Publications - Deutsch - Human-Computer Interaction & Visual Analytics Reasearch Department (vis) at Darmstadt University of Applied Sciences (h

Publikationen

2021
16.	Kawa Nazemi; Dirk Burkhardt; Alexander Kock Visual analytics for technology and innovation management: An interaction approach for strategic decisionmaking Artikel In: Multimedia Tools and Applications, Bd. 1198, 2021, ISSN: 1573-7721. Abstract \| Links \| BibTeX \| Schlagwörter: emerging trend identification, Information visualization, Innovation Management, Interaction Design, Multimodal Interaction, Technology Management, Visual analytics, Visual Trend Analytics @article{Nazemi2021b, title = {Visual analytics for technology and innovation management: An interaction approach for strategic decisionmaking }, author = {Kawa Nazemi and Dirk Burkhardt and Alexander Kock}, editor = {Rita Francese and Borko Furht}, doi = {10.1007/s11042-021-10972-3}, issn = {1573-7721}, year = {2021}, date = {2021-05-20}, journal = {Multimedia Tools and Applications}, volume = {1198}, abstract = {The awareness of emerging trends is essential for strategic decision making because technological trends can affect a firm’s competitiveness and market position. The rise of artificial intelligence methods allows gathering new insights and may support these decision-making processes. However, it is essential to keep the human in the loop of these complex analytical tasks, which, often lack an appropriate interaction design. Including special interactive designs for technology and innovation management is therefore essential for successfully analyzing emerging trends and using this information for strategic decision making. A combination of information visualization, trend mining and interaction design can support human users to explore, detect, and identify such trends. This paper enhances and extends a previously published first approach for integrating, enriching, mining, analyzing, identifying, and visualizing emerging trends for technology and innovation management. We introduce a novel interaction design by investigating the main ideas from technology and innovation management and enable a more appropriate interaction approach for technology foresight and innovation detection.}, keywords = {emerging trend identification, Information visualization, Innovation Management, Interaction Design, Multimodal Interaction, Technology Management, Visual analytics, Visual Trend Analytics}, pubstate = {published}, tppubtype = {article} } Schließen The awareness of emerging trends is essential for strategic decision making because technological trends can affect a firm’s competitiveness and market position. The rise of artificial intelligence methods allows gathering new insights and may support these decision-making processes. However, it is essential to keep the human in the loop of these complex analytical tasks, which, often lack an appropriate interaction design. Including special interactive designs for technology and innovation management is therefore essential for successfully analyzing emerging trends and using this information for strategic decision making. A combination of information visualization, trend mining and interaction design can support human users to explore, detect, and identify such trends. This paper enhances and extends a previously published first approach for integrating, enriching, mining, analyzing, identifying, and visualizing emerging trends for technology and innovation management. We introduce a novel interaction design by investigating the main ideas from technology and innovation management and enable a more appropriate interaction approach for technology foresight and innovation detection. Schließen doi:10.1007/s11042-021-10972-3 Schließen
2014
15.	Kawa Nazemi Adaptive Semantics Visualization Promotionsarbeit Technische Universität Darmstadt, 2014, (Reprint by Eugraphics Association (EG)). Abstract \| Links \| BibTeX \| Schlagwörter: Adaptive Information Visualization, Adaptive User Interfaces, Adaptive Visualization, Computer Based Learning, Data Analytics, E-Learning, Exploratory learning, Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, Intelligent Systems, Interaction analysis, Interaction Design, Ontology visualization, personalization, Policy modeling, reference model, Semantic data modeling, Semantic visualization, Semantic web, Semantics visualization, User behavior, User Interactions, User Interface, User modeling, User-centered design, Visual analytics @phdthesis{Nazemi2014f, title = {Adaptive Semantics Visualization}, author = {Kawa Nazemi}, url = {https://diglib.eg.org/handle/10.2312/12076, EG Lib https://diglib.eg.org/bitstream/handle/10.2312/12076/nazemi.pdf, full text}, doi = {10.2312/12076}, year = {2014}, date = {2014-11-27}, school = {Technische Universität Darmstadt}, abstract = {Human access to the increasing amount of information and data plays an essential role for the professional level and also for everyday life. While information visualization has developed new and remarkable ways for visualizing data and enabling the exploration process, adaptive systems focus on users' behavior to tailor information for supporting the information acquisition process. Recent research on adaptive visualization shows promising ways of synthesizing these two complementary approaches and make use of the surpluses of both disciplines. The emerged methods and systems aim to increase the performance, acceptance, and user experience of graphical data representations for a broad range of users. Although the evaluation results of the recently proposed systems are promising, some important aspects of information visualization are not considered in the adaptation process. The visual adaptation is commonly limited to change either visual parameters or replace visualizations entirely. Further, no existing approach adapts the visualization based on data and user characteristics. Other limitations of existing approaches include the fact that the visualizations require training by experts in the field. In this thesis, we introduce a novel model for adaptive visualization. In contrast to existing approaches, we have focused our investigation on the potentials of information visualization for adaptation. Our reference model for visual adaptation not only considers the entire transformation, from data to visual representation, but also enhances it to meet the requirements for visual adaptation. Our model adapts different visual layers that were identified based on various models and studies on human visual perception and information processing. In its adaptation process, our conceptual model considers the impact of both data and user on visualization adaptation. We investigate different approaches and models and their effects on system adaptation to gather implicit information about users and their behavior. These are than transformed and applied to affect the visual representation and model human interaction behavior with visualizations and data to achieve a more appropriate visual adaptation. Our enhanced user model further makes use of the semantic hierarchy to enable a domain-independent adaptation. To face the problem of a system that requires to be trained by experts, we introduce the canonical user model that models the average usage behavior with the visualization environment. Our approach learns from the behavior of the average user to adapt the different visual layers and transformation steps. This approach is further enhanced with similarity and deviation analysis for individual users to determine similar behavior on an individual level and identify differing behavior from the canonical model. Users with similar behavior get similar visualization and data recommendations, while behavioral anomalies lead to a lower level of adaptation. Our model includes a set of various visual layouts that can be used to compose a multi-visualization interface, a sort of "visualization cockpit". This model facilitates various visual layouts to provide different perspectives and enhance the ability to solve difficult and exploratory search challenges. Data from different data-sources can be visualized and compared in a visual manner. These different visual perspectives on data can be chosen by users or can be automatically selected by the system. This thesis further introduces the implementation of our model that includes additional approaches for an efficient adaptation of visualizations as proof of feasibility. We further conduct a comprehensive user study that aims to prove the benefits of our model and underscore limitations for future work. The user study with overall 53 participants focuses with its four conditions on our enhanced reference model to evaluate the adaptation effects of the different visual layers.}, note = {Reprint by Eugraphics Association (EG)}, keywords = {Adaptive Information Visualization, Adaptive User Interfaces, Adaptive Visualization, Computer Based Learning, Data Analytics, E-Learning, Exploratory learning, Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, Intelligent Systems, Interaction analysis, Interaction Design, Ontology visualization, personalization, Policy modeling, reference model, Semantic data modeling, Semantic visualization, Semantic web, Semantics visualization, User behavior, User Interactions, User Interface, User modeling, User-centered design, Visual analytics}, pubstate = {published}, tppubtype = {phdthesis} } Schließen Human access to the increasing amount of information and data plays an essential role for the professional level and also for everyday life. While information visualization has developed new and remarkable ways for visualizing data and enabling the exploration process, adaptive systems focus on users' behavior to tailor information for supporting the information acquisition process. Recent research on adaptive visualization shows promising ways of synthesizing these two complementary approaches and make use of the surpluses of both disciplines. The emerged methods and systems aim to increase the performance, acceptance, and user experience of graphical data representations for a broad range of users. Although the evaluation results of the recently proposed systems are promising, some important aspects of information visualization are not considered in the adaptation process. The visual adaptation is commonly limited to change either visual parameters or replace visualizations entirely. Further, no existing approach adapts the visualization based on data and user characteristics. Other limitations of existing approaches include the fact that the visualizations require training by experts in the field. In this thesis, we introduce a novel model for adaptive visualization. In contrast to existing approaches, we have focused our investigation on the potentials of information visualization for adaptation. Our reference model for visual adaptation not only considers the entire transformation, from data to visual representation, but also enhances it to meet the requirements for visual adaptation. Our model adapts different visual layers that were identified based on various models and studies on human visual perception and information processing. In its adaptation process, our conceptual model considers the impact of both data and user on visualization adaptation. We investigate different approaches and models and their effects on system adaptation to gather implicit information about users and their behavior. These are than transformed and applied to affect the visual representation and model human interaction behavior with visualizations and data to achieve a more appropriate visual adaptation. Our enhanced user model further makes use of the semantic hierarchy to enable a domain-independent adaptation. To face the problem of a system that requires to be trained by experts, we introduce the canonical user model that models the average usage behavior with the visualization environment. Our approach learns from the behavior of the average user to adapt the different visual layers and transformation steps. This approach is further enhanced with similarity and deviation analysis for individual users to determine similar behavior on an individual level and identify differing behavior from the canonical model. Users with similar behavior get similar visualization and data recommendations, while behavioral anomalies lead to a lower level of adaptation. Our model includes a set of various visual layouts that can be used to compose a multi-visualization interface, a sort of "visualization cockpit". This model facilitates various visual layouts to provide different perspectives and enhance the ability to solve difficult and exploratory search challenges. Data from different data-sources can be visualized and compared in a visual manner. These different visual perspectives on data can be chosen by users or can be automatically selected by the system. This thesis further introduces the implementation of our model that includes additional approaches for an efficient adaptation of visualizations as proof of feasibility. We further conduct a comprehensive user study that aims to prove the benefits of our model and underscore limitations for future work. The user study with overall 53 participants focuses with its four conditions on our enhanced reference model to evaluate the adaptation effects of the different visual layers. Schließen EG Lib full text doi:10.2312/12076 Schließen
14.	Kawa Nazemi Adaptive Semantics Visualization Promotionsarbeit Technische Universität Darmstadt, 2014, (Department of Computer Science. Supervised by Dieter W. Fellner.). Abstract \| Links \| BibTeX \| Schlagwörter: Adaptive Information Visualization, Adaptive User Interfaces, Computer Based Learning, Data Analytics, eGovernance, Exploratory learning, Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, Intelligent Systems, Interaction Design, Ontology visualization, personalization, Policy modeling, Semantic data modeling, Semantic visualization, Semantic web, User behavior, User Interactions, User Interface, User modeling, User-centered design, Visual analytics @phdthesis{Nazemi2014g, title = {Adaptive Semantics Visualization}, author = {Kawa Nazemi}, url = {http://tuprints.ulb.tu-darmstadt.de/id/eprint/4319, TU Darmstadt Prints http://tuprints.ulb.tu-darmstadt.de/4319/1/Nazemi_Diss.pdf, full text}, year = {2014}, date = {2014-11-23}, address = {Darmstadt, Germany}, school = {Technische Universität Darmstadt}, abstract = {Human access to the increasing amount of information and data plays an essential role for the professional level and also for everyday life. While information visualization has developed new and remarkable ways for visualizing data and enabling the exploration process, adaptive systems focus on users’ behavior to tailor information for supporting the information acquisition process. Recent research on adaptive visualization shows promising ways of synthesizing these two complementary approaches and make use of the surpluses of both disciplines. The emerged methods and systems aim to increase the performance, acceptance, and user experience of graphical data representations for a broad range of users. Although the evaluation results of the recently proposed systems are promising, some important aspects of information visualization are not considered in the adaptation process. The visual adaptation is commonly limited to change either visual parameters or replace visualizations entirely. Further, no existing approach adapts the visualization based on data and user characteristics. Other limitations of existing approaches include the fact that the visualizations require training by experts in the field. In this thesis, we introduce a novel model for adaptive visualization. In contrast to existing approaches, we have focused our investigation on the potentials of information visualization for adaptation. Our reference model for visual adaptation not only considers the entire transformation, from data to visual representation, but also enhances it to meet the requirements for visual adaptation. Our model adapts different visual layers that were identified based on various models and studies on human visual perception and information processing. In its adaptation process, our conceptual model considers the impact of both data and user on visualization adaptation. We investigate different approaches and models and their effects on system adaptation to gather implicit information about users and their behavior. These are than transformed and applied to affect the visual representation and model human interaction behavior with visualizations and data to achieve a more appropriate visual adaptation. Our enhanced user model further makes use of the semantic hierarchy to enable a domain-independent adaptation. To face the problem of a system that requires to be trained by experts, we introduce the canonical user model that models the average usage behavior with the visualization environment. Our approach learns from the behavior of the average user to adapt the different visual layers and transformation steps. This approach is further enhanced with similarity and deviation analysis for individual users to determine similar behavior on an individual level and identify differing behavior from the canonical model. Users with similar behavior get similar visualization and data recommendations, while behavioral anomalies lead to a lower level of adaptation. Our model includes a set of various visual layouts that can be used to compose a multi-visualization interface, a sort of "‘visualization cockpit"’. This model facilitates various visual layouts to provide different perspectives and enhance the ability to solve difficult and exploratory search challenges. Data from different data-sources can be visualized and compared in a visual manner. These different visual perspectives on data can be chosen by users or can be automatically selected by the system. This thesis further introduces the implementation of our model that includes additional approaches for an efficient adaptation of visualizations as proof of feasibility. We further conduct a comprehensive user study that aims to prove the benefits of our model and underscore limitations for future work. The user study with overall 53 participants focuses with its four conditions on our enhanced reference model to evaluate the adaptation effects of the different visual layers.}, note = {Department of Computer Science. Supervised by Dieter W. Fellner.}, keywords = {Adaptive Information Visualization, Adaptive User Interfaces, Computer Based Learning, Data Analytics, eGovernance, Exploratory learning, Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, Intelligent Systems, Interaction Design, Ontology visualization, personalization, Policy modeling, Semantic data modeling, Semantic visualization, Semantic web, User behavior, User Interactions, User Interface, User modeling, User-centered design, Visual analytics}, pubstate = {published}, tppubtype = {phdthesis} } Schließen Human access to the increasing amount of information and data plays an essential role for the professional level and also for everyday life. While information visualization has developed new and remarkable ways for visualizing data and enabling the exploration process, adaptive systems focus on users’ behavior to tailor information for supporting the information acquisition process. Recent research on adaptive visualization shows promising ways of synthesizing these two complementary approaches and make use of the surpluses of both disciplines. The emerged methods and systems aim to increase the performance, acceptance, and user experience of graphical data representations for a broad range of users. Although the evaluation results of the recently proposed systems are promising, some important aspects of information visualization are not considered in the adaptation process. The visual adaptation is commonly limited to change either visual parameters or replace visualizations entirely. Further, no existing approach adapts the visualization based on data and user characteristics. Other limitations of existing approaches include the fact that the visualizations require training by experts in the field. In this thesis, we introduce a novel model for adaptive visualization. In contrast to existing approaches, we have focused our investigation on the potentials of information visualization for adaptation. Our reference model for visual adaptation not only considers the entire transformation, from data to visual representation, but also enhances it to meet the requirements for visual adaptation. Our model adapts different visual layers that were identified based on various models and studies on human visual perception and information processing. In its adaptation process, our conceptual model considers the impact of both data and user on visualization adaptation. We investigate different approaches and models and their effects on system adaptation to gather implicit information about users and their behavior. These are than transformed and applied to affect the visual representation and model human interaction behavior with visualizations and data to achieve a more appropriate visual adaptation. Our enhanced user model further makes use of the semantic hierarchy to enable a domain-independent adaptation. To face the problem of a system that requires to be trained by experts, we introduce the canonical user model that models the average usage behavior with the visualization environment. Our approach learns from the behavior of the average user to adapt the different visual layers and transformation steps. This approach is further enhanced with similarity and deviation analysis for individual users to determine similar behavior on an individual level and identify differing behavior from the canonical model. Users with similar behavior get similar visualization and data recommendations, while behavioral anomalies lead to a lower level of adaptation. Our model includes a set of various visual layouts that can be used to compose a multi-visualization interface, a sort of "‘visualization cockpit"’. This model facilitates various visual layouts to provide different perspectives and enhance the ability to solve difficult and exploratory search challenges. Data from different data-sources can be visualized and compared in a visual manner. These different visual perspectives on data can be chosen by users or can be automatically selected by the system. This thesis further introduces the implementation of our model that includes additional approaches for an efficient adaptation of visualizations as proof of feasibility. We further conduct a comprehensive user study that aims to prove the benefits of our model and underscore limitations for future work. The user study with overall 53 participants focuses with its four conditions on our enhanced reference model to evaluate the adaptation effects of the different visual layers. Schließen TU Darmstadt Prints full text Schließen
13.	Peter Sonntagbauer; Kawa Nazemi; Susanne Sonntagbauer; Giorgio Prister; Dirk Burkhardt (Hrsg.) Handbook of Research on Advanced ICT Integration for Governance and Policy Modeling Buch Business Science Reference (IGI Global), Hershey PA, USA, Hershey PA, USA, 2014, ISBN: 978-1-466-66236-0. Abstract \| Links \| BibTeX \| Schlagwörter: Artificial Intelligence, eGovernance, Information visualization, Interaction Design, Machine Leanring, Policy modeling @book{Sonntagbauer2014, title = {Handbook of Research on Advanced ICT Integration for Governance and Policy Modeling}, editor = {Peter Sonntagbauer and Kawa Nazemi and Susanne Sonntagbauer and Giorgio Prister and Dirk Burkhardt}, url = {https://www.igi-global.com/book/handbook-research-advanced-ict-integration/102238, link to publisher}, doi = {10.4018/978-1-4666-6236-0}, isbn = {978-1-466-66236-0}, year = {2014}, date = {2014-06-01}, pages = {508}, publisher = {Business Science Reference (IGI Global), Hershey PA, USA}, address = {Hershey PA, USA}, series = {Handbook of Research}, abstract = {As governments and policy makers take advantage of information and communication technologies, leaders must understand how to navigate the ever-shifting landscape of modern technologies in order to be most effective in enacting change and leading their constituents. The Handbook of Research on Advanced ICT Integration for Governance and Policy Modeling builds on the available literature, research, and recent advances in e-governance to explore advanced methods and applications of digital tools in government. This collection of the latest research in the field presents an essential reference for academics, researchers, and advanced-level students, as well as government leaders, policy makers, and experts in international relations. Reviews and Testimonials Sonntagbauer, Nazemi, Sonntagbauer, Prister, and Burhardt present an essential reference text for advanced students, academics, government leaders, policy makers, experts, and researchers in the field of international relations on the subject of e-governance and the advanced methods and applications of digital tools in government. Utilizing the latest available literature and research into recent advances in the field of e-governance, the text explores citizen engagement, civil service, decision-making strategies, e-participation modeling and a variety of other subjects as they pertain to the overall topic.}, keywords = {Artificial Intelligence, eGovernance, Information visualization, Interaction Design, Machine Leanring, Policy modeling}, pubstate = {published}, tppubtype = {book} } Schließen As governments and policy makers take advantage of information and communication technologies, leaders must understand how to navigate the ever-shifting landscape of modern technologies in order to be most effective in enacting change and leading their constituents. The Handbook of Research on Advanced ICT Integration for Governance and Policy Modeling builds on the available literature, research, and recent advances in e-governance to explore advanced methods and applications of digital tools in government. This collection of the latest research in the field presents an essential reference for academics, researchers, and advanced-level students, as well as government leaders, policy makers, and experts in international relations. Reviews and Testimonials Sonntagbauer, Nazemi, Sonntagbauer, Prister, and Burhardt present an essential reference text for advanced students, academics, government leaders, policy makers, experts, and researchers in the field of international relations on the subject of e-governance and the advanced methods and applications of digital tools in government. Utilizing the latest available literature and research into recent advances in the field of e-governance, the text explores citizen engagement, civil service, decision-making strategies, e-participation modeling and a variety of other subjects as they pertain to the overall topic. Schließen link to publisher doi:10.4018/978-1-4666-6236-0 Schließen
12.	Kawa Nazemi; Dirk Burkhardt; Reimond Retz; Arjan Kuijper; Jörn Kohlhammer Adaptive Visualization of Linked-Data Konferenzbeitrag In: George Bebis; Richard Boyle; Bahram Parvin; Darko Koracin; Ryan McMahan; Jason Jerald; Hui Zhang; Steven M Drucker; Chandra Kambhamettu; Maha El Choubassi; Zhigang Deng; Mark Carlson (Hrsg.): Proceedings of International Symposium on Visual Computing (ISVC 2014). Advances in Visual Computing., S. 872–883, Springer International Publishing, Cham, 2014, ISBN: 978-3-319-14364-4. Abstract \| Links \| BibTeX \| Schlagwörter: Adaptive Information Visualization, Adaptive User Interfaces, Adaptive Visualization, Data Analytics, Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, Intelligent Systems, Interaction analysis, Interaction Design, personalization, reference model, Semantic visualization, Semantic web, User behavior, User modeling, User-centered design, Visual analytics @inproceedings{Nazemi2014b, title = {Adaptive Visualization of Linked-Data}, author = {Kawa Nazemi and Dirk Burkhardt and Reimond Retz and Arjan Kuijper and Jörn Kohlhammer}, editor = {George Bebis and Richard Boyle and Bahram Parvin and Darko Koracin and Ryan McMahan and Jason Jerald and Hui Zhang and Steven M Drucker and Chandra Kambhamettu and Maha El Choubassi and Zhigang Deng and Mark Carlson}, url = {https://link.springer.com/chapter/10.1007/978-3-319-14364-4_84, Springer link}, doi = {10.1007/978-3-319-14364-4_84}, isbn = {978-3-319-14364-4}, year = {2014}, date = {2014-03-01}, booktitle = {Proceedings of International Symposium on Visual Computing (ISVC 2014). Advances in Visual Computing.}, pages = {872--883}, publisher = {Springer International Publishing}, address = {Cham}, series = {LNCS 8888}, abstract = {Adaptive visualizations reduces the required cognitive effort to comprehend interactive visual pictures and amplify cognition. Although the research on adaptive visualizations grew in the last years, the existing approaches do not consider the transformation pipeline from data to visual representation for a more efficient and effective adaptation. Further todays systems commonly require an initial training by experts from the field and are limited to adaptation based either on user behavior or on data characteristics. A combination of both is not proposed to our knowledge. This paper introduces an enhanced instantiation of our previously proposed model that combines both: involving different influencing factors for and adapting various levels of visual peculiarities, on content, visual layout, visual presentation, and visual interface. Based on data type and users’ behavior, our system adapts a set of applicable visualization types. Moreover, retinal variables of each visualization type are adapted to meet individual or canonical requirements on both, data types and users’ behavior. Our system does not require an initial expert modeling.}, keywords = {Adaptive Information Visualization, Adaptive User Interfaces, Adaptive Visualization, Data Analytics, Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, Intelligent Systems, Interaction analysis, Interaction Design, personalization, reference model, Semantic visualization, Semantic web, User behavior, User modeling, User-centered design, Visual analytics}, pubstate = {published}, tppubtype = {inproceedings} } Schließen Adaptive visualizations reduces the required cognitive effort to comprehend interactive visual pictures and amplify cognition. Although the research on adaptive visualizations grew in the last years, the existing approaches do not consider the transformation pipeline from data to visual representation for a more efficient and effective adaptation. Further todays systems commonly require an initial training by experts from the field and are limited to adaptation based either on user behavior or on data characteristics. A combination of both is not proposed to our knowledge. This paper introduces an enhanced instantiation of our previously proposed model that combines both: involving different influencing factors for and adapting various levels of visual peculiarities, on content, visual layout, visual presentation, and visual interface. Based on data type and users’ behavior, our system adapts a set of applicable visualization types. Moreover, retinal variables of each visualization type are adapted to meet individual or canonical requirements on both, data types and users’ behavior. Our system does not require an initial expert modeling. Schließen Springer link doi:10.1007/978-3-319-14364-4_84 Schließen
11.	Dirk Burkhardt; Kawa Nazemi; Wilhelm Retz; Jörn Kohlhammer Visual explanation of government-data for policy making through open-data inclusion Konferenzbeitrag In: The 9th International Conference for Internet Technology and Secured Transactions (ICITST-2014), S. 83-89, IEEE, 2014, ISBN: 978-1-908320-39-1. Abstract \| Links \| BibTeX \| Schlagwörter: eGovernance, Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, Interaction Design, Policy modeling, Semantic visualization, User-centered design @inproceedings{7038782, title = {Visual explanation of government-data for policy making through open-data inclusion}, author = {Dirk Burkhardt and Kawa Nazemi and Wilhelm Retz and Jörn Kohlhammer}, url = {http://ieeexplore.ieee.org/document/7038782/, IEEE Xplore}, doi = {10.1109/ICITST.2014.7038782}, isbn = {978-1-908320-39-1}, year = {2014}, date = {2014-01-01}, booktitle = {The 9th International Conference for Internet Technology and Secured Transactions (ICITST-2014)}, pages = {83-89}, publisher = {IEEE}, abstract = {Commonly, data used in public authorities are statistical data about certain indicator. Such valid kind of data allows an objective observation about indicator developments over time. In case of a significant deviation from the normal indicator level, it is difficult to understand the reasons for upcoming problems. In our paper we present an approach that allows an enhanced information gathering through an improved information overview about the depending aspects to such an indicator by considering governmental data-sources that provide also other types of data than just statistics. Even more, our approach integrates a system that allows generating explanations for Open Government Data, especially to specific indicators, based on Linked-Open Data. This enables decision-makers to get hints for unexpected reasons of concrete problems that may influence an indicator.}, keywords = {eGovernance, Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, Interaction Design, Policy modeling, Semantic visualization, User-centered design}, pubstate = {published}, tppubtype = {inproceedings} } Schließen Commonly, data used in public authorities are statistical data about certain indicator. Such valid kind of data allows an objective observation about indicator developments over time. In case of a significant deviation from the normal indicator level, it is difficult to understand the reasons for upcoming problems. In our paper we present an approach that allows an enhanced information gathering through an improved information overview about the depending aspects to such an indicator by considering governmental data-sources that provide also other types of data than just statistics. Even more, our approach integrates a system that allows generating explanations for Open Government Data, especially to specific indicators, based on Linked-Open Data. This enables decision-makers to get hints for unexpected reasons of concrete problems that may influence an indicator. Schließen IEEE Xplore doi:10.1109/ICITST.2014.7038782 Schließen
10.	Kawa Nazemi; Dirk Burkhardt; Wilhelm Retz; Jörn Kohlhammer Adaptive Visualization of Social Media Data for Policy Modeling Konferenzbeitrag In: George Bebis; Richard Boyle; Bahram Parvin; Darko Koracin; Ryan McMahan; Jason Jerald; Hui Zhang; Steven M Drucker; Chandra Kambhamettu; Maha El Choubassi; Zhigang Deng; Mark Carlson (Hrsg.): Proceeding of the International Symposium on Visual Computing (ISVC 2014). Advances in Visual Computing., S. 333–344, Springer International Publishing, Cham, 2014, ISBN: 978-3-319-14249-4. Abstract \| Links \| BibTeX \| Schlagwörter: Adaptive Information Visualization, Adaptive User Interfaces, Adaptive Visualization, Data Analytics, Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, Intelligent Systems, Interaction analysis, Interaction Design, personalization, Semantic visualization, Semantic web, User behavior, User Interactions, User Interface, User modeling, User-centered design, Visual analytics @inproceedings{Nazemi2014g, title = {Adaptive Visualization of Social Media Data for Policy Modeling}, author = {Kawa Nazemi and Dirk Burkhardt and Wilhelm Retz and Jörn Kohlhammer}, editor = {George Bebis and Richard Boyle and Bahram Parvin and Darko Koracin and Ryan McMahan and Jason Jerald and Hui Zhang and Steven M Drucker and Chandra Kambhamettu and Maha El Choubassi and Zhigang Deng and Mark Carlson}, url = {https://link.springer.com/chapter/10.1007/978-3-319-14249-4_32, Springer link}, doi = {10.1007/978-3-319-14249-4_32}, isbn = {978-3-319-14249-4}, year = {2014}, date = {2014-01-01}, booktitle = {Proceeding of the International Symposium on Visual Computing (ISVC 2014). Advances in Visual Computing.}, pages = {333--344}, publisher = {Springer International Publishing}, address = {Cham}, series = {LNCS 8887}, abstract = {The visual analysis of social media data emerged a huge number of interactive visual representations that use different characteristics of the data to enable the process of information acquisition. The social data are used in the domain of policy modeling to gather information about citizens' demands, opinions, and requirements and help to decide about political policies. Although existing systems already provide a huge number of visual analysis tools, the search and exploration paradigm is not really clear. Furthermore, the systems commonly do not provide any kind of human centered adaptation for the different stakeholders involved in the policy making process. In this paper, we introduce a novel approach that investigates the exploration and search paradigm from two different perspectives and enables a visual adaptation to support the exploration and analysis process.}, keywords = {Adaptive Information Visualization, Adaptive User Interfaces, Adaptive Visualization, Data Analytics, Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, Intelligent Systems, Interaction analysis, Interaction Design, personalization, Semantic visualization, Semantic web, User behavior, User Interactions, User Interface, User modeling, User-centered design, Visual analytics}, pubstate = {published}, tppubtype = {inproceedings} } Schließen The visual analysis of social media data emerged a huge number of interactive visual representations that use different characteristics of the data to enable the process of information acquisition. The social data are used in the domain of policy modeling to gather information about citizens' demands, opinions, and requirements and help to decide about political policies. Although existing systems already provide a huge number of visual analysis tools, the search and exploration paradigm is not really clear. Furthermore, the systems commonly do not provide any kind of human centered adaptation for the different stakeholders involved in the policy making process. In this paper, we introduce a novel approach that investigates the exploration and search paradigm from two different perspectives and enables a visual adaptation to support the exploration and analysis process. Schließen Springer link doi:10.1007/978-3-319-14249-4_32 Schließen
2013
9.	Kawa Nazemi; Jörn Kohlhammer Visual Variables in Adaptive Visualizations. Konferenzbeitrag In: Shlomo Berkovsky; Eelco Herder; Pasquale Lops; Olga C Santos (Hrsg.): 21st Conference on User Modeling, Adaptation, and Personalization. UMAP 2013 Extended Proceedings. Proceeding of 1st International Workshop on User-Adaptive Visualizations., CEUR Workshop Proceedings, Rome, Italy,, 2013, ISSN: 1613-0073. Abstract \| Links \| BibTeX \| Schlagwörter: Adaptive Information Visualization, Adaptive User Interfaces, Adaptive Visualization, Human Factors, Human-computer interaction (HCI), Information visualization, Intelligent Systems, Interaction analysis, Interaction Design, Semantic visualization @inproceedings{nazemi2013visual, title = {Visual Variables in Adaptive Visualizations.}, author = {Kawa Nazemi and Jörn Kohlhammer}, editor = {Shlomo Berkovsky and Eelco Herder and Pasquale Lops and Olga C Santos}, url = {http://ceur-ws.org/Vol-997/wuav2013_paper_06.pdf, full text}, issn = {1613-0073}, year = {2013}, date = {2013-06-01}, booktitle = {21st Conference on User Modeling, Adaptation, and Personalization. UMAP 2013 Extended Proceedings. Proceeding of 1st International Workshop on User-Adaptive Visualizations.}, publisher = {CEUR Workshop Proceedings}, address = {Rome, Italy,}, series = {Vol. 997}, abstract = {Visualizations provide various variables for the adaptation to the usage context and the users. Today’s adaptive visualizations make use of various visual variables to order or filter information or visualizations. However, the capabilities of visual variables in context of human information processing and tasks are not comprehensively exploited. This paper discusses the value of the different visual variables providing beneficial and more accurately adapted information visualizations.}, keywords = {Adaptive Information Visualization, Adaptive User Interfaces, Adaptive Visualization, Human Factors, Human-computer interaction (HCI), Information visualization, Intelligent Systems, Interaction analysis, Interaction Design, Semantic visualization}, pubstate = {published}, tppubtype = {inproceedings} } Schließen Visualizations provide various variables for the adaptation to the usage context and the users. Today’s adaptive visualizations make use of various visual variables to order or filter information or visualizations. However, the capabilities of visual variables in context of human information processing and tasks are not comprehensively exploited. This paper discusses the value of the different visual variables providing beneficial and more accurately adapted information visualizations. Schließen full text Schließen
8.	Dirk Burkhardt; Kawa Nazemi; Peter Sonntagbauer; Susanne Sonntagbauer; Jörn Kohlhammer Interactive Visualizations in the Process of Policy Modelling. Konferenzbeitrag In: Maria Wimmer; Marjin Janssen; Ann Macintosh; Hans J Scholl; Efthimios Tambouris (Hrsg.): Electronic Government and Electronic Participation Joint Proceedings of Ongoing Research of IFIP EGOV and IFIP ePart 2013, S. 104–115, Gesellschaft für Informatik e.V. (GI), 2013, ISBN: 978-3-88579-615-2. Links \| BibTeX \| Schlagwörter: eGovernance, Interaction Design, Policy modeling, Semantic visualization, Semantic web, User Interactions, User-centered design @inproceedings{burkhardt2013interactive, title = {Interactive Visualizations in the Process of Policy Modelling.}, author = {Dirk Burkhardt and Kawa Nazemi and Peter Sonntagbauer and Susanne Sonntagbauer and Jörn Kohlhammer}, editor = {Maria Wimmer and Marjin Janssen and Ann Macintosh and Hans J Scholl and Efthimios Tambouris}, url = {https://subs.emis.de/LNI/Proceedings/Proceedings221/104.pdf, LNI GI- full text https://pdfs.semanticscholar.org/78a3/e0732eabaeb7c84b50a28a70bcddde40f562.pdf, Semantic scholars - full text}, isbn = {978-3-88579-615-2}, year = {2013}, date = {2013-01-01}, booktitle = {Electronic Government and Electronic Participation Joint Proceedings of Ongoing Research of IFIP EGOV and IFIP ePart 2013}, pages = {104--115}, publisher = {Gesellschaft für Informatik e.V. (GI)}, keywords = {eGovernance, Interaction Design, Policy modeling, Semantic visualization, Semantic web, User Interactions, User-centered design}, pubstate = {published}, tppubtype = {inproceedings} } Schließen LNI GI- full text Semantic scholars - full text Schließen
7.	Kawa Nazemi; Reimond Retz; Jürgen Bernard; Jörn Kohlhammer; Dieter W. Fellner Adaptive Semantic Visualization for Bibliographic Entries Konferenzbeitrag In: George Bebis; Richard Boyle; Bahram Parvin; Darko Koracin; Baoxin Li; Fatih Porikli; Victor Zordan; James Klosowski; Sabine Coquillart; Xun Luo; Min Chen; David Gotz (Hrsg.): Proceedings of International Symposium on Visual Computing (ISVC 2013). Advances in Visual Computing., S. 13–24, Springer Berlin Heidelberg, Berlin, Heidelberg, 2013, ISBN: 978-3-642-41939-3. Abstract \| Links \| BibTeX \| Schlagwörter: Adaptive Information Visualization, Adaptive User Interfaces, Adaptive Visualization, Data Analytics, Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, Intelligent Systems, Interaction analysis, Interaction Design, personalization, Semantic visualization, Semantic web, User behavior, User Interactions, Visual analytics @inproceedings{Nazemi2013b, title = {Adaptive Semantic Visualization for Bibliographic Entries}, author = {Kawa Nazemi and Reimond Retz and Jürgen Bernard and Jörn Kohlhammer and Dieter W. Fellner}, editor = {George Bebis and Richard Boyle and Bahram Parvin and Darko Koracin and Baoxin Li and Fatih Porikli and Victor Zordan and James Klosowski and Sabine Coquillart and Xun Luo and Min Chen and David Gotz}, url = {https://link.springer.com/chapter/10.1007/978-3-642-41939-3_2, Springer link}, doi = {10.1007/978-3-642-41939-3_2}, isbn = {978-3-642-41939-3}, year = {2013}, date = {2013-01-01}, booktitle = {Proceedings of International Symposium on Visual Computing (ISVC 2013). Advances in Visual Computing.}, pages = {13--24}, publisher = {Springer Berlin Heidelberg}, address = {Berlin, Heidelberg}, series = {LNCS 8034}, abstract = {Adaptive visualizations aim to reduce the complexity of visual representations and convey information using interactive visualizations. Although the research on adaptive visualizations grew in the last years, the existing approaches do not make use of the variety of adaptable visual variables. Further the existing approaches often premises experts, who has to model the initial visualization design. In addition, current approaches either incorporate user behavior or data types. A combination of both is not proposed to our knowledge. This paper introduces the instantiation of our previously proposed model that combines both: involving different influencing factors for and adapting various levels of visual peculiarities, on visual layout and visual presentation in a multiple visualization environment. Based on data type and users’ behavior, our system adapts a set of applicable visualization types. Moreover, retinal variables of each visualization type are adapted to meet individual or canonic requirements on both, data types and users’ behavior. Our system does not require an initial expert modeling.}, keywords = {Adaptive Information Visualization, Adaptive User Interfaces, Adaptive Visualization, Data Analytics, Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, Intelligent Systems, Interaction analysis, Interaction Design, personalization, Semantic visualization, Semantic web, User behavior, User Interactions, Visual analytics}, pubstate = {published}, tppubtype = {inproceedings} } Schließen Adaptive visualizations aim to reduce the complexity of visual representations and convey information using interactive visualizations. Although the research on adaptive visualizations grew in the last years, the existing approaches do not make use of the variety of adaptable visual variables. Further the existing approaches often premises experts, who has to model the initial visualization design. In addition, current approaches either incorporate user behavior or data types. A combination of both is not proposed to our knowledge. This paper introduces the instantiation of our previously proposed model that combines both: involving different influencing factors for and adapting various levels of visual peculiarities, on visual layout and visual presentation in a multiple visualization environment. Based on data type and users’ behavior, our system adapts a set of applicable visualization types. Moreover, retinal variables of each visualization type are adapted to meet individual or canonic requirements on both, data types and users’ behavior. Our system does not require an initial expert modeling. Schließen Springer link doi:10.1007/978-3-642-41939-3_2 Schließen
2012
6.	Dirk Burkhardt; Kawa Nazemi Dynamic process support based on users' behavior Konferenzbeitrag In: 15th International Conference on Interactive Collaborative Learning (ICL), S. 1-6, 2012, ISBN: 978-1-4673-2425-0. Abstract \| Links \| BibTeX \| Schlagwörter: Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Interaction Design, Process Support, User-centered design @inproceedings{Burkhardt2012, title = {Dynamic process support based on users' behavior}, author = {Dirk Burkhardt and Kawa Nazemi}, url = {http://ieeexplore.ieee.org/document/6402079/, IEEE Xplore}, doi = {10.1109/ICL.2012.6402079}, isbn = {978-1-4673-2425-0}, year = {2012}, date = {2012-09-01}, booktitle = {15th International Conference on Interactive Collaborative Learning (ICL)}, pages = {1-6}, abstract = {Nowadays there is a gap between the possibilities and the massively existing data on the one side and the user as main worker on the other side. In different scenarios e.g. search, exploration, analysis and policy-modeling a user has to deal with massive information, but for this work he usually gets a static designed system. So meanwhile data-driven work-processes are increasing in its complexity the support of the users who are working with these data is limited on basic features. Hence this paper describes a concept for a process-supporting approach, which includes relevant aspects of users' behaviors in support him to successfully finish also complex tasks. This will be achieved by a process-based guidance with an automatic tools selection for every process and activity on the one hand. And on the other hand the consideration of expert-level of a user to a single task and process. This expert-level will be classified during each task and process interaction and allow the automatically selection of optimal tools for a concrete task. In final the user gets for every task an automatically initialized user-interface with useful and required tools.}, keywords = {Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Interaction Design, Process Support, User-centered design}, pubstate = {published}, tppubtype = {inproceedings} } Schließen Nowadays there is a gap between the possibilities and the massively existing data on the one side and the user as main worker on the other side. In different scenarios e.g. search, exploration, analysis and policy-modeling a user has to deal with massive information, but for this work he usually gets a static designed system. So meanwhile data-driven work-processes are increasing in its complexity the support of the users who are working with these data is limited on basic features. Hence this paper describes a concept for a process-supporting approach, which includes relevant aspects of users' behaviors in support him to successfully finish also complex tasks. This will be achieved by a process-based guidance with an automatic tools selection for every process and activity on the one hand. And on the other hand the consideration of expert-level of a user to a single task and process. This expert-level will be classified during each task and process interaction and allow the automatically selection of optimal tools for a concrete task. In final the user gets for every task an automatically initialized user-interface with useful and required tools. Schließen IEEE Xplore doi:10.1109/ICL.2012.6402079 Schließen
2011
5.	Kawa Nazemi; Dirk Burkhardt; Christian Stab; Matthias Breyer; Reiner Wichert; Dieter W. Fellner Natural Gesture Interaction with Accelerometer-Based Devices in Ambient Assisted Environments Buchkapitel In: Reiner Wichert; Birgid Eberhardt (Hrsg.): S. 75–90, Springer Berlin Heidelberg, Berlin, Heidelberg, 2011, ISBN: 978-3-642-18167-2. Abstract \| Links \| BibTeX \| Schlagwörter: Human-computer interaction (HCI), Intelligent Systems, Interaction Design, Interactive multimedia @inbook{Nazemi2011, title = {Natural Gesture Interaction with Accelerometer-Based Devices in Ambient Assisted Environments}, author = {Kawa Nazemi and Dirk Burkhardt and Christian Stab and Matthias Breyer and Reiner Wichert and Dieter W. Fellner}, editor = {Reiner Wichert and Birgid Eberhardt}, url = {https://doi.org/10.1007/978-3-642-18167-2_6 https://link.springer.com/chapter/10.1007/978-3-642-18167-2_6, Springer page}, doi = {10.1007/978-3-642-18167-2_6}, isbn = {978-3-642-18167-2}, year = {2011}, date = {2011-01-01}, pages = {75--90}, publisher = {Springer Berlin Heidelberg}, address = {Berlin, Heidelberg}, abstract = {Using modern interaction methods and devices enables a more natural and intuitive interaction. Currently, only mobile phones and game consoles which are supporting such gesture-based interactions have good payment-rates. This comes along, that such devices will be bought not only by the traditional technical experienced consumers. The interaction with such devices becomes so easy, that also older people playing or working with them. Especially older people have more handicaps, so for them it is difficult to read small text, like they are used as description to buttons on remote controls for televisions. They also become fast overstrained, so that bigger technical systems are no help for them. If it is possible to interact with gestures, all these problems can be avoided. But to allow an intuitive and easy gesture interaction, gestures have to be supported, which are easy to understand. Because of that fact, in this paper we tried to identify intuitive gestures for common interaction scenarios on computer-based systems for uses in ambient assisted environment. In this evaluation, the users should commit their opinion of intuitive gestures for different presented scenarios/tasks. Basing on these results, intuitively useable systems can be developed, so that users are able to communicate with technical systems on more intuitive level using accelerometer-based devices.}, keywords = {Human-computer interaction (HCI), Intelligent Systems, Interaction Design, Interactive multimedia}, pubstate = {published}, tppubtype = {inbook} } Schließen Using modern interaction methods and devices enables a more natural and intuitive interaction. Currently, only mobile phones and game consoles which are supporting such gesture-based interactions have good payment-rates. This comes along, that such devices will be bought not only by the traditional technical experienced consumers. The interaction with such devices becomes so easy, that also older people playing or working with them. Especially older people have more handicaps, so for them it is difficult to read small text, like they are used as description to buttons on remote controls for televisions. They also become fast overstrained, so that bigger technical systems are no help for them. If it is possible to interact with gestures, all these problems can be avoided. But to allow an intuitive and easy gesture interaction, gestures have to be supported, which are easy to understand. Because of that fact, in this paper we tried to identify intuitive gestures for common interaction scenarios on computer-based systems for uses in ambient assisted environment. In this evaluation, the users should commit their opinion of intuitive gestures for different presented scenarios/tasks. Basing on these results, intuitively useable systems can be developed, so that users are able to communicate with technical systems on more intuitive level using accelerometer-based devices. Schließen https://doi.org/10.1007/978-3-642-18167-2_6 Springer page doi:10.1007/978-3-642-18167-2_6 Schließen
4.	Kawa Nazemi; Matthias Breyer; Jeanette Forster; Dirk Burkhardt; Arjan Kuijper Interacting with Semantics: A User-Centered Visualization Adaptation Based on Semantics Data Konferenzbeitrag In: Michael J Smith; Gavriel Salvendy (Hrsg.): Human Interface and the Management of Information. Interacting with Information. Symposium on Human Interface 2011., S. 239–248, Springer Berlin Heidelberg, Berlin, Heidelberg, 2011, ISBN: 978-3-642-21793-7. Abstract \| Links \| BibTeX \| Schlagwörter: Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, Interaction Design, Semantic visualization, Semantic web, User behavior, User Interactions @inproceedings{Nazemi2011cb, title = {Interacting with Semantics: A User-Centered Visualization Adaptation Based on Semantics Data}, author = {Kawa Nazemi and Matthias Breyer and Jeanette Forster and Dirk Burkhardt and Arjan Kuijper}, editor = {Michael J Smith and Gavriel Salvendy}, url = {https://link.springer.com/chapter/10.1007/978-3-642-21793-7_28, Springer link}, doi = {10.1007/978-3-642-21793-7_28}, isbn = {978-3-642-21793-7}, year = {2011}, date = {2011-01-01}, booktitle = {Human Interface and the Management of Information. Interacting with Information. Symposium on Human Interface 2011.}, pages = {239--248}, publisher = {Springer Berlin Heidelberg}, address = {Berlin, Heidelberg}, series = {LNCS 6771}, abstract = {Semantically annotated data gain more and more importance in future information acquiring processes. Especially the Linked Open Data (LOD) format has already experienced a great growth. However, the user-interfaces of web-applications mostly do not reflect the added value of semantics data. The following paper describes a new approach of user-centered data-adaptive semantics visualization, which makes use of the advantages of semantics data combined with an adaptive composition of information visualization techniques. It starts with a related work section, where existing LOD systems and information visualization techniques are described. After that, the new approach will bridge the gap between semantically annotated data (LOD) and information visualization and introduces a visualization system that adapts the composition of visualizations based on the underlying data structure. A case study of an example case will conclude this paper.}, keywords = {Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, Interaction Design, Semantic visualization, Semantic web, User behavior, User Interactions}, pubstate = {published}, tppubtype = {inproceedings} } Schließen Semantically annotated data gain more and more importance in future information acquiring processes. Especially the Linked Open Data (LOD) format has already experienced a great growth. However, the user-interfaces of web-applications mostly do not reflect the added value of semantics data. The following paper describes a new approach of user-centered data-adaptive semantics visualization, which makes use of the advantages of semantics data combined with an adaptive composition of information visualization techniques. It starts with a related work section, where existing LOD systems and information visualization techniques are described. After that, the new approach will bridge the gap between semantically annotated data (LOD) and information visualization and introduces a visualization system that adapts the composition of visualizations based on the underlying data structure. A case study of an example case will conclude this paper. Schließen Springer link doi:10.1007/978-3-642-21793-7_28 Schließen
3.	Dirk Burkhardt; Matthias Breyer; Christian Glaser; Kawa Nazemi; Arjan Kuijper Classifying Interaction Methods to Support Intuitive Interaction Devices for Creating User-Centered-Systems Konferenzbeitrag In: Constantine Stephanidis (Hrsg.): S. 20–29, Springer Berlin Heidelberg, Berlin, Heidelberg, 2011, ISBN: 978-3-642-21672-8. Abstract \| Links \| BibTeX \| Schlagwörter: Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Interaction Design, User behavior, User-centered design @inproceedings{Burk2011c, title = {Classifying Interaction Methods to Support Intuitive Interaction Devices for Creating User-Centered-Systems}, author = {Dirk Burkhardt and Matthias Breyer and Christian Glaser and Kawa Nazemi and Arjan Kuijper}, editor = {Constantine Stephanidis}, url = {https://link.springer.com/chapter/10.1007/978-3-642-21672-5_3, Springer link}, doi = {10.1007/978-3-642-21672-5_3}, isbn = {978-3-642-21672-8}, year = {2011}, date = {2011-01-01}, pages = {20--29}, publisher = {Springer Berlin Heidelberg}, address = {Berlin, Heidelberg}, series = {LNCS 6765}, abstract = {Nowadays a wide range of input devices are available to users of technical systems. Especially modern alternative interaction devices, which are known from game consoles etc., provide a more natural way of interaction. But the support in computer programs is currently a big challenge, because a high effort is to invest for developing an application that supports such alternative input devices. For this fact we made a concept for an interaction system, which supports the use of alternative interaction devices. The interaction-system consists as central element a server, which provides a simple access interface for application to support such devices. It is also possible to address an abstract device by its properties and the interaction-system overtakes the converting from a concrete device. For realizing this idea, we also defined a taxonomy for classifying interaction devices by its interaction method and in dependence to the required interaction results, like recognized gestures. Later, by using this system, it is generally possible to develop a user-centered system by integrating this interaction-system, because an adequate integration of alternative interaction devices provides a more natural and easy to understand form of interaction.}, keywords = {Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Interaction Design, User behavior, User-centered design}, pubstate = {published}, tppubtype = {inproceedings} } Schließen Nowadays a wide range of input devices are available to users of technical systems. Especially modern alternative interaction devices, which are known from game consoles etc., provide a more natural way of interaction. But the support in computer programs is currently a big challenge, because a high effort is to invest for developing an application that supports such alternative input devices. For this fact we made a concept for an interaction system, which supports the use of alternative interaction devices. The interaction-system consists as central element a server, which provides a simple access interface for application to support such devices. It is also possible to address an abstract device by its properties and the interaction-system overtakes the converting from a concrete device. For realizing this idea, we also defined a taxonomy for classifying interaction devices by its interaction method and in dependence to the required interaction results, like recognized gestures. Later, by using this system, it is generally possible to develop a user-centered system by integrating this interaction-system, because an adequate integration of alternative interaction devices provides a more natural and easy to understand form of interaction. Schließen Springer link doi:10.1007/978-3-642-21672-5_3 Schließen
2.	Kawa Nazemi; Dirk Burkhardt; Matthias Breyer; Arjan Kuijper Modeling Users for Adaptive Semantics Visualizations Konferenzbeitrag In: Constantine Stephanidis (Hrsg.): International Conference on Universal Access in Human-Computer Interaction. Universal Access in Human-Computer Interaction. Users Diversity., S. 88–97, Springer Berlin Heidelberg, Berlin, Heidelberg, 2011, ISBN: 978-3-642-21663-3. Abstract \| Links \| BibTeX \| Schlagwörter: Adaptive Information Visualization, Adaptive User Interfaces, Adaptive Visualization, Intelligent Systems, Interaction analysis, Interaction Design, User modeling @inproceedings{Nazemi2011d, title = {Modeling Users for Adaptive Semantics Visualizations}, author = {Kawa Nazemi and Dirk Burkhardt and Matthias Breyer and Arjan Kuijper}, editor = {Constantine Stephanidis}, url = {https://link.springer.com/chapter/10.1007/978-3-642-21663-3_10, Springer link}, doi = {10.1007/978-3-642-21663-3_10}, isbn = {978-3-642-21663-3}, year = {2011}, date = {2011-01-01}, booktitle = {International Conference on Universal Access in Human-Computer Interaction. Universal Access in Human-Computer Interaction. Users Diversity.}, volume = {2}, pages = {88--97}, publisher = {Springer Berlin Heidelberg}, address = {Berlin, Heidelberg}, series = {LNCS 6766}, abstract = {The automatic adaptation of information visualization systems to the requirements of users plays a key-role in today's research. Different approaches from both disciplines try to face this phenomenon. The modeling of user is an essential part of a user-centered adaptation of visualization. In this paper we introduce a new approach for modeling users especially for semantic visualization systems. The approach consists of a three dimensional model, where semantic data, user and visualization are set in relation in different abstraction layer.}, keywords = {Adaptive Information Visualization, Adaptive User Interfaces, Adaptive Visualization, Intelligent Systems, Interaction analysis, Interaction Design, User modeling}, pubstate = {published}, tppubtype = {inproceedings} } Schließen The automatic adaptation of information visualization systems to the requirements of users plays a key-role in today's research. Different approaches from both disciplines try to face this phenomenon. The modeling of user is an essential part of a user-centered adaptation of visualization. In this paper we introduce a new approach for modeling users especially for semantic visualization systems. The approach consists of a three dimensional model, where semantic data, user and visualization are set in relation in different abstraction layer. Schließen Springer link doi:10.1007/978-3-642-21663-3_10 Schließen
1.	Kawa Nazemi; Matthias Breyer; Christian Stab; Dirk Burkhardt; Dieter W. Fellner Intelligent Exploration System - An Approach for User-Centered Exploratory Learning Konferenzbeitrag In: Argiris Tzikopoulos; Anna Zoakou (Hrsg.): Proceeding of the Workshop of the EDEN Open Classroom 2011 Conference. RURALeNTER - Lifelong Learning in Rural and Remote Areas, S. 71 - 83, EPINOIA S.A., Pallini - Athens, Greece, 2011, ISBN: 978-960-473-323-1, (reprint). Abstract \| Links \| BibTeX \| Schlagwörter: E-Learning, Exploratory learning, Human Factors, Interaction Design, Semantic visualization @inproceedings{Nazemi2011e, title = {Intelligent Exploration System - An Approach for User-Centered Exploratory Learning}, author = {Kawa Nazemi and Matthias Breyer and Christian Stab and Dirk Burkhardt and Dieter W. Fellner}, editor = {Argiris Tzikopoulos and Anna Zoakou}, url = {http://www.ea.gr/ep/ruenter/news/RURALeNTER_WP6_%20ProceedingsofEuropeanWorkshop%20_V1.0_30October2011_EA.pdf, full text}, doi = {10.5281/zenodo.3455885}, isbn = {978-960-473-323-1}, year = {2011}, date = {2011-01-01}, booktitle = {Proceeding of the Workshop of the EDEN Open Classroom 2011 Conference. RURALeNTER - Lifelong Learning in Rural and Remote Areas}, pages = {71 - 83}, publisher = {EPINOIA S.A.}, address = {Pallini - Athens, Greece}, abstract = {The following paper describes the conceptual design of an Intelligent Exploration System (IES) that offers a user-adapted graphical environment of web-based knowledge repositories, to support and optimize the explorative learning. The paper starts with a short definition of learning by exploring and introduces the Intelligent Tutoring System and Semantic Technologies for developing such an Intelligent Exploration System. The IES itself will be described with a short overview of existing learner or user analysis methods, visualization techniques for exploring knowledge with semantics technology and the explanation of the characteristics of adaptation to offer a more efficient learning environment.}, note = {reprint}, keywords = {E-Learning, Exploratory learning, Human Factors, Interaction Design, Semantic visualization}, pubstate = {published}, tppubtype = {inproceedings} } Schließen The following paper describes the conceptual design of an Intelligent Exploration System (IES) that offers a user-adapted graphical environment of web-based knowledge repositories, to support and optimize the explorative learning. The paper starts with a short definition of learning by exploring and introduces the Intelligent Tutoring System and Semantic Technologies for developing such an Intelligent Exploration System. The IES itself will be described with a short overview of existing learner or user analysis methods, visualization techniques for exploring knowledge with semantics technology and the explanation of the characteristics of adaptation to offer a more efficient learning environment. Schließen full text doi:10.5281/zenodo.3455885 Schließen

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