Scheduled data backups to secure storage

Purpose

1. Automate scheduled data backups of critical research datasets to secure, compliant storage solutions as required by research data management policies.

2. Automating backup guarantees regular, reliable, and tamper-proof replication of project datasets, research findings, lab results, and sensitive documentation to prevent data loss and ensure business continuity.

3. Supports scalable, cross-departmental research activities by automatically archiving raw, processed, and metadata in alignment with institutional and industry-specific compliance.

4. Automates archival versioning and retention policies to facilitate rapid data recovery, review, and auditing as mandated by funding agencies and research partners.

Trigger Conditions

1. Time-based triggers: scheduled intervals (e.g., daily, weekly, monthly) automate initiation of backup.

2. Event-based triggers: research data updates, file upload completion, or milestone achievement automates workflow.

3. Manual override: authorized staff can automate ad-hoc backups for urgent research projects.

4. API/webhook triggers: backup automation when research management systems or ELNs send new entries/events.

Platform Variants

1. AWS S3

• Feature: S3 PUT Object API, lifecycle rules, S3 Copy operations for automated backup and archiving; sample config: schedule Lambda to copy files nightly.
  

2. Azure Blob Storage

• Feature: Blob Storage REST API/Blob Storage Lifecycle Management; configure Logic Apps or Functions to automate data transfer to secure container.
  

3. Google Cloud Storage (GCS)

• Feature: GCS Transfer Service API; configure scheduled transfers from source datasets to automated secure GCS buckets.
  

4. OneDrive for Business

• Feature: Microsoft Graph API / Scheduled Flows; automated backup flows with path, retention rules, and notifications.
  

5. Dropbox Business

• Feature: Scheduled Dropbox API uploads; configure automated scripts to backup selected research folders.
  

6. Backblaze B2

• Feature: B2 API automated copy and upload endpoints; automate scripts to push new backup sets.
  

7. Wasabi Hot Cloud Storage

• Feature: S3-compatible API; automate connections and scheduled backup scripts via SDK or CLI.
  

8. DigitalOcean Spaces

• Feature: S3-compatible API for automating scheduled research project backup uploads.
  

9. Box

• Feature: Box API upload endpoint; Flow automation to migrate new and changed files.
  

10. Nextcloud

• Feature: WebDAV API, external storage scheduler for automated on-premises or cloud data sync.
  

11. Synology NAS

• Feature: Synology Drive API, Hyper Backup; automate periodical backup tasks to NAS or paired cloud.
  

12. OwnCloud

• Feature: WebDAV for automated scheduled sync; configure tasks in research directories.
  

13. IBM Cloud Object Storage

• Feature: Scheduled IBM Cloud Functions or CLI/Terraform automates backup from research data locations.
  

14. iDrive

• Feature: Command line scheduler and API; automate recurring backup jobs to secure vault.
  

15. Egnyte

• Feature: Egnyte Public API; automate workflows to move project data on interval.
  

16. Zoho WorkDrive

• Feature: WorkDrive API + Scheduler; automate regular research data uploads.
  

17. SharePoint

• Feature: Microsoft Graph API/Power Automate; configure scheduled document library backup flows.
  

18. SFTP/FTPS Servers

• Feature: Automated scheduled SFTP/FTPS transfers using scripting or orchestration tools.
  

19. Filebase

• Feature: S3 API for automation; automate programmable uploads to decentralized backend.
  

20. Mega.nz

• Feature: Mega Command Line API; automate scheduled uploads from research endpoints.
  

Benefits

1. Automates compliance with research data retention regulations and policies.

2. Provides automated, version-controlled backups for reproducibility and audit.

3. Enables secure, encrypted, and automated backup to local, hybrid, or cloud environments.

4. Minimizes risk of human error—backups are automated, scheduled, and monitored.

5. Supports scaling of research activities without manual data management; automation allows staff and researchers to focus on core scientific tasks.

6. Facilitates automated disaster recovery, data restoration, and validation.