@inproceedings{10.1007/978-3-030-39688-6_40,

title = {Process Support and Visual Adaptation to Assist Visual Trend Analytics in Managing Transportation Innovations},

author = {Dirk Burkhardt and Kawa Nazemi and Egils Ginters},

editor = {Egils Ginters and Mario Arturo Ruiz Estrada and Miquel Angel Piera Eroles},

url = {https://rd.springer.com/chapter/10.1007%2F978-3-030-39688-6_40, Springer },

doi = {10.1007/978-3-030-39688-6_40},

isbn = {978-3-030-39688-6},

year  = {2020},

date = {2020-01-30},

booktitle = {ICTE in Transportation and Logistics 2019},

pages = {319--327},

publisher = {Springer International Publishing. Lecture Notes in Intelligent Transportation and Infrastructure},

address = {Cham},

abstract = {In the domain of mobility and logistics, a variety of new technologies and business ideas are arising. Beside technologies that aim on ecologically and economic transportation, such as electric engines, there are also fundamental different approaches like central packaging stations or deliveries via drones. Yet, there is a growing need for analytical systems that enable identifying new technologies, innovations, business models etc. and give also the opportunity to rate those in perspective of business relevance. Commonly adaptive systems investigate only the users' behavior, while a process-related supports could assist to solve an analytical task more efficient and effective. In this article an approach that enables non-experts to perform visual trend analysis through an advanced process support based on process mining is described. This allow us to calculate a process model based on events, which is the baseline for process support feature calculation. These features and the process model enable to assist non-expert users in complex analytical tasks.},

keywords = {Human Factors, Human-computer interaction (HCI), Mobility, personalization, Process Support, Process-Mining, User behavior, User Interactions, User Interface, User modeling, User-centered design, Visual analytics},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1007/978-3-319-20612-7_4,

title = {Explorative Visualization of Impact Analysis for Policy Modeling by Bonding Open Government and Simulation Data},

author = {Dirk Burkhardt and Kawa Nazemi and Egils Ginters and Artis Aizstrauts and Jörn Kohlhammer},

editor = {Sakae Yamamoto},

url = {https://link.springer.com/chapter/10.1007/978-3-319-20612-7_4. Springer Link},

doi = {doi.org/10.1007/978-3-319-20612-7_4},

isbn = {978-3-319-20612-7},

year  = {2015},

date = {2015-03-01},

booktitle = {International Conference on Human Interface and the Management of Information (HIMI 2015). Information and Knowledge Design.},

pages = {34--45},

publisher = {Springer International Publishing},

address = {Cham},

series = {LNCS 9172},

abstract = {Problem identification and solution finding are major challenges in policy modeling. Statistical indicator-data build the foundation for most of the required analysis work. In particular finding effective and efficient policies that solve an existing political problem is critical, since the forecast validation of the effectiveness is quite difficult. Simulation technologies can help to identify optimal policies for solutions, but nowadays many of such simulators are stand-alone technologies. In this paper we introduce a new visualization approach to enable the coupling of statistical indicator data from Open Government Data sources with simulators and especially simulation result data with the goal to provide an enhanced impact analysis for political analysts and decision makers. This allows, amongst others a more intuitive and effective way of solution finding.},

keywords = {Exploration, Semantics visualization, Simulation, User behavior, User Interactions, User Interface, User-centered design, Visual analytics},

pubstate = {published},

tppubtype = {inproceedings}

}

@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}

}

@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{Burkhardt2014f,

title = {Visualization Adaptation Based on Environmental Influencing Factors},

author = {Dirk Burkhardt and Kawa Nazemi and Jose Daniel Encarnacao and Wilhelm Retz and Jörn Kohlhammer},

editor = {Masaaki Kurosu},

url = {https://link.springer.com/chapter/10.1007/978-3-319-07233-3_38, Springer link},

isbn = {978-3-319-07233-3},

year  = {2014},

date = {2014-01-01},

booktitle = {International Conference on Human-Computer (HCI 2014). Human-Computer Interaction. Theories, Methods, and Tools.},

pages = {411--422},

publisher = {Springer International Publishing},

address = {Cham},

series = {LNCS 8510},

abstract = {Working effectively with computer-based devices is challenging, especially under mobile conditions, due to the various environmental influences. In this paper a visualization adaptation approach is described, to support the user under discriminatory environmental conditions. For this purpose, a context model for environmental influencing factors is being defined. Based on this context model, an approach to adapt visualizations in regards of certain environmental influences is being evolved, such as the light intensity, air quality, or heavy vibrations.},

keywords = {Adaptive information visualization, Adaptive user interfaces, User modeling, User-centered design, Visual analytics},

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{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{6402080,

title = {Towards process-oriented Information Visualization for supporting users},

author = {Dirk Burkhardt and Tobias Ruppert and Kawa Nazemi},

url = {https://ieeexplore.ieee.org/document/6402080/?anchor=citations, IEEE Xplore},

doi = {10.1109/ICL.2012.6402080},

isbn = {978-1-4673-2427-4},

year  = {2012},

date = {2012-07-01},

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

pages = {1-8},

publisher = {IEEE Press},

organization = { Institute of Electrical and Electronics Engineering IEEE},

abstract = {Nowadays daily office work consists of dealing with big numbers of data and data sources, and furthermore of working with complex computer programs. In consequence many users have problems to use such programs effective and efficient. In particular beginners have significant problems to use the programs correctly due to complex functionality and interaction options. To avoid this overload of the user, the Information Visualization community has recently developed some approaches that aim to support the users. Unfortunately, these approaches are limited to one special aspect, and sometimes they are just appropriate for one special task. Thus, in this paper we introduce a process-oriented user-supporting approach. It allows selecting adequate supporting techniques in correlation to a performed process and activity to guide the user and help him to solve his task. Furthermore, we show the benefits of designing programs and applications, which implement process definitions for the existing tasks to provide the user with better process orientation. This guides the user through difficult and complex processes.},

keywords = {Human Factors, Human-centered user interfaces, Information visualization, User Interface, User-centered design},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1007/978-3-642-21753-1_55,

title = {SemaZoom: Semantics Exploration by Using a Layer-Based Focus and Context Metaphor},

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

editor = {Masaaki Kurosu},

url = {https://doi.org/10.1007/978-3-642-21753-1_55, DOI

https://link.springer.com/chapter/10.1007/978-3-642-21753-1_55, Springer page},

doi = {10.1007/978-3-642-21753-1_55},

isbn = {978-3-642-21753-1},

year  = {2011},

date = {2011-01-01},

booktitle = {Human Centered Design},

pages = {491--499},

publisher = {Springer Berlin Heidelberg},

address = {Berlin, Heidelberg},

series = {LNCS 6776},

abstract = {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.},

keywords = {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},

pubstate = {published},

tppubtype = {inproceedings}

}