How do you ensure long-term data usability?

1 Choose appropriate data formats

One of the key factors that affect data usability is the format of the data. You should choose formats that are widely accepted, standardized, and compatible with different software and platforms. Avoid proprietary or obsolete formats that may become inaccessible or unreadable over time. For example, use plain text, CSV, or XML for tabular data, PDF/A for documents, TIFF or PNG for images, and WAV or MP3 for audio.

2 Document your data

Another important aspect of data usability is the documentation of the data. Documentation provides essential information about the data, such as its origin, context, content, structure, quality, and limitations. Documentation helps users to understand, interpret, and analyze the data correctly and efficiently. You should document your data using clear and consistent metadata standards, vocabularies, and conventions. For example, use DDI for social science data, Dublin Core for general data, or ISO 19115 for geographic data.

3 Validate your data

Data validation is the process of checking and verifying the accuracy, completeness, and consistency of the data. Validation helps to identify and correct any errors, gaps, or anomalies in the data that may affect its usability. You should validate your data throughout the data lifecycle, using appropriate methods and tools. For example, use checksums to detect file corruption, use quality control procedures to ensure data integrity, or use schema validation to ensure data conformity.

4 Preserve your data

Data preservation is the act of protecting and maintaining the data for long-term access and use. Preservation involves applying technical, organizational, and legal measures to ensure that the data is secure, reliable, and compliant. You should preserve your data using suitable storage media, backup systems, and preservation services. For example, use cloud storage, external hard drives, or optical discs for backup, use trusted repositories, archives, or libraries for preservation, or use persistent identifiers, licenses, or agreements for access.

5 Share your data

Data sharing is the practice of making the data available and accessible to other users, such as researchers, collaborators, or the public. Sharing enhances the usability of the data by increasing its visibility, discoverability, and reusability. You should share your data using appropriate platforms, policies, and practices. For example, use data portals, journals, or networks for dissemination, use open access, FAIR, or CARE principles for management, or use citation, attribution, or feedback mechanisms for recognition.

6 Review your data

Data review is the process of evaluating and updating the data to ensure its usability over time. Review involves monitoring and assessing the data's performance, impact, and value. You should review your data regularly, using relevant indicators and metrics. For example, use usage statistics, citations, or altmetrics to measure the data's reach, use feedback, reviews, or comments to gauge the data's quality, or use audits, surveys, or interviews to identify the data's needs.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?