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.

Migration Data – The Influence of Narrative Patterns on Attitude

Datadriven Storytelling in the Financial Sector

Maritime Trade Flows – Storytelling and transshipment of containers

DATAVISUALIZATION: A History Of Terror in the course of time

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.

Making Open Data Accessible: Visualizing Demographic Information

Visualizing Demographic Data: Evaluating Dot Maps

Towards bridging the gap between Privacy Terms and Society

DATA AND SOCIETY: Ethical aspects of datavisualization

2020

 

Designing a personalized health dashboard: an interdisciplinary and participatory approach.
Miriam Weijers, Carolien Bastiaens, Frans Feron, Kay Schroeder
in Journal, JMIR – Journal of Medical Internet Research, under review
http://dx.doi.org/10.2196/24061
Evaluation of a Financial Portfolio Visualization using Computer Displays and Mixed Reality Devices with Domain Experts
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
Bridging the gap between machine modelling and engineers – User-centred data dashboarding in condition-based monitoring,
Rowan Foreman
Thesis, Zuyd University of Applied Sciences 2020
Potentiale der Informationsvisualisierung im Datenschutz – eine kommunikationswissenschaftliche Betrachtung
Kay Schroeder
Bookchapter in „Datenrecht in der Digitalisierung“
Erich Schmidt Verlag (2020)
ISBN 978-3-503-18782-9
Bridging the gap between Data and Humans
Kay Schroeder
Inaugurational speech
Zuyd University of Applied Sciences
Datavisualization in business processes with focus on Human-Data interaction,
Rowan Koenen
Thesis, Zuyd University of Applied Sciences 2020
Towards bridging the gap between Privacy Terms and Humans through Information Visualization
Kay Schroeder, Batoul Ajdadilish, André Calero Valdez
in Journal, PinG (2020)
https://doi.org/10.37307/j.2196-9817.2020.01.17

 

2019

 

The Evolution of Enterprise Architecture in Scopes of Digital Transformation
A.L. Levina, A.D. Borremans, A.A. Lepekhin, K.Schroeder
in Proceedings of the DTMIS-2019
https://doi:10.1088/1757-899X/940/1/012019
Live view plaats delict – evaluating techology acceptance and user experience in a instructed reality scenario
Kay Schroeder, Ellen Pijpers
in Study, HDI Lab, 2020
Temporal Exploration of AIS Trajectory Data – Visualizing Movement and Density
Rowan Foreman
Study, Zuyd University of Applied Sciences
AIR Portal – APG Investment Reporting
Kenny Jeurissen
Thesis, Zuyd University of Applied Sciences, 2019
Virtual Reality – Limitless Possibilities for Service Design
Benjamin Lucas, Kay Schroeder
in American Marketing Association – SERVSIG