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Research Data Management

Checklist for Data Management Planning

1. Types of Data & Source
  • What type of data will be collected or generated (e.g., experimental, qualitative, image)?
  • How much data will be generated for this research?
  • Will you use data from other sources? If yes, where is it from? Is there any condition required for obtaining and using the data?

2. Data Documentation & Organisation

Data Description and Structure
  • How data will be organised in your research project (e.g., naming conventions, folder structure)?
  • How will you track different versions of your data? What versioning methods will you use to ensure different versions of your files identifiable for the future use?
Data Formats
  • What file formats will be used? Are you using file formats that are standard to your files? Are these formats conform to use and re-use data in the future (e.g., open standard/non-proprietary)?
  • Are there any special conditions to read and manipulate your research data (e.g., operating systems, software or tools)?
  • What metadata will be used to describe your data?
  • Are you using metadata that is standard to your research field?
  • How will you manage and store the metadata?
  • What documentation will be created to explain how the data can be interpreted and used (e.g., README file)?
3. Dealing with Sensitive Data
  • Will your research involve any sensitive data (e.g., personally identifiable information, health protected data, proprietary data)?
  • How will you manage the sensitive data in your research project to protect privacy (e.g., anonymisation, encryption, access control)?
  • Are there any legal terms or ethical concerns that may prevent you from sharing your research data?
  • How will you ensure your data management practices comply with the IRB review (if applicable)?

4. Data Storage & Preservation

Storage and Backup
  • Do you have sufficient storage for your research data?
  • How and where will the data be stored (e.g., platforms or devices that will be used to store the data, physical locations of the data)?
  • How often and where will the data be backed up?
  • How will the data be recovered in the event of an incident?
Long-term Storage and Preservation
  • How long should the data be retained?
  • Where will you store your data for long-term access (e.g., archives, discipline-specific repositories, generic repositories like Yale-NUS Dataverse)?
  • How will you prepare your data for long-term preservation (e.g., anonymization, format conversion)?
  • Is there a need to archive specific software or tools for data access in the future?

5. Access, Sharing & Re-use

  • Who will have the right to access or use the data (e.g., closed, Yale-NUS community, public)?
  • Who will hold the intellectual property rights for the data?
  • Will there be any embargoes on the data?
  • Which license will you choose for your research data? Any limitations on re-use, redistribution, commercial use and etc.?
  • Will your research data be published in a journal requiring all underlying to be made available?

6. Roles & Responsibilities

  • Who is responsible for managing the data?
  • Who will have the responsibility to ensure the implementation of the data management plan?