Scientific Publications

@inproceedings{Burkhardt2025,

title = {Enabling Smart Manufacturing with Visual Analytics for Plant Workers},

author = {Dirk Burkhardt and Gerald Ristow},

editor = {Meike Klettke and Ralf Schenkel and Andreas Henrich and Daniela Nicklas and Maximilian E. Schüle and Klaus Meyer-Wegener},

url = {https://dirk.burkhardt.xyz/wp-content/uploads/2025/03/2025btw.pdf, Paper as PDF},

doi = {10.18420/BTW2025-33},

issn = {2944-7682},

year  = {2025},

date = {2025-02-28},

urldate = {2025-02-28},

booktitle = {Datenbanksysteme für Business, Technologie und Web (BTW 2025)},

pages = {665-678},

publisher = {Gesellschaft für Informatik},

address = {Bonn},

series = {Lecture Notes in Informatics (LNI) - Proceedings, Volume P-361},

abstract = {Smart manufacturing is increasingly making use of visual analytics to optimize production or to identify early problem signs. However, current solutions and approaches require professionals, especially from the data science area, to make use of it, which is for most production companies not affordable. In this paper, we describe first a best practice to sensorize plants from the wood and beverage industry to enable smart manufacturing in general. Second, we describe a new approach that aims at providing easy-to-use visual analytics functionalities that are designed to be used directly by plant workers. Plant workers usually have encompassing experience in the production and the plant, but lack of computer experience and corresponding mathematical knowledge for data analysis. Through lowering the barriers for plant workers in performing data analysis of the IoT sensors with simplified and almost automated analysis functions would give them the ability to gain insights into the production and achieve similar production optimizations and problem preventions as data science experts could. The main contributions of this article are on the one hand the best practice of how production lines of the wood and beverage industry could be made ready for smart manufacturing, but also an approaches that enable non-data scientists, especially plant workers, to perform sufficient analysis about optimal production settings and early problem cause identification.},

keywords = {Human-Computer Interaction, Internet of Things, Smart Manufacturing, User-Centered Design, Visual Analytics},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Nazemi2019c,

title = {A Visual Analytics Approach for Analyzing Technological Trends in Technology and Innovation Management},

author = {Kawa Nazemi and Dirk Burkhardt},

editor = {George Bebis and Richard Boyle and Bahram Parvin and Darko Koracin and Daniela Ushizima and Sek Chai and Shinjiro Sueda and Xin Lin and Aidong Lu and Daniel Thalmann and Chaoli Wang and Panpan Xu},

url = {https://dirk.burkhardt.xyz/wp-content/uploads/2019/10/2019isvc.pdf, Paper as PDF

https://dx.doi.org/10.5281/zenodo.3473065, doi:10.5281/zenodo.3473065 (Poster)},

doi = {10.1007/978-3-030-33723-0_23},

isbn = {978-3-030-33723-0},

year  = {2019},

date = {2019-10-09},

booktitle = {Advances in Visual Computing},

pages = {283--294},

publisher = {Springer International Publishing},

address = {Cham},

abstract = {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.},

keywords = {Artificial Intelligence, Data Analytics, Human Factors, Human-Centered Interfaces, Human-Computer Interaction, Information Visualization, Intelligent Systems, maschine learning, Visual Analytics},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Burkhardt2019b,

title = {A Mobile Visual Analytics Approach for Instant Trend Analysis in Mobile Contexts},

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

url = {https://dirk.burkhardt.xyz/wp-content/uploads/2019/09/2019vare-i.pdf, Dowload as PDF},

doi = {  10.5281/zenodo.3473041},

isbn = {978-88-85741-41-6},

year  = {2019},

date = {2019-09-18},

booktitle = {5th International Conference of the Virtual and Augmented Reality in Education (VARE2019)},

pages = {11--19},

publisher = {CAL-TEK SRL},

address = {Rende, Italy},

abstract = {The awareness of market trends becomes relevant for a broad number of market branches, in particular the more they are challenged by the digitalization. Trend analysis solutions help business executives identifying upcoming trends early. But solid market analysis takes their time and are often not available on consulting or strategy discussions. This circumstance often leads to unproductive debates where no clear strategy, technology etc. could be identified. Therefore, we propose a mobile visual trend analysis approach that enables a quick trend analysis to identify at least the most relevant and irrelevant aspects to focus debates on the relevant options. To enable an analysis like this, the exhausting analysis on powerful workstations with large screens has to adopted to mobile devices within a mobile behavior. Our main contribution is the therefore a new approach of a mobile knowledge cockpit, which provides different analytical visualizations within and intuitive interaction design.},

note = {Nominated for Best Paper Award},

keywords = {Business Analytics, Decision Support Systems, Human-Computer Interaction, Information Visualization, Mobile Devices, Mobile Visual Analytics, Visual Trend Analysis},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Burkhardt2010,

title = {Intuitive Semantic-Editing for regarding Needs of Domain-Experts},

author = {Dirk Burkhardt and Cristian Erik Hofmann and Kawa Nazemi and Christian Stab and Matthias Breyer and Dieter W. Fellner},

editor = {J. Herrington and C. Montgomerie},

url = {https://dirk.burkhardt.xyz/wp-content/uploads/2018/11/2010edmedia-i.pdf, Paper as PDF

https://www.learntechlib.org/primary/p/34735/, DigLib Site},

isbn = {978-1-880094-81-5},

year  = {2010},

date = {2010-06-29},

booktitle = {Proceedings of ED-MEDIA 2010--World Conference on Educational Multimedia, Hypermedia & Telecommunications},

pages = {860--869},

publisher = {Association for the Advancement of Computing in Education (AACE)},

address = {Waynesville, NC},

abstract = {Ontologies are used to represent knowledge and their semantic information from different topics, to allow users a better way to explore knowledge and find information faster, because of the data-structuring. To achieve a well filled knowledgebase, editors have to be used, to enter new and to edit existing information. But most of the existing ontology-editors are designed for experienced ontology-experts. Experts from other topic fields e.g. physicians are often novices in the area of ontology-creating, they need adequate tools, which hide the complexity of ontology-structures. In the area of e-learning experts are also teachers as well. In this paper we will present a method, how the needs of domain-experts can be regarded and so an editor can designed, which allows an editing and adding of information by users without having experiences of creating ontologies. With such an editor domain-experts are able to commit their expert-knowledge into the ontology.},

keywords = {Human-Computer Interaction, Ontology, Semantic Editing, Semantic Web, User-Centered Interaction},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Hofmann2010,

title = {Towards a Workflow-based Design of Multimedia Annotation Systems},

author = {Cristian Erik Hofmann and Dirk Burkhardt and Matthias Breyer and Kawa Nazemi and Christian Stab and Dieter W. Fellner},

editor = {J. Herrington and C. Montgomerie},

url = {https://dirk.burkhardt.xyz/wp-content/uploads/2018/11/2010edmedia-ii.pdf, Paper as PDF

https://www.learntechlib.org/primary/p/34788/, DigLib Site},

isbn = {978-1-880094-81-5 },

year  = {2010},

date = {2010-06-29},

booktitle = {Proceedings of ED-MEDIA 2010 - World Conference on Educational Multimedia, Hypermedia & Telecommunications},

pages = {1224--1233},

publisher = {Association for the Advancement of Computing in Education (AACE)},

address = {Waynesville, NC},

abstract = {Annotation techniques for multimedia contents have found their way into multiple areas of daily use as well as professional fields. A large number of research projects can be assigned to different specific subareas of digital annotation. Nevertheless, the annotation process, bringing out multiple workflows depending on different application scenarios, has not sufficiently been taken into consideration. A consideration of respective processes and workflows requires detailed knowledge about practices of digital multimedia annotation. In order to establish fundamental groundwork towards workflow-related research, this paper presents a comprehensive process model of multimedia annotation which results from a conducted empirical study. Furthermore, we provide a survey of the tasks that have to be accomplished by users and computing devices, tools and algorithms that are used to handle specific tasks, and types of data that are transferred between workflow steps. These aspects are assigned to the identified sub-processes of the model.},

keywords = {Algorithm, Human-Computer Interaction, Multimedia Annotation System, Workflow},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Burkhardt2009,

title = {Technology Support for Analyzing User Interactions to Create User-Centered Interactions},

author = {Dirk Burkhardt and Kawa Nazemi and Nadeem Bhatti and Christoph Hornung},

editor = {Constantine Stephanidis},

url = {https://dirk.burkhardt.xyz/wp-content/uploads/2018/11/2009hcii.pdf, Paper as PDF

http://2009.hci.international/, Conference Site},

doi = {10.1007/978-3-642-02707-9_1},

isbn = {978-3-642-02707-9},

year  = {2009},

date = {2009-01-01},

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

volume = {5614},

pages = {3--12},

publisher = {Springer Berlin Heidelberg},

address = {Berlin, Heidelberg},

abstract = {Alternative interaction devices become more important in the communication between users and computers. Parallel graphical User Interfaces underlay a continuous development and research. But today does no adequate connection exist between these both aspects. So if a developer wants to provide an alternative access over more intuitive interaction devices, he has to implement this interaction-possibility on his own by regarding the users perception. A better way to avoid this time-consuming development-process is presented in this paper. This method can easy implement by a developer and users get the possibility to interact on intuitive way.},

keywords = {Gesture Recognition, Human-Computer Interaction, User-Centered Interaction},

pubstate = {published},

tppubtype = {inproceedings}

}