {Procedia Computer Science}, abstract = {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.}, keywords = {Data Analytics, Information visualization, Mobility, Prediction, Transportation, Visual analytics, Visual Interfaces, Visual Tasks}, pubstate = {published}, tppubtype = {article} } Close 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. Close Link to Publisher doi:10.1016/j.procs.2019.01.117 Close
87.	Dirk Burkhardt; Kawa Nazemi Visual legal analytics – A visual approach to analyze law-conflicts of e-Services for e-Mobility and transportation domain Journal Article ICTE in Transportation and Logistics 2018 (ICTE 2018), 149 , pp. 515-524, 2019, ISSN: 1877-0509. Abstract \| Links \| BibTeX \| Tags: E-Government, e-Mobility Services, e-Transportation Services, Law Visualization, Legal analysis, Semantic Data, Visual analytics @article{Burkhardt2019, title = {Visual legal analytics – A visual approach to analyze law-conflicts of e-Services for e-Mobility and transportation domain}, author = {Dirk Burkhardt and Kawa Nazemi}, url = {http://www.sciencedirect.com/science/article/pii/S1877050919301784, Link to Publisher}, doi = {10.1016/j.procs.2019.01.170}, issn = {1877-0509}, year = {2019}, date = {2019-01-01}, journal = {ICTE in Transportation and Logistics 2018 (ICTE 2018)}, volume = {149}, pages = {515-524}, series = {Procedia Computer Science}, abstract = {The impact of the electromobility has next to the automotive industry also an increasing impact on the transportation and logistics domain. In particular the today’s starting switches to electronic trucks/scooter lead to massive changes in the organization and planning in this field. Public funding or tax reduction for environment friendly solutions forces also the growth of new mobility and transportation services. However, the vast changes in this domain and the high number of innovations of new technologies and services leads also into a critical legal uncertainty. The clarification of a legal status for a new technology or service can become cost intensive in a dimension that in particular startups could not invest. In this paper we therefore introduce a new approach to identify and analyze legal conflicts based on a business model or plan against existing laws. The intention is that an early awareness of critical legal aspect could enable an early adoption of the planned service to ensure its legality. Our main contribution is distinguished in two parts. Firstly, a new Norm-graph visualization approach to show laws and legal aspects in an easier understandable manner. And secondly, a Visual Legal Analytics approach to analyze legal conflicts e.g. on the basis of a business plans. The Visual Legal Analytics approach aims to provide a visual analysis interface to validate the automatically identified legal conflicts resulting from the pre-processing stage with a graphical overview about the derivation down to the law roots and the option to check the original sources to get further details. At the end analyst can so verify conflicts as relevant and resolve it by advancing e.g. the business plan or as irrelevant. An evaluation performed with lawyers has proofed our approach.}, keywords = {E-Government, e-Mobility Services, e-Transportation Services, Law Visualization, Legal analysis, Semantic Data, Visual analytics}, pubstate = {published}, tppubtype = {article} } Close The impact of the electromobility has next to the automotive industry also an increasing impact on the transportation and logistics domain. In particular the today’s starting switches to electronic trucks/scooter lead to massive changes in the organization and planning in this field. Public funding or tax reduction for environment friendly solutions forces also the growth of new mobility and transportation services. However, the vast changes in this domain and the high number of innovations of new technologies and services leads also into a critical legal uncertainty. The clarification of a legal status for a new technology or service can become cost intensive in a dimension that in particular startups could not invest. In this paper we therefore introduce a new approach to identify and analyze legal conflicts based on a business model or plan against existing laws. The intention is that an early awareness of critical legal aspect could enable an early adoption of the planned service to ensure its legality. Our main contribution is distinguished in two parts. Firstly, a new Norm-graph visualization approach to show laws and legal aspects in an easier understandable manner. And secondly, a Visual Legal Analytics approach to analyze legal conflicts e.g. on the basis of a business plans. The Visual Legal Analytics approach aims to provide a visual analysis interface to validate the automatically identified legal conflicts resulting from the pre-processing stage with a graphical overview about the derivation down to the law roots and the option to check the original sources to get further details. At the end analyst can so verify conflicts as relevant and resolve it by advancing e.g. the business plan or as irrelevant. An evaluation performed with lawyers has proofed our approach. Close Link to Publisher doi:10.1016/j.procs.2019.01.170 Close
2018
86.	Kawa Nazemi; Dirk Burkhardt Juxtaposing Visual Layouts – An Approach for Solving Analytical and Exploratory Tasks through Arranging Visual Interfaces Inproceedings A. G. Bruzzone; Egils Ginters; E. G. Mendívil; J. M. Guitierrez; F. Longo (Ed.): The 4th International Conference of the Virtual and Augmented Reality in Education, I3M, 2018, ISBN: 978-88-85741-21-8. Abstract \| Links \| BibTeX \| Tags: Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, Visual analytics @inproceedings{Nazemi2018b, title = {Juxtaposing Visual Layouts – An Approach for Solving Analytical and Exploratory Tasks through Arranging Visual Interfaces}, author = {Kawa Nazemi and Dirk Burkhardt}, editor = {A. G. Bruzzone and Egils Ginters and E. G. Mendívil and J. M. Guitierrez and F. Longo}, doi = {10.5281/zenodo.2542952}, isbn = {978-88-85741-21-8}, year = {2018}, date = {2018-09-18}, booktitle = {The 4th International Conference of the Virtual and Augmented Reality in Education}, publisher = {I3M}, abstract = {Interactive visualization and visual analytics systems enables solving a variety of tasks. Starting with simple search tasks for outliers, anomalies etc. in data to analytical comparisons, information visualizations may lead to a faster and more precise solving of tasks. There exist a variety of methods to support users in the process of task solving, e.g. superimposing, juxtaposing or partitioning complex visual structures. Commonly all these methods make use of a single data source that is visualized at the same time. We propose in this paper an approach that goes beyond the established methods 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 interfaces to enable solving complex tasks.}, keywords = {Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, Visual analytics}, pubstate = {published}, tppubtype = {inproceedings} } Close Interactive visualization and visual analytics systems enables solving a variety of tasks. Starting with simple search tasks for outliers, anomalies etc. in data to analytical comparisons, information visualizations may lead to a faster and more precise solving of tasks. There exist a variety of methods to support users in the process of task solving, e.g. superimposing, juxtaposing or partitioning complex visual structures. Commonly all these methods make use of a single data source that is visualized at the same time. We propose in this paper an approach that goes beyond the established methods 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 interfaces to enable solving complex tasks. Close doi:10.5281/zenodo.2542952 Close
85.	Dirk Burkhardt; Kawa Nazemi Visualizing Law - A Norm-Graph Visualization Approach based on Semantic Legal Data Inproceedings The 4th International Conference of the Virtual and Augmented Reality in Education, I3M, 2018, ISBN: 978-88-85741-21-8. Abstract \| Links \| BibTeX \| Tags: Human Factors, Human-computer interaction (HCI), Information visualization, Semantics visualization, Visual analytics @inproceedings{Burkhardt2018, title = {Visualizing Law - A Norm-Graph Visualization Approach based on Semantic Legal Data}, author = {Dirk Burkhardt and Kawa Nazemi}, doi = {10.5281/zenodo.2543729}, isbn = {978-88-85741-21-8}, year = {2018}, date = {2018-09-16}, booktitle = {The 4th International Conference of the Virtual and Augmented Reality in Education}, publisher = {I3M}, abstract = {Laws or in general legal documents regulate a wide range of our daily life and also define the borders of business models and commercial services. However, legal text and laws are almost hard to understand. From other domains it is already known that visualizations can help understanding complex aspects easier. In fact, in this paper we introduce a new approach to visualize legal texts in a Norm-graph visualization. In the developed Norm-graph visualization it is possible to show major aspects of laws and make it easier for users to understand it. The Norm-graph is based on semantic legal data, a so called Legal-Concept-Ontology.}, keywords = {Human Factors, Human-computer interaction (HCI), Information visualization, Semantics visualization, Visual analytics}, pubstate = {published}, tppubtype = {inproceedings} } Close Laws or in general legal documents regulate a wide range of our daily life and also define the borders of business models and commercial services. However, legal text and laws are almost hard to understand. From other domains it is already known that visualizations can help understanding complex aspects easier. In fact, in this paper we introduce a new approach to visualize legal texts in a Norm-graph visualization. In the developed Norm-graph visualization it is possible to show major aspects of laws and make it easier for users to understand it. The Norm-graph is based on semantic legal data, a so called Legal-Concept-Ontology. Close doi:10.5281/zenodo.2543729 Close
84.	Tilman Deuschel On the Influence of Human Factors in Adaptive User Interface Design Inproceedings Adjunct Publication of the 26th Conference on User Modeling, Adaptation and Personalization, pp. 187–190, ACM, Singapore, Singapore, 2018, ISBN: 978-1-4503-5784-5. Abstract \| Links \| BibTeX \| Tags: Adaptive User Interfaces, design principles, empirical evaluation @inproceedings{Deuschel2018, title = {On the Influence of Human Factors in Adaptive User Interface Design}, author = {Tilman Deuschel}, doi = {10.1145/3213586.3213587}, isbn = {978-1-4503-5784-5}, year = {2018}, date = {2018-07-08}, booktitle = {Adjunct Publication of the 26th Conference on User Modeling, Adaptation and Personalization}, pages = {187--190}, publisher = {ACM}, address = {Singapore, Singapore}, series = {UMAP '18}, abstract = {The increased utilisation of adaptive visualisation techniques in commercial software requires design principles that provide guidance on how to design user interfaces that change their appearance during runtime. To contribute to the ongoing adaptive user interface (AUI) research, the development of a model is proposed that enables the methodological development of design principles for AUIs. The adoption of the conceptual framework of design-science is proposed for that purpose. Following the framework, the literature of AUI research (to identify observed user behaviour) as well as the literature of human factors (to explain the observed behaviour) have been reviewed. Design principles are built based on this knowledge. This thesis can contribute to an quality improvement of AUI systems.}, keywords = {Adaptive User Interfaces, design principles, empirical evaluation}, pubstate = {published}, tppubtype = {inproceedings} } Close The increased utilisation of adaptive visualisation techniques in commercial software requires design principles that provide guidance on how to design user interfaces that change their appearance during runtime. To contribute to the ongoing adaptive user interface (AUI) research, the development of a model is proposed that enables the methodological development of design principles for AUIs. The adoption of the conceptual framework of design-science is proposed for that purpose. Following the framework, the literature of AUI research (to identify observed user behaviour) as well as the literature of human factors (to explain the observed behaviour) have been reviewed. Design principles are built based on this knowledge. This thesis can contribute to an quality improvement of AUI systems. Close doi:10.1145/3213586.3213587 Close
83.	Kawa Nazemi Intelligent Visual Analytics - A Human-Adaptive Approach for Complex and Analytical Tasks Book Chapter W Karwowski; T Ahram (Ed.): Intelligent Human Systems Integration: Proceedings of the International Conference on Intelligent Human Systems Integration (IHSI 2018): Integrating People and Intelligent Systems. Advances in Intelligent Systems and Computing (AISC 722), pp. 180–190, Springer International Publishing, Cham, 2018, ISBN: 978-3-319-73888-8. Abstract \| Links \| BibTeX \| Tags: Adaptive Visualization, Human Factors, Intelligent Systems @inbook{Nazemi2018, title = {Intelligent Visual Analytics - A Human-Adaptive Approach for Complex and Analytical Tasks}, author = {Kawa Nazemi}, editor = {W Karwowski and T Ahram}, url = {https://doi.org/10.1007/978-3-319-73888-8_29}, doi = {10.1007/978-3-319-73888-8_29}, isbn = {978-3-319-73888-8}, year = {2018}, date = {2018-01-01}, booktitle = {Intelligent Human Systems Integration: Proceedings of the International Conference on Intelligent Human Systems Integration (IHSI 2018): Integrating People and Intelligent Systems. Advances in Intelligent Systems and Computing (AISC 722)}, pages = {180--190}, publisher = {Springer International Publishing}, address = {Cham}, abstract = {Visual Analytics enables solving complex and analytical tasks by combining automated data analytics methods and interactive visualizations. The complexity of tasks, the huge amount of data and the complex visual representation may overstrain the users of such systems. Intelligent and adaptive visualizations system show already promising results to bridge the gap between human and the complex visualization. We introduce in this paper a revised version of layer-based visual adaptation model that considers the human perception and cognition abilities. The model is then used to enhance the most popular Visual Analytics model to enable the development of Intelligent Visual Analytics systems.}, keywords = {Adaptive Visualization, Human Factors, Intelligent Systems}, pubstate = {published}, tppubtype = {inbook} } Close Visual Analytics enables solving complex and analytical tasks by combining automated data analytics methods and interactive visualizations. The complexity of tasks, the huge amount of data and the complex visual representation may overstrain the users of such systems. Intelligent and adaptive visualizations system show already promising results to bridge the gap between human and the complex visualization. We introduce in this paper a revised version of layer-based visual adaptation model that considers the human perception and cognition abilities. The model is then used to enhance the most popular Visual Analytics model to enable the development of Intelligent Visual Analytics systems. Close https://doi.org/10.1007/978-3-319-73888-8_29 doi:10.1007/978-3-319-73888-8_29 Close
2017
82.	Dirk Burkhardt; Sachin Pattan; Kawa Nazemi; Arjan Kuijper Search Intention Analysis for Task- and User-Centered Visualization in Big Data Applications Journal Article Procedia Computer Science, 104 , pp. 539 - 547, 2017, ISSN: 1877-0509, (ICTE 2016, Riga Technical University, Latvia). Abstract \| Links \| BibTeX \| Tags: Information visualization, Intelligent Systems, User behavior, User Interactions, User Interface, User-centered design, Visual analytics @article{Burkhardt2017c, title = {Search Intention Analysis for Task- and User-Centered Visualization in Big Data Applications}, author = {Dirk Burkhardt and Sachin Pattan and Kawa Nazemi and Arjan Kuijper}, url = {http://www.sciencedirect.com/science/article/pii/S1877050917301710, Elsevier Science Direct https://www.sciencedirect.com/science/article/pii/S1877050917301710/pdf?md5=505e85e86e138c532368faf70d2ab1e2&pid=1-s2.0-S1877050917301710-main.pdf, full text}, doi = {https://doi.org/10.1016/j.procs.2017.01.170}, issn = {1877-0509}, year = {2017}, date = {2017-12-01}, journal = {Procedia Computer Science}, volume = {104}, pages = {539 - 547}, abstract = {A new approach for classifying users’ search intentions is described in this paper. The approach uses the parameters: word frequency, query length and entity matching for distinguishing the user's query into exploratory, targeted and analysis search. The approach focuses mainly on word frequency analysis, where different sources for word frequency data are considered such as the Wortschatz frequency service by the University of Leipzig and the Microsoft Ngram service (now part of the Microsoft Cognitive Services). The model is evaluated with the help of a survey tool and few machine learning techniques. The survey was conducted with more than one hundred users and on evaluating the model with the collected data, the results are satisfactory. In big data applications the search intention analysis can be used to identify the purpose of a performed search, to provide an optimal initially set of visualizations that respects the intended task of the user to work with the result data.}, note = {ICTE 2016, Riga Technical University, Latvia}, keywords = {Information visualization, Intelligent Systems, User behavior, User Interactions, User Interface, User-centered design, Visual analytics}, pubstate = {published}, tppubtype = {article} } Close A new approach for classifying users’ search intentions is described in this paper. The approach uses the parameters: word frequency, query length and entity matching for distinguishing the user's query into exploratory, targeted and analysis search. The approach focuses mainly on word frequency analysis, where different sources for word frequency data are considered such as the Wortschatz frequency service by the University of Leipzig and the Microsoft Ngram service (now part of the Microsoft Cognitive Services). The model is evaluated with the help of a survey tool and few machine learning techniques. The survey was conducted with more than one hundred users and on evaluating the model with the collected data, the results are satisfactory. In big data applications the search intention analysis can be used to identify the purpose of a performed search, to provide an optimal initially set of visualizations that respects the intended task of the user to work with the result data. Close Elsevier Science Direct full text doi:https://doi.org/10.1016/j.procs.2017.01.170 Close
81.	Dirk Burkhardt; Kawa Nazemi Informationsvisualisierung und Visual Analytics zur Unterstützung von E-Government Prozessen Inproceedings Korinna Bade; Matthias Pietsch; Susanne Raabe; Lars Schütz (Ed.): Technologische Trends im Spannungsfeld von Beteiligung – Entscheidung – Planung, pp. 29–38, Shaker Verlag, Aachen, Germany, 2017, ISBN: 978-3844054392. Abstract \| Links \| BibTeX \| Tags: eGovernance, Information visualization, Visual analytics @inproceedings{Burkhardt2017b, title = {Informationsvisualisierung und Visual Analytics zur Unterstützung von E-Government Prozessen}, author = {Dirk Burkhardt and Kawa Nazemi}, editor = {Korinna Bade and Matthias Pietsch and Susanne Raabe and Lars Schütz}, url = {https://www.shaker.de/de/content/catalogue/index.asp?lang=de&ID=8&ISBN=978-3-8440-5439-2&search=yes, Publisher Site https://dx.doi.org/10.2370/9783844054392, doi:10.2370/9783844054392 (Full Proceedings)}, doi = {10.5281/zenodo.2576074}, isbn = {978-3844054392}, year = {2017}, date = {2017-01-05}, booktitle = {Technologische Trends im Spannungsfeld von Beteiligung – Entscheidung – Planung}, pages = {29--38}, publisher = {Shaker Verlag}, address = {Aachen, Germany}, abstract = {Politische und gesellschaftliche Prozesse werden durch Informationen sehr stark geprägt, wie auch die jüngsten Ereignisse aufzeigen. Diese Informationen können, trotz enormer Fortschritte, nicht immer aus den sehr großen, heterogenen und verteilten Daten entnommen werden. „Big Data“ stellt somit auch in der öffentlichen Verwaltung eine immer größere Herausforderung dar. Sowohl durch eine umfangreiche Erhebung von Statistiken, als auch durch Dokumente wie Berichte und Studien, wachsen in Behörden die zu bewältigenden Informationsaufgaben. Darüber hinaus spielt die Berücksichtigung von Bürgermeinungen, vor allem auf kommunaler Ebene, eine immer größere Rolle. Eine Auswertung ohne moderne Informationstechnik ist dabei kaum mehr möglich. Damit aber aus diesen Daten tatsächlich die relevanten Informationen extrahiert werden, bedarf es Informationsvisualisierung und Visual Analytics Systeme die sehr detaillierte, aber dennoch einfache und schnelle Analysen für den Menschen erlauben. Dies stellt aber sehr hohe Anforderungen an die visuellen Systeme, da sie gleichzeitig auch den Nutzer und dessen Fähigkeiten berücksichtigen müssen.}, keywords = {eGovernance, Information visualization, Visual analytics}, pubstate = {published}, tppubtype = {inproceedings} } Close Politische und gesellschaftliche Prozesse werden durch Informationen sehr stark geprägt, wie auch die jüngsten Ereignisse aufzeigen. Diese Informationen können, trotz enormer Fortschritte, nicht immer aus den sehr großen, heterogenen und verteilten Daten entnommen werden. „Big Data“ stellt somit auch in der öffentlichen Verwaltung eine immer größere Herausforderung dar. Sowohl durch eine umfangreiche Erhebung von Statistiken, als auch durch Dokumente wie Berichte und Studien, wachsen in Behörden die zu bewältigenden Informationsaufgaben. Darüber hinaus spielt die Berücksichtigung von Bürgermeinungen, vor allem auf kommunaler Ebene, eine immer größere Rolle. Eine Auswertung ohne moderne Informationstechnik ist dabei kaum mehr möglich. Damit aber aus diesen Daten tatsächlich die relevanten Informationen extrahiert werden, bedarf es Informationsvisualisierung und Visual Analytics Systeme die sehr detaillierte, aber dennoch einfache und schnelle Analysen für den Menschen erlauben. Dies stellt aber sehr hohe Anforderungen an die visuellen Systeme, da sie gleichzeitig auch den Nutzer und dessen Fähigkeiten berücksichtigen müssen. Close Publisher Site doi:10.2370/9783844054392 (Full Proceedings) doi:10.5281/zenodo.2576074 Close
80.	Kawa Nazemi; Dirk Burkhardt; Arjan Kuijper Analyzing the Information Search Behavior and Intentions in Visual Information Systems Journal Article Journal of Computer Science Technology Updates, 4 , 2017. Abstract \| Links \| BibTeX \| Tags: Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, User behavior, User Interactions, User Interface, User modeling, User-centered design, Visual analytics @article{Nazemi2017, title = {Analyzing the Information Search Behavior and Intentions in Visual Information Systems}, author = {Kawa Nazemi and Dirk Burkhardt and Arjan Kuijper}, url = {https://www.cosmosscholars.com/images/JCSTU/JCSTU-V4N2A2-Nazemi.pdf, full text}, doi = {10.15379/2410-2938.2017.04.02.02}, year = {2017}, date = {2017-01-01}, journal = {Journal of Computer Science Technology Updates}, volume = {4}, abstract = {Visual information search systems support different search approaches such as targeted, exploratory or analytical search. Those visual systems deal with the challenge of composing optimal initial result visualization sets that face the search intention and respond to the search behavior of users. The diversity of these kinds of search tasks require different sets of visual layouts and functionalities, e.g. to filter, thrill-down or even analyze concrete data properties. This paper describes a new approach to calculate the probability towards the three mentioned search intentions, derived from users’ behavior. The implementation is realized as a web-service, which is included in a visual environment that is designed to enable various search strategies based on heterogeneous data sources. In fact, based on an entered search query our developed search intention analysis web-service calculates the most probable search task, and our visualization system initially shows the optimal result set of visualizations to solve the task. The main contribution of this paper is a probability-based approach to derive the users’ search intentions based on the search behavior enhanced by the application to a visual system.}, keywords = {Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, User behavior, User Interactions, User Interface, User modeling, User-centered design, Visual analytics}, pubstate = {published}, tppubtype = {article} } Close Visual information search systems support different search approaches such as targeted, exploratory or analytical search. Those visual systems deal with the challenge of composing optimal initial result visualization sets that face the search intention and respond to the search behavior of users. The diversity of these kinds of search tasks require different sets of visual layouts and functionalities, e.g. to filter, thrill-down or even analyze concrete data properties. This paper describes a new approach to calculate the probability towards the three mentioned search intentions, derived from users’ behavior. The implementation is realized as a web-service, which is included in a visual environment that is designed to enable various search strategies based on heterogeneous data sources. In fact, based on an entered search query our developed search intention analysis web-service calculates the most probable search task, and our visualization system initially shows the optimal result set of visualizations to solve the task. The main contribution of this paper is a probability-based approach to derive the users’ search intentions based on the search behavior enhanced by the application to a visual system. Close full text doi:10.15379/2410-2938.2017.04.02.02 Close

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