A Practical Approach to Provenance Capturing for Reproducible Visual Analytics at an Ocean Research Institute
| dc.contributor.author | Bernstetter, Armin | en_US |
| dc.contributor.author | Kwasnitschka, Tom | en_US |
| dc.contributor.author | Peters, Isabella | en_US |
| dc.contributor.editor | Angelini, Marco | en_US |
| dc.contributor.editor | El-Assady, Mennatallah | en_US |
| dc.date.accessioned | 2023-06-10T06:09:14Z | |
| dc.date.available | 2023-06-10T06:09:14Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | Reproducibility - and the lack thereof - has been an important topic for some time in the field of Human-Computer Interaction. Visual analytics workflows and in extension immersive analytics workflows are no exception there and benefit from being more transparent and reproducible. At our research institute, domain scientists in ocean research are using interactive visualization workflows for sensemaking processes. We are building a framework that supports these workflows by shifting the focus from solely lying on the end-product (i.e. published insights and visualizations) towards the generation process. We do this by capturing, organizing, and visualizing provenance artifacts using a modular and extensible web-based application. We not only apply this framework to conventional 2D display-based work but also workflows inside a unique and spatially immersive projection dome. | en_US |
| dc.description.sectionheaders | Decision-making and Explanation | |
| dc.description.seriesinformation | EuroVis Workshop on Visual Analytics (EuroVA) | |
| dc.identifier.doi | 10.2312/eurova.20231095 | |
| dc.identifier.isbn | 978-3-03868-222-6 | |
| dc.identifier.issn | 2664-4487 | |
| dc.identifier.pages | 43-48 | |
| dc.identifier.pages | 6 pages | |
| dc.identifier.uri | https://doi.org/10.2312/eurova.20231095 | |
| dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/eurova20231095 | |
| 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 -> Scientific visualization; Visual analytics; Collaborative interaction | |
| dc.subject | Human centered computing | |
| dc.subject | Scientific visualization | |
| dc.subject | Visual analytics | |
| dc.subject | Collaborative interaction | |
| dc.title | A Practical Approach to Provenance Capturing for Reproducible Visual Analytics at an Ocean Research Institute | en_US |