Optimising cohort data in Europe

Component

Resource and resource type

Capability

Aggregation capability (integration): − Generating fixed data items for data structure and comparison Rules and directives (knowledge integration mechanisms): (i) Evaluating how others researchers use metadata. (ii) Generating common codes for data structure. (iii) Making an informed selection of these codes for a minimal dataset. Group problem solving and decision-making (knowledge integration mechanisms): − Increasing the acceptance of standards though training and preparation of staff with different backgrounds. Combinative capabilities: − Listing all the methods for standard metadata descriptions used currently in different catalogues. 1) For costs and funds: - Aggregation and transferability capabilities (integration): − Research infrastructure giving references for provided data descriptions to researchers. − Appropriability capabilities (integration): research infrastructures support and credit researchers in uploading their data description. 2) Research community consensus: − Rules and directives (knowledge integration mechanisms). − Consensus is implemented through standard information and communication systems from the researcher community and enforced through by transnational and international agencies.

Common datasets: specialised tangible resources. Emergence context of resource

Design of common and minimum datasets

(i.e. common datasets): occur only once there is

sufficient metadata about the common data elements other researchers use.

Metadata collection

Structural information: tangible, versatile resources.

Descriptive metadata and contextual metadata: tangible and versatile resources, contextual metadata presents barriers to entry and includes resource immobility.

Documentation/ level of metadata

1) Costs and funds: tangible resources, present resource immobility issues. 2) Research community consensus: intangible resources.

Incentives for metadata sharing