Immersive Analytics of Heterogeneous Biological Data Informed through Need-finding Interviews
| dc.contributor.author | Ripken, Christine | en_US |
| dc.contributor.author | Tusk, Sebastian | en_US |
| dc.contributor.author | Tominski, Christian | en_US |
| dc.contributor.editor | Vrotsou, Katerina and Bernard, Jürgen | en_US |
| dc.date.accessioned | 2021-06-12T11:22:08Z | |
| dc.date.available | 2021-06-12T11:22:08Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | The goal of this work is to improve existing biological analysis processes by means of immersive analytics. In a first step, we conducted need-finding interviews with 12 expert biologists to understand the limits of current practices and identify the requirements for an enhanced immersive analysis. Based on the gained insights, a novel immersive analytics solution is being developed that enables biologists to explore highly interrelated biological data, including genomes, transcriptomes, and phenomes. We use an abstract tabular representation of heterogeneous data projected onto a curved virtual wall. Several visual and interactive mechanisms are offered to allow biologists to get an overview of large data, to access details and additional information on the fly, to compare selected parts of the data, and to navigate up to about 5 million data values in real-time. Although a formal user evaluation is still pending, initial feedback indicates that our solution can be useful to expert biologists. | en_US |
| dc.description.sectionheaders | Immersive Analytics and Interaction | |
| dc.description.seriesinformation | EuroVis Workshop on Visual Analytics (EuroVA) | |
| dc.identifier.doi | 10.2312/eurova.20211092 | |
| dc.identifier.isbn | 978-3-03868-150-2 | |
| dc.identifier.pages | 13-17 | |
| dc.identifier.uri | https://doi.org/10.2312/eurova.20211092 | |
| dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/eurova20211092 | |
| dc.publisher | The Eurographics Association | en_US |
| dc.subject | Human centered computing | |
| dc.subject | Visual analytics | |
| dc.subject | Computing methodologies | |
| dc.subject | Virtual reality | |
| dc.title | Immersive Analytics of Heterogeneous Biological Data Informed through Need-finding Interviews | en_US |