Model-driven production of data-centric infographics: An application to the impact measurement domain

Sergio España*, Vijanti Ramautar*, Sietse Overbeek, Tijmen Derikx

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review


Context and motivation: Infographics are an engaging medium for communication. Sometimes, organisations create several infographics with the same graphic design and different data; e.g., when reporting on impact measurement. Question/problem: The conventional process to produce such recurrent data-centric infographics causes rework related to the disconnection between software environments. Principal ideas/results: This paper redesigns the process following the model-driven engineering paradigm. We present a domain-specific language to model infographics, and an interpreter that generates the infographics automatically. We have been able to model and generate infographics that report impact measurement results, which the participants of a comparative experiment have found as attractive as the original ones, and that are hard, but not impossible, to distinguish from them. Contribution: An innovative model-driven approach that eliminates the software environment disconnection and could facilitate the use of data-centric infographics for reporting purposes.
Original languageEnglish
Title of host publicationResearch Challenges in Information Science
Subtitle of host publication16th International Conference, RCIS 2022, Barcelona, Spain, May 17–20, 2022, Proceedings
EditorsRenata Guizzardi, Jolita Ralyté, Xavier Franch
Place of PublicationCham, Switzerland
Number of pages18
ISBN (Print)9783031057595
Publication statusPublished - 2022

Publication series

NameLecture Notes in Business Information Processing
Volume446 LNBIP
ISSN (Print)1865-1348
ISSN (Electronic)1865-1356


  • Domain-specific language
  • Infographics
  • Impact measurement
  • Ethical social and environmental accounting
  • Model-driven engineering
  • Experiment


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