🔑 Free Exclusive Career Checklist:
Research Data Management Librarian
This checklist outlines the essential steps to support researchers in managing, preserving, sharing, and reusing research data responsibly and effectively across the research lifecycle.
1. Research Data Management Foundations
| Step | Action Item | Status |
|---|---|---|
| 1.1 | Understand the Research Lifecycle: Clearly explain how data fits into proposal writing, data collection, analysis, publication, and long-term preservation. | |
| 1.2 | FAIR Data Principles: Explain and apply Findable, Accessible, Interoperable, and Reusable (FAIR) principles to research datasets. | |
| 1.3 | Data Management Plans (DMPs): Support researchers in creating, reviewing, and updating funder-compliant Data Management Plans. | |
| 1.4 | File Organization & Documentation: Recommend best practices for file naming, folder structures, README files, and data dictionaries. | |
| 1.5 | Data Formats: Identify preferred, sustainable file formats for long-term access and preservation. |
2. Metadata, Repositories & Preservation
| Step | Action Item | Status |
|---|---|---|
| 2.1 | Metadata Standards: Apply appropriate metadata schemas (e.g., Dublin Core, DataCite, DDI) based on discipline and repository. | |
| 2.2 | Repository Selection: Advise on choosing institutional, disciplinary, or general repositories for data deposit. | |
| 2.3 | Persistent Identifiers: Assign and explain DOIs, ORCID iDs, and other persistent identifiers for datasets and researchers. | |
| 2.4 | Digital Preservation: Understand versioning, checksums, backups, and long-term storage strategies. | |
| 2.5 | Data Citation: Teach researchers how to cite datasets properly in publications. |
3. Ethics, Compliance & Professional Practice
| Step | Action Item | Status |
|---|---|---|
| 3.1 | Legal & Ethical Data Use: Advise on copyright, licensing (CC BY, CC0), consent, and data reuse permissions. | |
| 3.2 | Sensitive Data Handling: Support anonymization, access controls, and compliance with GDPR, HIPAA, or local regulations. | |
| 3.3 | Training & Outreach: Deliver workshops, guides, and consultations on research data management best practices. | |
| 3.4 | Service Assessment: Track consultations, deposits, and researcher engagement to demonstrate impact. | |
| 3.5 | Professional Development: Stay current with RDM standards, policies, and communities of practice. |
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