Shortest Paths and Centrality in Uncertain Networks A summary of the PVLDB 2021 research paper by Arkaprava Saha, Ruben Brokkelkamp, Yllka Velaj, Arijit Khan, and Francesco Bonchi [Background: Uncertain Graph and Shortest Path] Uncertain networks, i.e., graphs where each edge is associated with a probability of existence, have received a great deal of attention thanks to their expressivity and applicability in many real world contexts. Uncertainty in a network might arise due to noisy measurements [2], edge imputation using inference and prediction models [1, 3], and explicit manipulation of edges, e.g., for privacy purposes [4]. Researchers have studied 𝑘-nearest neighbor queries [5, 6], reachability queries [7], clustering [8], sampling [9], network design [10], and embedding [11], just to mention a few. Shortest-path queries [12, 13, 14], on the other hand, are one of the fundamental graph primitives with a plethora of applications, e.g., traffic routing, finding functional pa