Automated Refined Comic Generation: From Investigation Provenance to Data Comics using Visual Narrative Structure
| dc.contributor.author | Roggenbuck, Kay Arne | en_US |
| dc.contributor.author | Vilanova, Anna | en_US |
| dc.contributor.author | Elzen, Stef van den | en_US |
| dc.contributor.editor | Diehl, Alexandra | en_US |
| dc.contributor.editor | Kucher, Kostiantyn | en_US |
| dc.contributor.editor | Médoc, Nicolas | en_US |
| dc.date.accessioned | 2025-05-26T06:54:37Z | |
| dc.date.available | 2025-05-26T06:54:37Z | |
| dc.date.issued | 2025 | |
| dc.description.abstract | Visual analytics has become an important approach for criminal investigations due to the increasing amount of physical and digital data related to cases. Although state-of-the-art tools are used daily to search for evidence in the data and report the investigator's findings, building such reports remains a labor-intensive manual process. Furthermore, these reports commonly contain only a manually selected set of the investigation results, but not how these results were derived. This lack of information about the chain of evidence not only weakens reproducibility and transparency, but also makes the evidence vulnerable by jurists in court. Instead of textual reports we believe annotated visuals of the actual data exploration process better portray what the investigators did and how they came to the evidence. To this end, we introduce ARC, a framework for automatically generating comic summaries for digital investigations based on the Visual Narrative Structure from comic theory. Especially, ARC is the first framework that fully automatically generates and refines comic summaries based on interactions with investigation tools. | en_US |
| dc.description.sectionheaders | Posters | |
| dc.description.seriesinformation | EuroVis 2025 - Posters | |
| dc.identifier.doi | 10.2312/evp.20251122 | |
| dc.identifier.isbn | 978-3-03868-286-8 | |
| dc.identifier.pages | 3 pages | |
| dc.identifier.uri | https://doi.org/10.2312/evp.20251122 | |
| dc.identifier.uri | https://diglib.eg.org/handle/10.2312/evp20251122 | |
| dc.publisher | The Eurographics Association | en_US |
| dc.rights | Attribution 4.0 International License | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | CCS Concepts: Human-centered computing → Visual analytics; Visualization techniques | |
| dc.subject | Human centered computing → Visual analytics | |
| dc.subject | Visualization techniques | |
| dc.title | Automated Refined Comic Generation: From Investigation Provenance to Data Comics using Visual Narrative Structure | en_US |