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Mission and Vision

The world is currently confronting unprecedented challenges, encompassing a global pandemic, ongoing conflicts, and environmental and energy crises. In response to these crises, there has been a significant surge in emergency public spending, accompanied by a relaxation of due diligence checks and oversight. Consequently, this has given rise to patterns of corruption and fraudulent activities, exerting profound and detrimental impacts on the European economy, society, environment, and politics.

As an example, corruption and fraud have the potential to undermine the volume of aid reaching targeted organizations, introducing inefficiencies in resource distribution and creating an uneven business landscape. Such circumstances can extend the duration of recovery efforts and intensify economic crises. Within civil society, the diversion of resources away from their intended purposes due to corruption and fraud can result in a decline in the quality of essential services, such as healthcare, fostering a lack of trust in public institutions and undermining social cohesion. In the environmental realm, corruption may lead to the unjust allocation of natural resources and environmentally dangerous practices. Lastly, corruption poses a direct threat to democracy by endangering institutions and eroding public trust in government and the rule of law, making it increasingly challenging to establish and keep stable political systems.

CEDAR sees these challenges as catalysts for research, innovation, and collaboration. The initiative establishes ambitious objectives aimed at pushing the boundaries of current practices by incorporating novel, multi-dimensional concepts, leveraging rich datasets, developing efficient algorithms, creating scalable tools, and implementing comprehensive, forward-thinking strategies.

Drawing on the expertise gained from prior and ongoing EU-funded projects, CEDAR will create an inclusive, federated, and privacy-preserving Data Commons space, to establish a secure and reliable space for sharing information among stakeholders across multiple domains. CEDAR will ensure that more data becomes available in the economy and society while keeping companies and individuals who generate the data in full control in a trusted, secure, and transparent manner.

Key Objectives

CEDAR will develop methods, tools, guidelines for automated digitalisation of data sources existing in public administrations, in the framework of the fight against corruption and fraudulent activities, and mainly in pursuit of the following four driving objectives:

  • Identify, collect, generate, harmonise, synchronise, protect, and share new large-scale, high-quality, high-value datasets relevant for increasing transparency and accountability of public governance in Europe.
  • Build and improve methods and tools for effective data management and machine learning (ML) operations (DataOps, MLOps) in order to facilitate efficient, scalable, automated, and trustworthy management of open data spaces, with a view to enable a more transparent public governance.
  • Develop new data analytics and machine learning methods for robust, data-efficient, human-centric, and well-informed decision making.
  • Validate and promote CEDAR results with relevant public and private stakeholders and generate direct, tangible, and immediate impact on European economy, society, and environment.

Key Results

  • High-quality, high-value datasets and data models – Validation of new datasets and technologies in the context of fighting corruption, with a view to align with the EU strategic priorities on digitalisation, economy and democracy.
  • Innovative & Scalable DataOps & MLOps technologies – Development and improvement of existing 1) DataOps technologies, including connectors for integrating novel data sources with existing CEDs (Common European Data Spaces), for effective, scalable, trustworthy, and interoperable data management that carry traceable information about the data origins and applied operations, and 2) MLOps technologies for efficient and trustworthy management and deployment of ML models and analytics pipelines.
  • Robust Machine Learning & analytics models & algorithms – Development of robust algorithms to facilitate human-centric and evidence-based decision-making in public administration with the ultimate goal to obtain advanced data analytics and Machine Learning solutions that can combine vast amounts of data:
    (1) from multiple sources (social media, news articles, financial statements, government registries and reports, and other sensors); (2) in different modalities (numbers, text, images, videos), and (3) incorporating different contexts.
  • Applications & user-centric dashboards – Production of Visualisation Dashboard & User-Centric Interfaces (UIs) to facilitate advanced decision making and to offer a high-level view of the most important insights as well as (2) detailed representations of the data points, highlighting connections, patterns, and trends.
  • Know-how, best practices, Standardisation & Policy recommendations – Contribution to relevant Standardisation activities and European policy making, defining result-specific business models and business plans, and developing a sustainability roadmap.
  • Co-creation & Pilot Studies - All project results will be co-created and piloted in a relevant setting with the end users, thereby enabling preparation of results for a real-world uptake across different communities and countries. Co-creation of the above-mentioned data and data technologies will involve 3 different pilots in 3 different countries (Italy, Slovenia and Ukraine), through which we will facilitate a more data-driven public sector and enable a more transparent public governance in Europe.