Informatics playbook¶
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Contents:
- Chapter 1: Licensing for Research Data
- Intended audience
- Why is this important?
- Takeaways
- A) License is public, discoverable, and standard
- B) License requires no further negotiation and its scope is both unambiguous and covers all of the data
- C) Data covered by the license are easily accessible
- D) License has little or no restrictions on the type of (re)use
- E) License has little or no restrictions on who can (re)use the data
- Lessons learned:
- Acknowledgments
- Chapter 2: Best practices for Using Identifiers
- Intended audience
- Why is this important?
- Status and contribution mechanisms
- Takeaways
- Lesson 1. Credit any derived content using its original identifier
- Lesson 2. Help local IDs travel well; document prefix and patterns
- Lesson 3. Opt for simple, durable web resolution
- Lesson 4. Avoid embedding meaning or relying on it for uniqueness
- Lesson 5. Design new identifiers for diverse uses by others
- Lesson 6. Implement a version-management policy
- Lesson 7. Do not reassign or delete identifiers
- Lesson 8. Make URIs clear and findable
- Lesson 9. Document the identifiers you issue and use
- Lesson 10. Reference and display responsibly
- Acknowledgments
- Chapter 3: Sharing Educational Resources
- Intended audience
- Current version / status
- Guidance
- Lessons learned / summary
- Why this is important
- Status and feedback mechanisms
- Takeaway List
- Deep dive into takeaways
- 1. Submit your educational resource to the CLIC Educational Clearinghouse
- 2. Consider making your resource an Open Educational Resource
- 3. Make metadata available for an educational resource by publishing metadata using a standard such as MIER or Harper Lite
- 4. Add metadata that encourages reuse of your educational resource
- 5. Encourage the formation of an educational community around an educational resource
- 6. Foster growth and updates of your material through quarterly hackathons or sprints
- Acknowledgments
- Chapter 4: Managing Translational Informatics Projects
- Intended audience
- Why is this important
- Takeaways
- Pick the project management technique that is appropriate for your project (Agile, Waterfall Model, Kanban, etc)
- Understand the implications of that management technique for the full lifecycle of your project
- Get familiar with your (diverse) stakeholders
- Have a process for team onboarding (Some guidance here for using forms)
- Have a process communications
- Have a process for shared document management
- Organize work into a roadmap that is clear and achievable
- Pick the work tracking platform that is right for your (whole) team
- Focus your planning efforts in discrete horizons (eg. 2 weeks, 2 months, 2 years)
- Make sure that all of the work that is planned is also assigned
- Don’t make security or licensing an afterthought
- Don’t be afraid to course correct
- Acknowledgments
- Chapter 5: Software and Cloud Architecture
- Chapter 6: Understanding Data Harmonization
- Chapter 7: Repository Architecture for Data Discovery
- Chapter 8: Best practices for attribution and use of attribution
- Chapter 9: Best practices of annotating clinical texts for information extraction tasks
- Intended Audience
- Current Version
- Status and Feedback Mechanisms
- Why is this important?
- Roles
- Project Lifecycle
- Takeaways
- Examples
- Open-sourced text annotation tools
- Annotation toolkits
- TRUST: clinical Text Retrieval and Use towards Scientific rigor and Transparent process.
- Acknowledgment
- References
- Chapter 10: Selecting an eConsent Platform
- Authors
- Intended audience
- Key Words
- Version history
- Why is this important?
- Development of an eConsent Assessment Framework
- Understanding Your eConsent Needs - Performing a Needs Assessment
- Evaluating eConsent platforms for potential implementation
- Use and applicability of the eConsent Assessment Framework
- Limitations of the eConsent Assessment Framework
- Summary
- About the authors and contributors to this playbook chapter
- Acknowledgements
- Funding
- Tutorial: How to write a chapter using markdown