Advisory Group on Data
Background
The Advisory Group on Data (AGoD) is a discussion group of the EFSA Advisory Forum set up in 2021 to answer various challenges in the food safety data system.
The group is composed of representatives of the Advisory Forum (on a voluntary basis), technical experts delegated by Advisory Forum members, EFSA staff and a representative of the European Commission. As of 2024 the participating countries are: Austria, Croatia, Denmark, Finland, France, Germany, Hungary, Italy, Ireland, Netherlands, Norway, Portugal, Sweden, and Switzerland.
It meets around seven times per year, of which 4 meetings take place back-to-back with the Advisory Forum meetings.
Objectives and tasks
The mission of the group is to identify and launch tangible projects solving the most pressing pain points of the Member States and bringing benefits to the European food systems data and risk assessment community.
The group is the guardian of the EFSA Advisory Forum Task Force on Data Collection and Data Modelling’s data-related recommendations, maintaining coherence among different actions, overseeing harmonisation efforts and ensuring added value for multiple Member States. The Task Force’s recommendations covered four key areas: Data Reporting, Data Modelling, IT Architecture and Data Analysis, plus recommendations cutting across the four areas.
The Group is a governance body informing the strategic prioritisation and funding of data related projects emanating from the Task Force recommendations. It acts as a think tank providing input on project idea generation linked to Advisory Forum recommendations and as a channel providing access to knowledge, expertise, competencies and staff in Member States.
The group has six subgroups to foster discussions on a more detailed and technical level:
- Developing and Sharing Tools and Tech - focuses on detailed and operational questions related to data collection and connection, data architecture and process automation, on the following topics: mechanisms and tools for data accessibility and data connection; ‘code-to-data’ solutions for the enrichment of data points; data process automation and sharing; collaborative projects on data architecture and tools.
- Digital Platforms and Ecosystems - focuses on communication, collaboration, sharing and knowledge-management questions on the following topics: contribution and discovery of knowledge in a digital ecosystem; data discoverability, (re-)usability by applying open data, metadata standards, and ecosystem of APIs; use of terminologies and ontologies to amplify digital ecosystem interactions; quality assurance and independence in a digital ecosystem; use of open food safety data; communication and collaboration possibilities in food and the food safety data domain (including communication and knowledge-management solutions for AGoD).
- Innovative Data Analytics and New Data Streams - focuses on: enhancing services using new data streams, big data and computational analysis; developing and/or implementing new algorithms (predominantly based on AI methods); using AI-based solutions in a risk analysis framework; trust, legal, ethical and transparency questions of AI-based and other advanced computational solutions; explore the use of traceability data and other new data streams (structured and unstructured); new approaches in food consumption and composition data collection.
- Data Literacy and Data Capacity – focuses on: initiatives aimed at achieving the required level of data literacy through data-related education activities, including the European food risk assessment fellowship programme, capacity-building initiatives, EU datathons and other regular and ad hoc training opportunities; discussions on encouraging future training and recruitment efforts in food safety institutions to focus on increasing data analytical capacities; supporting datathons and crowdsourcing activities to encourage use of food safety data and virtuous spiral feedback; organising an annual food safety data science conference; sharing good practices on techniques and coding languages, upskilling and training efforts.
- Data Quality - focuses on data collection (harmonisation of standards, evaluation of quality criteria, proposal of key performance indicator dashboards, etc.) and the usage of any data, possibly not-perfect data, including: enhancing data capital governance and data management processes; data quality planning and monitoring; automating methods for data quality assurance processes; developing guidelines and checklists for the use of imperfect data (i.e. data which was collected for other purposes than the present one).
- Data Modelling and Terminology - focuses on ontologies, data models, data catalogues and interoperability questions including initiating discussions on a common single ‘European food safety data model’ along the food chain, considering international participants (e.g. the World Health Organization, the Food and Agriculture Organization, the World Organisation for Animal Health and non-EU national regulatory authorities).