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#graph neural networks Dataset Open access

Redes de proveedores del Estado peruano: vínculos entidad-proveedor, concentración, dependencia y validación de sanciones, 2022–2024

Sep 2026 · Figshare

Abstract

This dataset contains network-based public procurement data from Peru for the period 2022–2024, prepared for the analysis of concentration, dependency, and atypical structures in state supplier networks.The database includes entity–supplier relationships, supplier-level and entity-level network measures, and consortium-based links between suppliers. It contains information on awarded amounts, number of procurement items, recurrence of supplier–entity relationships, supplier concentration, entity dependency, degree, weighted degree, PageRank, betweenness centrality, community membership, community size, HHI indicators, direct contracting, single-bid participation, consortium participation, and other procurement-related characteristics.The dataset is organized into multiple analytical components, including annual entity–supplier edge lists, supplier-year node attributes, entity-year node attributes, and supplier–supplier links derived from consortium participation.An external validation variable related to subsequent supplier sanctions is also included. This variable is intended for ex post validation and should not be used as a predictor when training unsupervised graph-based anomaly-detection models.The database was constructed from official public procurement information from Peru’s Organismo Especializado para las Contrataciones Públicas Eficientes (OECE/SEACE) and related official sanction records. It is intended to support reproducible research using network analysis, graph representation learning, graph autoencoders, GraphSAGE, and explainable graph neural network methods.

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