Description

This curriculum spans the technical and operational complexity of a multi-year data preservation program, comparable to designing and maintaining a large-scale archival system across distributed infrastructure, regulatory domains, and technology lifecycles.

Module 1: Data Integrity and Long-Term Storage Architecture

Selecting erasure coding versus replication strategies based on storage cost, durability requirements, and recovery time objectives.
Designing multi-tier storage layouts that balance performance (SSD), capacity (HDD), and archival (tape/cloud) layers with data access patterns.
Implementing checksum validation workflows at write, read, and periodic intervals to detect silent data corruption.
Choosing between object storage and filesystem-based archives for large-scale unstructured data preservation.
Integrating geographic redundancy with consistency models that minimize cross-region bandwidth while ensuring recoverability.
Configuring storage APIs to enforce immutability and WORM (Write Once, Read Many) compliance for regulated data.
Evaluating storage hardware longevity, including bit rot mitigation and firmware obsolescence planning.
Mapping data retention policies to storage class transitions using automated lifecycle rules.

Module 2: Metadata Management for Data Provenance

Defining mandatory metadata schemas (e.g., PREMIS, Dublin Core) aligned with domain-specific preservation needs.
Embedding technical metadata at ingestion, including file format, creation environment, and processing history.
Implementing automated metadata extraction pipelines for diverse data types (images, logs, sensor feeds).
Resolving conflicts between embedded metadata and external catalog records during data migration.
Designing metadata versioning to track changes without overwriting original context.
Securing metadata access controls to prevent unauthorized modification while enabling auditability.
Integrating provenance tracking with workflow systems to log data transformations and ownership changes.
Planning for metadata format obsolescence by scheduling periodic schema migration and validation.

Module 3: Format Sustainability and Migration Planning

Assessing format obsolescence risk using tools like PRONOM and institutional usage trends.
Establishing format normalization pipelines that convert proprietary formats to preservation-grade standards (e.g., TIFF, PDF/A).
Implementing automated format validation at ingest using DROID or file utility checks.
Designing migration workflows that preserve semantic meaning and visual fidelity across versions.
Documenting transformation rules and maintaining sidecar logs for audit and rollback purposes.
Balancing format migration frequency against resource costs and data stability requirements.
Creating emulation strategies as an alternative to migration for complex interactive or executable content.
Coordinating with software vendors to obtain format specifications for at-risk proprietary formats.

Module 4: Scalable Ingest and Validation Pipelines

Designing parallelized ingestion workflows to handle high-volume data streams without bottlenecks.
Implementing content-based validation rules, including file header checks and payload structure analysis.
Configuring deduplication at ingestion using cryptographic hashing while preserving provenance.
Integrating virus scanning and malware detection without introducing latency in the ingest path.
Handling incomplete or interrupted transfers with resume-capable protocols and state tracking.
Logging ingest failures with actionable diagnostics for operator intervention or automated retry.
Enforcing data packaging standards (e.g., BagIt) to ensure completeness and transport integrity.
Allocating resources for real-time validation versus batch post-processing based on data criticality.

Module 5: Access Control and Usage Governance

Mapping data sensitivity levels to access tiers using attribute-based access control (ABAC).
Implementing time-bound access tokens for external researchers or temporary collaborators.
Logging all data access events with user identity, timestamp, and requested operations for audit trails.
Enforcing anonymization or redaction rules dynamically at query time for regulated datasets.
Integrating with institutional identity providers (e.g., SAML, OAuth) for centralized user management.
Designing tiered access policies that balance openness with privacy and intellectual property constraints.
Handling access revocation across distributed caches and replicas consistently and promptly.
Managing data use agreements by embedding policy enforcement into access workflows.

Module 6: Disaster Recovery and Continuity Planning

Defining RPO (Recovery Point Objective) and RTO (Recovery Time Objective) for different data classes.
Testing failover procedures between primary and secondary preservation sites under simulated outages.
Validating backup integrity through periodic restore drills on isolated environments.
Documenting chain-of-custody procedures for data recovery involving third-party vendors.
Securing offsite storage locations with environmental controls and intrusion detection.
Automating backup verification with checksum comparisons and metadata reconciliation.
Establishing communication protocols for declaring and managing data emergencies.
Archiving recovery playbooks in durable, accessible formats separate from primary systems.

Module 7: Auditability and Compliance Frameworks

Implementing write-once audit logs with cryptographic chaining to prevent tampering.
Mapping data handling practices to regulatory requirements (e.g., GDPR, HIPAA, FISMA).
Generating compliance reports that demonstrate adherence to retention and access policies.
Conducting internal audits using automated tools to detect policy deviations.
Preparing for external audits by organizing evidence trails and access logs in standardized formats.
Integrating data classification labels into audit systems to prioritize monitoring efforts.
Responding to data subject requests (e.g., right to erasure) without compromising preservation integrity.
Updating compliance controls in response to legal or jurisdictional changes affecting stored data.

Module 8: Monitoring, Metrics, and System Health

Deploying distributed monitoring agents to track storage utilization, I/O latency, and node health.
Setting dynamic thresholds for anomaly detection based on historical access and error patterns.
Correlating system logs across preservation layers to identify cascading failures.
Generating preservation health dashboards for technical and executive stakeholders.
Implementing automated alerts with escalation paths for critical integrity or availability issues.
Measuring fixity check completion rates and error trends to assess system reliability.
Using metadata completeness scores as a KPI for data quality across the repository.
Scheduling regular system calibration, including clock synchronization and certificate renewal.

Module 9: Technology Refresh and Obsolescence Management

Establishing a technology refresh cycle based on vendor support timelines and hardware failure rates.
Planning data migration from legacy systems with deprecated protocols (e.g., NFSv3, iSCSI targets).
Documenting system dependencies for software stacks used in data rendering and access.
Conducting pilot migrations to validate compatibility with new storage or processing platforms.
Retiring hardware securely with data sanitization procedures compliant with NIST 800-88.
Maintaining a registry of software versions and dependencies for reproducibility.
Engaging with open-source communities to extend support for critical preservation tools.
Allocating budget and resources for periodic re-architecting of preservation infrastructure.