Scientific Publications

@inproceedings{Burkhardt2020b,

title = {Innovations in Mobility and Logistics: Assistance of Complex Analytical Processes in Visual Trend Analytics},

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

editor = {Janis Grabis and Andrejs Romanovs and Galina Kulesova},

url = {https://dirk.burkhardt.xyz/wp-content/uploads/2020/11/2020itms-ii.pdf, Paper as PDF},

doi = {10.1109/ITMS51158.2020.9259309},

isbn = {978-1-7281-9105-8},

year  = {2020},

date = {2020-11-19},

booktitle = {2020 61st International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS)},

pages = {1-6},

publisher = {IEEE},

abstract = {A variety of new technologies and ideas for businesses are arising in the domain of logistics and mobility. It can be differentiated between fundamental new approaches, e.g. central packaging stations or deliveries via drones and minor technological advancements that aim on more ecologically and economic transportation. The 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 is growing. The users’ behavior is commonly investigated in adaptive systems, which is considering the induvial preferences of users, but neglecting often the tasks and goals of the analysis. A process-related supports could assist to solve an analytical task in a more efficient and effective way. We introduce in this paper an approach that enables non-professionals to perform visual trend analysis through an advanced process assistance based on process mining and visual adaptation. This allows generating a process model based on events, which is the baseline for process support feature calculation. These features in form of visual adaptations and the process model enable assisting non-experts in complex analytical tasks.},

keywords = {Adaptive Visualization, Logistics, Process Mining, Transportation, Trend Analytics, Visual Analytics},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Burkhardt2020,

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://dirk.burkhardt.xyz/wp-content/uploads/2020/02/2019icte-ii.pdf, Paper as PDF},

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

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

year  = {2020},

date = {2020-01-31},

booktitle = {ICTE in Transportation and Logistics 2019},

pages = {319--327},

publisher = {Springer International Publishing},

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 = {Adaptive Visualization, Process Mining, Transportation and Logistics},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Burkhardt2014,

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://dirk.burkhardt.xyz/wp-content/uploads/2018/11/2014hcii.pdf, Paper as PDF

http://2014.hci.international, Conference Site},

doi = {10.1007/978-3-319-07233-3_38},

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

year  = {2014},

date = {2014-01-01},

booktitle = {Human-Computer Interaction. Theories, Methods, and Tools. HCI 2014},

volume = {8510},

pages = {411--422},

publisher = {Springer International Publishing},

address = {Switzerland},

series = {Lecture Notes in Computer Science, vol 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 Visualization, Information Visualization, Sensor Fusion, User Experience, User-Centered Interaction},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Nazemi2011c,

title = {Modeling Users for Adaptive Semantics Visualizations},

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

editor = {Constantine Stephanidis},

url = {https://dirk.burkhardt.xyz/wp-content/uploads/2018/11/2011hcii-v.pdf, Paper as PDF

http://2011.hci.international/, Conference Site},

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

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

year  = {2011},

date = {2011-07-09},

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

volume = {6766},

pages = {88--97},

publisher = {Springer},

address = {Berlin, Heidelberg, Germany},

series = {Lecture Notes in Computer Science, vol 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 Visualization, Semantic Visualization, User Model},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Nazemi2011d,

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://dirk.burkhardt.xyz/wp-content/uploads/2018/11/2011hcii-iv.pdf, Paper as PDF

http://2011.hci.international/, Conference Site},

doi = {10.1007/978-3-642-21753-1_63},

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

year  = {2011},

date = {2011-07-09},

booktitle = {Human Centered Design},

volume = {6776},

pages = {566--575},

publisher = {Springer},

address = {Berlin, Heidelberg, Germany},

series = {Lecture Notes in Computer Science, vol 6776},

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 Visualization, Human-Centered Interfaces, Human-Computer-Interfaces, Semantics Visualization},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1007/978-3-642-21672-5_35,

title = {Search Intention Analysis for User-Centered Adaptive Visualizations},

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

editor = {Constantine Stephanidis},

url = {https://dirk.burkhardt.xyz/wp-content/uploads/2018/11/2011hcii-ii.pdf, Paper as PDF

http://2011.hci.international/, Conference Site},

doi = {10.1007/978-3-642-21672-5_35},

isbn = {978-3-642-21672-5},

year  = {2011},

date = {2011-07-09},

booktitle = {Universal Access in Human-Computer Interaction. Design for All and eInclusion},

volume = {6765},

pages = {317--326},

publisher = {Springer},

address = {Berlin, Heidelberg, Germany},

series = {Lecture Notes in Computer Science, vol 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 Visualization, Search Result Visualization, Semantic Visualization, Semantic Web, User  Intention  Analysis, User-Centered Interaction},

pubstate = {published},

tppubtype = {inproceedings}

}