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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.

Deposit and publish data in DR-NTU (Data)

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.

To get started, ensure that you have an account, then:

  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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  4. How to upload data files in a dataset record

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1 to 10 of 920 Results
Aug 14, 2020 - Subramanian Periyal Srilakshmi
Subramanian Periyal Srilakshmi, 2020, "Related files for: Halide Perovskite Quantum Dots Photosensitized-Amorphous Oxide Transistors for Multimodal Synapses", https://doi.org/10.21979/N9/JFNION, DR-NTU (Data), V2
This dataset contains electrical and materials measurements for the analysis of the journal article titled "Halide Perovskite Quantum Dots Photosensitized-Amorphous Oxide Transistors for Multimodal Synapses"
Aug 13, 2020Marius Erdt
This dataverse hosts the data for the NRF funded project Fully automatic CityGML-compliant city model derivation on demand.
Liang Zhao-Xun(Nanyang Technological University)
Liang Zhao-Xun logo
Aug 12, 2020School of Biological Sciences (SBS)
Appointment: Associate Professor Research topics: • Molecular mechanism underlying bacterial pathogenesis and antibiotic resistance • Genomics-guided discovery of microbial natural products For more information, visit webpage.
Aug 12, 2020 - Fully automatic CityGML-compliant city model derivation on demand
Erdt, Marius; Zhang, Xingzi; Johan, Henry, 2020, "Source code to generate LoD1 CityGML models from city area maps", https://doi.org/10.21979/N9/FBWTIC, DR-NTU (Data), V2, UNF:6:zN4RTInDz93o+Dgg2Xk9oA== [fileUNF]
Application source code to generate level of detail 1 models in CityGML format from an input image. In particular, the image has to be a city area map showing ground plans of buildings.
Aug 11, 2020 - Fully automatic CityGML-compliant city model derivation on demand
Erdt, Marius; Zhang, Xingzi; Johan, Henry, 2020, "Source code and sample input CityGML models for automatic derivation of lower levels of detail", https://doi.org/10.21979/N9/9IIGWX, DR-NTU (Data), V1
This dataset contains the source code for automatically creating lower levels of detail from a given CityGML building model. E.g. a level of detail 3 model can be reduced to level of detail 0, 1, or 2. Exemplary sample models are included as well.
Aug 11, 2020 - Fully automatic CityGML-compliant city model derivation on demand
Erdt, Marius; Zhang, Xingzi; Johan, Henry, 2020, "Source code to generate a training dataset for text recognition of Singapore's city area names and block numbers", https://doi.org/10.21979/N9/5LJ3YC, DR-NTU (Data), V1
Source code for training a deep learning model to recognise hand written text in an image. In particular, the model recognises Singapore's city area names as well as HDB block numbers.
Aug 7, 2020 - Software Reliability and Security Lab
Zhu, Chenguang; Li, Yi; Rubin, Julia; Chechik, Marsha, 2020, "Replication Data for: "GenSlice: Generalized Semantic History Slicing"", https://doi.org/10.21979/N9/LPHCUS, DR-NTU (Data), V1
This dataset contains the raw experiment data and replication package for the ICSME'20 paper: "GenSlice: Generalized Semantic History Slicing". The replication package is also available at: https://github.com/Chenguang-Zhu/icsme20-artifact (2020-08-06)
Aug 6, 2020 - Ng Si En, Timothy
Ng, Timothy Si En, 2020, "Replication Data for: Forming-Less Compliance-Free Multi-State Memristors as Synaptic Connections for Brain-Inspired Computing", https://doi.org/10.21979/N9/YWTJBM, DR-NTU (Data), V3, UNF:6:RrJmBWPTzVxOHhkjk7DChA== [fileUNF]
This dataset contains electrical and materials measurements for the analysis of the paper "Forming-Less Compliance-Free Multi-State Memristors as Synaptic Connections for Brain-Inspired Computing"
Aug 6, 2020 - Social and Affective Neuroscience
Esposito, Gianluca; Gabrieli, Giulio, 2019, "Related Data for: Machine Learning Estimation of users' Implicit and Explicit Aesthetic Judgments of Web-Pages", https://doi.org/10.21979/N9/YCDXNE, DR-NTU (Data), V2, UNF:6:OXjgBp2o1P5HHQM/zPdxYA== [fileUNF]
The aesthetic appearance of websites can influence the perception of their usability, reliability, and trustworthiness. Several studies investigated the relationship between single aesthetic features and explicit aesthetic judgments, demonstrating the existence of attribution bia...
Subramanian Periyal Srilakshmi(Nanyang Technological University)
Aug 6, 2020School of Materials Science and Engineering (MSE)
Appointment: PhD student
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