SFB/Transregio 161 "Quantitative Methods for Visual Computing"

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3,571 to 3,580 of 3,661 Results

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. [SDB19] 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. [SDB19] Chri...
Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering" Jun 21, 2022 - SFB-TRR 161 A07 "Visual Attention Modeling for Optimization of Information Visualizations" Wang, Yao; Bulling, Andreas, 2022, "Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"", https://doi.org/10.18419/DARUS-2826, DaRUS, V1, UNF:6:AuvgRc09o1rESd63AqlW9Q== [fileUNF] Despite its importance for assessing the effectiveness of communicating information visually, fine-grained recallability of information visualisations has not been studied quantitatively so far. We propose a question-answering paradigm to study visualisation recallability and present VisRecall -- a novel dataset consisting of 200 information visual...
10_blur.zip Jun 21, 2022 - Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering" ZIP Archive - 4.6 MB - MD5: 4f82bd8d7e56649dc799dc0153f35189
10.zip Jun 21, 2022 - Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering" ZIP Archive - 3.7 MB - MD5: 0302e172f0cdb8cef6a84f4ecfb31caf
1_blur.zip Jun 21, 2022 - Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering" ZIP Archive - 2.3 MB - MD5: 01535147f2b09ae9ce65b154af5f2ba4
1.zip Jun 21, 2022 - Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering" ZIP Archive - 1.5 MB - MD5: 617d99e6308bb96a9ae502bb01c9d0f8
2_blur.zip Jun 21, 2022 - Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering" ZIP Archive - 4.0 MB - MD5: a12312bef04db29bba518c53b386f684

koh.tab

Jun 30, 2022 - Replication Data for: "ParSetgnostics: Quality Metrics for Parallel Sets"

Tabular Data - 44.1 KB - 3 Variables, 1077 Observations -

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 -

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 -

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 -

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...

Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"

Jun 21, 2022 - SFB-TRR 161 A07 "Visual Attention Modeling for Optimization of Information Visualizations"

Wang, Yao; Bulling, Andreas, 2022, "Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"", https://doi.org/10.18419/DARUS-2826, DaRUS, V1, UNF:6:AuvgRc09o1rESd63AqlW9Q== [fileUNF]

Despite its importance for assessing the effectiveness of communicating information visually, fine-grained recallability of information visualisations has not been studied quantitatively so far. We propose a question-answering paradigm to study visualisation recallability and present VisRecall -- a novel dataset consisting of 200 information visual...

10_blur.zip

Jun 21, 2022 - Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"

ZIP Archive - 4.6 MB -

10.zip

Jun 21, 2022 - Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"

ZIP Archive - 3.7 MB -

1_blur.zip

Jun 21, 2022 - Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"

ZIP Archive - 2.3 MB -

1.zip

Jun 21, 2022 - Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"

ZIP Archive - 1.5 MB -

2_blur.zip

Jun 21, 2022 - Data for "VisRecall: Quantifying Information Visualisation Recallability via Question Answering"

ZIP Archive - 4.0 MB -

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