The improvement of the human ability to manage data, extract information and gain knowledge from it is of vital importance for a society in the course of digitization. Visualisation is an effective way to enhance the human capabilities to extract and interpret information as also to support human decision making. within the human data interaction group we focus on three research lines:
Human Data Interaction
Due to digitisation, the correct interpretation and communication of data is taking a key role in more and more areas. Data visualisation offers new opportunities to improve the accessibility of data and algorithms – in the exploration as well as presentation scenarios. In addition, new techniques and contexts such as virtual reality and augmented reality or multimodal interactions like audio and physical interactions enables us to interact with data in novel ways. Within this field of research we investigate how the interaction between people and data can be enhanced by new methods and contexts.
Storytelling – Data in context
Though there are various instruments with which we can explore data, techniques to annotate data, to summarize it narratively or to employ storytelling are still relatively underdeveloped. Based on the exponential growth of global data, the ever-increasing availability and the resulting need thereof to use this data, it’s important to research, describe and publish methods that simplify the correct usage of data (understanding, background, assumptions, applicability, implications). There is a need to develop methods to summarize ‘narratives’. A core element thereof are methods to contextualise data.
Data and Society
The amount of available data is ever-increasing. The politics of ‘open data’ promises more transparency and more democracy, especially concerning government and public services data. Currently, working with and understanding this data carries (too) high demands for large parts of the population. As a result of this, the opposite becomes true. Individuals or companies use and/or interpret the data for their own interests. ‘Open data’ can only achieve the intended goal when all individuals are provided with tools that help them to understand data that is interesting/relevant to them. The development of such tools for various audiences in cooperation with the partner institutions is an objective of the knowledge domain.
Nowadays, data can be collected and used in new contexts. It is tempting to assume that existing problems can be solved with this data. This may be partially true, however, “If you only have a hammer (data), everything appears to be a nail (the problem)”. And so, a frequent occurrence is that only certain aspects (those which are covered by data and/or can be solved with data) are tackled. This subsequently leads to a dominance of statistical methods and a focus on the status quo at the expense of systematic approaches. It’s vital to critically review and to safeguard the role of data – and in particular the role of data visualisation – so that qualitative approaches – where needed – may flourish and be incorporated in the visualisation.
Betty Ajdadilish, Steffi Kohl, Kay Schröder
Eurographics Conference on Visualization (EuroVis) 2022
https://doi.org/10.2312/evp.20221136
Kay Schröder, Poornima Belavadi, Martina Ziefle, Andre Calero- Valdez
International Conference on Human-Computer Interaction. Lecture Notes in Computer Science, vol 13320. Springer, Cham.
https://doi.org/10.1007/978-3-031-06018-2_28
Steffi Kohl, Kay Schroeder, Mark Graus, Emir Efendic, Jos Lemmink
In Creativity and Cognition (C&C ’22). ACM – Association for Computing Machinery, New York, NY, USA, 118–124.
https://doi.org/10.1145/3527927.3532810
Ed Overes, Elizaveta Pliushch, Jiska Balk
International Scientific Conference “Digital Transformation on Manufacturing, Infrastructure and Service” DTMIS 2022.
Kay Schröder, Steffi Kohl, Frederique de Jong, Marco Putzu, Martina Ziefle, Andre Calero-Valdez
in Information Visualization. International Conference on Human-Computer Interaction. Lecture Notes in Computer Science, vol 13320. Springer, Cham.
https://doi.org/10.1007/978-3-031-06018-2_29
André Calero Valdez, Emil N. Iftekhar, Robert Böhm, Sarah Cuschieri, Thomas Czypionka, Uga Dumpis, Giulia Giordano, Claudia Hanson, Zdenek Hel, Anna Helova, Ilona Kickbusch, Lilian Kojan, Mirjam Kretzschmar, Tyll Krueger, Jenny Krutzinna, Berit Lange, Jeffrey V Lazarus, Helena Machado, Martin McKee, Kai Nagel, Miquel Oliu-Barton, Matjaž Perc, Elena Petelos, Nedyu Popivanov, Bary Pradelski, Barbara Prainsack, Kay Schroeder, Sotirios Tsiodras, Paul Wilmes, Guntram Wolff
BMJ journal 2022
https://doi.org/10.1136/bmj.o90
Kay Schröder, Steffi Kohl, Betty Ajdadilish
International Conference on Human-Computer Interaction. Lecture Notes in Computer Science, vol 13320. Springer, Cham.
https://doi.org/10.1007/978-3-031-06018-2_27
Enrico Pezzella, Ed Overes
International Scientific Conference “Digital Transformation on Manufacturing, Infrastructure and Service” DTMIS 2022
Kay Schröder, Steffi Kohl
International Conference on Human-Computer Interaction. Lecture Notes in Computer Science, vol 13320. Springer, Cham.
https://doi.org/10.1007/978-3-031-05890-5_22
Miriam Weijers, Carolien Bastiaens, Frans Feron, Kay Schroeder
in Journal, JMIR – Journal of Medical Internet Research, 2021
https://doi.org/10.2196/24061
G.Y. Silkina, A.L. Kutuzov, S.Y. Shevchenko, E. C. Overes
GDTM conference, 2021
Pavlov, N., Zotova, E., Shaban, A., Overes, E
DTMIS ’20: Proceedings of the International Scientific Conference – Digital Transformation on Manufacturing, Infrastructure and Service
November 2020; Article No.: 51; Pages 1–5
https://doi.org/10.1145/3446434.3446537
Capo, D., Levina, A., Dubgorn, A., & Schröder, K.
IOP Conference Series: Materials Science and Engineering, Volume 1001, International Scientific and Practical Conference Environmental Risks and Safety in Mechanical Engineering(ERSME-2020) 20-22 October 2020
https://doi.org/10.1088/1757-899X/1001/1/012044
K. Schroeder, B. Ajdadilish, A.P.Henkel, A.Calero Valdez
in Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, CHI ’20, pages 8, ACM, New York, NY, USA, April 202
https://doi.org/10.1145/3313831.3376556
Rowan Foreman
Thesis, Zuyd University of Applied Sciences 2020
Kay Schroeder
Bookchapter in „Datenrecht in der Digitalisierung“
Erich Schmidt Verlag (2020)
ISBN 978-3-503-18782-9
Kay Schroeder
Inaugurational speech
Zuyd University of Applied Sciences
Rowan Koenen
Thesis, Zuyd University of Applied Sciences 2020
Kay Schroeder, Batoul Ajdadilish, André Calero Valdez
in Journal, PinG (2020)
https://doi.org/10.37307/j.2196-9817.2020.01.17
A.L. Levina, A.D. Borremans, A.A. Lepekhin, K.Schroeder
in Proceedings of the DTMIS (2020)
https://doi:10.1088/1757-899X/940/1/012019
Kay Schroeder, Ellen Pijpers
in Study, HDI Lab, 2020
Rowan Foreman
Study, Zuyd University of Applied Sciences
Kenny Jeurissen
Thesis, Zuyd University of Applied Sciences
Benjamin Lucas, Kay Schroeder
in American Marketing Association – SERVSIG