Periodic Reporting for period 2 - Data4Impact (Big DATA approaches FOR improved monitoring of research and innovation performance and assessment of the societal IMPACT in the Health, Demographic Change and Wellbeing Societal Challenge)
Okres sprawozdawczy: 2018-08-01 do 2019-10-31
Building upon state-of-the-art in innovation research, the Data4Impact consortium established an integrated conceptual framework. In line with the framework, a series of indicators were developed on the performance and societal impact of 40+ research programmes in the health domain. The comprehensive set of data and indicators combine publication, patent, company/innovation, clinical guidelines, project monitoring, as well as various social media/media and other types of online data. Through a series of dissemination activities and validation workshops involving EU (FP7 and H2020), three national settings (Sweden, UK, Germany) and key stakeholders, the proposed methods and indicators were successfully validated.
However, the overarching finding and lesson learned in Data4Impact is that stakeholders’ needs are very diverse. Balancing these stakeholder needs is a challenge to big data, but also an opportunity because big data can serve as a means to answer a broad multitude of policy questions due to its bottom-up nature. This potential hinges on technological solutions – one needs platforms, tools and services which serve policymakers’ needs. This is a key activity for Data4Impact and the envisaged follow-up/exploitation activities after the end of the project. Data4Impact partners have been developing an online monitoring platform (which is hosted at monitor.data4impact.eu) that allows stakeholders to view these indicators for different entities, as well as make comparisons between projects/programmes and across time.
A) A monitoring of research and innovation performance which captures the broader spectrum of ways in which research and innovation activities translate into outputs and impact
Data4Impact derived meaningful data and indicators for policymakers, programme funders and other stakeholders based on a wealth of information brought together from a variety of sources and state-of-the-art methods. As a result, we are not only able to understand better the ways in which impact is generated but also improve our model and align it with the diverse needs and requirements of policymakers and stakeholders. The integrated AMOSIA conceptual framework that builds on the state-of-the-art in innovation research and is linked to the impact dimension (WP2) served as the basis for the Data4Impact’s work. Following this framework, the Data4Impact consortium defined relevant input sources, identified data analysis workflows and integrated them into a common platform (WP3) to enable visualisation and interrogation of project/funder quality indicators. The Data4Impact Monitoring Platform, which is a key output of WP6, facilitates the monitoring of R&I performance by showcasing the multidimensionality of the outputs and impact of R&I activities. Data4Impact’s work in other Work Packages was also highly relevant for the development of improved monitoring of research and innovation performance, for instance the development of novel indicators based on the unstructured data from company websites was directly related to the creation of novel approaches in WP5 to monitor the impact of research which extended beyond the traditional indicators used in the field.
B) A reliable assessment of the societal benefits generated by public funding for research and innovation, and the impact it has on tackling major societal challenges
Data4Impact employed big data sources and approaches to derive data on the societal impact of research. The impact of Data4Impact’s research was further reinforced by combining output/result and impact with input and throughput data in a systematic way, resulting in a comprehensive set of evidence for national and EU-level policymakers and funders. The extended conceptual framework established in WP2 provided an overview of different stages and unique data points throughout the innovation process as well as showed how they are interconnected at the higher level. WP3 provided platform and tools to acquire the input and throughput data supporting the analysis workflows and integrating the metrics and indicators data in the Data4Impact platform database. Data4Impact’s work in other Work Packages was also highly relevant for the development of a reliable assessment of the societal benefits generated by public funding for R&I. For instance, our topic modelling activities carried out WP4 linked all stages of input-to-impact through an additional dimension.