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DR-NTU (Data) is for research data deposit. For research paper deposits, please use DR-NTU.

Mission: DR-NTU (Data) curates, stores, preserves, makes available and enables the download of digital data generated by the NTU research community. The repository develops and provides guidance for managing, sharing, and reusing research data to promote responsible data sharing in support of open science and research integrity.

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What can be deposited? Final, non-sensitive research data from projects carried out at NTU. The uploaded content must not infringe upon the copyrights or other intellectual property rights, and must be void of all identifiable information.

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31 to 40 of 76,898 Results
NewData103_CompModelPh1a_BasicMixedModel_v2.R
Jun 24, 2026 - When AI Apologises: Dynamic Trust Updating and the Role of Personality
R Syntax - 301.5 KB - MD5: 3c01024e5268791e1539c08ee674e274
Code
Used to generate Big 5 related results.
NewData103_CompModelPh1aHuman_BasicMixedModel_v2.R
Jun 24, 2026 - When AI Apologises: Dynamic Trust Updating and the Role of Personality
R Syntax - 154.7 KB - MD5: 8b57c6a4da97f6725431c3b204a17811
Code
Used to generate main results with BIC as covariate.
ParticipantParams.tab
Jun 24, 2026 - When AI Apologises: Dynamic Trust Updating and the Role of Personality
Tabular Data - 15.9 KB - 8 Variables, 245 Observations - UNF:6:JGbH9j8s+4DzIbEvjtEIxw==
Data
Data containing individual participants' damage and recovery estimates.
Revised Chat Survey Extractor v2.3.R
Jun 24, 2026 - When AI Apologises: Dynamic Trust Updating and the Role of Personality
R Syntax - 22.4 KB - MD5: f16231e8e4a1614c5a82b9f310aae1e6
Code
Used to pre-process the raw (not anonymized - unavailable on repo due to confidentiality) data to sift out bad data.
STIAS_mean_condition_GAM_c2008_reference_v2_readable_contrasts.R
Jun 24, 2026 - When AI Apologises: Dynamic Trust Updating and the Role of Personality
R Syntax - 25.5 KB - MD5: 29c564400bc13c2dfae77b1a2f7c7b2f
Code
Redundant.
Replication Data for: A Semi-automated Framework for Global Detection of Previously Undocumented Submarine Calderas
Jun 23, 2026 - Andrea VEROLINO
Verolino, Andrea, 2026, "Replication Data for: A Semi-automated Framework for Global Detection of Previously Undocumented Submarine Calderas", https://doi.org/10.21979/N9/FLUTSL, DR-NTU (Data), V1, UNF:6:EAzbh2xcpwfeBnqGcBldVA== [fileUNF]
Here I provide the output original and filtered datasets from the Crater Detection Algorithm (CDA) we used to find submarine calderas globally. The original CDA used by Lee and Hogan (2021) only detects depressions, regardless of whether they are at the top of a mound or on a fla...
Filtered features dataset (n=514).tab
Jun 23, 2026 - Replication Data for: A Semi-automated Framework for Global Detection of Previously Undocumented Submarine Calderas
Tabular Data - 104.2 KB - 22 Variables, 514 Observations - UNF:6:b+JtDqGhWenSRPyv3RNxtQ==
Negative_dataset_(n=_55818).tab
Jun 23, 2026 - Replication Data for: A Semi-automated Framework for Global Detection of Previously Undocumented Submarine Calderas
Tabular Data - 8.2 MB - 15 Variables, 55818 Observations - UNF:6:ktNeLO53/Yf4eSfsKJ3BTg==
Positive_dataset_(n=_31617).tab
Jun 23, 2026 - Replication Data for: A Semi-automated Framework for Global Detection of Previously Undocumented Submarine Calderas
Tabular Data - 4.7 MB - 15 Variables, 31617 Observations - UNF:6:nbbUZNOyxOaTL1esMc3hnQ==
Vertical Greenery Buffers Against Stress: Evidence from Psychophysiological Responses in Virtual Reality
Jun 19, 2026 - QIU Lin
Chan, Sarah Hian May; Qiu, Lin; Ky, Phong Mai, 2026, "Vertical Greenery Buffers Against Stress: Evidence from Psychophysiological Responses in Virtual Reality", https://doi.org/10.21979/N9/WZNVEH, DR-NTU (Data), V1
This dataset contains all data related to the project: Vertical Greenery Buffers Against Stress: Evidence from Psychophysiological Responses in Virtual Reality. This research examines the stress-buffering effects of vertical greenery using virtual reality. 111 participants were r...
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