Working paper on Public data availability, interoperability and reusability

Analysis of the European and State Members legal framework of procurement data quality, reusability and interoperability.

Working paper on privacy and intellectual property constraints

Analysis of the privacy and intellectual property constraints on procurement data reusability and interoperability.

Compendium of good practices of use of data to improve integrity in public procurement

The compendium gathers information of different European public bodies about uses of data to improve integrity in public procurement

Selected data and selected individual indicators

Single variables (i.e., red flags) are selected on the basis of their relevance, analytical soundness, timeliness and accessibility. There will also be a detection of missing data to assess the impact of the imputation on the composite indicator results, to spot the presence of outliers in the dataset and thus to make it possible the development of a robust composite indicator.

Normalized, weighted and aggregated data

Definition and application of the more adequate scale/s of normalization, weights and aggregation method through a specific context analysis needed to be carefully appraised when developing a composite indicator of corruption risk in public procurement.

Definition of the relational structure (i.e., the structure of relationships) among single indices and assessment of the dimensionality of the data

The relational structure among single indices might be related to a more complex and multidimensional configuration rather than a simple and uni-dimensional one, where high correlations (and, possibly, causal dependencies) can be observed not only between sub-groups (or sub-dimension) of red flags but also from a complex and multidimensional perspective.

Validation of the CI on the basis of the Sensitivity analysis

The sensitivity analysis is a proper tool to assess the CI validity, as it studies how the variation in the output (e.g. CIs value and rankings) can be apportioned to different sources of variation in the assumptions, and to the way the given composite indicator depends upon the information fed into it. It also quantifies the overall uncertainty as a result of the uncertainties in the model input, and it helps to gauge the robustness of the composite indicator and identify which units (e.g. contracting authorities, provinces, regions, States) get favoured or weakened (i.e., getting higher/lower than expected corruption risk scores) under certain assumptions adopted during the corruption risk assessment procedure.


Info.nodes and the Università di Perugia will coordinate the development of the database.

The database is the IT structure that will allow a) the partners to in-depth analyse the data referring to corruption cases in public procurement; b) the users to navigate or download the collected data in an open format for the re-use.

Data Viz Dashboard

The dashboard offers a graphic and interactive representation of the indicators developed in the previous phases

Lessons learned

Model of transferability of the CORE methodology for the definition of CI


It is about the potential use of the Funds addressed to cover the project strategy related to the Next Generation EU