2016 |
| 24. | Kawa Nazemi; Martin Steiger; Dirk Burkhardt; Jörn Kohlhammer Information Visualization and Policy Modeling Book Chapter In: Big Data: Concepts, Methodologies, Tools, and Applications, Information Science Reference, IGI Global, Hershey PA, USA, 2016, ISBN: 978-1-466-69840-6, (reprint). @inbook{Nazemi2016,
title = {Information Visualization and Policy Modeling},
author = {Kawa Nazemi and Martin Steiger and Dirk Burkhardt and Jörn Kohlhammer},
url = {https://www.igi-global.com/chapter/information-visualization-and-policy-modeling/150163, IGI Global},
doi = {10.4018/978-1-4666-9840-6.ch008},
isbn = {978-1-466-69840-6},
year = {2016},
date = {2016-01-01},
booktitle = {Big Data: Concepts, Methodologies, Tools, and Applications},
publisher = {Information Science Reference, IGI Global},
address = {Hershey PA, USA},
institution = {Information Resources Management Association USA},
organization = {Information Resources Management Association USA},
abstract = {Policy design requires the investigation of various data in several design steps for making the right decisions, validating, or monitoring the political environment. The increasing amount of data is challenging for the stakeholders in this domain. One promising way to access the “big data” is by abstracted visual patterns and pictures, as proposed by information visualization. This chapter introduces the main idea of information visualization in policy modeling. First abstracted steps of policy design are introduced that enable the identification of information visualization in the entire policy life-cycle. Thereafter, the foundations of information visualization are introduced based on an established reference model. The authors aim to amplify the incorporation of information visualization in the entire policy design process. Therefore, the aspects of data and human interaction are introduced, too. The foundation leads to description of a conceptual design for social data visualization, and the aspect of semantics plays an important role.},
note = {reprint},
keywords = {Human-centered user interfaces, Information visualization, Semantic data modeling, Semantic visualization, User-centered design, Visual analytics},
pubstate = {published},
tppubtype = {inbook}
}
Policy design requires the investigation of various data in several design steps for making the right decisions, validating, or monitoring the political environment. The increasing amount of data is challenging for the stakeholders in this domain. One promising way to access the “big data” is by abstracted visual patterns and pictures, as proposed by information visualization. This chapter introduces the main idea of information visualization in policy modeling. First abstracted steps of policy design are introduced that enable the identification of information visualization in the entire policy life-cycle. Thereafter, the foundations of information visualization are introduced based on an established reference model. The authors aim to amplify the incorporation of information visualization in the entire policy design process. Therefore, the aspects of data and human interaction are introduced, too. The foundation leads to description of a conceptual design for social data visualization, and the aspect of semantics plays an important role. |
2015 |
| 23. | Dirk Burkhardt; Kawa Nazemi; Egils Ginters Best-Practice Piloting Based on an Integrated Social Media Analysis and Visualization for E-Participation Simulation in Cities Journal Article In: Procedia Computer Science. 2015 International Conference Virtual and Augmented Reality in Education, vol. 75, pp. 66 - 74, 2015, ISSN: 1877-0509. @article{Burkhardt2015e,
title = {Best-Practice Piloting Based on an Integrated Social Media Analysis and Visualization for E-Participation Simulation in Cities},
author = {Dirk Burkhardt and Kawa Nazemi and Egils Ginters},
editor = {Eduardo González Mendívil and Pablo Guillermo Ramírez Flores and Jorge Martín Gutiérrez and Egils Ginters},
doi = {10.1016/j.procs.2015.12.214},
issn = {1877-0509},
year = {2015},
date = {2015-11-19},
journal = {Procedia Computer Science. 2015 International Conference Virtual and Augmented Reality in Education},
volume = {75},
pages = {66 - 74},
abstract = {E-Participation and the engagement of citizens in politics are on the agenda in many countries. Therefore, a number of project and programs were initiated that aim at finding creative and effective solutions for involving citizens. One intended aspect is the provision of transparency that enables citizens to analyze socio-economical indicators and serves as basement for initial data storing for e-participation scenarios simulation. A beyond going step is to consider citizens’ opinions in the policy making process. Unfortunately this will only be possible; if a significant number of citizens know what concrete aspect should be realized. The growth and establishment of social media nowadays allow most people to discuss political ideas and critics virtually and anonymously achieving higher credibility of the data usable for policy making. However, the major barrier is the different topical languages, the representatives’ role and weak visualization of the results. This article dealt with a best-practice piloting approach for discussing and realizing innovative solutions with a variety of stakeholders from different domains. The core of this paper is how to deal and manage the different perspective on development process, to aim on designing a common set of requirements and development procedure. The methodology is practically and beneficial applied as social media integration solution in the EC FP7 FUPOL research project.},
keywords = {E-Participation, Policy Making, Semantic visualization, Simulation},
pubstate = {published},
tppubtype = {article}
}
E-Participation and the engagement of citizens in politics are on the agenda in many countries. Therefore, a number of project and programs were initiated that aim at finding creative and effective solutions for involving citizens. One intended aspect is the provision of transparency that enables citizens to analyze socio-economical indicators and serves as basement for initial data storing for e-participation scenarios simulation. A beyond going step is to consider citizens’ opinions in the policy making process. Unfortunately this will only be possible; if a significant number of citizens know what concrete aspect should be realized. The growth and establishment of social media nowadays allow most people to discuss political ideas and critics virtually and anonymously achieving higher credibility of the data usable for policy making. However, the major barrier is the different topical languages, the representatives’ role and weak visualization of the results. This article dealt with a best-practice piloting approach for discussing and realizing innovative solutions with a variety of stakeholders from different domains. The core of this paper is how to deal and manage the different perspective on development process, to aim on designing a common set of requirements and development procedure. The methodology is practically and beneficial applied as social media integration solution in the EC FP7 FUPOL research project. |
| 22. | Kawa Nazemi; Dirk Burkhardt; Egils Ginters; Jorn Kohlhammer Semantics Visualization – Definition, Approaches and Challenges Journal Article In: Procedia Computer Science, vol. 75, pp. 75 - 83, 2015, ISSN: 1877-0509, (2015 International Conference Virtual and Augmented Reality in Education). @article{NAZEMI201575,
title = {Semantics Visualization – Definition, Approaches and Challenges},
author = {Kawa Nazemi and Dirk Burkhardt and Egils Ginters and Jorn Kohlhammer},
url = {http://www.sciencedirect.com/science/article/pii/S1877050915036777, Elsevier Science Direct https://www.sciencedirect.com/science/article/pii/S1877050915036777/pdf?md5=b7e921e7548cdf69e35324864b0b2ea1&pid=1-s2.0-S1877050915036777-main.pdf, full text},
doi = {https://doi.org/10.1016/j.procs.2015.12.216},
issn = {1877-0509},
year = {2015},
date = {2015-01-01},
journal = {Procedia Computer Science},
volume = {75},
pages = {75 - 83},
abstract = {The visualization of the simulation results must be done in conformity with beneficiaries perception and professional domain understanding. It means that right data must be identified before. Semantic technologies provide new ways for accessing data and acquiring knowledge. The underlying structures allow finding information easier, gathering meanings and associations of the data entities and associating the data to users’ knowledge. Even though the focus of the research in this area is more to provide “machine readable” data, human-centered systems benefit from the technologies too. Especially graphical representations of the semantically structured data play a key-role in today's research. The meaningful relations of data entities and the meaningful and labeled clustering of data in form of semantic concepts enable new ways to visualize data. With these new ways, various challenges are related with deploying semantics visualizations beyond analytical search and simulation. The goal is to give a common understanding of the term semantics as it is used in semantic web. This paper dealt with the general idea of semantics visualization. First a short introduction to semantic formalisms is given followed by a general definition. Subsequently approaches and techniques of existing semantics visualizations are presented, where-as a new classification is introduced to describe the techniques. The article concludes with future challenges in semantics visualization focusing on users, data and tasks.},
note = {2015 International Conference Virtual and Augmented Reality in Education},
keywords = {Semantic visualization, Simulation, Visual analytics, Visualization and virtualization},
pubstate = {published},
tppubtype = {article}
}
The visualization of the simulation results must be done in conformity with beneficiaries perception and professional domain understanding. It means that right data must be identified before. Semantic technologies provide new ways for accessing data and acquiring knowledge. The underlying structures allow finding information easier, gathering meanings and associations of the data entities and associating the data to users’ knowledge. Even though the focus of the research in this area is more to provide “machine readable” data, human-centered systems benefit from the technologies too. Especially graphical representations of the semantically structured data play a key-role in today's research. The meaningful relations of data entities and the meaningful and labeled clustering of data in form of semantic concepts enable new ways to visualize data. With these new ways, various challenges are related with deploying semantics visualizations beyond analytical search and simulation. The goal is to give a common understanding of the term semantics as it is used in semantic web. This paper dealt with the general idea of semantics visualization. First a short introduction to semantic formalisms is given followed by a general definition. Subsequently approaches and techniques of existing semantics visualizations are presented, where-as a new classification is introduced to describe the techniques. The article concludes with future challenges in semantics visualization focusing on users, data and tasks. |
2014 |
| 21. | Kawa Nazemi Adaptive Semantics Visualization PhD Thesis Technische Universität Darmstadt, 2014, (Reprint by Eugraphics Association (EG)). @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}
}
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. |
| 20. | Kawa Nazemi Adaptive Semantics Visualization PhD Thesis Technische Universität Darmstadt, 2014, (Department of Computer Science. Supervised by Dieter W. Fellner.). @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}
}
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. |
| 19. | Kawa Nazemi; Wilhelm Retz; Jörn Kohlhammer; Arjan Kuijper User Similarity and Deviation Analysis for Adaptive Visualizations Inproceedings In: Sakae Yamamoto (Ed.): International Conference on Human Interface and the Management of Information (HMI 2014). Human Interface and the Management of Information. Information and Knowledge Design and Evaluation., pp. 64–75, Springer International Publishing, Cham, 2014, ISBN: 978-3-319-07731-7. @inproceedings{Nazemi2014e,
title = {User Similarity and Deviation Analysis for Adaptive Visualizations},
author = {Kawa Nazemi and Wilhelm Retz and Jörn Kohlhammer and Arjan Kuijper},
editor = {Sakae Yamamoto},
url = {https://link.springer.com/chapter/10.1007/978-3-319-07731-4_7, Springer link},
doi = {10.1007/978-3-319-07731-4_7},
isbn = {978-3-319-07731-7},
year = {2014},
date = {2014-08-01},
booktitle = {International Conference on Human Interface and the Management of Information (HMI 2014). Human Interface and the Management of Information. Information and Knowledge Design and Evaluation.},
pages = {64--75},
publisher = {Springer International Publishing},
address = {Cham},
series = {LNCS 8521},
abstract = {Adaptive visualizations support users in information acquisition and exploration and therewith in human access of data. Their adaptation effect is often based on approaches that require the training by an expert. Further the effects often aims to support just the individual aptitudes. This paper introduces an approach for modeling a canonical user that makes the predefined training-files dispensable and enables an adaptation of visualizations for the majority of users. With the introduced user deviation algorithm, the behavior of individuals can be compared to the average user behavior represented in the canonical user model to identify behavioral anomalies. The further introduced similarity measurements allow to cluster similar deviated behavioral patterns as groups and provide them effective visual adaptations.},
keywords = {Adaptive Information Visualization, Adaptive User Interfaces, Adaptive Visualization, Data Analytics, reference model, Semantic visualization, Semantics visualization, User behavior, User Interactions, User Interface, User modeling, User-centered design, Visual analytics},
pubstate = {published},
tppubtype = {inproceedings}
}
Adaptive visualizations support users in information acquisition and exploration and therewith in human access of data. Their adaptation effect is often based on approaches that require the training by an expert. Further the effects often aims to support just the individual aptitudes. This paper introduces an approach for modeling a canonical user that makes the predefined training-files dispensable and enables an adaptation of visualizations for the majority of users. With the introduced user deviation algorithm, the behavior of individuals can be compared to the average user behavior represented in the canonical user model to identify behavioral anomalies. The further introduced similarity measurements allow to cluster similar deviated behavioral patterns as groups and provide them effective visual adaptations. |
| 18. | Dirk Burkhardt; Kawa Nazemi; Jörn Kohlhammer Visual Process Support to Assist Users in Policy Making Book Chapter In: Peter Sonntagbauer; Kawa Nazemi; Susanne Sonntagbauer; Giorgio Prister; Dirk Burkhardt (Ed.): Handbook of Research on Advanced ICT Integration for Governance and Policy Modeling, pp. 149–162, IGI Global, 2014, ISBN: 978-1-466-66236-0. @inbook{burkhardt2014visual,
title = {Visual Process Support to Assist Users in Policy Making},
author = {Dirk Burkhardt and Kawa Nazemi and Jörn Kohlhammer},
editor = {Peter Sonntagbauer and Kawa Nazemi and Susanne Sonntagbauer and Giorgio Prister and Dirk Burkhardt},
url = {https://www.igi-global.com/chapter/visual-process-support-to-assist-users-in-policy-making/116661, IGI Global},
doi = {10.4018/978-1-4666-6236-0.ch009},
isbn = {978-1-466-66236-0},
year = {2014},
date = {2014-06-01},
booktitle = {Handbook of Research on Advanced ICT Integration for Governance and Policy Modeling},
journal = {Handbook of Research on Advanced ICT Integration for Governance and Policy Modeling},
pages = {149--162},
publisher = {IGI Global},
series = {Handbook of Research},
crossref = {Sonntagbauer2014},
abstract = {The policy making process requires the involvement of various stakeholders, who bring in very heterogeneous experiences and skills concerning the policymaking domain, as well as experiences of ICT solutions. Current solutions are primarily designed to provide “one-solution-fits-all” answers, which in most cases fail the needs of all stakeholders. In this chapter, the authors introduce a new approach to assist users based on their tasks. Therefore, the system observes the interaction of the user and recognizes the current phase of the policymaking process and the profile of the user to assist him more sufficiently in solving his task. For this purpose, the system automatically enables or disables supporting features such as visualization, tools, and supporting techniques.},
keywords = {Information visualization, Interaction analysis, Process Support, Semantic visualization, Visual analytics},
pubstate = {published},
tppubtype = {inbook}
}
The policy making process requires the involvement of various stakeholders, who bring in very heterogeneous experiences and skills concerning the policymaking domain, as well as experiences of ICT solutions. Current solutions are primarily designed to provide “one-solution-fits-all” answers, which in most cases fail the needs of all stakeholders. In this chapter, the authors introduce a new approach to assist users based on their tasks. Therefore, the system observes the interaction of the user and recognizes the current phase of the policymaking process and the profile of the user to assist him more sufficiently in solving his task. For this purpose, the system automatically enables or disables supporting features such as visualization, tools, and supporting techniques. |
| 17. | Kawa Nazemi; Dirk Burkhardt; Reimond Retz; Arjan Kuijper; Jörn Kohlhammer Adaptive Visualization of Linked-Data Inproceedings 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 (Ed.): Proceedings of International Symposium on Visual Computing (ISVC 2014). Advances in Visual Computing., pp. 872–883, Springer International Publishing, Cham, 2014, ISBN: 978-3-319-14364-4. @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}
}
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. |
| 16. | Dirk Burkhardt; Kawa Nazemi; Wilhelm Retz; Jörn Kohlhammer Visual explanation of government-data for policy making through open-data inclusion Inproceedings In: The 9th International Conference for Internet Technology and Secured Transactions (ICITST-2014), pp. 83-89, IEEE, 2014, ISBN: 978-1-908320-39-1. @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}
}
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. |
| 15. | Kawa Nazemi; Dirk Burkhardt; Wilhelm Retz; Jörn Kohlhammer Adaptive Visualization of Social Media Data for Policy Modeling Inproceedings 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 (Ed.): Proceeding of the International Symposium on Visual Computing (ISVC 2014). Advances in Visual Computing., pp. 333–344, Springer International Publishing, Cham, 2014, ISBN: 978-3-319-14249-4. @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}
}
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. |
2013 |
| 14. | Christian Stab; Dirk Burkhardt; Matthias Breyer; Kawa Nazemi Visualizing Search Results of Linked Open Data Book Chapter In: Tim Hussein; Heiko Paulheim; Stephan Lukosch; Jürgen Ziegler; Ga "e (Ed.): Semantic Models for Adaptive Interactive Systems, pp. 133–149, Springer London, London, 2013, ISBN: 978-1-4471-5301-6. @inbook{Stab2013,
title = {Visualizing Search Results of Linked Open Data},
author = {Christian Stab and Dirk Burkhardt and Matthias Breyer and Kawa Nazemi},
editor = {Tim Hussein and Heiko Paulheim and Stephan Lukosch and Jürgen Ziegler and Ga "e},
url = {https://link.springer.com/chapter/10.1007/978-1-4471-5301-6_7, Springer link},
doi = {10.1007/978-1-4471-5301-6_7},
isbn = {978-1-4471-5301-6},
year = {2013},
date = {2013-10-01},
booktitle = {Semantic Models for Adaptive Interactive Systems},
pages = {133--149},
publisher = {Springer London},
address = {London},
series = {Human–Computer Interaction Series},
abstract = {Finding accurate information of high quality is still a challenging task particularly with regards to the increasing amount of resources in current information systems. This is especially true if policy decisions that impact humans, economy or environment are based on the demanded information. For improving search result generation and analyzing user queries more and more information retrieval systems utilize Linked Open Data and other semantic knowledge bases. Nevertheless, the semantic information that is used during search result generation mostly remains hidden from the users although it significantly supports users in understanding and assessing search results. The presented approach combines information visualizations with semantic information for offering visual feedback about the reasons the results were retrieved. It visually represents the semantic interpretation and the relation between query terms and search results to offer more transparency in search result generation and allows users to unambiguously assess the relevance of the retrieved resources for their individual search. The approach also supports the common search strategies by providing visual feedback for query refinement and enhancement. Besides the detailed description of the search system, an evaluation of the approach shows that the use of semantic information considerably supports users in assessment and decision-making tasks.},
keywords = {Human-centered user interfaces, Human-computer interaction (HCI), Linked Data, LOD, Semantic visualization, Semantic web, User behavior, User Interactions, User-centered design, Visual analytics},
pubstate = {published},
tppubtype = {inbook}
}
Finding accurate information of high quality is still a challenging task particularly with regards to the increasing amount of resources in current information systems. This is especially true if policy decisions that impact humans, economy or environment are based on the demanded information. For improving search result generation and analyzing user queries more and more information retrieval systems utilize Linked Open Data and other semantic knowledge bases. Nevertheless, the semantic information that is used during search result generation mostly remains hidden from the users although it significantly supports users in understanding and assessing search results. The presented approach combines information visualizations with semantic information for offering visual feedback about the reasons the results were retrieved. It visually represents the semantic interpretation and the relation between query terms and search results to offer more transparency in search result generation and allows users to unambiguously assess the relevance of the retrieved resources for their individual search. The approach also supports the common search strategies by providing visual feedback for query refinement and enhancement. Besides the detailed description of the search system, an evaluation of the approach shows that the use of semantic information considerably supports users in assessment and decision-making tasks. |
| 13. | Kawa Nazemi; Jörn Kohlhammer Visual Variables in Adaptive Visualizations. Inproceedings In: Shlomo Berkovsky; Eelco Herder; Pasquale Lops; Olga C Santos (Ed.): 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. @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}
}
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. |
| 12. | Dirk Burkhardt; Kawa Nazemi; Peter Sonntagbauer; Susanne Sonntagbauer; Jörn Kohlhammer Interactive Visualizations in the Process of Policy Modelling. Inproceedings In: Maria Wimmer; Marjin Janssen; Ann Macintosh; Hans J Scholl; Efthimios Tambouris (Ed.): Electronic Government and Electronic Participation Joint Proceedings of Ongoing Research of IFIP EGOV and IFIP ePart 2013, pp. 104–115, Gesellschaft für Informatik e.V. (GI), 2013, ISBN: 978-3-88579-615-2. @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}
}
|
| 11. | Kawa Nazemi; Reimond Retz; Jürgen Bernard; Jörn Kohlhammer; Dieter W. Fellner Adaptive Semantic Visualization for Bibliographic Entries Inproceedings 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 (Ed.): Proceedings of International Symposium on Visual Computing (ISVC 2013). Advances in Visual Computing., pp. 13–24, Springer Berlin Heidelberg, Berlin, Heidelberg, 2013, ISBN: 978-3-642-41939-3. @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}
}
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. |
2012 |
| 10. | Jörn Kohlhammer; Kawa Nazemi; Tobias Ruppert; Dirk Burkhardt Toward Visualization in Policy Modeling Journal Article In: IEEE Computer Graphics and Applications (CG&A), vol. 32, no. 5, pp. 84-89, 2012, ISSN: 0272-1716. @article{6311373,
title = {Toward Visualization in Policy Modeling},
author = {Jörn Kohlhammer and Kawa Nazemi and Tobias Ruppert and Dirk Burkhardt},
url = {http://ieeexplore.ieee.org/document/6311373/, IEEE Xplore},
doi = {10.1109/MCG.2012.107},
issn = {0272-1716},
year = {2012},
date = {2012-09-01},
journal = {IEEE Computer Graphics and Applications (CG&A)},
volume = {32},
number = {5},
pages = {84-89},
publisher = {IEEE Press},
abstract = {This article looks at the current and future roles of information visualization, semantics visualization, and visual analytics in policy modeling. Many experts believe that you can't overestimate visualization's role in this respect.},
keywords = {Data Analytics, eGovernance, Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, Intelligent Systems, Policy modeling, Semantic data modeling, Semantic visualization, Visual analytics},
pubstate = {published},
tppubtype = {article}
}
This article looks at the current and future roles of information visualization, semantics visualization, and visual analytics in policy modeling. Many experts believe that you can't overestimate visualization's role in this respect. |
2011 |
| 9. | Dirk Burkhardt; Matthias Breyer; Kawa Nazemi; Arjan Kuijper Search Intention Analysis for User-Centered Adaptive Visualizations Conference Universal Access in Human-Computer Interaction. Design for All and eInclusion. UAHCI 2011., LNCS 6765 Springer, Berlin, Heidelberg, 2011, ISBN: 978-3-642-21671-8. @conference{C35-P-22190,
title = {Search Intention Analysis for User-Centered Adaptive Visualizations},
author = {Dirk Burkhardt and Matthias Breyer and Kawa Nazemi and Arjan Kuijper},
editor = {C Stephanidis},
url = {https://link.springer.com/chapter/10.1007/978-3-642-21672-5_35, Springer link},
doi = {10.1007/978-3-642-21672-5_35},
isbn = {978-3-642-21671-8},
year = {2011},
date = {2011-01-01},
booktitle = {Universal Access in Human-Computer Interaction. Design for All and eInclusion. UAHCI 2011.},
pages = {317-326},
publisher = {Springer, Berlin, Heidelberg},
series = {LNCS 6765},
abstract = {Searching information on web turned to a matter of course in the last years. The visualization and filtering of the results of such search queries plays a key-role in different disciplines and is still today under research. In this paper a new approach for classifying the search intention of users' is presented. The approach uses existing and easy parameters for a differentiation between explorative and targeted search. The results of the classification are used for a differentiated presentation based on graphical visualization techniques.},
keywords = {Adaptive Information Visualization, Search result visualization, Semantic visualization, Semantic web, User behavior, User centered modeling},
pubstate = {published},
tppubtype = {conference}
}
Searching information on web turned to a matter of course in the last years. The visualization and filtering of the results of such search queries plays a key-role in different disciplines and is still today under research. In this paper a new approach for classifying the search intention of users' is presented. The approach uses existing and easy parameters for a differentiation between explorative and targeted search. The results of the classification are used for a differentiated presentation based on graphical visualization techniques. |
| 8. | Kawa Nazemi; Dirk Burkhardt; Alexander Praetorius; Matthias Breyer; Arjan Kuijper Adapting User Interfaces by Analyzing Data Characteristics for Determining Adequate Visualizations Inproceedings In: Masaaki Kurosu (Ed.): Human Centered Design, pp. 566–575, Springer Berlin Heidelberg, Berlin, Heidelberg, 2011, ISBN: 978-3-642-21753-1. @inproceedings{Nazemi2011c,
title = {Adapting User Interfaces by Analyzing Data Characteristics for Determining Adequate Visualizations},
author = {Kawa Nazemi and Dirk Burkhardt and Alexander Praetorius and Matthias Breyer and Arjan Kuijper},
editor = {Masaaki Kurosu},
url = {https://doi.org/10.1007/978-3-642-21753-1_63, DOI
https://link.springer.com/chapter/10.1007/978-3-642-21753-1_63, Springer page},
doi = {10.1007/978-3-642-21753-1_63},
isbn = {978-3-642-21753-1},
year = {2011},
date = {2011-01-01},
booktitle = {Human Centered Design},
pages = {566--575},
publisher = {Springer Berlin Heidelberg},
address = {Berlin, Heidelberg},
abstract = {Today the information visualization takes in an important position, because it is required in nearly every context where large databases have to be visualized. For this challenge new approaches are needed to allow the user an adequate access to these data. Static visualizations are only able to show the data without any support to the users, which is the reason for the accomplished researches to adaptive user-interfaces, in particular for adaptive visualizations. By these approaches the visualizations were adapted to the users' behavior, so that graphical primitives were change to support a user e.g. by highlighting user-specific entities, which seems relevant for a user. This approach is commonly used, but it is limited on changes for just a single visualization. Modern heterogeneous data providing different kinds of aspects, which modern visualizations try to regard, but therefore a user often needs more than a single visualization for making an information retrieval. In this paper we describe a concept for adapting the user-interface by selecting visualizations in dependence to automatically generated data characteristics. So visualizations will be chosen, which are fitting well to the generated characteristics. Finally the user gets an aquatically arranged set of visualizations as initial point of his interaction through the data.},
keywords = {Adaptive Information Visualization, Adaptive User Interfaces, Adaptive Visualization, Data Analytics, Human Factors, Human-computer interaction (HCI), Information visualization, Intelligent Systems, personalization, reference model, Semantic visualization, Semantic web, User behavior},
pubstate = {published},
tppubtype = {inproceedings}
}
Today the information visualization takes in an important position, because it is required in nearly every context where large databases have to be visualized. For this challenge new approaches are needed to allow the user an adequate access to these data. Static visualizations are only able to show the data without any support to the users, which is the reason for the accomplished researches to adaptive user-interfaces, in particular for adaptive visualizations. By these approaches the visualizations were adapted to the users' behavior, so that graphical primitives were change to support a user e.g. by highlighting user-specific entities, which seems relevant for a user. This approach is commonly used, but it is limited on changes for just a single visualization. Modern heterogeneous data providing different kinds of aspects, which modern visualizations try to regard, but therefore a user often needs more than a single visualization for making an information retrieval. In this paper we describe a concept for adapting the user-interface by selecting visualizations in dependence to automatically generated data characteristics. So visualizations will be chosen, which are fitting well to the generated characteristics. Finally the user gets an aquatically arranged set of visualizations as initial point of his interaction through the data. |
| 7. | Christian Stab; Kawa Nazemi; Matthias Breyer; Dirk Burkhardt; Arjan Kuijper Interacting with Semantics and Time Inproceedings In: Julie A Jacko (Ed.): Human-Computer Interaction. Users and Applications. Proceedings of HCI International 2011, pp. 520–529, Springer Berlin Heidelberg, Berlin, Heidelberg, 2011, ISBN: 978-3-642-21619-0. @inproceedings{Stab2011,
title = {Interacting with Semantics and Time},
author = {Christian Stab and Kawa Nazemi and Matthias Breyer and Dirk Burkhardt and Arjan Kuijper},
editor = {Julie A Jacko},
url = {https://link.springer.com/chapter/10.1007/978-3-642-21619-0_64, Springer link},
doi = {10.1007/978-3-642-21619-0_64},
isbn = {978-3-642-21619-0},
year = {2011},
date = {2011-01-01},
booktitle = {Human-Computer Interaction. Users and Applications. Proceedings of HCI International 2011},
volume = {4},
pages = {520--529},
publisher = {Springer Berlin Heidelberg},
address = {Berlin, Heidelberg},
series = {LNCS 6764},
abstract = {Time appears in many different semantic information systems like historical databases, multimedia systems or social communities as a common attribute. Beside the temporal information, the resources in these domains are categorized in a domain-specific schema and interconnected by semantic relations. Nevertheless, the high potential of these systems is not yet exhausted completely. Even today most of these knowledge systems present time-dependent semantic knowledge in textual form, what makes it difficult for the average user to understand temporal structures and dependencies. For bridging this gap between human and computer and for simplifying the exploration of time-dependent semantic knowledge, we developed a new interactive timeline visualization called SemaTime. The new designed temporal navigation concept offers an intuitive way for exploring and filtering time-depended resources. Additionally SemaTime offers navigation and visual filtering methods on the conceptual layer of the domain and is able to depict semantic relations. In this paper we describe the conceptual design of SemaTime and illustrate its application potentials in semantic search environments.},
keywords = {Data Analytics, Human Factors, Human-centered user interfaces, Information visualization, Ontology visualization, Semantic visualization, Semantic web, Temporal Visualization, User behavior},
pubstate = {published},
tppubtype = {inproceedings}
}
Time appears in many different semantic information systems like historical databases, multimedia systems or social communities as a common attribute. Beside the temporal information, the resources in these domains are categorized in a domain-specific schema and interconnected by semantic relations. Nevertheless, the high potential of these systems is not yet exhausted completely. Even today most of these knowledge systems present time-dependent semantic knowledge in textual form, what makes it difficult for the average user to understand temporal structures and dependencies. For bridging this gap between human and computer and for simplifying the exploration of time-dependent semantic knowledge, we developed a new interactive timeline visualization called SemaTime. The new designed temporal navigation concept offers an intuitive way for exploring and filtering time-depended resources. Additionally SemaTime offers navigation and visual filtering methods on the conceptual layer of the domain and is able to depict semantic relations. In this paper we describe the conceptual design of SemaTime and illustrate its application potentials in semantic search environments. |
| 6. | Kawa Nazemi; Matthias Breyer; Jeanette Forster; Dirk Burkhardt; Arjan Kuijper Interacting with Semantics: A User-Centered Visualization Adaptation Based on Semantics Data Inproceedings In: Michael J Smith; Gavriel Salvendy (Ed.): Human Interface and the Management of Information. Interacting with Information. Symposium on Human Interface 2011., pp. 239–248, Springer Berlin Heidelberg, Berlin, Heidelberg, 2011, ISBN: 978-3-642-21793-7. @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}
}
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. |
| 5. | Kawa Nazemi; Matthias Breyer; Christian Stab; Dirk Burkhardt; Dieter W. Fellner Intelligent Exploration System - An Approach for User-Centered Exploratory Learning Inproceedings In: Argiris Tzikopoulos; Anna Zoakou (Ed.): Proceeding of the Workshop of the EDEN Open Classroom 2011 Conference. RURALeNTER - Lifelong Learning in Rural and Remote Areas, pp. 71 - 83, EPINOIA S.A., Pallini - Athens, Greece, 2011, ISBN: 978-960-473-323-1, (reprint). @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}
}
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. |
2010 |
| 4. | Christian Stab; Kawa Nazemi; Dieter W. Fellner SemaTime - Timeline Visualization of Time-Dependent Relations and Semantics Conference Advances in Visual Computing. 6th International Symposium, Proceeding of ISVC 2010, LNCS 6455 Springer-Verlag, Berlin Heidelberg, 2010, ISBN: 978-3-642-17276-2. @conference{C35-P-21759,
title = {SemaTime - Timeline Visualization of Time-Dependent Relations and Semantics},
author = {Christian Stab and Kawa Nazemi and Dieter W. Fellner},
editor = {Bebis [G et al.]},
url = {https://doi.org/10.1007/978-3-642-17277-9_53, DOI
https://link.springer.com/chapter/10.1007/978-3-642-17277-9_53, Springer Link},
doi = {10.1007/978-3-642-17277-9_53},
isbn = {978-3-642-17276-2},
year = {2010},
date = {2010-01-01},
booktitle = {Advances in Visual Computing. 6th International Symposium, Proceeding of ISVC 2010},
pages = {514-523},
publisher = {Springer-Verlag},
address = {Berlin Heidelberg},
series = {LNCS 6455},
abstract = {Timeline based visualizations arrange time-dependent entities along a time-axis and are used in many different domains like digital libraries, criminal investigation and medical information systems to support users in understanding chronological structures. By the use of semantic technologies, the information is categorized in a domain-specific, hierarchical schema and specified by semantic relations. Commonly semantic relations in timeline visualizations are depicted by interconnecting entities with a directed edge. However it is possible that semantic relations change in the course of time. In this paper we introduce a new timeline visualization for time-dependent semantics called SemaTime that offers a hierarchical categorization of time-dependent entities including navigation and filtering features. We also present a novel concept for visualizing time-dependent relations that allows the illustration of time-varying semantic relations and affords an easy understandable
visualization of complex, time-dependent interrelations.},
keywords = {Information visualization, Interactive information visualization, Semantic visualization, Time, Timeline visualization, Visual analytics},
pubstate = {published},
tppubtype = {conference}
}
Timeline based visualizations arrange time-dependent entities along a time-axis and are used in many different domains like digital libraries, criminal investigation and medical information systems to support users in understanding chronological structures. By the use of semantic technologies, the information is categorized in a domain-specific, hierarchical schema and specified by semantic relations. Commonly semantic relations in timeline visualizations are depicted by interconnecting entities with a directed edge. However it is possible that semantic relations change in the course of time. In this paper we introduce a new timeline visualization for time-dependent semantics called SemaTime that offers a hierarchical categorization of time-dependent entities including navigation and filtering features. We also present a novel concept for visualizing time-dependent relations that allows the illustration of time-varying semantic relations and affords an easy understandable
visualization of complex, time-dependent interrelations. |
| 3. | Kawa Nazemi; Dirk Burkhardt; Matthias Breyer; Christian Stab; Dieter W. Fellner Semantic Visualization Cockpit: Adaptable Composition of Semantics-Visualization Techniques for Knowledge-Exploration Conference International Conference on Interactive Collaborative Learning (ICL), Kassel University Press, 2010, 2010. @conference{C35-P-21605,
title = {Semantic Visualization Cockpit: Adaptable Composition of Semantics-Visualization Techniques for Knowledge-Exploration},
author = {Kawa Nazemi and Dirk Burkhardt and Matthias Breyer and Christian Stab and Dieter W. Fellner},
url = {https://pdfs.semanticscholar.org/46d4/1ca0256a1024fd32f5f37280a359f60ae2f1.pdf, Full text
https://www.semanticscholar.org/paper/Semantic-Visualization-Cockpit%3A-Adaptable-Composit-Nazemi-Burkhardt/46d41ca0256a1024fd32f5f37280a359f60ae2f1, Semantic Scholars},
year = {2010},
date = {2010-01-01},
booktitle = {International Conference on Interactive Collaborative Learning (ICL)},
pages = {163-173},
publisher = {Kassel University Press, 2010},
abstract = {Semantic-Web and ontology-based information processing systems are established technologies and techniques, in more than only research areas and institutions. Different worldwide projects and enterprise companies identified already the added value of semantic technologies and work on different sub-topics for gathering and conveying knowledge. As the process of gathering and structuring semantic information plays a key role in the most developed applications, the process of transferring and adopting knowledge to and by humans is neglected, although the complex structure of knowledge-design opens many research-questions. The following paper describes a new approach for visualizing semantic information as a composition of different adaptable ontology-visualization techniques. We start with a categorized description of existing ontology visualization techniques and show potential gaps. After that the new approach will be described and its added value to existing systems. A case
study within the greatest German program for semantic information processing will show the usage of the system in real scenarios.},
keywords = {Exploratory learning, Intelligent user interfaces, Semantic visualization, Semantic web},
pubstate = {published},
tppubtype = {conference}
}
Semantic-Web and ontology-based information processing systems are established technologies and techniques, in more than only research areas and institutions. Different worldwide projects and enterprise companies identified already the added value of semantic technologies and work on different sub-topics for gathering and conveying knowledge. As the process of gathering and structuring semantic information plays a key role in the most developed applications, the process of transferring and adopting knowledge to and by humans is neglected, although the complex structure of knowledge-design opens many research-questions. The following paper describes a new approach for visualizing semantic information as a composition of different adaptable ontology-visualization techniques. We start with a categorized description of existing ontology visualization techniques and show potential gaps. After that the new approach will be described and its added value to existing systems. A case
study within the greatest German program for semantic information processing will show the usage of the system in real scenarios. |
| 2. | Dirk Burkhardt; Cristian Erik Hofmann; Kawa Nazemi; Christian Stab; Matthias Breyer; Dieter W. Fellner Intuitive Semantic-Editing for Regarding Needs of Domain-Experts Conference Proceedings of ED-Media 2010, The Association for the Advancement of Computing in Education (AACE), 2010, ISBN: 978-1-880094-81-5. @conference{C35-P-21399,
title = {Intuitive Semantic-Editing for Regarding Needs of Domain-Experts},
author = {Dirk Burkhardt and Cristian Erik Hofmann and Kawa Nazemi and Christian Stab and Matthias Breyer and Dieter W. Fellner},
url = {http://www.learntechlib.org/p/34735/, link to paper},
isbn = {978-1-880094-81-5},
year = {2010},
date = {2010-01-01},
booktitle = {Proceedings of ED-Media 2010},
pages = {860-869},
publisher = {The Association for the Advancement of Computing in Education (AACE)},
abstract = {Ontologies are used to represent knowledge and their semantic information from different topics, to allow users a better way to explore knowledge and find information faster, because of the data-structuring. To achieve a well filled knowledgebase, editors have to be used, to enter new and to edit existing information. But most of the existing ontology-editors are designed for experienced ontology-experts. Experts from other topic fields e.g. physicians are often novices in the area of ontology-creating, they need adequate tools, which hide the complexity of ontology-structures. In the area of e-learning experts are also teachers as well. In this paper we will present a method, how the needs of domain-experts can be regarded and so an editor can designed, which allows an editing and adding of information by users without having experiences of creating ontologies. With such an editor domain-experts are able to commit their expert-knowledge into the ontology.},
keywords = {Graphical interactive user interfaces, Intelligent user interfaces, Semantic data modeling, Semantic visualization, Semantic web},
pubstate = {published},
tppubtype = {conference}
}
Ontologies are used to represent knowledge and their semantic information from different topics, to allow users a better way to explore knowledge and find information faster, because of the data-structuring. To achieve a well filled knowledgebase, editors have to be used, to enter new and to edit existing information. But most of the existing ontology-editors are designed for experienced ontology-experts. Experts from other topic fields e.g. physicians are often novices in the area of ontology-creating, they need adequate tools, which hide the complexity of ontology-structures. In the area of e-learning experts are also teachers as well. In this paper we will present a method, how the needs of domain-experts can be regarded and so an editor can designed, which allows an editing and adding of information by users without having experiences of creating ontologies. With such an editor domain-experts are able to commit their expert-knowledge into the ontology. |
| 1. | Dirk Burkhardt; Christian Stab; Kawa Nazemi; Matthias Breyer; Dieter W. Fellner Approaches for 3D-Visualizations and Knowledge Worlds for Exploratory Learning Conference 2nd International Conference on Education and New Learning Technologies, IATED, Barcelona, Spain, 2010, ISBN: 978-84-613-9386-2. @conference{C35-P-21396,
title = {Approaches for 3D-Visualizations and Knowledge Worlds for Exploratory Learning},
author = {Dirk Burkhardt and Christian Stab and Kawa Nazemi and Matthias Breyer and Dieter W. Fellner},
url = {https://library.iated.org/publications/EDULEARN10, Direct Link to publisher},
doi = {10.5281/zenodo.3455879},
isbn = {978-84-613-9386-2},
year = {2010},
date = {2010-01-01},
booktitle = {2nd International Conference on Education and New Learning Technologies},
pages = {006427-006437},
publisher = {IATED},
address = {Barcelona, Spain},
abstract = {Graphical knowledge representations open promising perspectives to support the explorative learning on web. 2D-visualization are recently evaluated as gainful knowledge exploration systems, whereas 3D-visualization systems did not find their way into web-based explorative learning. 3D-visualizations and "3D Knowledge Worlds", as virtual environment in context of e-learning, comprise a high degree of authenticity, because the used metaphors are known by the users from the real world. But different challenges like the usage of 3D-Knowledge World without losing the learning context and the focused learning goals are rarely investigated and considered. New technologies provide the opportunity to introduce 3D-visualizations and environments on web to support a web-based explorative learning. Therefore it is necessary to investigate the prospects of 3D-visualization for transferring and adopting knowledge on web.
The following paper describes different approaches to use 3D-visualization and Knowledge Worlds for conveying knowledge on web-based systems using web-based contents. The approaches for 3D visualizations are classified into different layout algorithm and the knowledge worlds are classified interaction character.},
keywords = {3D Visualization, E-Learning environments, Semantic visualization, Web based learning},
pubstate = {published},
tppubtype = {conference}
}
Graphical knowledge representations open promising perspectives to support the explorative learning on web. 2D-visualization are recently evaluated as gainful knowledge exploration systems, whereas 3D-visualization systems did not find their way into web-based explorative learning. 3D-visualizations and "3D Knowledge Worlds", as virtual environment in context of e-learning, comprise a high degree of authenticity, because the used metaphors are known by the users from the real world. But different challenges like the usage of 3D-Knowledge World without losing the learning context and the focused learning goals are rarely investigated and considered. New technologies provide the opportunity to introduce 3D-visualizations and environments on web to support a web-based explorative learning. Therefore it is necessary to investigate the prospects of 3D-visualization for transferring and adopting knowledge on web.
The following paper describes different approaches to use 3D-visualization and Knowledge Worlds for conveying knowledge on web-based systems using web-based contents. The approaches for 3D visualizations are classified into different layout algorithm and the knowledge worlds are classified interaction character. |
