A descriptive attribute-based framework for annotations in data visualization

Vanhulst, Pierre (Human-IST Institute, University of Fribourg, Switzerland) ; Evequoz, Florian (Human-IST Institute, Fribourg, Switzerland; University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis)) ; Tuor, Raphael (Human-IST Institute, Switzerland) ; Lalanne. Denis (Human-IST Institute, Switzerland)

Annotations are observations made during the exploration of a specific data visualization, which can be recorded as text or visual data selection. This article introduces a classification framework that allows a systematic description of annotations. To create the framework, a real dataset of 302 annotations authored by 16 analysts was collected. Then, three coders independently described the annotations by eliciting categories that emerged from the data. This process was repeated for several iterative phases, until a high inter-coder agreement was reached. The final descriptive attribute-based framework comprises the following dimensions: insight on data, multiple observations, data units, level of interpretation, co-references and detected patterns. This framework has the potential to provide a common ground to assess the expressiveness of different types of visualization over the same data. This potential is further illustrated in a concrete use case.


Keywords:
Faculty:
Economie et Services
School:
HEG-VS
Institute:
Institut Informatique de gestion
Subject(s):
Informatique
Publisher:
Cham, Springer
Date:
2019-07
Cham
Springer
Pagination:
pp. 143-166
Published in:
Computer vision, imaging and computer graphics theory and applications : 13th International Joint Conference, VISIGRAPP 2018 Funchal–Madeira, Portugal, January 27–29, 2018, Revised Selected Papers
Series Statement:
Communications in Computer and Information Science, vol. 997
Author of the book:
Bechmann, Dominique ; ed. ; University of Strasbourg France
et al.
DOI:
ISSN:
1865-0929
ISBN:
978-3-030-26755-1
Appears in Collection:

Note: The status of this file is: restricted


 Record created 2019-10-24, last modified 2019-11-28

Fulltext:
Download fulltext
PDF.PDF

Rate this document:

Rate this document:
1
2
3
 
(Not yet reviewed)