Instructor Notes

General Advice


  • This workshop is designed for a mixed audience of PhD students and postdocs. Some will have never thought about RDM; others will have some experience. Pitch the teaching at beginners but use the challenges to stretch more experienced participants.

  • The workshop can be delivered in person or online. All challenges are designed to work in both settings — participants work in pairs or small groups using the shared challenge data files.

  • Encourage participants to relate every topic to their own research. The think-pair-share and group discussion formats work well for this.

  • The timing for each episode is a guide. If a discussion is productive, let it run — but keep an eye on the clock for Part 2, which has more content to cover.

Part 1: Research Data Management Principles


Episode 1: Why Does Research Data Management Matter?

  • The horror stories are there to motivate — keep them brief and punchy.
  • The data audit (Challenge 1) works well as an icebreaker. Give people time to think before sharing.

Episode 2: Planning Your Data — DMPs, Budgeting, and Funder Policies

  • The DMP Speed Round (Challenge 2) is a group exercise. Circulate and prompt groups that are stuck — common prompts: “What instruments will you use?”, “How much data per sample?”, “Where will you store 3 years of data?”
  • For the funder policy section, don’t try to cover every funder in detail. Focus on EPSRC and highlight that other funders differ.

Episode 3: FAIR Data Principles

  • Challenge 3 (data access statements) is key — it connects FAIR principles to something participants will actually have to write. Make sure to discuss all three fictional examples.

Episode 4: Data Storage, Security, and Organisation

  • Challenge 4 (FAIR self-assessment) can be uncomfortable for participants who score low. Frame it positively: this is about identifying areas for improvement, not judgement.

Episode 5: Sharing, Preserving, and Licensing Your Data

  • Challenge 5 (Fix This Folder) is hands-on. Make sure participants actually rename files on their laptops rather than just discussing what they would do.

Part 1 Capstone (Challenge 6a–c)

  • All groups work through the same three sub-challenges. Keep to time — 5 minutes each. Use a visible timer.

Part 2: Chemistry-Specific Data Management


Episode 6: The Reproducibility Crisis in Chemistry

  • Challenge 7 (Reproducibility Detective) generates good discussion. If time permits, ask groups to share the most surprising missing detail they found.

Episode 7: Electronic Lab Notebooks

  • This is a teaching-only episode. If participants have questions about specific ELNs, note them for discussion during the break or afterwards.

Episode 8: Metadata and Chemical Data Standards

  • Challenge 9b (InChI and SMILES) requires internet access. Test the NCI Chemical Identifier Resolver beforehand to make sure it is available.

Episode 9: Chemistry Data Repositories

  • Challenge 10 requires internet access. If re3data.org is slow, have a backup plan (e.g. show a pre-prepared search result).

Episode 10: Managing Data from Common Chemistry Techniques

  • Challenge 11 (multi-technique DMP) is the most substantial exercise in Part 2. Give groups time to discuss before reporting back.

Episode 11: PSDI and the Chemistry Data Landscape

  • If delivering with PSDI colleagues, this is a natural handover point for a live demo of PSDI tools.

Post-Workshop


  • Remind participants about the post-workshop action plan exercise (Challenge 13). Encourage them to complete it within a week while the workshop is fresh.
  • Share the feedback form link.

Why Does Research Data Management Matter?


Planning Your Data: DMPs, Budgeting, and Funder Policies


FAIR Data Principles


Data Storage, Security, and Organisation


Sharing, Preserving, and Licensing Your Data


The Reproducibility Crisis in Chemistry


Electronic Lab Notebooks for Chemists


Metadata and Chemical Data Standards


Chemistry Data Repositories and Databases


Managing Data from Common Chemistry Techniques


PSDI and the Chemistry Data Landscape