The project builds on the roadmap developed by the EU project EuroDISH (www.eurodish.eu) and the recommendations of the European Strategy Forum on Research Infrastructures for a food and health research infrastructure (ESFRI). ESFRI facilitates policy-making on research infrastructures in Europe.
The vision of the RICHFIELDS project is to design a Platform to collect, align and share consumer, business and research data in order to provide the scientific research community with innovative datasets and the ability to generate new knowledge about consumers’ food choices and health. The project developed a conceptual framework in the form of a ‘Core Offering Proposal’ and a three-stage process for developing the data platform: ‘Core’, ‘Growth’ and ‘Maturity’:
• Core Offering: starting point for the establishment of a Minimum Viable Product and Minimum Viable Ecosystem
• Growth: extended set of data users, data providers and services
• Maturity: fully operational Data Platform aligning and sharing consumer, business and research data
Figure 1 shows the ‘Core Offering Proposal’: the content of the Consumer Data Platform
Further findings from RICHFIELDS are summarised below.
PHASE 1: HOW TO MAP AND STORE DATA
An inventory management system (RIMS) has been created for storage and assessment of online tools (e.g. mobile phone applications), which produce consumer generated food and beverage purchase, preparation or consumption data. It contains two parts:
• A typology categorising the purpose of the tools.
• Metadata to enable assessment of data quality
Additionally, through a survey in eight EU Member States, we gained insight into the extent of public willingness to share data that are generated by electronic systems with researchers. These insights lead to the following recommendations:
• Identify appropriate means of maintaining trust, minimising risk to individuals and society and enhancing the perceived moral authority of science.
• Seek a more nuanced understanding of the way in which the public perceives the possible solutions and models through the use case studies.
• Be mindful of possible cross-country differences in sensitivities about the issue of data sharing.
PHASE 2: HOW TO LINK DATA
Researchers conducted 10 case studies to investigate the technical components, interfaces and services necessary for data to be linked through the platform:
• Business generated data on purchase and procurement (3 case studies)
• Existing or future resources regarding food composition and intake surveys, clinical interventions, consumer diet, health and lifestyle (4 case studies)
• Laboratories and facilities that undertake consumer research on food choice, purchase, and consumption (3 case studies)
The findings of a case study about how businesses collect data were presented in a stakeholder workshop, resulting in feedback and suggestions on the needs and wants for such a research infrastructure. Recommendations from this workshop:
• A powerful search engine would be needed to find relevant data for specific research questions, offering analysis and interpretation services for the data available on the platform.
• Developing case studies showing the benefits of data sharing for businesses was seen as a useful tool to more easily persuade businesses to share data with the platform.
• The platform should provide information about how the original data was collected by the data provider and feed back to data providers about when and for what purpose their data has been used.
• The added value should be clear in terms of what they can expect in return compared to their competitors.
PHASE 3: DESIGNING THE PLATFORM
The design includes the technical backbone, a business model and the internal and external governance. Data combination and management focuses on the physical infrastructure, software, and potential data access and exchange. Hence concepts such as open and big data, and standards to link data from different sources are addressed. A semantic model to encode data and information to enable sharing of data with end-users or information systems has been developed. RICHFIELDS has also generated an ontology, which encompasses among others a definition of categories in data, to aid re-use and integration of data, information, and knowledge.
Sustainable business models allow the data platform to be self-sustaining, ensuring value for all stakeholders as well as defining the services that would be provided, the supply chain, and the revenue model. RICHFIELDS has explored potential business models for future implementation, depending on the value proposition, supply chain configuration and revenue system.
The needs of users and data providers as well Intellectual Property Rights (IPR) and ethical constraints are core elements of the governance framework, which must consider privacy, ownership, (inter-)national regulations, standardisation, and quality management.
