4.12 Store data according to the needs of your users
Hosting, Infrastructure, and Systems
Set expiration dates on data so it can be archived, made available offline, or removed when no longer used or required, with the remaining content tagged for future management.
Criteria
- Reduce redundancy: Human-testable
Regularly audit for and delete redundant, abandoned, or single-use data – often referred to as dark data – to reduce storage demand and energy use.- A Call for Research on Storage Emissions (PDF)
- Dark data is killing the planet – we need digital decarbonisation
- Dark Data Is Leaving a Huge Carbon Footprint, And We Have to Do Something About It
- Exploring the sustainability challenges facing digitalization and internet data centers
- GPF – General Policy Framework (PDF) – 8.8 – Hosting (Hot / Cold Data)
- Green by Default
- Microsoft Azure WAF – Only store what is relevant
- The Cloud Is Material
- What is dark data?
- Expiration dates: Machine-testable
Assign expiration and/or maximum retention dates to stored data where appropriate, treating excess data as a form of technical debt. Simultaneously observe any applicable minimum data retention periods. Make data cleanup an established organization-wide routine to prevent long-term data accumulation.- AWS WAF – SUS04-BP03 – Use policies to manage the lifecycle of your datasets
- AWS WAF – SUS04-BP05 – Remove unneeded or redundant data
- GPF – General Policy Framework (PDF) – 7.2 – Back-End (Data Retention)
- Help users to Know that a page is up to date
- How to Create Your Own localStorage with Expiry Time in JavaScript
- How to label a webpage as being out-of-date
- Using an expiry date in JavaScript to create self-destructing data
- Classify and tag: Machine-testable
Implement a data classification and tagging policy to improve visibility, simplify management, and enable efficient removal of outdated or unused data. - Justify storage: Human-testable
Store data only when it cannot be easily or accurately regenerated.- AWS WAF – SUS04-BP08 – Back up data only when difficult to recreate
- Back up data only when difficult to recreate
- GPF – General Policy Framework (PDF) – 1.6 – Strategy (Data Collection)
- GPF – General Policy Framework (PDF) – 7.2 – Back-End (Data Retention)
- Green by Default
- Microsoft Azure WAF – Only store what is relevant
- This Earth Day, Reduce Your Corporate Carbon Footprint with Data Minimization
- Optimize logging: Machine-testable
Optimize log collection and storage by scheduling backups during low-activity hours, rotating logs appropriately, and using off-site, sustainable providers.- An Engineer’s Checklist of Logging Best Practices
- AWS WAF – SUS04-BP08 – Back up data only when difficult to recreate
- Data Compression
- GPF – General Policy Framework (PDF) – 1.6 – Strategy (Data Collection)
- GPF – General Policy Framework (PDF) – 7.2 – Back-End (Data Retention)
- GR491 – 3-7041 – Transfer Compression
- Microsoft Azure WAF – Batch Processing
- Microsoft Azure WAF – Only store what is relevant
- Asset downloads: Human-testable
Make large, long-term assets available for easy download in order to provide users with regular offline access without requiring persistant server resources.
Benefits
- Economic
Storing less data reduces the expense of operating excessively large storage and archiving systems. - Environment
Reducing data storage brings down the carbon emissions driven by storage system operation. - Security
Storing smaller amounts of data reduces the amount of data exposed to potential security issues and reduces monitoring effort.
GRI
- Materials: Low
- Energy: Low
- Water: Low
- Emissions: Low