1. Working Group 4 Data and metadata lifecycle management  1. Policies and infrastructure for data and metadata changes  2. Supporting file and data formats  3. Policies for change control for data and metadata  4. Provenance and approval of data and metadata versioning

2. Priorities for Small Science data repositories  Preserve the Data (Urgent) Descriptions of data, experimental designs, use cases, policies about inclusion and exclusion of data points… Can be thought of as a conversation between humans that supports the need to re-create the experiment and independent analysis. Unambiguous linkage between data sets and publications  Accessibility of Data When you have it preserved, support access appropriately (search support, etc.)  Formulation of public policies pertaining to curation of data  ? Formalization of a vocabulary to describe relations among datasets, change policies….  ? Automation Support for automated data exchange and use Schemas to capture machine-processable data

3. Data and Applications where does the complexity belong?  Simple data Complex Applications  Complex data Simple applications  Data Schemas Applications Where the intelligence is invested will have an impact on managing the lifecycle of data sets Applications require curation as well as the data. Schemas do as well

4. How can data standards be motivated and managed?  Data standards stakeholders Researchers Publishers Data Curators Funding agencies  What are the motivations for adopting and enforcing standards? Publication attribution – data sets must be recognized publicly as creditable publications (Carrot) Requirement of publishing (paper not accepted unless data is recorded in a suitable repository (Stick) Publishers may find that their journals are more widely used to the extent that the data is openly accessible Publishers may actively oppose open publication of data Funding agencies may require open publication of data as a condition of funding

5. Curation issues  Classes of metadata? Author-generated Machine-generated Third-party (repository curators) User annotations (Web 2.0 style?)?  What sort of metadata is important for a data set independent of the publications that reference it?

6. ‘Ownership’ of data and metadata  Who can edit datasets? Assertion: datasets should never change, but rather should be versioned with changes clearly journaled Is there a need for conventions concerning post- publication status changes? (fraud/errors/augmentation…)  Who can edit metadata? Assertion: metadata is a curatable object independent of that which is described: the creator or curator is responsible for change policy (not the data set creator)

7. Additional Questions  What are the natural institutional homes for repositories?  Is there support in the data repository world for retrieval of known-item data sets (this is the canonical identifier problem)  Life-cycle of data sets imply that death may be an event in the cycle. How are policies concerning life and death of publications, datasets, and the relationships between them assured?