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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.

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

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57,981 to 57,990 of 73,650 Results
Ed0- from hydrolight.txt
Sep 21, 2020 - Dissolved organic matter from tropical peatlands impacts shelf sea light availability on coral reefs in the Singapore Strait, Southeast Asia
Plain Text - 2.0 KB - MD5: f832527ed8f571e81cbc5ead2763627d
Downwelling irradiance spectrum modelled for March 2019 (used for measured vs calculated Kd comparison)
water a and b.txt
Sep 21, 2020 - Dissolved organic matter from tropical peatlands impacts shelf sea light availability on coral reefs in the Singapore Strait, Southeast Asia
Plain Text - 11.4 KB - MD5: 1d86d8132b489d5882cc92f618fd6912
Singapore Straits biogeochemical time series(Nanyang Technological University)
Sep 21, 2020Marine biogeochemistry group
Panda images dataset
Sep 18, 2020 - Wai Kin Adams KONG
Chen, Peng; Swarup, Pranjal; Matkowski, Wojciech Michal; Kong, Adams Wai Kin; Han, Su; Zhang, Zhihe; Rong, Hou, 2020, "Panda images dataset", https://doi.org/10.21979/N9/8CYVGF, DR-NTU (Data), V4
The data used in the study titled "A Study on Giant Panda Recognition Based on Images of a Large Proportion of Captive Pandas".
annotations.7z
Sep 18, 2020 - Panda images dataset
7Z Archive - 2.3 MB - MD5: 8c244d6ee19446c32cd70389a58445bd
Annotations of the raw images added separately.
images.7z.001
Sep 18, 2020 - Panda images dataset
Unknown - 1000.0 MB - MD5: 5434b478e3ebe501cc03fe40c0e863f8
The panda raw data which is a 12GB file is split into 13 parts. Download all parts and unarchive together using 7Zip.
images.7z.002
Sep 18, 2020 - Panda images dataset
Unknown - 1000.0 MB - MD5: 230dfd13cfd47b40a08144568e3fe193
The panda raw data which is a 12GB file is split into 13 parts. Download all parts and unarchive together using 7Zip.
images.7z.003
Sep 18, 2020 - Panda images dataset
Unknown - 1000.0 MB - MD5: 3af58555a5f92dae144f33ee811007d5
The panda raw data which is a 12GB file is split into 13 parts. Download all parts and unarchive together using 7Zip.
images.7z.004
Sep 18, 2020 - Panda images dataset
Unknown - 1000.0 MB - MD5: e13c5e8011593eb65cc4032464e804f9
The panda raw data which is a 12GB file is split into 13 parts. Download all parts and unarchive together using 7Zip.
images.7z.005
Sep 18, 2020 - Panda images dataset
Unknown - 1000.0 MB - MD5: 9d81a94d228e4cc390eb7150536b2bfd
The panda raw data which is a 12GB file is split into 13 parts. Download all parts and unarchive together using 7Zip.
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