What is an Ecosystem?

Our STRONG-AYA ecosystems exist to generate a stronger culture of successful and sustainable working between researchers, clinicians, patients, policy experts and other stakeholders and to integrate traditional clinical, epidemiological and data science processes with patient-centred data. The definition of our ecosystems is made up on people, technology and processes. In addition to our federated technical infrastructure, our ecosystems consist of:

1. An inter-professional, interdisciplinary and service user community, working together and sharing knowledge, ideas, processes and information that meet the overall purposes of STRONG-AYA

2. A set of local databases (storing pseudonymised individual-level patient data in a local private repository, or ‘safe space’ within the data governance structure of each partner

3. Applications through which local data managers will all be able to: prepare, and make data FAIR inside their local ecosystem (that they ‘own’ ethically and legally), and examine their own data to monitor completeness and evaluate data quality

4. Tools (such as ‘Apps’) that can optimise the knowledge gained by us and others from our work that can run predefined analyses automatically (‘in real time’, ‘on demand’, ‘on the fly’) upon these data to answer various research or policy questions

5. Sophisticated web-based software application, which serves multiple stakeholders (e.g. clinicians, patients, policy makers) with various levels of access and permissions according to our centrally defined ecosystem with local autonomy in mind

This digital ecosystem will allow STRONG AYA members to view information and data to monitor, evaluate and compare outcomes, at a level befitting their user profile, to enable data-driven cancer research.

  • Our ecosystems operate on the following principles:
  • Better use and re-use of our data, information and expertise – including ways to clean, integrate, package, analyse – improves our ability to learn from and apply the information that is shared among our stakeholders.
  • Data should be Findable, Accessible, Interoperable & Re-usable (‘FAIR’)
  • Cooperation, connection, inter-dependence and creativity bring together data science, clinical care, clinical research, epidemiology and service users