1. Working Group: Practical Policy Rainer Stotzka, Reagan Moore

2. 2  Extend the concept of “Data in Context” to “Collection in Context”  A collection provides the context for understanding data  Provenance metadata  Descriptive metadata  Structural metadata  Workflows  Administrative metadata  However, each collection has a driving purpose that represents the consensus of a user community  We observe the the members of the user community evolve, implying re-purposing of the collection.  The evolution redefines the required metadata for the collection context Concept Extensions

3. 3  Local project  Members have detailed tacit knowledge of the semantics, structure, description  Data grid  Data are shared with other institutions, requiring description and access controls  Digital Library  Data are published for the entire discipline, requiring provenance, description, structural information  Reference Collection  Data are published for use by future researchers, requiring knowledge of generation and management of the collection  Reproducible data-driven research  The workflows, input parameters and files, and output results from each execution of a workflow need to be saved  The policies and procedures used to manage an archive also need to be saved  Preservation is “communication with the future”  Preservation requires “validation of communication from the past” Example Collection Evolution

4. 4  Identify the most important policies  Practical implementations for managing research data collections  Provide recommendations for a “starter kit”  Testbeds:  Evaluate standard policies  Test interoperability across WGs Policy: Assertion or assurance that is enforced about a collection or a dataset Practical Policy Working Group Focuses:

5. 5 Policy-Based Data Environments  Purpose  Reason a collection is assembled  Properties  Attributes needed to ensure the purpose  Policies  Controls for enforcing desired properties,  mapped to computer actionable rules  Procedures  Functions that implement the policies  Mapped to computer executable workflows  Persistent state information  Results of applying the procedures  mapped to system metadata  Property verification  Validation that state information conforms to the desired purpose  mapped to periodically executed policies

6. Collection Purpose Completeness Correctness Consensus Defines Consistency Attribute HasFeature Has Defines Policy Has Property Defines Procedure Control s Updates Client Action Periodic Assessment Criteria Policy Policy Enforcement Point Workflow Invokes Has SubType Isa Function Chains Operation Isa Persistent State Information Persistent State Information Isa Digital Object Updates Has Replication Policy Checksum Policy Quota Policy Data Type Policy Isa Integrity Isa Authenticity Isa Access control Isa GetUserACL SetDataType SetQuota DataObjRepl SysChksumDataObj Isa DATA_ID DATA_REPL_NUM DATA_CHECKSUM Isa HasFeature Concept Graph for Policy-based Management

7. Policy Categories Collection- based Policies Integrity Data Lifecycle Management Data Staging Federation Description Publication Compliance Data Management Plans Access Control Preservation Provenance Replication Regulatory Management Administrative Assessment