Research Data Management

If you have any RDM questions not answered in our Guidelines, please feel free to contact us.

It is no longer sufficient to store your research data on your laptop, external hard drive or other personal devices. Security of and future access to research data, and POPIA compliance, requires a secure and reliable storage environment. The UFS has local data storage infrastructure that provides compliance with legislation and easy access to your research data.

Where can I store my research data?

UFS ICT Services' High-Performance Computing hosts UFS research data on secure, access-controlled local storage. figshare is the front-end system that helps UFS researchers to upload and manage their research data. DMPOnline is an online data management planning tool for your data management plans (DMPs) and documentation related to your research data.

How long can I store my research data?

Your research data can be stored for as long as you need. Funders and collaborators will have certain requirements, but if you are unsure of how long to store your research data, the UFS RDM policy provides guidance.

How can I share my research data?

figshare allows for sharing of your research data. You have a few options:

• Include collaborators in your projects.
• Share your dataset(s) with a private URL.
• Publish your dataset(s).

How will I know how much storage space I will need?

Here are some steps to help you determine your research data storage requirements.

1. Data volume: Estimate the total amount of data you expect to generate or collect during your research project. Consider the size of individual files, the number of files, and any potential growth or changes in data volume over time.
2. Data types: Identify the types of data you will be working with, such as text documents, images, videos, sensor data, genomic sequences, or other specialised formats. Different data types may have varying storage requirements.
3. Data generation rate: Determine the rate at which new data will be generated or collected. If you have a continuous data collection process, estimate how much data you expect to accumulate over specific time periods (daily, weekly, monthly).
4. Data retention period: Define the duration for which you need to retain the research data. Some projects require long-term storage, while others may only need temporary storage for a specific period.
5. Data processing and analysis: Consider the computational requirements for processing and analysing your research data. This includes any intermediate or derived data that may be generated during your analysis workflow. Ensure that you have enough storage capacity of these temporary files.
6. Collaboration and sharing: Determine whether you will collaborate with others or need to share your research data with colleagues, collaborators, or the wider research community. This may require additional storage capacity and mechanisms for sharing.
7. Regulatory and ethical considerations: Consider any legal, regulatory, or ethical requirements related to data storage and privacy. Depending on your research filed, there may be specific guidelines or regulations that dictate how data should be stored and protected.
8. Backup and redundancy: Account for backup and redundancy requirements to ensure data integrity and availability. Implementing backup systems and redundancy measures can protect against data loss and minimise downtime in case of hardware failures.
9. Scalability: Anticipate future growth and scalability needs. Assess whether your storage solution can accommodate increasing data volumes or changing requirements over time.
10. Budget: Evaluate your budget for research data storage. Different storage options have varying costs, so consider your budget constraints and choose a solution that balances your requirements and available resources.