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Aug 26, 2024 - EXC IntCDC Research Project 10 'Co-Design from Architectural, Social and Computational Perspectives'
Öney, Seyda; Abdelaal, Moataz; Kurzhals, Kuno; Betz, Paul; Kropp, Cordula; Weiskopf, Daniel, 2024, "Supplemental Material for: Testing the Test: Observations When Assessing Visualization Literacy of Domain Experts", https://doi.org/10.18419/darus-4448, DaRUS, V1, UNF:6:acOzV3rGb0G3gj7FIA/o4w== [fileUNF]
These documents contain supplemental material for the paper "Testing the Test: Observations When Assessing Visualization Literacy of Domain Experts" which was conditionally accepted at the BELIV 2024 Workshop in conjunction with the IEEE VIS 2024 Conference. The CSV file contains... |
Aug 26, 2024 -
Supplemental Material for: Testing the Test: Observations When Assessing Visualization Literacy of Domain Experts
Tabular Data - 51.3 KB - 5 Variables, 307 Observations - UNF:6:acOzV3rGb0G3gj7FIA/o4w==
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Aug 26, 2024 -
Supplemental Material for: Testing the Test: Observations When Assessing Visualization Literacy of Domain Experts
Adobe PDF - 3.0 MB -
MD5: d8ad02189522a6f2722308f90ceb1749
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Aug 15, 2024 - EXC IntCDC Research Project 18 'Holistic Quality Model for Extension of Existing Buildings'
Di Bari, Roberta; Lauer, Anja Patricia Regina; Schlopschnat, Christoph; Treml, Simon; Opgenorth, Nils; Skoury, Lior; Stark, Tim; Bechert, Simon; Göbel, Monika; Wagner, Hans Jakob; Wood, Dylan; Leistner, Philip; Knippers, Jan; Menges, Achim; Sawodny, Oliver; Wortmann, Thomas, 2024, "Computational design and robotic fabrication for high environmental quality timber constructions: the livMatS Biomimetic Shell case study", https://doi.org/10.18419/darus-4434, DaRUS, V1
The dataset includes the raw data and the corresponding report for the life cycle assessment of the building demonstrator 'livMatS Biomimetic Shell' (Website). The pressure on the construction industry to reduce its environmental impact is leading practitioners to investigate the... |
MS Excel Spreadsheet - 103.7 KB -
MD5: c80c9a1a9709136d94b8476fc2ecdd1b
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MD5: 9e88954438599028d441f5a7813a347d
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MD5: 530dfe5a82d1c21dc6e4e2764c6d9c2e
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MD5: 783a0b75957e1b572b199e3a6b7cb3e2
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