Research and Innovation (R&I) policymakers need access to the right evidence to design and implement high-impact interventions that deliver innovation, growth and wellbeing. Big data and data analytics offer many opportunities to transform R&I policy with a new generation of indicators, that are more relevant, inclusive, timely, trusted and open (RITO) than those already available. Such data can enable better decisions with bigger (and better measured) impacts. However, concerns about the representativity, accuracy and inclusiveness of new data sources and methods could hinder their acceptance. EURITO aims to build trust around these indicators so they can be adopted effectively.
The EURITO project engages policymakers and researchers as stakeholder groups throughout the project, and promotes a user-driven, agile, rigorous and transparent process that goes from identifying policy needs to developing relevant indicators for R&I policy. The overall aim of the project is to develop new mapping methods (data, software and knowledge) of the innovation ecosystem, that will lead to better R&I policy, new opportunities for open innovation, an enhanced understanding of innovation systems and new networks between policymakers, researchers and data businesses.
This is achieved through five connected phases:
Scoping identifies R&I policymaker needs and data gaps
Exploration takes eight key questions identified from the scoping phase and develops short pilots using big data and new data analytics to address these questions
Data collection and analysis scales up four data pilots with the biggest policy potential enabling the production of Relevant, Inclusive, Timely, Trusted and Open (RITO) indicators for R&I policy
Validation, systemically validates all of the indicators generated in the data collection and analysis stage with the goal of building trust around their use
Communication and dissemination seek to enhance the impact and transparency of outputs by disseminating them in a way that is actionable and reproducible, including through open datasets, open source repositories, and interactive data visualisations and dashboards