“Collaboration Process Mining for Distributed Systems”

Call for Papers – Special Issue: “Collaboration Process Mining for Distributed Systems”

Journal: Information Systems
Publisher: Elsevier
Impact Factor: 3.4 | CiteScore: 9.8
Submission deadline: 13 July 2026

This special issue addresses the growing need for process‑mining techniques that can analyse collaboration processes across distributed systems, where multiple actors—such as manufacturers, retailers, hospitals, doctors, patients, robots, or IoT devices—interact in complex, cross‑organizational workflows. Standard process‑mining methods focus on processes inside a single organisation or system; this SI seeks to extend those methods to inter‑organizational and multi‑agent settings, where data is fragmented, heterogeneous, privacy‑sensitive, and case‑correlation‑rich.

Why this issue matters

• In domains like supply‑chain management, healthcare, smart systems, and multi‑robot/IoT environments, collaboration is distributed across many participants sharing responsibilities yet operating with separate information systems, data formats, and access constraints.

• Existing process‑mining approaches often fail to capture cross‑organizational bottlenecks, coordination gaps, and hidden inefficiencies that arise when data cannot be centrally pooled due to confidentiality, privacy, or technical barriers.

• Object‑centric process mining and collaboration‑mining paradigms offer a promising direction by modelling interactions among multiple objects and participants, enabling richer analysis of inter‑organizational processes and distributed systems.

Key themes and research topics

The SI welcomes techniques, methods, and applications that advance collaboration‑mining capabilities for distributed, cross‑organizational settings. Topics include:

• Cross‑organisational process simulations

  • Simulation‑based analysis of end‑to‑end collaboration processes spanning multiple organisations or systems.

• Distributed event‑log preprocessing and correlation

  • Methods for preprocessing, cleaning, and correlating event logs spread across different domains and formats.

• Discovery of collaboration process models

  • Algorithms to discover process models of collaborative workflows involving multiple participants and systems.

• Conformance and multi‑perspective analysis

  • Conformance‑checking techniques and multi‑perspective analyses (e.g., organisational, resource, data views) for collaboration processes.

• Privacy‑preserving and federated process mining

  • Approaches to federated process mining, privacy‑preserving mining, and secure data sharing that respect confidentiality while enabling joint analysis.

• Streaming collaboration mining and object‑centric mining

  • Real‑time stream‑based collaboration mining and object‑centric process‑mining techniques for distributed systems.

• Case notions and monitoring/repair

  • Novel case‑notions suitable for collaboration‑mining and mechanisms for monitoring and repairing distributed collaboration processes.

• Application‑domain studies

  • Use cases in healthcare, supply‑chain management, multi‑agent systems, IoT, and multi‑robot collaboration that demonstrate the value of collaboration‑mining methods.

Guest editors

• Dr. Lorenzo Rossi (Executive Guest Editor), University of Camerino, Italy

• Prof. Andrea Delgado, University of the Republic, Uruguay

• Dr. Sara Pettinari, Gran Sasso Science Institute, Italy

• Dr. Mahsa Pourbafrani, RWTH Aachen University, Germany

• Prof. Mathias Weske, Hasso‑Plattner‑Institut, Germany

Submission details

• Submission platform: Information Systems via Editorial Manager:
  https://www.editorialmanager.com/infosys

• When submitting, select article type “VSI: CoMinDS”.

• Submission window:

  • Submissions open: 8 December 2025

  • Submission deadline: 13 July 2026

  • Editorial acceptance deadline: 14 December 2026

• All manuscripts must follow the Guide for Authors and will undergo standard peer review.

This special issue is ideal for information‑systems, data‑mining, and business‑process‑management scholars who wish to develop and apply advanced collaboration‑mining methods for distributed, cross‑organisational workflows.

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