Accepted Papers

Main conference

Enterprise Intelligence, Complexity, and Decision Support

• M. Schnellmann, H. A. Proper, From Gut Feeling to Data-Driven Decisions: Exploring Digital Twin supported Decision-Making for Real Estate Management
• J. L. R. Moreira, E. Stoica, J. P. S. Piest, F. Bukhsh, W. Levelt, A Measurement Method for Quantifying Application Landscape Complexity with Enterprise Architecture
• F. J. Cavero, A. García-Fernández, J. A. Parejo, M. Resinas, A. Ruiz-Cortés, Pricing Intelligence: Rethinking IS Engineering in Volatile SaaS Environments

Forecasting, Drift, and Prescriptive Process Analytics

• B. R. A. Zuniga, A. Yeshchenko, H. van der Aa, Version Clustering: A Top-Down Approach for Process Concept Drift Detection
• Y. Yu, J. Peeperkorn, J. De Smedt, J. De Weerdt, Time Series Foundation Models for Process Model Forecasting
• N.-D. Le, A. Buliga, M. Ronzani, A. Padella, M. de Leoni, Balancing KPIs through Multi-Objective Prescriptive Process Analytics

Conceptual Modeling, Ontologies, and Value

• I. Valle, T. P. Sales, E. Guerra, L. O. B. da Silva Santos, H. Proper, G. Guizzardi, Modeling Value Canvas: A tool to rationalize the value of domain modeling
• W. Morlidge, E. Watkiss-Leek, G. Hannah, H. Rostron, A. Ng, E. Johnson, A. Mitchell, T. R. Payne, V. Tamma, J. de Berardinis, The AnIML Ontology: Enabling Semantic Interoperability for Large-Scale Experimental Data in Interconnected Scientific Labs
• Y. Wuwang, N. Kannengießer, T. Dehling, B. Sturm, A. Sunyaev, Decentralization drivers for purposeful decentralization of distributed ledger technology systems

Enriching Process Mining with Context and Sustainability

• A. Moradbeikie, I. M. Grigore, S. I. Lopes, S. Barbon Junior, Sensor2EventLog: Bridging Continuous IoT Data and Process Mining through Eventization
• A. Swevels, F. Zerbato, D. Fahland, Process Mining in Context: Extending Domain Data Models for Iterative Analysis
• N. Wolf, H. Wittges, S. Rinderle-Ma, SuXXES: Integrating Sustainability Data into Process Event Logs

Human-in-the-Loop Engineering and Development Practices

• C. Sancricca, C. Cesana, E. Gallo, A. Gottardi, C. Cappiello, How Poor Data Quality Weakens the Performance of Question–Answering Systems
• S. Surana, A. Srinivasan, M. Bain, Engineering Systems for Data Analysis Using Interactive Structured Inductive Programming
• D. Ly, F. B. Aydemir, F. Dalpiaz, From Concept to Action: How Do Agile Software Teams Decompose User Stories into Tasks?

Process Discovery and Analysis

• P. Schalk, A. Polyvyanyy, Mind the Gap: On Formal Relationships Between Log Complexity and the Complexity of Discovered Models
• T.-H. Huang, L. Jansen, M. Pegoraro, G. Park, W. van der Aalst, Flexible and Hierarchical Decomposition of Workflow Nets for Process Analysis
• A. Karunaratne, A. Polyvyanyy, A. Moffat, Conditioning and Stability in Process Discovery

Engineering AI Systems across Cloud, Edge, and Cyber-Physical Environments

• A. Puglisi, F. Monti, F. Leotta, C. Napoli, M. Mecella, SlimAI4Edge: A cloud-edge framework for downsizing AI models as-a-service
• D. Zyberaj, L. Mazur, P. Hirmer, N. Petrovic, M. Aiello, Req2Road: A GenAI Pipeline for SDV Test Artifact Generation and On-Vehicle Execution
• A. Hassan, M. S. Saeed, B. Senouci, B. Benatallah, Domain-Specific Fine-Tuning of Large Language Models for HW/SW Interface Generation: An Empirical Study
• H. Stein, S. Janzen, C. K. Agnes, D. T. Ninh, W. Maass, Towards Decision Support Systems for Cost-effective and Energy-efficient AI Operations in Data Centers

LLM-Driven Modeling and Human–AI Collaboration

• I. Reinhartz-Berger, A. Tsoury, Iterative vs. Plan-Driven Approaches in LLM-Assisted Modeling: An Empirical Study
• J. Zdravkovic, J. Stirna, C. H. Tsai, K. Sandkuhl, An AI Enterprise Modeling Project Assistant – Needs and Possibilities
• S. J. Ali, Z. Zheng, D. Bork, Shortcut or Understanding? Diagnosing LLM Type Prediction in Conceptual Models
• Y. J. Chung, K. Bae, E. Yu, Modeling and Analyzing Identity-Sensitive Requirements in Human-AI Collaboration

Agent-Based and Multi-Stakeholder Process Interaction

• A. Ghasemi, L. Kulms, T. Lichtenstein, M. Weske, Agent-Based Simulation of Flexible Process Interactions
• Q. Shen, A. Polyvyanyy, N. Lipovetzky, T. Kampik, Mining Agent Roles from Event Data for Effective Process Simulation
• V. Pant, E. Yu, Computational Foundations for Strategic Coopetition: Bridging Conceptual Modeling and Game Theory in Multi-Stakeholder Information Systems

LLMs and AI for Process Understanding

• T. Sulzer, H. Voelzer, B. Weber, Evaluation of an Architecture for an LLM-based Analytics System for Exploratory Process Mining
• J. Neuberger, H. van der Aa, H. Lopez, I. Khrop, Enabling Small Language Models for Text-to-Process Extraction: Balancing Accuracy and Efficiency through Distant Supervision
• W. Zhang, K. Andree, A. Kalenkova, L. Pufahl, L. Mitchell, Explaining ML-Based Decision Models Through Process Mining Techniques

Predictive and Neuro-Symbolic Process Analytics

• H. Mustroph, M. Kunkler, S. Rinderle-Ma, Predicting Conformance Deviations and Their Positions in Future Event Sequences
• J. Wang, K. Chen, C. Hou, T. Li, L. Lin, B. Cao, J. Fan, A Heterogeneous Hypergraph-Transformer Hybrid Architecture for Business Process Next-Activity Prediction
• F. De Santis, G. Park, W. M. P. van der Aalst, F. Zanichelli, Compliance-Aware Predictive Process Monitoring: A Neuro-Symbolic Approach
• D. Gaikwad, G. Park, W. van der Aalst, Neuro-Symbolic Process Anomaly Detection

Responsible, Fair, and Human-Centered AI

• L. Djennane, Z. Kardkovacs, B. Benatallah, Y. Gaci, Z. Farah, Proxy Analysis in Bias Testing
• O. Diaz, X. Garmendia, R. Medeiros, STAR: A Socio-Technical Readiness Model for Assessing Task Readiness for AI Augmentation
• M. Fumagalli, S. M. Nicoletti, D. Calvanese, G. Guizzardi, News-Informed Probabilistic Models for AI Risk Analysis
• M. Peixoto, F. Baião, R. Guizzardi, G. Guizzardi, Explaining and Mitigating Biased Decisions: An Ontological Approach

Object-Centric Process Mining and Conformance

• L. Liss, W. van der Aalst, Object-Centric Conformance Checking on Object-Centric Causal Nets
• H. Hooshyar, M. Fumagalli, M. Montali, G. Guizzardi, Time and Relations into Focus: Ontological Foundations of Object-Centric Event Data
• M. Basmer, R.-D. Falcusan, M. Montali, M. Weidlich, Porifera: A Relational Approach to Conformance Checking for Object-Centric Behavioral Constraints

Process Mining Data Quality and Repair

• S. Kalukapuge, A. Janusz, M. T. Wynn, DupliMend: Online Detection and Refinement of Imprecise Activity Labels
• M. Comuzzi, S. Ra, D. Narmatova, S. Cho, Y. Hong, S. Jung, Towards Agentic AI for Event Log Quality Assessment
• S. Dissegna, C. Di Francescomarino, M. Ronzani, Graph-based Event Log Repair

Forum and demo track

Vision papers

• S. Hacks, Train While You Fight – Technical Requirements for Advanced Distributed Learning Platforms
• J. Akoka, I. Comyn-Wattiau, C. Du Mouza, Automated Extraction of Conceptual Representations from Research Articles Using Large Language Models
• V. G. dos Santos, B. Benatallah, S. T. MacMahon, Constraint-Aware Pipeline for Generating High-Quality Utterances from OpenAPI Specifications using LLMs
• R. Grati, N. Fattouch, K. Boukadi, F. De Luzi, M. Mecella, A. Saffeh, A case study of eXplainable AI in smart agriculture. Lessons learned for information systems engineers
• K. Saxena, B. Sarmah, S. Pasquali, ProvenanceTrace: Atomic Claim Verification Across Financial and Open-Domain AI Systems
• D. Xhani, J. L. R. Moreira, M. van Sinderen, L. F. Pires, G. Guizzardi, M. Machado, Towards a FAIR Data Management Framework for Ontology-Driven Explainable Machine Learning
• C. Capitán-Agudo, C. Di Ciccio, C. Cabanillas, M. Resinas, Towards Explaining Process Variants With Examples
• A. Bagozi, D. Bianchini, M. Garda, M. Melchiori, A. Rula, OntoLLM: A Framework for Trustworthy LLM Pipelines
• J. C. Orth, A. Palma, M. Angelini, Towards Human-AI Collaborative Cybersecurity Compliance Assessment
• M. Wang, K. Winter, Q.-V. Dang, R. Dijkman, Detecting and Explaining Temporal Behavioral Deviations in Business Process Simulation Models
• F. Zampino, L. Genga, A. Longo, M. S. Zappatore, R. Dijkman, A Method for Process Model Matching with LLMs
• H. H. Beyel, M. Prokop, J. Kretinsky, G. De Giacomo, W. M. P. van der Aalst, Capturing Processes in Probabilistic Timed Automata
• A. Gianola, Z. Hameed, M. Montali, A. Seidel, M. Weske, S. Winkler, Detecting Dynamic Relationships in Object-Centric Event Logs
• F. Scafoglieri, M. Papandrea, T. Leidi, Towards Ontology-Guided Data Augmentation: The Case of Entity Resolution
• A. Rozenberga, M. Kirikova, J. Stirna, Designing a Configurable Requirements Engineering Tool for Teaching
• A. Casciani, A. Giovannetti, S. Macagnano, A. Marrella, M. L. Bernardi, M. Cimitile, F. M. Maggi, Predictive Process Monitoring via Automated Planning

Tool papers

• S. Ahrari, A. Bernasconi, F. Invernici, A. Colombo, MLegis: Demonstrating a Property Graph-Based Information System for Legislative Analytics
• V. Diemieniev, J. Saathoff, M. Schlegelmilch, P. Zaniewski, T.-H. Huang, G. Park, Performance Spectrum Patterns Miner
• C. G. Moyano, F. Six, J. Mendling, PMDAgile: A Process-Model-Driven Tool for Agile Software Development
• A. Bagozi, D. Bianchini, V. De Antonellis, M. Garda, M. Melchiori, A. Rula, D3SD: A Web-based Tool for Data Service Design in Cyber-Physical Production Networks
• L. Bein, L. Pufahl, KARIBDIS – A Knowledge-graph-based Business Process Management System for Semantically Explainable Process Execution Support
• A. Casciani, F. Italia, L. Lestingi, M. Marinacci, A. Marrella, A. Matta, FIDES: A Neuro-Symbolic Conversational Tool for Faithful Production Process Intelligence
• M. Kryston, E. Marangone, A. Marcelletti, C. Di Ciccio, CONFETTY: A Tool for Enforcement and Data Confidentiality on Blockchain-Based Processes

Doctoral consortium

Process Mining: Supporting Analysis and Use in Practice

• Z. Ahmadi, Interactive Context-Aware Navigation of Process Models
• A. Claude, Scaffolding Hypothesis Testing in Process Mining through AI-Mediated Analytical Role Simulation
• A. Sekulovska, The impact of process mining archetypes on business process performance

Requirements Engineering

• F. Hollauf, Engineering Temporal Requirements
• J. Kollmorgen, Beyond the User–Product Relationship: Extending the Scope of UX Evaluation
• A. Slupczynski, A Modernization Decision Framework for Legacy Information Systems

Data Foundation for Information System Engineering

• H. Hooshyar, Object-Centric Event Data: Conceptualization, Extraction and Querying
• V. Chan, Integrating Geospatial Data into Business Process Management

Tutorials

• M. Vitali, S. Werner, Evaluating the Sustainability of Information Systems
• A. Casciani, L. Lestingi, A. Marrella, A. Matta, Developing Neuro-Symbolic Conversational Systems for Reliable Multi-Perspective Production Process Intelligence
• I. Donadello, F. M. Maggi, J. Oukharijane, Declarative Process Mining for Adaptive Information Systems: the Declare4Py Python library

Journal first track

• J. Peeperkorn, J. De Smedt, J. De Weerdt, Model-driven stochastic trace clustering
• A. Karunaratne, A. Polyvyanyy, A. Moffat, The Effects of Log Noise in Process Mining
• S. Brinkkemper, S. Molenaar, F. Dalpiaz, Concept Definition Review: A Method for Studying Terminology in Software Engineering
• A. Bagozi, D. Bianchini, M. Garda, M. Melchiori, A. Rula, A multi-layered data service model for Cyber-Physical Production Networks
• A. Bagozi, D. Bianchini, M. Garda, M. Melchiori, A. Rula, Ontology-enhanced RAG for a personalised and sustainable food advisory system
• F. Corradini, A. Marcelletti, A. Morichetta, B. Re, L. Verducci, A Mapping Methodology Enabling Object-Centric Process Mining on Blockchain Applications
• F. Corradini, A. Galassi, A. Marcelletti, B. Re, CoBlock: a Domain-Specific Language for Compliance Checking on Smart Contract Execution Data
• R. Eshuis, A. Ghose, Synthesizing goal models from declarative data-centric process models
• A. Andreou, M. Bernabei, A. Christoforou, S. Colabianchi, F. Costantino, F. Leotta, J. G. Mathew, M. Mecella, F. Monti, Assessing smart manufacturing by combining IT systems and enabling technologies in a fuzzy cognitive maturity model
• F. Bianchini, A. M. Braccini, F. De Luzi, M. Macrì, M. Mecella, Exploring AI Chatbot Adoption for Knowledge Workers: A Unified Theory of Acceptance and Use of Technology Extension
• M. Barrientos, K. Winter, S. Rinderle-Ma, Impact analysis of regulatory requirement changes on business process compliance
• Q. Shen, A. Polyvyanyy, N. Lipovetzky, T. Kampik, Applying organizational mining to discover agent systems from event data
• A. Buliga, C. Di Francescomarino, C. Ghidini, I. Donadello, F. M. Maggi, Guiding the generation of counterfactual explanations through temporal background knowledge for predictive process monitoring
• B. Pernici, C. Cappiello, C. A. Bono, C. Sancricca, T. Catarci, M. Angelini, M. Filosa, M. Palmonari, F. De Paoli, S. Bergamaschi, G. Simonini, A. Mozzillo, L. Zecchini, Sustainable quality in data preparation

Research Project Exhibition Track

list available soon