DR-NTU (Data)

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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

FAIR Datasets

NIE Data Repository (Harvested)

Asian School of the Environment (ASE)

College of Computing and Data Science (CCDS)

Earth Observatory of Singapore (EOS)

Graduate College

Lee Kong Chian School of Medicine

Nanyang Business School (NBS)

School of Art, Design and Media (ADM)

School of Biological Sciences (SBS)

School of Chemistry, Chemical Engineering and Biotechnology (CCEB)

School of Civil and Environmental Engineering (CEE)

School of Electrical and Electronic Engineering (EEE)

School of Humanities

School of Materials Science and Engineering (MSE)

School of Mechanical and Aerospace Engineering (MAE)

School of Physical and Mathematical Sciences (SPMS)

School of Social Sciences (SSS)

S. Rajaratnam School of International Studies

Wee Kim Wee School of Communication and Information (WKWSCI)

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55,401 to 55,410 of 74,567 Results

2016-1-7-cg.mat Mar 9, 2021 - Replication Data for: Unraveling the presence of multiple plagioclase populations and identification of representative two-dimensional sections using a statistical and numerical approach MATLAB Data - 32.2 MB - MD5: 4b15cc5f033f1e356455a7888bbb3880
2-1.tif Mar 9, 2021 - Replication Data for: Unraveling the presence of multiple plagioclase populations and identification of representative two-dimensional sections using a statistical and numerical approach TIFF Image - 122.3 KB - MD5: b2c102db7ef2bc8ad94cd9888469a351
2-2.tif Mar 9, 2021 - Replication Data for: Unraveling the presence of multiple plagioclase populations and identification of representative two-dimensional sections using a statistical and numerical approach TIFF Image - 73.3 KB - MD5: 86ff98b8dabb30f7b6076d7617158100
2-edge.tif Mar 9, 2021 - Replication Data for: Unraveling the presence of multiple plagioclase populations and identification of representative two-dimensional sections using a statistical and numerical approach TIFF Image - 336.2 KB - MD5: c195d6905fa4bb9da2d9e72c890dccf4
2.tif Mar 9, 2021 - Replication Data for: Unraveling the presence of multiple plagioclase populations and identification of representative two-dimensional sections using a statistical and numerical approach TIFF Image - 254.5 KB - MD5: 5fc1ebc03108d4a167d36f1a4130a8b2
2-touched-edge.tif Mar 9, 2021 - Replication Data for: Unraveling the presence of multiple plagioclase populations and identification of representative two-dimensional sections using a statistical and numerical approach TIFF Image - 636.5 KB - MD5: 3790bbfcf8e463023fcea4b98b142fc9
2-touched.tif Mar 9, 2021 - Replication Data for: Unraveling the presence of multiple plagioclase populations and identification of representative two-dimensional sections using a statistical and numerical approach TIFF Image - 327.2 KB - MD5: a0cece2ff67188b4a77bfbc18bd7f50c
3.tif Mar 9, 2021 - Replication Data for: Unraveling the presence of multiple plagioclase populations and identification of representative two-dimensional sections using a statistical and numerical approach TIFF Image - 75.7 KB - MD5: 92950779b924a92de50753bf66293d89
400-rimdi-200profile.mat Mar 9, 2021 - Replication Data for: Unraveling the presence of multiple plagioclase populations and identification of representative two-dimensional sections using a statistical and numerical approach MATLAB Data - 3.3 MB - MD5: 55e8adfe67b0626f1484f259e526c108
400-rimgao-200profiles.mat Mar 9, 2021 - Replication Data for: Unraveling the presence of multiple plagioclase populations and identification of representative two-dimensional sections using a statistical and numerical approach MATLAB Data - 3.6 MB - MD5: c61cf650203f0f87cab3fa1b06df2706

2016-1-7-cg.mat

Mar 9, 2021 - Replication Data for: Unraveling the presence of multiple plagioclase populations and identification of representative two-dimensional sections using a statistical and numerical approach

MATLAB Data - 32.2 MB -

2-1.tif

TIFF Image - 122.3 KB -

2-2.tif

TIFF Image - 73.3 KB -

2-edge.tif

TIFF Image - 336.2 KB -

2.tif

TIFF Image - 254.5 KB -

2-touched-edge.tif

TIFF Image - 636.5 KB -

2-touched.tif

TIFF Image - 327.2 KB -

3.tif

TIFF Image - 75.7 KB -

400-rimdi-200profile.mat

MATLAB Data - 3.3 MB -

400-rimgao-200profiles.mat

MATLAB Data - 3.6 MB -

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