## Summary

Organisation and planning are key to a successful research project. Best practices and policies are often in place to ensure data management is considered at all stages of the research lifecycle. However, data management is not just an administrative task; it is key for promoting good scientific practices and for many more reasons.

Good data management helps: increase the integrity of your research, contribute to the impact of your research, improves the quality of your research, supports future reuse of your data and makes your job easier as a researcher!

#### Task 1:

Think of your own research, can you imagine what tasks you will take on?

1. Write down all the different tasks which you anticipate will occur during the entire research project. The more detailed you make this list, the better overview you will have of your project.
2. Once you have a complete list created, assign them to the appropriate stages of the lifecycle. If some tasks will take place over multiple stages, you can note them in both sections.

This list can be the starting point for your planning, if you want to go one step further you can place these tasks on a timeline. This will help keep you focused and help you set realistic goals.

Some examples of tasks are: selecting a research topic, choosing a research methodology, thinking about resources
(money, people), discussing ideas with colleagues and/or supervisors, writing down and finalising details of research proposal the project’s research design, preparing and submitting an application for ethics approval, arranging software needed for data analyses, preparing manuscripts for journal publication, writing a data management plan, selecting a data storage location, etc...

The VU's data management plan template is modeled from the research lifecycle, so you can use the information gathered throughout the course when designing your own data management plan.

#### Task 2: