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. 2023 May 19;10(1):303.
doi: 10.1038/s41597-023-02213-z.

FOPPA: an open database of French public procurement award notices from 2010-2020

Lucas Potin  1   2 , Vincent Labatut  3   4 , Pierre-Henri Morand  2   5 , Christine Largeron  6
Affiliations

FOPPA: an open database of French public procurement award notices from 2010-2020

Lucas Potin et al. Sci Data. .

Abstract

Public Procurement refers to governments' purchasing activities of goods, services, and construction of public works. In the European Union (EU), it is an essential sector, corresponding to 15% of the GDP. EU public procurement generates large amounts of data, because award notices related to contracts exceeding a predefined threshold must be published on the TED (EU's official journal). Under the framework of the DeCoMaP project, which aims at leveraging such data in order to predict fraud in public procurement, we constitute the FOPPA (French Open Public Procurement Award notices) database. It contains the description of 1,380,965 lots obtained from the TED, covering the 2010-2020 period for France. We detect a number of substantial issues in these data, and propose a set of automated and semi-automated methods to solve them and produce a usable database. It can be leveraged to study public procurement in an academic setting, but also to facilitate the monitoring of public policies, and to improve the quality of the data offered to buyers and suppliers.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Overview of the method proposed to correct and complete the raw TED data and constitute the FOPPA database.
Fig. 2
Fig. 2
Successive filtering phases applied to match TED agents with SIRENE entries, as a part of the Agent Identification step from Fig. 1.
Fig. 3
Fig. 3
Structure of the FOPPA database, shown as an Entity-Relation diagram.
Fig. 4
Fig. 4
Distribution of the four possible outcomes of the identification process for the known (a) and manually retrieved (b) SIRETs.
Fig. 5
Fig. 5
Distribution of the concentration ratio (a) and singleton ratio (b) over unique agents.
See this image and copyright information in PMC

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