Best practices for good research data management

This page contains guidelines and checklists on common research data management questions. The material provided here is meant to serve as guidance for Chalmers' guiding principles on good research practices.

What is Research Data Management?

Research Data Management (RDM) means maintaining well-organized and well-documented research data throughout the research data lifecycle. By organizing, structuring, and documenting research data in a well-thought-out way, it becomes easier to:

  • report on the research process according to good research practice

  • keep track of and follow legal requirements,

  • reproduce and verify results,

  • find, understand and re-use research data during and after a research project. 

  • archive and share data.

 

What do we mean by research data?

Here we mean data which underpins scientific research. Research data comes in different types and formats – experiment results, measurements, survey responses, texts,  images and film can all be research data. Research data can be raw or processed in different ways - from sensor data and simulation outputs to a table presented in an article.

Best Practices in Research Data Management

A PhD student leaves the group. Two years later, a reviewer asks for the raw data behind Figure 3. Where are the data? Can they be opened? Does anybody know what the column headers mean? Good research data management is the difference between 'yes' and a frantic email thread.

Chalmers sets down three guiding principles for good research practice in order to avoid such situations. The principles are the following:

  1. All research activities at Chalmers shall establish and maintain a data management plan.

  2. The right to decide on the use of research data shall be retained within Chalmers and data shall as far as possible be stored under Chalmers control.

  3. All research data that are considered important for long-term documentation of research should be as FAIR as possible.

These principles are grouped with principles for open access to scientific publications and for responsible internationalization in the document linked above.

You can read more about managing research data throughout its lifecycle on our research data lifecycle page.