Annotations in Different Steps of Visual Analytics

Christoph Schmidt, Bastian Grundel, Heidrun Schumann, Paul Rosenthal

2021

Abstract

Annotations in Visual Analytics (VA) have become a common means to support the analysis by integrating additional information into the VA system. Here, annotations often differ between the individual steps of VA. For example, during data preprocessing it may be necessary to add information on the data, such as redundancy or discrepancy information, while annotations, used during exploration, often refer to the externalization of findings and insights. Describing the particular needs for these step-dependent annotations is challenging. To tackle this issue, we examine the data preprocessing, data cleansing, and data exploration steps for the analysis of heterogeneous and error prone data in respect to the design of specific annotations. By that, we describe their peculiarities for each step in the analysis, and thus aim to improve the visual analytics approach on clinical data. We show the applicability of our annotation concept by integrating it into an existing visual analytics tool to analyze and annotate data from the ophthalmic domain. In interviews and application sessions with experts, we assess the usefulness of our annotation concept for the analysis of the visual acuity development for patients, undergoing a specific therapy.

Paper Citation

in Harvard Style

Schmidt C., Grundel B., Schumann H. and Rosenthal P. (2021). Annotations in Different Steps of Visual Analytics. In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 3: IVAPP; ISBN 978-989-758-488-6, SciTePress, pages 155-163. DOI: 10.5220/0010198001550163

in Bibtex Style

@conference{ivapp21,
author={Christoph Schmidt and Bastian Grundel and Heidrun Schumann and Paul Rosenthal},
title={Annotations in Different Steps of Visual Analytics},
booktitle={Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 3: IVAPP},
year={2021},
pages={155-163},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010198001550163},
isbn={978-989-758-488-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 3: IVAPP
TI - Annotations in Different Steps of Visual Analytics
SN - 978-989-758-488-6
AU - Schmidt C.
AU - Grundel B.
AU - Schumann H.
AU - Rosenthal P.
PY - 2021
SP - 155
EP - 163
DO - 10.5220/0010198001550163
PB - SciTePress