Publications
2019 | |
21. | Kawa Nazemi; Dirk Burkhardt A Visual Analytics Approach for Analyzing Technological Trends in Technology and Innovation Management Inproceedings In: George Bebis; Richard Boyle; Bahram Parvin; Darko Koracin; Daniela Ushizima; Sek Chai; Shinjiro Sueda; Xin Lin; Aidong Lu; Daniel Thalmann; Chaoli Wang; Panpan Xu (Ed.): Advances in Visual Computing, pp. 283–294, Springer International Publishing, Cham, 2019, ISBN: 978-3-030-33723-0. Abstract | Links | BibTeX | Tags: Artificial Intelligence, Data Analytics, Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, Intelligent Systems, maschine learning, Visual analytics @inproceedings{Nazemi_ISVC2019, Visual Analytics provides with a combination of automated techniques and interactive visualizations huge analysis possibilities in technology and innovation management. Thereby not only the use of machine learning data mining methods plays an important role. Due to the high interaction capabilities, it provides a more user-centered approach, where users are able to manipulate the entire analysis process and get the most valuable information. Existing Visual Analytics systems for Trend Analytics and technology and innovation management do not really make use of this unique feature and almost neglect the human in the analysis process. Outcomes from research in information search, information visualization and technology management can lead to more sophisticated Visual Analytics systems that involved the human in the entire analysis process. We propose in this paper a new interaction approach for Visual Analytics in technology and innovation management with a special focus on technological trend analytics. |
2018 | |
20. | Kawa Nazemi; Dirk Burkhardt Juxtaposing Visual Layouts – An Approach for Solving Analytical and Exploratory Tasks through Arranging Visual Interfaces Inproceedings In: A. G. Bruzzone; Egils Ginters; E. G. Mendívil; J. M. Guitierrez; F. Longo (Ed.): The 4th International Conference of the Virtual and Augmented Reality in Education, I3M, 2018, ISBN: 978-88-85741-21-8. Abstract | Links | BibTeX | Tags: Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, Visual analytics @inproceedings{Nazemi2018b, Interactive visualization and visual analytics systems enables solving a variety of tasks. Starting with simple search tasks for outliers, anomalies etc. in data to analytical comparisons, information visualizations may lead to a faster and more precise solving of tasks. There exist a variety of methods to support users in the process of task solving, e.g. superimposing, juxtaposing or partitioning complex visual structures. Commonly all these methods make use of a single data source that is visualized at the same time. We propose in this paper an approach that goes beyond the established methods and enables visualizing different databases, data-sets and sub-sets of data with juxtaposed visual interfaces. Our approach should be seen as an expandable method. Our main contributions are an in-depth analysis of visual task models and an approach for juxtaposing visual layouts as visual interfaces to enable solving complex tasks. |
2017 | |
19. | Kawa Nazemi; Dirk Burkhardt; Arjan Kuijper Analyzing the Information Search Behavior and Intentions in Visual Information Systems Journal Article In: Journal of Computer Science Technology Updates, vol. 4, 2017. Abstract | Links | BibTeX | Tags: Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, User behavior, User Interactions, User Interface, User modeling, User-centered design, Visual analytics @article{Nazemi2017, Visual information search systems support different search approaches such as targeted, exploratory or analytical search. Those visual systems deal with the challenge of composing optimal initial result visualization sets that face the search intention and respond to the search behavior of users. The diversity of these kinds of search tasks require different sets of visual layouts and functionalities, e.g. to filter, thrill-down or even analyze concrete data properties. This paper describes a new approach to calculate the probability towards the three mentioned search intentions, derived from users’ behavior. The implementation is realized as a web-service, which is included in a visual environment that is designed to enable various search strategies based on heterogeneous data sources. In fact, based on an entered search query our developed search intention analysis web-service calculates the most probable search task, and our visualization system initially shows the optimal result set of visualizations to solve the task. The main contribution of this paper is a probability-based approach to derive the users’ search intentions based on the search behavior enhanced by the application to a visual system. |
2016 | |
18. | 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). Abstract | Links | BibTeX | Tags: Human-centered user interfaces, Information visualization, Semantic data modeling, Semantic visualization, User-centered design, Visual analytics @inbook{Nazemi2016, 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. |
2014 | |
17. | Kawa Nazemi Adaptive Semantics Visualization PhD Thesis Technische Universität Darmstadt, 2014, (Reprint by Eugraphics Association (EG)). Abstract | Links | BibTeX | Tags: 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, 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. |
16. | Kawa Nazemi Adaptive Semantics Visualization PhD Thesis Technische Universität Darmstadt, 2014, (Department of Computer Science. Supervised by Dieter W. Fellner.). Abstract | Links | BibTeX | Tags: 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, 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. |
15. | 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. Abstract | Links | BibTeX | Tags: 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, 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. |
14. | 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. Abstract | Links | BibTeX | Tags: eGovernance, Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, Interaction Design, Policy modeling, Semantic visualization, User-centered design @inproceedings{7038782, 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. |
13. | 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. Abstract | Links | BibTeX | Tags: 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, 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 | |
12. | 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. Abstract | Links | BibTeX | Tags: Human-centered user interfaces, Human-computer interaction (HCI), Linked Data, LOD, Semantic visualization, Semantic web, User behavior, User Interactions, User-centered design, Visual analytics @inbook{Stab2013, 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. |
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. Abstract | Links | BibTeX | Tags: 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, 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. | Dirk Burkhardt; Kawa Nazemi Dynamic process support based on users' behavior Inproceedings In: 15th International Conference on Interactive Collaborative Learning (ICL), pp. 1-6, 2012, ISBN: 978-1-4673-2425-0. Abstract | Links | BibTeX | Tags: Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Interaction Design, Process Support, User-centered design @inproceedings{Burkhardt2012, 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. |
9. | 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. Abstract | Links | BibTeX | Tags: 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 @article{6311373, 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 | |
8. | Dirk Burkhardt; Matthias Breyer; Christian Stab; Kawa Nazemi Facilitate Access to E-Knowledge for Adult People in Rural Areas Inproceedings In: Candel I Torres; Gómez L Chova; López A Martínez (Ed.): Proceedings of the 4th International Conference of Education, Research and Innovation (ICERI2011)., pp. 2050-2057, International Association of Technology, Education and Development, Madrid, Spain, 2011, ISBN: 978-84-615-3324-4. Abstract | Links | BibTeX | Tags: Adult Learning, E-Learning, E-Learning environments, Exploratory learning, Human Factors, Human-centered user interfaces @inproceedings{Burkhardt2011b, The today society especially in the western world is stamped by a lifelong learning. This matter results because of an increasing technology development primary in Information Communication Technologies (ICT). These technology developments have their reasons in creating new effective and efficient systems that allows a higher productivity or quality and decreases the production cost, which is necessary for a stable and healthy company. But the goal of these new technologies is also to provide more possibilities for the “normal” users, so that they for instance can easily and cheap get updated about the status of their family members or friends over the internet. So ICT allows a wide range of possibilities, also for providing education with these technologies. So in this connection ICT can contribute to achieving universal education worldwide, through transfer of education and training, and offering improved conditions for lifelong learning, encompassing adults that are not participating to the formal education process, and improving professional skills (UNESCO, 2009). And skills are today the main factor for wealth in a society. A modern established method to provide a flexible learning, especially for lifelong learning for adults, is learning over the internet. By this kind of eLearning it does not matter where a specific user or student lives or tries to learn, he only needs access to the internet and has with it access to a huge amount of information and eLearning materials. But in fact for this way of learning the user needs experiences in dealing with the internet and also with the learning platforms. Because of that fact often only younger students up to the age of ca. 30 years are able use the existing eLearning platforms in an efficient way. This young target group stands in opposition to the demographic effect that the average age of most of the European residents increases constantly. So it becomes to a national and European challenge to support also the middle-aged adults for holding them up-to-date educated. But to provide an advanced education for these adult people is difficult, because it can be very time consuming and expensive, if they are trained on the traditional way with courses and tutors or trainers. So another approach is useful, next to the traditional advanced education. In our paper we describe an approach to provide a facilitated access to eKnowledge and so to virtual learning. With the described approach we address especially older adults between the age of 30 and 40 to support them in advanced learning. This allows bringing them up-to-date, so that they can achieve a similar education level than younger once which e.g. coming from the university. For reducing the access barrier many aspects, next to the general strategy, have to be to regarded, e.g. usability and also user experience aspects to avoid that middle and older adults get overstrained, which results often that they dislike the entire online learning strategy. So these technical features need to be hidden or so far reduced and abstracted that also these kinds of adults will understand the usefulness. In this paper we also take care for such aspects and presenting a concept and implementation of an eLearning portal that is primary designed for supporting the needs and behaviours of middle-aged adults. The main contribution of this paper is the abstraction and reduction of learning functionalities, implemented in a well-known learning environment. |
7. | Dirk Burkhardt; Kawa Nazemi; Christian Stab; Matthias Breyer; Reiner Wichert; Dieter W. Fellner Ambient Assisted Living - AAL, VDE Verlag, 2011, ISSN: 3800734001. Abstract | Links | BibTeX | Tags: Ambient Intelligence, Gesture based interaction, Human-centered user interfaces, Human-computer interaction (HCI) @conference{Burkhardt25.0, Die Verwendung von modernen Interaktionsmethoden und Geräten erlaubte eine natürlichere und intuitive Interaktion. Gegenwärtig haben lediglich die Smartphones und Spielekonsolen großen Absatz, welche eine gestenbasierte Interaktion unterstützen. Dies geht einher, dass solche Geräte nicht nur von technisch versierten Konsumenten gekauft werden. Die Interaktion mit solchen Geräten gestaltet sich so einfach, dass oftmals auch ältere Personen mit diesen spielen oder arbeiten. Insbesondere ältere Personen sind häufig gehandicapt, so haben sie oftmals Probleme kleinere Text zu lesen, wie sie häufig auf Fernbedienungen gedruckt sind. Ebenso neigen sie dazu, schnell überfordert zu sein, so dass gerade größere technische Systeme keine Hilfe sind. Wenn die Geräte mit Gesten steuerbar sind, sind die genannten Probleme oftmals vermeidbar. Um aber eine intuitive und einfache Gesteninteraktion zu ermöglichen, müssen entsprechend verständliche und nachvollziehbare Gesten unterstützt werden. Aus diesem Grund versuchen wir in diesem Paper intuitive Gesten für gängige Interaktionsszenarien an computerbasierten Systemen für den Einsatz in unterstützenden Umgebungen zu identifizieren. Im Rahmen der Evaluation sollen die Probanden hierfür ihre bevorzugten Gesten für die verschiedenen Interaktionsszenarien einbringen. Auf Grundlage der Ergebnisse kann später ein intuitiv bedienbares System, unter Verwendung eines beschleunigungssensorbasierten Geräts, entwickelt werden, mit welchem die Nutzer auf intuitive Weise kommunizieren können. |
6. | Dirk Burkhardt; Kawa Nazemi; Matthias Breyer; Christian Stab; Arjan Kuijper SemaZoom: Semantics Exploration by Using a Layer-Based Focus and Context Metaphor Inproceedings In: Masaaki Kurosu (Ed.): Human Centered Design, pp. 491–499, Springer Berlin Heidelberg, Berlin, Heidelberg, 2011, ISBN: 978-3-642-21753-1. Abstract | Links | BibTeX | Tags: Graph visualization, Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, User behavior, User Interactions, User Interface, User interfaces, User-centered design, Visual analytics @inproceedings{10.1007/978-3-642-21753-1_55, The Semantic Web is a powerful technology for organizing the data in our information based society. The collection and organization of information is an important step for showing important information to interested people. But the usage of such semantic-based data sources depends on effective and efficient information visualizations. Currently different kinds of visualizations in general and visualization metaphors do exist. Many of them are also applied for semantic data source, but often they are designed for semantic web experts and neglecting the normal user and his perception of an easy useable visualization. This kind of user needs less information, but rather a reduced qualitative view on the data. These two aspects of large amount of existing data and one for normal users easy to understand visualization is often not reconcilable. In this paper we create a concept for a visualization to show a bigger set of information to such normal users without overstraining them, because of layer-based data visualization, next to an integration of a Focus and Context metaphor. |
5. | 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. Abstract | Links | BibTeX | Tags: Data Analytics, Human Factors, Human-centered user interfaces, Information visualization, Ontology visualization, Semantic visualization, Semantic web, Temporal Visualization, User behavior @inproceedings{Stab2011, 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. |
4. | 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. Abstract | Links | BibTeX | Tags: Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, Interaction Design, Semantic visualization, Semantic web, User behavior, User Interactions @inproceedings{Nazemi2011cb, 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. |
3. | Dirk Burkhardt; Matthias Breyer; Christian Glaser; Kawa Nazemi; Arjan Kuijper Classifying Interaction Methods to Support Intuitive Interaction Devices for Creating User-Centered-Systems Inproceedings In: Constantine Stephanidis (Ed.): pp. 20–29, Springer Berlin Heidelberg, Berlin, Heidelberg, 2011, ISBN: 978-3-642-21672-8. Abstract | Links | BibTeX | Tags: Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Interaction Design, User behavior, User-centered design @inproceedings{Burk2011c, 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. |
2010 | |
2. | Kawa Nazemi; Matthias Breyer; Christian Stab; Dirk Burkhardt; Dieter W. Fellner Intelligent Exploration System - an Approach for User-Centered Exploratory Learning Conference 2nd International Conference on Education and New Learning Technologies, 2010, ISBN: 978-84-613-9386-2. Abstract | Links | BibTeX | Tags: Exploration, Exploratory learning, Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, Intelligent Systems, Intelligent tutoring systems, Knowledge discovery @conference{C35-P-21397, 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. |
2009 | |
1. | Kawa Nazemi; Matthias Breyer; Christoph Hornung SeMap: A Concept for the Visualization of Semantics as Maps Book Chapter In: Constantine Stephanidis (Ed.): Universal Access in Human-Computer Interaction. Applications and Services: 5th International Conference, UAHCI 2009, San Diego, CA, USA, July 19-24, 2009. Proceedings, Part III, pp. 83–91, Springer Berlin Heidelberg, Berlin, Heidelberg, 2009, ISBN: 978-3-642-02713-0. Abstract | Links | BibTeX | Tags: Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Information visualization @inbook{Nazemi2009, The enhancement of the individual knowledge is a basic need that came up with changes in our society, whereas the process of learning disappears more and more. In the recent past the disappearance of a predefined learning process was named ambient learning, which came up to cope the changing need of every time and everywhere learning. Learning contents get more structure by new technologies like semantics, which specifies and defines more the semantic structure and with it the meaning of information. Users working with information system are confronted with different processes for getting the required information. The following paper introduces a new visualization technique, which uses the everyday processes of information search for imparting knowledge. The visualization technique utilizes the surplus of semantics to encourage the process of ambient learning. |