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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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64,541 to 64,550 of 73,632 Results
Replication Data for: Ionic-Liquid Doping Enables High Transconductance, Fast Response Time, and High Ion Sensitivity in Organic Electrochemical Transistors
May 28, 2020 - WU Xihu
Xihu Wu; Abhijith Surendran; Jieun Ko; Oliver Filonik; Eva M. Herzig; Peter Müller‐Buschbaum; Wei Lin Leong, 2020, "Replication Data for: Ionic-Liquid Doping Enables High Transconductance, Fast Response Time, and High Ion Sensitivity in Organic Electrochemical Transistors", https://doi.org/10.21979/N9/KFBGNX, DR-NTU (Data), V1
This dataset contain the raw data fo the publication.
Figures _ For Raw Data _ Adv Mat.pptx
May 28, 2020 - Replication Data for: Ionic-Liquid Doping Enables High Transconductance, Fast Response Time, and High Ion Sensitivity in Organic Electrochemical Transistors
MS Powerpoint - 9.3 MB - MD5: e17714c4e8b927f6bcd9a5479c7812e7
WU Xihu(Nanyang Technological University)
May 28, 2020Centre for Micro-/Nano -electronics (NOVITAS)
Replication Data for: Towards Automated Verification of Smart Contract Fairness
May 27, 2020 - Software Reliability and Security Lab
Liu, Ye; Li, Yi; Lin, Shang-Wei, 2020, "Replication Data for: Towards Automated Verification of Smart Contract Fairness", https://doi.org/10.21979/N9/0BEVRT, DR-NTU (Data), V1
Software artifacts created for the paper titled "Towards Automated Verification of Smart Contract Fairness" accepted at FSE'20.
faircon_data.tar
May 27, 2020 - Replication Data for: Towards Automated Verification of Smart Contract Fairness
TAR Archive - 4.8 MB - MD5: 9c829d07a4d2a0208aa442b159087a67
Tarball containing contract code and raw console logs from the experiments.
Obtain_FairCon.md
May 27, 2020 - Replication Data for: Towards Automated Verification of Smart Contract Fairness
Markdown Text - 11.5 KB - MD5: bc233c7fde39d83eccec490a7de3ba14
Information on how to obtain FairCon.
README.md
May 27, 2020 - Replication Data for: Towards Automated Verification of Smart Contract Fairness
Markdown Text - 8.2 KB - MD5: c0a424f42840678f2362a5cf23ae6513
Information about the dataset usage.
Software Reliability and Security Lab(Nanyang Technological University)
May 27, 2020College of Computing and Data Science (CCDS)
Research data deposit for Yi Li's Software Reliability and Security (SRS) lab.
Investigating the peer review process in undergraduate academic communication courses at NTU (for students from Engineering, Science, Humanities and Social Sciences)
May 27, 2020 - Hsieh Yi Chin
Hsieh, Yi Chin; Hill, Chris, 2020, "Investigating the peer review process in undergraduate academic communication courses at NTU (for students from Engineering, Science, Humanities and Social Sciences)", https://doi.org/10.21979/N9/9EILKW, DR-NTU (Data), V2
This dataset contains data from the project titled "Investigating the peer review process in undergraduate academic communication courses at NTU (for students from Engineering, Science, Humanities and Social Sciences)"
E13, E21 (reviewed by E16, E18).pdf
May 27, 2020 - Investigating the peer review process in undergraduate academic communication courses at NTU (for students from Engineering, Science, Humanities and Social Sciences)
Adobe PDF - 1.3 MB - MD5: 4b1ad2ddb06e2740f408700be2193c97
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