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Deposit, archive and share your final research data in DR-NTU (Data)

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

According to the NTU Research Data Policy:

  • The final research data used in establishing and validating research findings must be deposited in the NTU Data Repository or a recognized open access data repository no later than publication of the article.
  • The final research data from projects carried out at NTU shall be made available for sharing unless there are prior formal agreements with external collaborators and parties on non-disclosure or proprietary use of the data.

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DR-NTU (Data) is open to NTU faculty, research staff and students. We recommend faculty to create your researcher dataverse under your school/institute/research centre dataverse, and deposit your datasets in your own dataverse. For research staff and students, you may want to deposit your datasets in an appropriate dataverse as advised by your School, Supervisors or Principal Investigators.

Prior to deposit, familiarise yourself with DR-NTU (Data) Terms of Use, Restrictions and Licenses, and FAQs. The uploaded content must not infringe upon the copyrights or other intellectual property rights, not violate any laws, not contain software viruses, and must be void of all identifiable information.

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  1. Use the search box below to identify a suitable school/institute/research centre dataverse.
    If you can’t find a suitable school/institute/research centre dataverse, please contact us at Research Data Management team, NTU Library.
  2. For faculty, click 'Add Data' and select 'New Dataverse' to create your researcher/project dataverse if you don't have one yet.
    If you have an existing researcher/project dataverse that is appropriate for your use, you can start adding datasets to it, by clicking ‘Add Data’ and select ‘New Dataset’.

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1 to 10 of 978 Results
Oct 21, 2020 - Social and Affective Neuroscience
Azhari, Atiqah; Gabrieli, Giulio; Esposito, Gianluca, 2020, "Parent-Infant Sync: Play and Video", https://doi.org/10.21979/N9/R7D1UP, DR-NTU (Data), V1, UNF:6:rNmW6W5SOUKQrHAXH+Daqw== [fileUNF]
This repository contains hyperscanning fNIRS recordings of Mother-Child and Father-Child dyads engaging in a 10 minutes long free play session. 29 father–child dyads (18 boys, 11 girls; father’s age = 38.07 years, child’s age = 42.21 months) and 36 mother–child dyads (21 boys, 15...
Oct 20, 2020 - Tong Ping
Tong, Ping, 2020, "Replication Data for: The geometry of the subducted slab beneath Sumatra revealed by regional and teleseismic traveltime tomography", https://doi.org/10.21979/N9/JANKP9, DR-NTU (Data), V1
Seismic data used in Liu et al. (2020). The geometry of the subducted slab beneath Sumatra revealed by regional and teleseismic traveltime tomography
Oct 20, 2020 - Tong Ping
Tong, Ping, 2020, "Replication Data for: Slab morphology beneath northern Sumatra revealed by regional and teleseismic traveltime tomography", https://doi.org/10.21979/N9/EBQHFG, DR-NTU (Data), V1
Seismic data used in Liu, S., Suardi, I., Zheng, M., Yang, D., Huang, X., & Tong, P. (2019). Slab morphology beneath northern Sumatra revealed by regional and teleseismic traveltime tomography. Journal of Geophysical Research: Solid Earth, 124. https://doi.org/10.1029/2019JB01762...
Oct 19, 2020 - Guillaume Thibault
Thibault, Guillaume; Yap, Wei Sheng; Shuy, Peter Jr.; Marvalim, Charlie, 2020, "Yeast FIT2 homolog is necessary to maintain cellular proteostasis and membrane lipid homeostasis", https://doi.org/10.21979/N9/I7MXVP, DR-NTU (Data), V1
Lipid droplets (LDs) are implicated in conditions of lipid and protein dysregulation. The fat storage inducing transmembrane (FIT) family induces LD formation. Here, we establish a model system to study the role of S. cerevisiae FIT homologues (ScFIT), SCS3 and YFT2, in proteosta...
Oct 17, 2020 - Li Gen
Li, Gen; Fung, Tat Ching; Yu, Qing Jun, 2020, "Data for: A coupled dynamic cohesive zone model for FRP-concrete mixed-mode separation", https://doi.org/10.21979/N9/XPGZ4G, DR-NTU (Data), V1, UNF:6:Y1XfCZpxgmvzHHHJ9tXPjw== [fileUNF]
Raw data used in the experimental study of CFRP-concrete dynamic debonding behaviour
Oct 16, 2020 - Marcos
Kong, Tian Fook; Shen, Xinhui; Marcos; Yang, Chun; Ibrahim, Imran Halimi, 2020, "Replication Data for: Dielectrophoretic trapping and impedance detection of Escherichia coli, Vibrio cholera, and Enterococci bacteria", https://doi.org/10.21979/N9/7JPCOJ, DR-NTU (Data), V1
Replication Data for: Dielectrophoretic trapping and impedance detection of Escherichia coli, Vibrio cholera, and Enterococci bacteria
Oct 16, 2020 - Aron Meltzner Group
Wan, Jeannette Xiu Wen; Meltzner, Aron J.; Switzer, Adam D.; Lin Ke; Wang Xianfeng; Bradley, Sarah L.; Natawidjaja, Danny H.; Suwargadi, Bambang W.; Horton, Benjamin P., 2020, "Replication data for "Relative sea-level stability and the radiocarbon marine reservoir correction at Natuna Island, Indonesia, since 6400 yr BP"", https://doi.org/10.21979/N9/EOFRNH, DR-NTU (Data), V1, UNF:6:AKzHidTPjV5zZVy4VcdGbQ== [fileUNF]
Geochronology data, field notes, field photos, site surveys, GPS waypoints, tidal predictions, and other analysis files supporting the figures and tables in the Marine Geology publication.
Oct 16, 2020 - (Research Project) Numerical Studies to Model Combined Blast and Fragments Loading on Protective Structures
Del Linz, Paolo; Fung, Tat Ching; Lee, Chi King, 2020, "Replication Data for: Fixed supports and realistic blast studies", https://doi.org/10.21979/N9/ZIESQS, DR-NTU (Data), V1
LS-DYNA input files for close-in simulaiton (Chapter 3) with RHT KC CSCM models
Oct 16, 2020 - (Research Project) Numerical Studies to Model Combined Blast and Fragments Loading on Protective Structures
Del Linz, Paolo; Fan, Sau Cheong; Fung, Tat Ching; Lee, Chi King, 2020, "Replication Data for: Advanced scenario modelling", https://doi.org/10.21979/N9/LKWTJF, DR-NTU (Data), V1
LS-DYNA input files for blast8 model in Chapter 4; LS-DYNA input files for fragment shape effect ( cone- cylinder-sphere)
Oct 14, 2020 - Yolanda C Lin
Lin, Yolanda Chia-Yi, 2020, "Assessing the risk from natural 'Black Swans' through the lens of Counterfactual Analysis", https://doi.org/10.21979/N9/MVCHXR, DR-NTU (Data), V1, UNF:6:Xaf6E1hAFLQkddTrK4g6Lg== [fileUNF]
Dataset related to the study on assessing risk from natural "black swan" events through the lens of counterfactual analysis, as demonstrated by multiple case studies on past events in Singapore.
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