PhD Topic: Risks and Opportunities of European Data Spaces  (DC4) 
Research objectives: The general objective is to study data sharing across 'public bodies', 'private companies' and 'citizens' in the Common European Data Spaces. The specific objectives are (i) to quantitatively estimate existing data flows between stakeholders in the Common European Data Spaces (ii) to design methodologies and frameworks for implementing data exchanges in abidance with the Data Governance Act (DGA) and Data Act (DA).
Expected Results: (i) methods and tools to enable DGA and DA compliant data flows between governments, companies and citizens, including an observatory doing periodic captures; (ii) developing legal and technological trustworthy solutions for enabling data altruism within Common European Data Spaces (iii) implementing developed methods for Solid Pods to enable data exchanges with the Common European Data Spaces.
The candidate is expected to make a research stay at Dublin City University.

PhD Topic: Open Models for AI/Data Risk Assessment (DC5) 

Research objectives: The candidate will (i) investigate open models to discover, represent and mitigate ethical and legal risks raised by the EU’s AI Regulation and Digital Services Act; (ii) capture the information flows required for AI certification and market surveillance between AI providers, AI users, AI importers and regulators and stakeholder’s whose health, safetyor fundamental rights may be impacted; (iii) develop an open semantic model to exchange information on risks assessments, risk treatments and risk impacts information in support of multi-stakeholder learning in specificverticals (iv) develop and assess a tool to capture, exchange and analyse risks for a specific high-risk verticals to support multi-stakeholder agreement on e.g. probabilistic risk thresholds and reasonably foreseeable forms of risk/misuse.
Expected Results: (i) a machine-readable ontology for risk and impact information exchange; (ii) design of methods and tools to extend the ontology in support of multi-stakeholder regulatory sandboxes for high-risk AI areas
The candidate is expected to make a research stay at Trinity College Dublin.

PhD Topic: Self-Aware Data Assets for Supporting Sovereignty (DC11) 
Research objectives: To devise innovative metadata elements and their processing procedures that dynamically capture the entire history of interactions involving the data asset, including details such as recipients and timestamps. Envisioned as a living organism, 'self-aware data assets' are pieces of data bundled with intelligence, that acquire awareness of its impact and the decisions influenced by its existence. The DC will craft a proof-of-concept (TRL2), enabling the interrogation of the data asset, especially concerning legal compliance and ethical responsibility inquiries. This intelligent data asset will possess the capability to discern its authorized movements within the Data Space, thereby assisting its custodians in navigating advanced compliance scenarios. Expected Results: (i) a machine-readable ontology for risk and impact information exchange; (ii) design of methods and tools to extend the ontology in support of multi-stakeholder regulatory sandboxes for high-risk AI areas; (iii) an implementation of the 'self-aware data asset'.
The candidate is expected to make a research stay at University of Bologna.