@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}

}

@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 = {https://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}

}

@inproceedings{Nazemi2014,

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}

}

@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 = {https://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}

}

@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}

}

@inproceedings{Nazemi2013,

title = {Adaptive Semantic Visualization for Bibliographic Entries},

author = {Kawa Nazemi and Reimond Retz and Jürgen Bernard and Jörn Kohlhammer and Dieter 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}

}

@inproceedings{Burkhardt2012,

title = {Dynamic process support based on users' behavior},

author = {Dirk Burkhardt and Kawa Nazemi},

url = {https://ieeexplore.ieee.org/document/6402079/, IEEE Xplore},

doi = {10.1109/ICL.2012.6402079},

isbn = {978-1-4673-2425-0},

year  = {2012},

date = {2012-09-01},

booktitle = {15th International Conference on Interactive Collaborative Learning (ICL)},

pages = {1-6},

abstract = {Nowadays there is a gap between the possibilities and the massively existing data on the one side and the user as main worker on the other side. In different scenarios e.g. search, exploration, analysis and policy-modeling a user has to deal with massive information, but for this work he usually gets a static designed system. So meanwhile data-driven work-processes are increasing in its complexity the support of the users who are working with these data is limited on basic features. Hence this paper describes a concept for a process-supporting approach, which includes relevant aspects of users' behaviors in support him to successfully finish also complex tasks. This will be achieved by a process-based guidance with an automatic tools selection for every process and activity on the one hand. And on the other hand the consideration of expert-level of a user to a single task and process. This expert-level will be classified during each task and process interaction and allow the automatically selection of optimal tools for a concrete task. In final the user gets for every task an automatically initialized user-interface with useful and required tools.},

keywords = {Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Interaction Design, Process Support, User-centered design},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{6337431,

title = {Interactive Exploration System: A User-Centered Interaction Approach in Semantics Visualizations},

author = {Dirk Burkhardt and Christian Stab and Martin Steiger and Matthias Breyer and Kawa Nazemi},

doi = {10.1109/CW.2012.45},

isbn = {978-1-4673-2736-7},

year  = {2012},

date = {2012-09-01},

booktitle = {2012 International Conference on Cyberworlds},

pages = {261-267},

publisher = {IEEE},

abstract = {Nowadays a wide range of input devices are available to users of technical systems. Especially modern alternative interaction devices, which are known from game consoles etc., provide a more natural way of interaction. In parallel to that the research on visualization of large amount of data advances very quickly. This research was also influenced by the semantic web and the idea of storing data in a structured and linked form. The semantically annotated data gains more and more importance in information acquisition processes. Especially the Linked Open Data (LOD) format already experienced a huge growth. However, the user-interfaces of web-applications mostly do not reflect the added value of semantics data. This paper describes the conceptual design and implementation of an Interactive Exploration System that offers a user-centered graphical environment of web-based knowledge repositories, to support and optimize explorative learning, and the integration of a taxonomy-based approach to enable the use of more natural interaction metaphors, as they are possible with modern devices like Wii Mote or Microsoft Kinect. Therefore we introduce a different classification for interaction devices, and current approaches for supporting the added values in semantics visualizations. Furthermore, we describe the concept of our IES, including a strategy to organize and structure today's existing input devices, and a semantics exploration system driven by user-experience. We conclude the paper with a description of the implementation of the IES and an application scenario.},

keywords = {Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Information visualization, Interaction Design, Semantics visualization, User-centered design, Visual analytics},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Nazemi2011c,

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}

}

@inproceedings{Burk2011c,

title = {Classifying Interaction Methods to Support Intuitive Interaction Devices for Creating User-Centered-Systems},

author = {Dirk Burkhardt and Matthias Breyer and Christian Glaser and Kawa Nazemi and Arjan Kuijper},

editor = {Constantine Stephanidis},

url = {https://link.springer.com/chapter/10.1007/978-3-642-21672-5_3, Springer link},

doi = {10.1007/978-3-642-21672-5_3},

isbn = {978-3-642-21672-8},

year  = {2011},

date = {2011-01-01},

pages = {20--29},

publisher = {Springer Berlin Heidelberg},

address = {Berlin, Heidelberg},

series = {LNCS 6765},

abstract = {Nowadays a wide range of input devices are available to users of technical systems. Especially modern alternative interaction devices, which are known from game consoles etc., provide a more natural way of interaction. But the support in computer programs is currently a big challenge, because a high effort is to invest for developing an application that supports such alternative input devices. For this fact we made a concept for an interaction system, which supports the use of alternative interaction devices. The interaction-system consists as central element a server, which provides a simple access interface for application to support such devices. It is also possible to address an abstract device by its properties and the interaction-system overtakes the converting from a concrete device. For realizing this idea, we also defined a taxonomy for classifying interaction devices by its interaction method and in dependence to the required interaction results, like recognized gestures. Later, by using this system, it is generally possible to develop a user-centered system by integrating this interaction-system, because an adequate integration of alternative interaction devices provides a more natural and easy to understand form of interaction.},

keywords = {Human Factors, Human-centered user interfaces, Human-computer interaction (HCI), Interaction Design, User behavior, User-centered design},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Nazemi2011d,

title = {Modeling Users for Adaptive Semantics Visualizations},

author = {Kawa Nazemi and Dirk Burkhardt and Matthias Breyer and Arjan Kuijper},

editor = {Constantine Stephanidis},

url = {https://link.springer.com/chapter/10.1007/978-3-642-21663-3_10, Springer link},

doi = {10.1007/978-3-642-21663-3_10},

isbn = {978-3-642-21663-3},

year  = {2011},

date = {2011-01-01},

booktitle = {International Conference on Universal Access in Human-Computer Interaction. Universal Access in Human-Computer Interaction. Users Diversity. },

volume = {2},

pages = {88--97},

publisher = {Springer Berlin Heidelberg},

address = {Berlin, Heidelberg},

series = {LNCS 6766},

abstract = {The automatic adaptation of information visualization systems to the requirements of users plays a key-role in today's research. Different approaches from both disciplines try to face this phenomenon. The modeling of user is an essential part of a user-centered adaptation of visualization. In this paper we introduce a new approach for modeling users especially for semantic visualization systems. The approach consists of a three dimensional model, where semantic data, user and visualization are set in relation in different abstraction layer.},

keywords = {Adaptive information visualization, Adaptive user interfaces, Adaptive visualization, Intelligent Systems, Interaction analysis, Interaction Design, User modeling},

pubstate = {published},

tppubtype = {inproceedings}

}

@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 = {https://www.ea.gr/ep/ruenter/news/RURALeNTER_WP6_%20ProceedingsofEuropeanWorkshop%20_V1.0_30October2011_EA.pdf, full text},

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}

}