Policy-based data management enables the creation of community-specific collections. Every collection is created for a purpose. The purpose defines the set of properties that will be associated with the collection. The properties are enforced by management policies that control the execution of procedures that are applied whenever data are ingested or accessed. The procedures generate state information that defines the outcome of enforcing the management policy. The state information can be queried to validate assessment criteria and verify that the required collection properties have been conserved. The integrated Rule-Oriented Data System implements the data management framework required to support policy-based data management. Policies are turned into computer actionable Rules. Procedures are composed from a microservice-oriented architecture. The result is a highly extensible and tunable system that can enforce management policies, automate administrative tasks, and periodically validate assessment criteria. iRODS 4.0+ represents a major effort to analyze, harden, and package iRODS for sustainability, modularization, security, and testability. This has led to a fairly significant refactorization of much of the underlying codebase. iRODS has been modularized whereby existing iRODS 3.x functionality has been replaced and provided by small, interoperable plugins. The core is designed to be as immutable as possible and serve as a bus for handling the internal logic of the business of iRODS. Seven major interfaces have been exposed by the core and allow extensibility and separation of functionality into plugins.

About the Author

Hao Xu is a research scientist at the Data Intensive Cyber Environment Center, University of North Carolina at Chapel Hill. He has been working on improving the rule engine and the rule language, and the metadata catalog of the integrated Rule-Oriented Data System (iRODS) since 2010. He developed pluggable rule engine architecture that allows interoperability between different programming languages and the iRODS data management systems. He also developed QueryArrow, a semantically unified query and update system that allows bidirectional integration of metadata from multiple heterogeneous data stores. His research interests include theory of data management, automatic theorem proving, programming languages, distributed data systems, and formal methods in software development. He has a B.E. in computer science and engineering and a B.S. minor in applied mathematics from Beihang University and a Ph.D. in computer science from University of North Carolina at Chapel Hill.

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