Metrics
1,089,191 Downloads

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.

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.

Who can deposit? NTU faculty, research staff and students.

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.

How to deposit?

Useful links: FAQs | Collection Guidelines | NTU Research Data Management | General terms of use and Privacy policy

Featured Dataverses

In order to use this feature you must have at least one published dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

Advanced Search

361 to 370 of 3,433 Results
May 24, 2025 - NIE Data Repository (Harvested)
Yee, Jia'en; Lim, Fei Victor; Ng, Betsy Ling Ling; Pan, Qianqian; Koh, Elizabeth; Sindoni, Maria Grazia, 2025, "Related Data for: The student digital literacies profiling tool: Instrument validation", https://doi.org/10.25340/R4/ZVCK4I
In an era of rapid technological change, digital literacies now extend beyond basic technical skills to include the ability to combine digital tools, features, and semiotic resources to convey meaning across diverse contexts. This paper presents a framework and validated survey t...
This Dataset is harvested from our partners. Clicking the link will take you directly to the archival source of the data.
May 23, 2025 - David WILKOWSKI
Wilkowski, David, 2025, "Related Data for: Topological optical skyrmion transfer to matter", https://doi.org/10.21979/N9/EAVRTG, DR-NTU (Data), V2, UNF:6:lwjP4tuiAt8pFa4bWpuLuQ== [fileUNF]
Source file for Topological optical skyrmion transfer to matter
May 23, 2025 - HE Huajun
He, Huajun; Wang, Bo; Shen, Xuhai; Feng, Minjun; Rao, Haixia; Ye, Senyun; Nguyen, Linh Lan; Duchamp, Martial; Li, Shuzhou; Tian, He; Sum, Tze Chien, 2025, "Replication Data for: Aqueous Colloidal Perovskite Quantum Emitters", https://doi.org/10.21979/N9/8YTAAI, DR-NTU (Data), V1
Aqueous solutions of nanoparticles are the cornerstones for applications in diagnostics, catalysis and more, where control over the nanoparticle's dispersion is pivotal to tailoring the final product properties. Of late, halide perovskite nanocrystals (HPNCs) with outstanding opt...
May 22, 2025 - Chin Siang NG
Ng, Chin Siang, 2025, "Effects of Zinc Oxide Nanoparticles on Vat Photopolymerziation", https://doi.org/10.21979/N9/36TOLK, DR-NTU (Data), V1
Benchmarking images to observe overcuring, tensile tests and DMA results..
Chin Siang NG (Nanyang Technological University)
May 22, 2025School of Mechanical and Aerospace Engineering (MAE)
May 22, 2025 - S-Lab for Advanced Intelligence
Xu, Qianxiong; Zhu, Lanyun; Liu, Xuanyi; Lin, Guosheng; Long, Cheng; Li, Ziyue; Zhao, Rui, 2025, "Unlocking the Power of SAM 2 for Few-Shot Segmentation", https://doi.org/10.21979/N9/XIDXVT, DR-NTU (Data), V1
Few-Shot Segmentation (FSS) aims to learn class-agnostic segmentation on few classes to segment arbitrary classes, but at the risk of overfitting. To address this, some methods use the well-learned knowledge of foundation models (e.g., SAM) to simplify the learning process. Recen...
May 20, 2025 - TAN Fangyi
Tan, Fangyi; Samanta, Dhrubajyoti, 2025, "Replication Data for: Reconciling record-breaking ocean temperatures within the Singapore Strait in 2023 with satellite and in-situ data", https://doi.org/10.21979/N9/HEXBWR, DR-NTU (Data), V1, UNF:6:Cl3gQnI/p2qdkYLRycqjDQ== [fileUNF]
This dataset contains the supplementary files and data that were used to produce the manuscript titled: "Reconciling record-breaking ocean temperatures within the Singapore Strait in 2023 with satellite and in-situ data".
May 16, 2025 - S-Lab for Advanced Intelligence
Liu, Chenxi; Miao, Hao; Xu, Qianxiong; Zhou, Shaowen; Long, Cheng; Zhao, Yan; Li, Ziyue, 2025, "Efficient Multivariate Time Series Forecasting via Calibrated Language Models with Privileged Knowledge Distillation", https://doi.org/10.21979/N9/6WWC6K, DR-NTU (Data), V1
Multivariate time series forecasting (MTSF) endeavors to predict future observations given historical data, playing a crucial role in time series data management systems. With advancements in large language models (LLMs), recent studies employ textual prompt tuning to infuse the...
May 14, 2025 - Project: Climate Crisis and Cultural Loss
Bauer, Ute Meta, 2025, "Climate Crisis and Cultural Loss Exhibition", https://doi.org/10.21979/N9/Y0XINX, DR-NTU (Data), V2
NTU Centre for Contemporary Art Singapore (NTU CCA Singapore) presents the two-part research presentation Climate Crisis and Cultural Loss. First unfolding at TBA21–Academy’s Ocean Space in Venice, Italy, the research inquiry later materialises in another configuration at ADM Gal...
Add Data

Log in to create a dataverse or add a dataset.

Share Dataverse

Share this dataverse on your favorite social media networks.

Link Dataverse
Reset Modifications

Are you sure you want to reset the selected metadata fields? If you do this, any customizations (hidden, required, optional) you have done will no longer appear.