dc.contributor.author | Hama, Layik | en_US |
dc.contributor.author | Beecham, Roger | en_US |
dc.contributor.author | Lomax, Nik | en_US |
dc.contributor.editor | Hoellt, Thomas | en_US |
dc.contributor.editor | Aigner, Wolfgang | en_US |
dc.contributor.editor | Wang, Bei | en_US |
dc.date.accessioned | 2023-06-10T06:34:36Z | |
dc.date.available | 2023-06-10T06:34:36Z | |
dc.date.issued | 2023 | |
dc.identifier.isbn | 978-3-03868-219-6 | |
dc.identifier.uri | https://doi.org/10.2312/evs.20231045 | |
dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/evs20231045 | |
dc.description.abstract | We introduce the Turing Geovisualisation Engine (TGVE), a web-based, open-source tool for interactive visualization and analysis of geospatial data. Built on ReactJS and R, TGVE is designed to support a variety of users, including data scientists and stakeholders who wish to engage the wider public with geospatial data. In this short paper, we provide an overview of TGVE's features and capabilities, including its ability to publish data and customize visualization settings using URL parameters. We highlight the potential impact of TGVE for geospatial research and offer examples of its use in practice. Additionally, we discuss current limitations of the tool and outline future work, such as improving compatibility with other geospatial data formats and addressing performance issues for large datasets. | en_US |
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: Information systems -> Geographic information systems; Web applications; Human-centered computing -> Visualization toolkits | |
dc.subject | Information systems | |
dc.subject | Geographic information systems | |
dc.subject | Web applications | |
dc.subject | Human centered computing | |
dc.subject | Visualization toolkits | |
dc.title | TGVE: a Tool for Analysis and Visualization of Geospatial Data | en_US |
dc.description.seriesinformation | EuroVis 2023 - Short Papers | |
dc.description.sectionheaders | 3D | |
dc.identifier.doi | 10.2312/evs.20231045 | |
dc.identifier.pages | 67-71 | |
dc.identifier.pages | 5 pages | |