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Module 2: Data Documentation and Storage

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The training curriculum is currently undergoing final revisions and quality checks. All materials will be released shortly. Until the official release, please refrain from using, distributing, or implementing any part of these resources.

Learning Objectives

  • Learning Objective 1 (LO1): Define research data with examples.
  • Learning Objective 2 (LO2): Recognise the responsibilities regarding Research Data Management during data collection and storage.
  • Learning Objective 3 (LO3): Apply documentation to data in accordance with policy and regulations relevant to the context of the Data Steward.

Total Module Duration

3.25 hours

Learning Objective 1

LO1: Define research data with examples.

Learning Activities

  • Presentation (20 mins): Define research data and introduce the importance of data collection during the research process.
  • Discussion (40 mins): Give the participants a case study (suggestions for where to source one provided in instructor notes) or ask them to present an example of a research project. Discuss in pairs what is the research data collected during different stages of the research process.

Materials to Prepare

  • Presentation slides on defining research data.
  • Example research project case study.

Instructor Notes

Presentation:

  • Introduce the concept of research data and how research data is collected during the different phases of the research life cycle. To help with the slide presentation, definitions of research data and how research data is collected can be found in Resources 1 and 2.

Discussion:

  • The instructor can initiate the discussion exercise by asking learners to discuss a research case (from their experience) or by playing one or two of the videos that are available within Resource 1 where researchers talk about their research.
  • The instructor can also use one of the case studies provided under Scary Tales (Resource 3) to demonstrate how things can go badly with poor research data collection.

Resources

Input for Presentation and discussion:

  1. Martinez-Lavanchy, P. M., et al. TU Delft Research Data Management 101 Course. Zenodo, 1 Mar. 2024. DOI.org (Datacite). https://doi.org/10.5281/ZENODO.10732095.
  2. Course: Essentials 4 Data Support (English) - Public | DANS. https://danstraining.moodlecloud.com/course/view.php?id=11. Accessed 17 Mar. 2025.
  3. Lang, Kevin, et al. Research Data ScaryTales. Zenodo, 12 Mar. 2025. DOI.org (Datacite). https://doi.org/10.5281/ZENODO.4066679.

Learning Objective 2

LO2: Recognise the responsibilities regarding Research Data Management during data collection and storage.

Learning Activities

  • Practical Exercise – Data Flow Map (45 mins): Facilitate the data flow map exercise that is provided in Resource 1.
  • Reflection activity (45 mins): Identify institutional data documentation and metadata documentation tools. Make this a think-pair-share exercise which is explained in more details in Resource 3.

Materials to Prepare

  • Presentation on storing data and metadata.
  • Reflection activity on institutional documentation tools.

Instructor Notes

Presentation:

  • Highlight the importance of storing contents of research as well as data and metadata (information about the data). The presentation can highlight which tools are available for data documentation. The facilitator can relate this to the local context by introducing (for example) different tools available according to the policies of their institutes or by initiating discussion among the learners.
  • The instructor can introduce the data flow map at this stage and use this to facilitate a practical exercise or use parts of it in a presentation format (see Resource 1).

Reflection Activity:

  • For the reflection activity, the instructor can first introduce some of the possible tools that are available for data and metadata documentation: for instance, README files, Data Management Plans, Electronic Lab Notebooks. Discuss this and other tools, especially prescribed tools within the learners institutional or national context. Let participants discuss what they use in their local context.

Resources

Input for Presentation and discussion:

  1. Exercise 1. Data Flow Map. https://tu-delft-library.github.io/rdm101-book/RDM101course-exercise1.pdf.
  2. Martinez-Lavanchy, P. M., et al. TU Delft Research Data Management 101 Course (Module 2). Zenodo, 1 Mar. 2024. DOI.org (Datacite). https://doi.org/10.5281/ZENODO.10732095.
  3. Think, Pair, Share | Kent State University. https://www.kent.edu/ctl/think-pair-share. Accessed 15 Apr. 2025.

Learning Objective 3

LO3: Apply documentation to data in accordance with policy and regulations relevant to the context of the Data Steward.

Learning Activities

  • Discussion (45 mins): Participants list their institutional policies (if any) that outline RDM. They discuss the best practices for data documentation and storage within these policies. This discussion can be done in small groups. At the end of the discussion, each group can present/summarise documentation/storage practices highlighted in the policy they discussed OR if they have real life examples to showcase the practice this would be even better. If there is no institutional policy in place then they can discuss what are the current RDM practices within their institute and what a policy document should take into account or the trainer can provide them with an existing RDM policy.

Materials to Prepare

  • Facilitate discussion by having one or two institutional policies to share with the group (refer to Resources 1–4 for some examples).

Instructor Notes

Discussion:

  • The instructor can introduce the goal of an institutional policy to outline how researchers are provided support to implement good RDM practices as well as data documentation and storage practices. Such a policy helps an institute to identify and address gaps and challenges in infrastructure, resources and other practices related to RDM.
  • The instructor should outline the key elements of an RDM policy concerning data documentation and storage which includes:
    • the goal of a policy as well as definitions,
    • scope of policy (which data it is dealing with),
    • roles and responsibilities of various stakeholders with regards to data documentation and storage, and
    • any compliance or recommendations that have to be adhered to or other practices to be followed (Resources 3, 4).
  • The instructor can find many institutional data policies online by doing an online search. Some links have been provided in the resource.

Resources

Input for Discussion:

  1. "Research Data Management Code of Conduct." Maastricht University Library, 3 Jul. 2024. https://library.maastrichtuniversity.nl/research/rdm/rdm-policies/research-data-management-code-of-conduct/.
  2. "RDM Policies." Vrije Universiteit Amsterdam. https://vu.nl/en/about-vu/more-about/rdm-policies. Accessed 25 Mar. 2025.
  3. "TU Delft & Faculty Policies." TU Delft. https://www.tudelft.nl/en/library/current-topics/research-data-management/r/policies/tu-delft-faculty-policies. Accessed 25 Mar. 2025.
  4. Policies and Guidelines for Research Data Management - For Employees - University of Oslo. https://www.uio.no/english/for-employees/support/research/research-data-management/policies-guidelines.html. Accessed 25 Mar. 2025.