High-dimensional data analysis requires dealing with numerous challenges, such as selecting meaningful dimensions, finding relevant projections, and removing noise. As a result, the extraction of relevant and meaningful information from high-dimensional data is a difficult problem. This project aims at advancing the field of quality-metric-driven data visualisation with the central research question of how to quantify the quality of transformations and mappings of high-dimensional data for visual analytics.
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51 to 55 of 55 Results
hassan.tab
Jun 30, 2022 - Replication Data for: "ParSetgnostics: Quality Metrics for Parallel Sets"
Tabular Data - 33.3 KB - 4 Variables, 647 Observations - UNF:6:452w0FICojAEWwAMO7rPdQ==
A categorical dataset reconstructed from Hassan et al. [HP14] describing data storage security and cost data. It is manually reconstructed from the Parallel Sets visualization in Figure 2 of the publication. The reconstruction method is described in the Process Metadata. The publication does not provide a source for the underlying data. [HP14] Sab...
koh.tab
Jun 30, 2022 - Replication Data for: "ParSetgnostics: Quality Metrics for Parallel Sets"
Tabular Data - 44.1 KB - 3 Variables, 1077 Observations - UNF:6:jm91tihAXgNNRcyGYtStlA==
A categorical dataset reconstructed from Koh et al. [KSDK11] describing property sales information from Singapor. It is manually reconstructed from the Parallel Sets visualization in Figure 4 of the publication by Koh et al. The reconstruction method is described in the Process Metadata. The publication does not provide a source for the underlying...
rogers-1.tab
Jun 30, 2022 - Replication Data for: "ParSetgnostics: Quality Metrics for Parallel Sets"
Tabular Data - 23.8 KB - 3 Variables, 1013 Observations - UNF:6:feip2wKBPgQTWR5JZ3oK8g==
The first categorical dataset reconstructed from Rogers et al. describing the results of a HCI study. It is manually reconstructed from the Parallel Sets visualization in Figure 1 (a) of the publication by Rogers et al. [RWH*16] The reconstruction method is described in the Process Metadata. The publication does not provide a source for the underly...
rogers-2.tab
Jun 30, 2022 - Replication Data for: "ParSetgnostics: Quality Metrics for Parallel Sets"
Tabular Data - 23.1 KB - 3 Variables, 1012 Observations - UNF:6:UPfzwP4EP7X8E9Uk4KxFbQ==
The second categorical dataset reconstructed from Rogers et al. describing the results of a HCI study. It is manually reconstructed from the Parallel Sets visualization in Figure 1 (b) of the publication by Rogers et al. [RWH*16] The reconstruction method is described in the Process Metadata. The publication does not provide a source for the underl...
schaetzle.tab
Jun 30, 2022 - Replication Data for: "ParSetgnostics: Quality Metrics for Parallel Sets"
Tabular Data - 15.7 KB - 2 Variables, 1021 Observations - UNF:6:E70xYkGzgv0fjFoXL7T9uA==
A categorical dataset reconstructed from Schätzle et al. [SDB*19] describing language change in Icelandic. It is manually reconstructed from the Parallel Sets visualization in Figure 3 of the publication. The reconstruction method is described in the Process Metadata. The publication does not provide a source for the underlying data. [SDB*19] Chri...
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