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.

Autorentext

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.Terrell Russell is serving as the Chief Technologist of the iRODS Consortium at the Renaissance Computing Institute (RENCI). Terrell works on build and test for iRODS as well as code review, package management, documentation, and high-level architecture design. He's interested in distributed systems, metadata, security, and open source software that accelerates science. Terrell holds a B.S. in computer engineering, a B.S. in information technology and service organizations, an M.S. in computer networking from North Carolina State University, and a Ph.D. in information science from the University of North Carolina at Chapel Hill. Terrell has been working on iRODS since 2008.Jason Coposky is the Executive Director of the iRODS Consortium at the Renaissance Computing Institute (RENCI). With over 20 years of industry experience, Jason has worked in a variety of areas including virtual reality, EDA, visualization, and data management. Prior to RENCI, Jason was Technical Director for a startupwhere he developed projection and distortion correction technologies. During his tenure at RENCI, he began as the first member of the Visualization team, creating novel large format display and multitouch systems. He then moved to the irods@renc114 project as technical lead where he later became Chief Technologist of the iRODS Consortium. In his current role, he provides management oversight for the entire Consortium.Arcot Rajasekar is a professor in the School of Library and Information Sciences at the University of North Carolina, Chapel Hill, and a chief scientist at the Renaissance Computing Institute (RENCI). Previously, he was at the San Diego Supercomputer Center at the University of California, San Diego, leading the Data Grids Technology Group. He has been involved in research and development of data grid middleware systems for over a decade and is a lead originator behind the concepts in the Storage Resource Broker (SRB) and the integrated Rule Oriented Data Systems (iRODS), two premier data grid middleware developed by the Data Intensive Cyber Environments Group. Dr. Rajasekar has a Ph.D. in computer science from the University of Maryland at College Park and has more than 100 publications in the areas of data grids, logic programming, deductive databases, digital library, and persistent archives.Reagan Moore (retired) was a professor in the School of Information and Library Science at the University of North Carolina, Chapel Hill, chief scientist for Data Intensive Cyber Environments at the Renaissance Computing Institute, and director of the Data Intensive Cyber Environments Center at University of North Carolina. He coordinates research efforts in development of data grids, digital libraries, and preservation environments. Developed software systems include the Storage Resource Broker data grid and the integrated Rule-Oriented Data System. Supported projects include the National Archives and Records Administration Transcontinental

Inhalt
Acknowledgments.- Introduction.- Integrated Rule-Oriented Data System.- iRODS Architecture.- Rule-Oriented Programming.- The iRODS Rule System.- iRODS Microservices.- Authors' Biographies.