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Institutional role in supporting open access, open science, open data

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Presentation on theme: "Institutional role in supporting open access, open science, open data"— Presentation transcript:

1 Institutional role in supporting open access, open science, open data
Lavanya Asokan, Office of Information, Knowledge & Library Services I’m Lavanya from Office of Information, Knowledge & Library Services, NTU, Singapore. I’ll be sharing about the recently launched open access data repository, DR-NTU (Data) in related to open access, open data and open science.

2 launch of NTU open access research data repository, DR-NTU (Data)
More funders, institutions and publishers are requiring research data to be made more openly accessible and reusable on a reliable and long-term basis. NTU would be able to meet these expectations on a centrally maintained institutional platform without having to worry about long-term access, cost and reliability issues. As a result, the open access repository has been implemented in response to the NTU Research Data Policy which requires data sharing by default unless there are prior formal agreements on non-disclosure or proprietary use of the data.  

3 NTU Research data policy
Research data to be deposited in institutional open access research data repository. Library is tasked to set up the repository This policy launched in Apr 2016 aims to ensure that research data generated in the conduct of research projects at NTU are managed in a systematic and comprehensive manner to ensure integrity, accountability, long term availability, appropriate sharing and compliance with requirements of funding agencies. According to the Policy, the final research data used in establishing and validating research findings has to be deposited in the NTU Data Repository or a recognized open access data repository no later than publication of the article.

4 Introduction to NTU open access research data repository, DR-NTU (Data)

5 DR-NTU (Data) So, I will begin with why use DR-NTU (Data)?
Better guarantee of perpetuity Enjoy benefits of data sharing No cost DR-NTU (Data) Meets NTU Research Data Policy requirements Meets journal publisher requirements DOI So, I will begin with why use DR-NTU (Data)? By depositing your data here, you’d not only reap the benefits of data sharing but will also get to enjoy better guarantee of perpetuity without having to bear any cost. When you deposit your data here, you would immediately get a DOI for your dataset. Some researchers have used it to fulfil publishers’ requirements. Last but not least, by using this new platform, aligns well with good research data management intentions behind the NTU Research Data Policy.

6 Open Access, Open Science, Open Data
Licensing own data Metadata Permissions Reusability Discoverable Data Sharing Sensitive data DOI Flexible options of data sharing.

7 Data curation services
Institutional role Platforms Policies Education Outreach Data curation services

8 Institutional role OA Mandate Policies NTU Research Data Policy
Platforms DR-NTU (Data) for research data DR-NTU (Open access for research papers)

9 Template question design, guides, samples, review drafts
Institutional role Education Data Management workshops Template question design, guides, samples, review drafts

10 Institutional role Sensitive data (lock up options) Metadata Open formats Folder structure DATA CURATION SERVICES Content organisation structure Permissions, Licensing, terms of use Links to internal publications, external data repository, publishers version The Office of Information, Knowledge and Library Services offers a suite of data curation services that include advice, review and training on metadata, file organisation, data documentation, as well as terms of use open formats and open access.

11 Institutional role Options for depositing and describing dataverse/dataset Outreach Schools Research centres/institutes Individual Principal Investigators Options for depositing and describing dataverse/dataset Librarians deposit data and provide drafts of metadata to fine-tune. Researchers deposit and provide metadata, librarians fine-tune together.

12 SCHOOL SUB-DATAVERSE RESEARCHER SUB-DATAVERSE DATASET RESEARCH CENTRE SUB-DATAVERSE DATASET Here’s an example of a school sub-dataverse, which in this case is the WKWKSCI one. On this screenshot, you see a WKWSCI researcher’s sub-dataverse as well as a WKWSCI research centre sub-dataverse. In these sub-dataverses, there’re dataset records.

13 DATASET RECORD This is an example of a dataset record.
Auto-generated data citation with DOI Export data citation Link to related publication This is an example of a dataset record. Each deposit gets an automatically generated data citation with DOI. There’re different citation tool format choices for people who wish to use your data to export your data citation. Data depositors are advised to provide the links to research paper publications that are related to their datasets.

14 METADATA In this example of metadata record, you get to see the time period as well as the start and end dates of data collection, in this case 2011 to The kinds of data collected in this dataset include recordings, transcriptions and translations. There is also the name and version of the software used during data collection and analysis. Besides, there is information about the necessary permissions obtained for publication purposes. It’s important to remember that the more contextual information that is provided, the easier it is for a potential data re-user. And that person could be yourself, say 8 years later.

15 SPECIFIC FILE RESTRICTIONS
File restriction option On this platform, there’s an option for you to lock up some files especially when they contain sensitive information. In this screen capture, you see the locked up files with a red padlock and without the ‘download’ button. Published datasets on the data repository are open and accessible to the general public. Unpublished datasets will not be open and accessible to the general public.

16 Changes to published datasets are tracked and recorded
VERSIONING Changes to published datasets are tracked and recorded Changes to published datasets are tracked and recorded too.

17 THANK YOU Thank you very much.


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