Welcome to the Unisa Research Data Management LibGuide. This Guide will provide information on processes, procedures and policy with regards to research data management (RDM), as well as access to resources and tools that can support researchers in managing their data.
It will also serve as a space to pilot platforms for archiving the research data
Please send any suggestions and comments to the compiler of this guide.
A sustainable digital format is one that is compatible, for the foreseeable future, with software needed to open and read it.
Unfortunately, as software applications change or disappear over time, data file formats can become obsolete. If you are using a proprietary and/or obscure file format, there is a risk of the format becoming obsolete--making your data unusable.
If you are working in a proprietary/less-sustainable format, consider converting your data to an open, widely-used format when you preserve and share your data. Many software programs allow for saving/converting datasets into more open formats (e.g. save SPSS dataset as CSV). This will better ensure that your data is usable by others and into the future.
Wherever possible, select data formats that have the following sustainability attributes:
If you are uncertain of which file formats to select for long-term preservation of your research data, here are some tips to help you decide:
To emphasis: The most appropriate file-format should be selected for the long-term preservation and continued access to research data.
The following should be taken into account when selecting an appropriate format:
Best file formats include:
A comprehensive guideline on various aspects of file formats has been compiled by the Digital Curation Centre (DCC)
This is a set of conventions you define for naming data files, and the folders you keep them in, and for saving multiple versions of files. Using naming/versioning conventions will:
Below are some general guidelines for naming files and folders. While it is recommended that these guidelines are followed, it is most important you ensure that:
Security refers to three main areas:
Everyone should keep their digital data safe from attack by computer malware.
If you work with sensitive data, you may need to comply with requirements and policies of the university, government, funding agencies and the like.
Backup refers to preserving additional copies of your data in a separate physical location from data files in storage. Backup preserves older copies so you can restore your data if accidental deletion/alteration or a disaster such as fire, flood, or hardware malfunction damages your data in storage.
To safeguard your important data assets, remember both storage and backup are essential.
What should you backup?
Everything that would be required to restore data in event of loss (data/software/scripts/documentation)
How many copies?
Follow the Rule of 3:
How often?
Backup frequency is dependent on the project and the data. Consider how much data you would be willing to lose.
What type?
Full: Backup all files
Incremental: Backup only files that have changed since last backup (either full or incremental)
Differential: Backup only files that have changed since last full backup
For more details go to: Backup your files - Windows 7
Test your system: Go through the exercise of accessing backup to see that procedure works & you can fully restore your data
Data must be archived in a controlled, secure environment in a way that safeguards the primary data, observations, or recordings. The archive must be accessible by scholars analyzing the data, and available to collaborators or others who have rights of access.
Storage refers to preserving your data files in a secure location you can access readily. Storage systems often provide mirroring, in which data is written simultaneously to two drives. This is not the same thing as backup since alterations in the primary files will be mirrored in the second copy. There are several options for data storage, each with their own pros and cons:
Primary research data should be stored securely for sufficient time following publication, analysis, or termination of the project.
The number of years that data should be retained varies from field to field and may depend on the nature of the data and the research.
Sustainable data management is crucial to the value of research and crucial to ensuring continued scholarship. Typically, in data storage, there is an access copy, for use, and an archival copy, essentially for preservation and back-up purposes. Backing up data cannot be overemphasized,just as natural disasters and breakdowns in systems and software cannot be predicted.
"Bags" are ideal for digital content normally kept as a collection of files. They are also well-suited to the export, for archival purposes, of content normally kept in database structures that receiving parties are unlikely to support. Relying on cross-platform (Windows and Unix) filesystem naming conventions, a bag's payload may include any number of directories and sub-directories (folders and sub-folders). A bag can specify payload content indirectly via a "fetch.txt" file that lists URLs for content that can be fetched over the network to complete the bag; simple parallelization (e.g. running 10 instances of Wget) can exploit this feature to transfer large bags very quickly.
Take a look at BagIt