# Analyze & Collaborate Stage

<figure><img src="https://1394946355-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FZL4sEq1AZ78TabPPsj8G%2Fuploads%2FHMcaBw2T4IRlv13jvTRj%2F0.jpeg?alt=media" alt=""><figcaption><p>Analyze &#x26; Collaborate Stage</p></figcaption></figure>

## **Analyze and Collaborate Stage – Summary Table**

| **Category**                           | **Details & Best Practices**                                                                                                                                                                                                                                                                                                                                                                                      |
| -------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **Stage Purpose**                      | Inspect, clean, transform, and model data to generate insights, draw conclusions, and support research decision‑making, while ensuring data remains high‑quality, reproducible, and reusable.                                                                                                                                                                                                                     |
| **Importance**                         | Decisions and practices at this stage directly affect the quality of analysis, long‑term usability, FAIR compliance, and EU funder reproducibility requirements.                                                                                                                                                                                                                                                  |
| **Document Every Step**                | - Record all data processing and transformation steps for reproducibility.- Use Electronic Lab Notebooks (ELNs), collaborative tools, or workflow‑tracking software (Jupyter, R Markdown, Galaxy, OMERO).- Capture: • Scripts, pipelines, and commands• Software versions and dependencies• Parameters or filtering applied- Thorough documentation supports UCPH Open Science and Horizon Europe/ERC compliance. |
| **Ensure Data Safety & Organization**  | - Annotate datasets as you analyze them; maintain clear folder structures and file naming conventions.- Store data in secure UCPH/reNEW solutions: ERDA, high‑security servers, SharePoint for collaboration.- Separate raw vs processed datasets to protect originals.- Export or convert proprietary formats to open formats (CSV, TIFF, JSON) for interoperability and future reuse.                           |
| **Facilitate Collaboration & Sharing** | - Share intermediate data using controlled, collaborative platforms (internal or approved external).- Implement explicit permissions and version control to prevent accidental overwriting.- Comply with GDPR for sensitive or personal data.- Aligns with EU funder (Horizon Europe, ERC) reproducibility and sharing expectations.                                                                              |
| **Benefits**                           | - Ensures data integrity and transparency.- Enhances reproducibility and team collaboration.- Prepares datasets for publication or repository deposition, supporting long‑term impact and reuse.                                                                                                                                                                                                                  |