1. Introduction to Research Data Management and Data Management Plans

COBL_learningoutcome_40x40px_2017_15.png  Learning objectives

When you have completed this lesson, you will be able to: 

  • Describe what research data management (RDM) is.
  • Describe what a data management plan (DMP) is.
  • Explain why good research data management is important. 

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COBL_litterature_40x40px_2017_18.png  What is research data?

All research is based on data – this can be data you collect yourself, or already existing data you reuse from other projects or databases. In defining exactly what research data is, we follow the definition that is provided in the UCPH Policy for Research Data Management: 

“Research data is any physical material or digital data collected, observed, generated, created or reused as part of research activities conducted at UCPH…”

The ‘research activities’ mentioned in the policy include students’ own research projects that they carry out as part of their bachelor’s or master’s degree programme, but do not include data collected by students as part of an assignment in a course. So, as a UCPH student  you are considered to be working with research data during your own thesis project, or when contributing to existing research projects at UCPH, in the role of student assistant for example.

The term research data includes:

  • Physical material such as books, biological samples (e.g. of animals, plants and humans), artefacts, notebooks and interviews on paper. 
  • Digital data such as digital text files, data files, video and audio recordings, digital images, computer code, and digital records describing physical materials.

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COBL_litterature_40x40px_2017_18.png  What is research data management?

Regardless of what data you work with and how your data are obtained, you need to collect, process, analyse and describe them well, so that you can trust the conclusions drawn from them. Research data management (RDM) is a collective term for the different actions you take to manage your data. The research data lifecycle illustrated below presents these actions in order from project start (‘plan’) to project end (‘preserve’).

DataLifecycle241120_biggerletters.png

As can be seen in the lifecycle, research data management includes:

  • Planning data management: Before the start of your project, you make a plan for how you will work with the data. You decide what data you will collect and how to collect them. You also identify whether there are any data management requirements to consider, whether you need any approvals to collect the data, and whether there are any issues you should discuss with your supervisor.
  • Collecting and documenting data: During the project, you collect the data and document your process, so that your future self and others understand what the data show and how they were collected.
  • Processing and analysing data: You process your raw dataset to a final dataset underlying your conclusions, e.g. through data filtering, coding, sorting and running statistical tests. 
  • Storing data securely: You store your data securely to prevent data loss, unintended changes in the data and breaches of confidentiality.
  • Sharing data openly: At the end of the project, you will decide whether you have data that you can share openly with others, by depositing data in a data repository.
  • Preserving data: After your project, you will decide which data to delete and which data to keep. For the data you want to keep you decide where, how and how long you will keep them.

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COBL_litterature_40x40px_2017_18.png  Why is good research data management important?

Good research data management throughout your project is not just something the university expects of you. It actually has many benefits for yourself and for your project. Here are some examples: 

  • You increase your efficiency by organising and versioning your files and folders and by using intuitive file names so you easily find your data in the future.
  • You reduce the risk of losing or corrupting your data by using secure storage facilities, making back-ups and having control over different file versions. 
  • You ensure that you are legally and ethically allowed to collect the data you need for your project, by systematically considering which protocols, permissions and approvals you need.
  • Others are more likely to trust that you have managed your data responsibly and have conducted your project professionally, when you make detailed documentation available to them that describes how you collected and processed the data.
  • You increase your opportunities for employment after the project, as through good data management you will develop professional skills that are increasingly sought after by companies and in academia.

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COBL_litterature_40x40px_2017_18.png  The Data Management Plan – a valuable tool

What is a Data Management Plan?
A data management plan (DMP) is a document in which you describe how you will collect, analyse and securely store the data, as well as preserve the data once the project is over. A DMP serves both as checklist for the project and a valuable tool that will help you think through all the different steps in a structured way, before you begin. It helps you identify requirements for data management and resources needed. It will also highlight issues that you may need to discuss with your supervisor.

Given the usefulness of producing a DMP, we recommend that you draft a DMP every time you start a new project. In fact, as a student at the University of Copenhagen it has become mandatory to create a Data Management Plan (DMP) at the start of your bachelor and master thesis projects.

How to make a Data Management Plan?
You can make your own DMP from scratch or simply use one of the many DMP templates available online. Maybe your supervisor or project lead has a specific template you must use? If not, it is a good idea to use the UCPH DMP template for students: This is the template we will be using throughout this course.

Animation showing what a DMP is and how it can benefit your project:

If you experience access denied, reload the page or try another browser.
For English subtitles, please look for the CC icon in the lower right corner of the video and press English.

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COBL_videolecture_40x40px_2017_4.png  Data Management plans in practice

Bachelor student Frida Birkedal Christiansen and supervisor Nicole Schmitt, Health and Medical Sciences, share their experiences on creating a DMP – and why this work is important. 

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COBL_tasks_40x40px_2017_10.png  Get started with your DMP

Download a copy of the template for the data management plan for students, which you can find here: DMP template for students Download DMP template for students.

Start filling in the first part of your project’s DMP by responding to the questions in Section 1.

DMP Details:

Title of the project   

Name and contact information of the student(s)  

Name, affiliation, contact information the supervisor(s)  

Expected start date of the project  

Expected end date of the project  

Short summary of the project, about 5-10 lines

Please remember to discuss the data management plan with your supervisor at the start of your project. Keep the DMP stored along with your data.

In the next lessons we will provide the background information necessary for you to start working on the other sections of your DMP.

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COBL_sparks_40x40px_2017_19.png  Practical tips for research data management planning  

When you start a new bachelor or master project at the UCPH, we recommend that you include the following steps in the planning process:

  1. Review your study program’s information pages on KUnet . Here you can, among others, find guidance on IT tools available to you. If you work with personal data, you should also read through the material specific to personal data in student projects.

  2. Browse through the University’s Policy for Research Data Management , to get an idea about what is expected of you when managing data. Please note that some aspects of the policy may not apply to your project.

  3. Investigate whether there are additional rules that apply to your project, such as those provided by the research group you are associated with, or the company you collaborate with. Ask your supervisor; they should know whether there are additional rules.

  4. Make a Data Management Plan:

    – Download a copy of the template Download template for the data management plan for students. Doublecheck with your supervisor that this is the template you should use, in some departments or study programs there may be another template. You can use the next lessons in this course as guidance to fill in the DMP.

    – Ask your supervisor for input. When making the DMP, you may find out that some questions are difficult to answer. We therefore recommend you discuss the document with your supervisor(s), and make sure they agree with your plans for data management.

    – Check whether there are local guidelines for where your DMP should be stored. If not, store your DMP along with your data and update your DMP if there are major changes to your project.

  5. Check out the resources on  Data Management Plans available on the UCPHs Research Portal Pages. The resources and templates presented there are intended for researchers and not students, but you can  use the pages for inspiration.

  6. Check this course’s RDM Glossary for definitions of terms used in this lesson and the other lessons.

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COBL_fieldtrip_40x40px_2017_8.png  Learn more

Research Data Management (eLearning course)
Within the framework of the Danish National Forum for Data Management, the Danish Universities have developed the eLearning course “Research Data Management Links to an external site.”. The course is targeted towards PhD students, and contains more detailed information and more cases that you might find useful. See a brief video about the course below. 

 

Holmstrand, K.F., den Boer, S.P.A., Vlachos, E., Martínez-Lavanchy, P.M., Hansen, K.K. (Eds.) (2019). Research Data Management (eLearning course).
doi: 10.11581/dtu:00000047

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 Published in 2024