Optimising cohort data in Europe

In the second step, we analyse the outcomes of the stakeholder dialogues in order to identify the patterns of capabilities and resources needed for the sustainability of data infrastructures in methodological, ethical and legal terms. In so doing, we use the RBV and the KBV perspectives for the formulation of a hypothetical and ideal model for the coordination and integration of cohort data. We match this model with the findings from ongoing and past projects and initiatives in order to identify existing building blocks to the sustainability of data infrastructures in cohort studies in methodological, ethical and legal terms. Finally, we derive a strategic agenda, i.e. the set of strategic tasks thought necessary to complement missing “building blocks”, structures and functions, embedded in an overall model for a better coordination of cohorts in a real world. In doing so, we provide strategic steps and tools for ensuring the sustainability of data infrastructures and interoperability within the methodological, ethical and legal domains in cohort research. 2. Pillar I: Standards - Standards for variables, minimal set of variables Since Pillar I concerns standards for variables, it requires mainly tangible resources that can be observed and measured. This is because standards need to be concretely implemented with clear rules, directives and application domains in order to have any relevance. In practical terms, a standard can be characterised as such only to the extent to which it is implemented and used by researchers and communities of practice. Resources for standards need to be both specialised (i.e. so that they could be applied to local and national contexts) and versatile (i.e. so that they could be extended to wider international contexts). In this context, the aim of Pillar I is to convert specialised tangible resources into tangible ones. We will show in this section how such conversion operates. The components required for pillar I include: 1) harmonisation levels, 2) common set of variables, 3) metadata standards, 4) design of common datasets, 5) metadata collection, 6) documentation/level of metadata, and 7) incentive for metadata sharing. For illustrative purposes, we are going to focus on metadata standards and harmonisation levels in this section. For metadata, the first step is to identify tangible resources that can foster the establishment of standards for variables and common metadata in particular. There are already existing, established tangible resources for metadata standards. Existing and recommended standards and modules such as the Data Documentation Initiative (DDI) and the European Union Statistics on Income and Living Conditions (EU-SILC) for surveys are available. Catalogues for the collection of recommended standards are already generated at the WHO level (e.g., Guidelines for Accurate and Transparent Health Estimates Reporting; GATHER).