ABSTRACT
Chapter 8 focuses on managing research data across its entire life cycle to ensure long-term integrity and usefulness. A key concept is data provenance – maintaining an audit trail of where data originate and how they evolve through processing. By documenting data lineage, researchers make it possible for others (and their future selves) to trace every transformation applied to a dataset. The chapter also stresses version control for data. As datasets are updated or corrected over time, it is crucial to save versioned copies or use tools (like Git or persistent identifiers) to track changes. Drawing on library science principles, it advises storing data in stable, nonproprietary formats, creating backups, and depositing data in archives or repositories for safekeeping. Ensuring data quality is an ongoing theme: implementing checks at every stage of the life cycle and using comprehensive metadata so that even years later, the context and meaning of data remain clear. The abstract underscores an expanded sense of responsibility: researchers must act as custodians of their data, not only analyzing it for current needs but also preparing it for future reuse. By investing in provenance tracking, versioning, and preservation, scientists uphold the reliability of the evidence base and enable cumulative, transparent science over time.
