Module 2: Essentials for Research Data#

In this module, we start to dig deeper into RDM by introducing multiple topics concerning the essentials of RDM.

At the end of this module you should be able to:

  • Identify different types of research data

  • Recognize what is considered confidential data in research

  • Realise what RDM entails within a research project

  • Recognize the responsibilities regarding RDM for TUD PhD candidates

  • Store and back up the research data of your project in a secure manner

These are different activities in this module you should complete:

✅ Watch the videos of TU Delft researchers telling you about the research data and confidential research data they work with
✅ If you work with personal data, read the information on the two linked websites
✅ Look at the research cycle interactive image and the RDM questions you need to ask yourself at each step of your project
✅ Watch the video about data storage & infrastructure available at TU Delft
✅ Complete the quiz about data storage
✅ Read the TU Delft RDM framework

Topic 1: Data within the research workflows#

TU Delft researchers working in different disciplines shared their thoughts on what they consider as data in their research field and how they work with confidential data.

In the next videos, we will get in touch with TU Delft researchers working in different disciplines. They share their thoughts on what they consider as data in their research field and how they work with confidential data. The first two videos are focused on Research Data and the last two videos are focused on Confidential Data.

Research Data definition#

Research data is any information that has been collected, observed, generated or created to validate research findings.

Depending on the discipline you work in, research data can be collected or produced in different ways. You can capture them in real-time (e.g. sensors, images), you can collect them using laboratory instruments and they can derive from interviews or numerical simulations, among others.

Research Data can be digital such as tabular data, videos, algorithms, scripts, transcripts, codebooks, etc. But, they can also be non-digital, for example, laboratory samples, sketchbooks, prototypes, etc.

We talked to some TU Delft researchers working in different disciplines and we asked them: ‘What is the research data you work with?’ Let’s see what they shared with us:

What do you consider as data in your research field?#

📽️ Sian Jones – Faculty Of Civil Engineering and Geosciences (CEG)

📽️ Wirawan Agahari – TU Delft Faculty of Technology, Policy and Management (TPM)

📽️ Aerospace researcher - TU Delft

In this video, a researcher from the Faculty of Aerospace Engineering at the TU Delft, tells us what data she collects or uses within her research project and what she needs to take care of when working with it.

Warning

⚠️ This video is only available with a TU Delft login ⚠️. Please click on this link

Confidential Data#

(from Research Data Management TU Delft)

There are multiple types of confidential data that you might be working with during your research project. Some examples include:

  • personal data (information about an identified or identifiable natural person)

  • national security data (e.g. nuclear research)

  • data falling under export control regulations

  • confidential data received from commercial, or other external partners

  • data related to competitive advantage (e.g. patent, IP)

  • data which could lead to reputation/brand damage (e.g. climate change, personal information, animal research)

  • politically-sensitive data (e.g. research commissioned by public authorities, research on societal issues)

When working with confidential data, you need additional security measures for your data to make sure that they are not accidentally released.

In the next two videos, researchers from TU Delft tell us about the confidential data they work with and what RDM best-practice they follow:

📽️ Sian Jones talking about collaboration with industry

📽️ Wirawan Agahari talking about personal data in his research

When you work with personal data at TU Delft, these are the materials to read:

Topic 2: The relevant RDM steps within a research project#

In the following interactive image you can go through a simplified cycle which can represent the workflow of your project. Have a look at the RDM questions you might need to ask yourself at each step of research. In the following interactive image you can go through a simplified cycle which can represent your project. Have a look at the RDM questions you might ask at each step of research.

Topic 3: Research Data infrastructure at TU Delft#

Before starting the data collection/creation within your project, it is good to reflect where you will store and how you will back up the data. Selecting a storage and backup strategy will mean that data is safe during your research project, including in the case of unpredicted problems. Following good data storage practices protect you from data loss and facilitate effective collaborations.

In this video, we will go through the infrastructure provided centrally at TU Delft for storing, backup and sharing Research Data. You should ask your supervisor if within your research group/department/ project there is a preferred approach for data storage and backup, or if there are customised solutions already in place.

Quiz - Use cases on storage#

After the topic on the Research data infrastructure, you should now be able to answer the questions of this quiz. Good luck!

Topic 4: The responsibilities for PhD candidates regarding RDM and Research Software at TU Delft#

In this section we would like to make you aware of the responsibilities of TU Delft PhD candidates regarding Research Data Management. These responsibilities are detailed in the University and Faculty Policies.

It is very important for TU Delft that researchers follow best practices on Research Data Management (RDM). That is why since 2018 TU Delft has published a set of policies which provide a clear division of roles and responsibilities around RDM.

Click to read the Research Data framework policy 📖

This Framework policy is accompanied by Faculty-specific research data management policies, which provide more detailed requirements and guidelines for the disciplines associated with each Faculty.

Click to read Faculty Research Data Management Policies 📖

Software is recognised at TU Delft as a valuable research output that needs to be well documented, preserved and, whenever possible, consistent with the FAIR principles. The TU Delft Research Software Policy provides a clear division of roles and responsibilities and sets out a simplified, streamlined process to help researchers share software openly. Check these resources:

TU Delft Research Software Policy 📖
TU Delft Guidelines on Research Software 📖

Question to you:

Were you already aware of any of these policies? And, now that you have looked at the different policies, are your responsibilities regarding Research Data and Software management clear to you?