Step 2 - Documentation

Throughout your research, you make many choices, from topic to methodology, from techniques to measurements, from data source to storage format. The choices you make at one stage will affect the choices you make at the next.

For your research to be reproducible in the future, even by you, all those choices need to be documented and available.

There may be more than one valid way to collect and to analyse data but if the same choices are not made later, the result may be different. Methods can vary, equipment may measure and record differently, approaches may have inherent biases for which adjustments need to be made. Each data point needs to be interpreted in the context in which it was collected.

The choices made at the time may seem obvious, but it may not be so in future. Choices are often limited by methodology or technology but both may undergo changes or digital disruption after the project is over, or even during the project.

Within a research group, another possible disruption is the loss of one of the members of the team. If that happens with someone whose role or skills are crucial to the project. Comprehensive documentation can be crucial to the future of the project when someone new takes over that role.

Documentation to safeguard the project

Documentation also reduces the risk to a research team from a low Bus Factor.

The Bus Factor is the number of people who, if they were suddenly lost to the team (e.g., if they were hit by a bus), would cause a major disruption to the project and would compromise the entire research process. It is also called the Lottery Number, which has a more positive connotation but the threat to the team remains the same.

Bus Factor
Bus factor

Individual circumstances can change suddenly and if it should occur to one member of the team whose loss would cause major disruption, that is considered to be a Bus Factor of 1. The smaller the number, the greater the danger to the project. The number of people that would have to be lost for the research project to fail must be as high as possible.

As an example, Terry is responsible for the coding for processing and analysing the data for a team project. To the rest of the team, his ability in coding is impressive, and they don’t believe they have the skills and aptitude to do this work so they rely upon him to lead in this process. Terry enjoys his work and his status within the group.

One day, Terry announces that his wife has been offered a lucrative position overseas and Terry is resigning. Suddenly, most of the knowledge of Terry’s role will be lost to the team. Without careful management, a major change to a research team could be more than just disruptive; it has the potential to corrupt the entire project.

Comprehensive documentation is the major strategy for minimising the disruption.

How?

First steps

Read How to start Documenting and more by the Consortium of European Social Science Data Archives and the European Research Infrastructure Consortium. Take note of sections on how you can start documenting a project at study level and data level, and the methods for qualitative and quantitative data.

  • Start by documenting in a text (.txt) file or Micrososft Word document - any start is a good start.
  • include information on where your results and working data are saved. 
  • include a copy your lab notebook if you have one onto a digital format.
  • save the documentation file somewhere that’s accessible to your supervisor or team such as Microsoft Teams, Sharepoint or Research Drive.

Find out more about shared storage spaces in Step 7 - Cloud backups.

Intermediate

Document in detail on how your workflow goes from your raw data to the finished results. This can be anything from a downloaded function list from SPSS/NVIVO to the code used to create it.

Consider developing a Standard Operating Procedure for your project team or lab.   

Read the PLoS article Ten simple rules on how to write a standard operating procedure and use the template the researchers have shared.

You could also try to Sync the document automatically to the cloud with your data. (??This needs a link to more information on how to do this??)

Advanced

Now that you’ve got a good head start, it’s time to learn about Git Repositories and wikis for documenting. Learn how to create a code repository in Github with their Hello world tutorial.

Or you could explore how research projects with published data have created documentation. Check out examples of documentation or readme files in these Australian researcher involved projects:

  • Dinusha, B., Howell, L., Silbert, M., Daraganova, G. (2021). Ten to Men: The Australian Longitudinal Study on Male Health, Release 3 (Waves 1-3),, ADA Dataverse, V4. (Dataset). doi:10.26193/JDE1TD
  • Komarek, A., M. (2021). Replication Data for the study on income, consumer preferences, and the future of livestock-derived food demand. Dataverse. (Data Collection). https://doi.org/10.7910/DVN/ZPWQBB

Internal Resources

External Resources