About

This page has links and images that support the material presented in the workshop.

Information sources

Here are links to some of the sources mentioned during the workshop presentations.

Handouts

  • File naming convention worksheet.
  • Naming and organizing your files and folders worksheet (MIT Libraries).
  • Repository selection & metadata consideration worksheet.

Better data practices

(Alaina Pearce)

  • Talk slides (PDF).

Preparing data for reuse

(Briana Wham)

  • Talk slides (PDF)

Consulting OpenAI

Just for fun, we thought we would ask OpenAI for some insights about data management practices.

The response below was generated from the prompt “suggestions about good enough data management practices”.

openai::create_chat_completion(model = "gpt-3.5-turbo",
                       messages = list(
                         list("role" = "user",
                              "content" = "suggestions about good enough data management practices")))
  1. Regular data backups: It is important to regularly backup all essential data to prevent loss in case of system failure or cyber attack.
  2. Data encryption: Protect sensitive data by encrypting it to prevent unauthorized access.
  3. Access controls: Implement strong access controls to ensure that only authorized personnel have access to sensitive data.
  4. Data storage: Store data in secure and reliable locations to prevent loss or corruption.
  5. Data validation: Regularly validate and clean data to ensure accuracy and integrity.
  6. Compliance with regulations: Ensure that data management practices comply with relevant regulations to avoid legal issues.
  7. Regular audits: Conduct regular audits of data management processes to identify and address any weaknesses or inefficiencies.
  8. Data retention policies: Implement clear data retention policies to ensure that data is not stored longer than necessary.
  9. Training: Provide training to employees on data management best practices to ensure that they understand and follow proper procedures.
  10. Disaster recovery plan: Develop a comprehensive disaster recovery plan to ensure that data can be recovered in case of a catastrophic event.