Title: Temporal outlier analysis of online civil trial cases based on graph and process mining techniques

Authors: Beniamino Di Martino; Luigi Colucci Cante; Antonio Esposito; Pietro Lupi; Massimo Orlando

Addresses: Department of Engineering, University of Campania 'Luigi Vanvitelli', Via Roma 29, Aversa, Italy; Department of Computer Science and Information Engineering, Asia University, 500 Lioufeng Rd, Wufeng – Taichung, Taiwan; CINI – Consorzio Interuniversitario Nazionale per l'Informatica, Via Ariosto, 25, Roma, Italy ' Department of Engineering, University of Campania 'Luigi Vanvitelli', Via Roma 29, Aversa, Italy; CINI – Consorzio Interuniversitario Nazionale per l'Informatica, Via Ariosto, 25, Roma, Italy ' Department of Engineering, University of Campania 'Luigi Vanvitelli', Via Roma 29, Aversa, Italy; CINI – Consorzio Interuniversitario Nazionale per l'Informatica, Via Ariosto, 25, Roma, Italy ' Directorate General for Automated Information Systems, Department of Judicial Organization, Personnel and Services, Ministry of Justice, Viale Crescenzio, n. 17/c, Roma, Italy ' Court of Livorno, Via Falcone e Borsellino 1/3, Livorno, Italy

Abstract: Since the complete digitisation of civil processes that took place in Italy in 2008, a lot of data regarding the life cycle of thousands of civil proceedings has been collected. However, despite the continuous monitoring that Italian courts are subjected to, and regulatory changes to the procedures that have been enacted in recent years, the average duration of proceedings is still far from acceptable. In order to identify elements which could point to the causes of such 'slowness', data provided by the Court of Livorno have been analysed through process mining and graph techniques, in order to assess the coherence and correct application of the process model. A methodology to identify and analyse the 'outlier' processes has been developed, as described in this work, to also detect characteristics which could justify delays in the processes' completion. In this work, process mining and statistical techniques have been applied to the analysis of the proceedings' data and outliers, with their characteristics, have been recognised.

Keywords: process mining; data model enrichment; outlier analysis; graph-based techniques.

DOI: 10.1504/IJBDI.2021.118746

International Journal of Big Data Intelligence, 2021 Vol.8 No.1, pp.31 - 46

Received: 16 Sep 2020
Accepted: 22 Sep 2020

Published online: 25 Oct 2021 *

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