What is Data Preservation and Why is it Important?

Data preservation is the process of maintaining data's safety, integrity, and accessibility over time. It involves using policies, regulations, and strategies to protect data and its metadata from loss or destruction, ensuring it can be reused in the future.

Data preservation is important for many reasons, including research, historical documentation, legal purposes, and compliance with regulations. Ensuring data remains stable and accessible supports reproducibility in research and safeguards valuable information for future use.

How Can Data Be Effectively Shared?

Data sharing is the process of making data available to others, typically to support transparency and reproducibility in research. Effective data sharing involves depositing data in a data repository, which provides long-term preservation and a stable access point.

It is important to follow the FAIR principles—making data Findable, Accessible, Interoperable, and Reusable. Sensitivity, size, and complexity of the dataset should be considered, along with the volume of requests that might be received.

What Are the Best Practices for Data Preservation?

To preserve data effectively, it is crucial to follow several best practices. These include storing data in durable formats, securing data in multiple locations, and using encryption. Regular backups and using data repositories for long-term preservation are also key strategies.

Other best practices involve combating bit rot by periodically copying data to new storage media, training on defensible preservation, creating an inventory of devices, and collecting data remotely to prevent over-preservation.

What Are Types of Data Preservation and Sharing Techniques?

Data preservation and sharing techniques vary, each with its own advantages and specific applications. These techniques help maintain data integrity, ensure accessibility, and facilitate proper data management.

Durable Formats

Choosing durable formats like XML, CSV, PDF, or TIFF ensures that data remains useful and accessible in the future. These formats are widely supported and less likely to become obsolete.

• XML: Extensible Markup Language is flexible and widely used for data representation.
• CSV: Comma-separated values are simple and supported by many applications.
• PDF: Portable Document Format is ideal for preserving the layout and content of documents.
• TIFF: Tagged Image File Format is used for high-quality images and documents.

Data Security

Securing data involves storing it in safe locations, using encryption, and employing access controls. This protects data from unauthorized access and ensures its integrity over time.

• Encryption: Encrypt data to protect it during transfer and storage.
• Access controls: Implement robust access controls to restrict data access to authorized users.
• Secure locations: Store data in secure, reliable locations to prevent loss or damage.
• Multi-location storage: Distribute data across multiple locations to safeguard against loss.

Data Backups

Regularly backing up data is crucial for recovery in case of data loss. Automated backup systems that verify data integrity are particularly effective.

• Automated systems: Use automated systems for regular backups and integrity checks.
• 3-2-1 rule: Maintain three copies of data on two different storage media.
• Offsite backups: Store backups in offsite locations for additional security.
• Verification: Regularly verify the integrity of backup data to ensure reliability.

Data Repositories

Using data repositories helps ensure long-term preservation and accessibility. Repositories often provide curation services, verifying data integrity, migrating formats, and creating descriptive records.

• Curation services: Repositories often include curation services to maintain data quality.
• Discipline-specific: Choose repositories specific to your discipline for better visibility.
• Multidisciplinary: Use multidisciplinary repositories if no discipline-specific ones are available.
• Repository registries: Use registries like re3data.org to find suitable repositories.

Metadata Management

Using metadata helps manage and target data collection, making it easier to find and use in the future. Proper metadata ensures data is well-documented and accessible.

• Descriptive metadata: Provide detailed descriptions to aid data discovery and use.
• Structural metadata: Include information on data structure for easier interpretation.
• Administrative metadata: Document administrative details, such as data ownership and access rights.
• Metadata standards: Follow established standards for metadata to ensure consistency and interoperability.

Data Observability

Data observability tools ensure data integrity and reliability, helping teams make informed decisions. These tools monitor data quality, detect anomalies, and provide insights for data management.

• Monitoring: Continuously monitor data quality and detect issues promptly.
• Insights: Gain insights into data usage and performance for better decision-making.
• Anomaly detection: Identify and address anomalies in data to maintain accuracy.
• Reliability: Ensure data reliability through proactive management and monitoring.

Data Custodians

Assigning a responsible custodian, such as a data repository, ensures data is properly curated and maintained. Custodians oversee data management and ensure compliance with preservation standards.

• Data curation: Custodians manage data curation to maintain quality and integrity.
• Compliance: Ensure compliance with data preservation standards and regulations.
• Access management: Oversee access controls to protect data from unauthorized use.
• Long-term preservation: Implement strategies for long-term data preservation.

What Are the Roles and Responsibilities of Data Stewards?

Data stewards, also known as data owners or referees, are responsible for ensuring that an organization's data is accessible, usable, safe, and trusted. They oversee the entire data lifecycle, including data quality, privacy, and security.

Data stewards set up validation rules, regularly audit data, and rectify issues to ensure data quality. They also stay up to date on data protection laws, classify data, and develop policies for data retention, privacy, use, and regulations.

What Are the Best Practices for Data Stewardship?

Best practices for data stewardship include establishing clear roles and policies, automating quality checks, and breaking down data silos. Empowering users with self-service tools and measuring success are also important.

Data stewardship involves managing data lineage, enforcing usage rules, and maintaining business and technical rules. These practices ensure data is well-managed, secure, and accessible for organizational needs.

How Does Secoda Enhance Data Preservation?

Secoda is a data management platform that centralizes and organizes a company's data and metadata. By acting as a single source of truth, it helps data teams find, understand, and use data more efficiently. Secoda employs AI and machine learning to make data accessible and understandable for all team members, regardless of their technical expertise.

Features of Secoda for Data Preservation

• Centralized Repository: Secoda acts as a single source of truth for all data and metadata, ensuring that data is preserved in a consistent and organized manner.
• AI-powered Indexing: The platform automatically categorizes and indexes data assets, making it easier to search and retrieve information, thereby supporting data preservation efforts.
• Automated Documentation: Secoda reduces the manual workload involved in documenting data, streamlining data management processes and ensuring that data remains well-documented and preserved.
• Data Lineage: The tool tracks relationships between people and data, visualizing interactions and ensuring that the history and context of data are preserved over time.
• Security: Secoda is SOC 2 Type 1 and 2 compliant and includes features like SAML, SSO, and MFA, ensuring that data is securely preserved and protected from unauthorized access.