Workshop theme:
Building on the success of the previous workshops at SWC2021 and SWC2023, the 3rd International PROMISE Workshop will delve deeper into the complexities of process mining within smart environments using cutting-edge technologies. The BT Ireland Innovation Centre (BTIIC), a collaboration between Ulster University and BT, will continue to lead and unify efforts for this workshop. This event will integrate theoretical principles with industrial practices to tackle challenging issues in machine learning, artificial intelligence, and data mining in complex business environments.

For sophisticated commercial information systems, a critical aspect is the development of intelligent environments using advanced technologies such as sensors, the Internet of Things (IoT), and cloud computing. The IoT facilitates real-time monitoring, enhances efficiency, and provides precise analysis across various sectors, including manufacturing, smart cities, logistics, and banking. The integration of IoT and process mining is poised to redefine future paradigms by allowing massive data collection and exchange.

In addition to these foundational technologies, the latest research in business process mining introduces innovative directions such as Federated Process Mining, Object-Oriented Process Mining, and the exploration of exogenous processes in business:

• Federated Process Mining involves decentralized data processing across different organizations or departments, preserving data privacy while enabling comprehensive process insights. This approach facilitates collaboration without compromising sensitive data, offering a new paradigm for cross-organizational process optimization.
• Object-Oriented Process Mining focuses on analyzing processes that involve complex interactions among various objects or entities, providing a more granular view of process dynamics. This method allows for the integration of object behavior and interactions, enhancing the understanding of intricate business processes.
• Exogenous Processes in Business examine how external factors influence business processes, integrating external data sources to provide a more holistic analysis of process performance and outcomes. This perspective enables organizations to better adapt to external changes and optimize processes in response to evolving market conditions.

Business process data from large corporations are inherently complex and pervasive. These processes are typically executed using organized information systems governed by business rules; however, due to their complexity and volume, flawless execution is not always achieved. Process logs from customer journeys and information management systems illustrate how internal and external factors can impact process outcomes. Smart process analytics is vital for aligning information systems with business goals, and process mining enables users to comprehend ongoing processes, identify flaws, and make timely predictions.

Several complexities in real-world Information Systems have been identified as significant challenges for researchers in Process Mining, such as:

• The heterogeneity of business environments necessitating large, intricate logs with diverse events, tasks, sequences, and durations.
• Capturing real-time process data.
• Facilitating automated and real-time compliance.
• Standardizing organizational processes to prevent deviations from standard execution.
• Identifying and evaluating IoT investment projects.

Topics of Interest:
The thematic areas in which contributions are sought, include, but are not limited to, the following:

• Monitoring and detection of complex behavior
• Applications of Process Mining in smart sensor environments
• Knowledge Discovery and Process Mapping in Smart Systems
• Multidimensional Process Mining for Healthcare
• Process Mining in Cybersecurity
• Stochastic Models and Process Mining
• Privacy-Preserving Process Mining
• Data Quality and Traceability in Process Analytics for IoT
• Process mining in software development
• Methods and Techniques for Privacy and Trust Management in Process Mining
• AI techniques for business process enhancement
• Process mining techniques for addressing AI challenges
• Process mining artifacts as knowledge representations for AI problem-solving
• Process mining and multi-agent systems
• Process mining and automated planning
• Genetic algorithms for process mining
• Information retrieval methods for process mining through Smart Applications
• Solutions for Process Mining & Big Data
• Fundamental Aspects of Online Process Mining
• Decision analytics in diverse and real-time business processes
• Process model conformance checking and quality management
• Federated Process Mining and privacy-preserving techniques
• Object-Oriented Process Mining approaches
• Exogenous processes and external data integration

Important Dates:

• Paper submission due: 15^th March 2025
• Notification of acceptance: 10^th April 2025
• Camera-ready papers due: 20 April 2025
• Conference date: 27^th – 30^th May 2023

Accepted and presented papers will be published in the IEEE Xplore Digital Library and indexed by Scopus. Selected papers may be invited for extended versions in indexed journals.

Submission Instructions:
A regular paper with the maximum length of 6 pages. All manuscripts should be formatted in the IEEE Computer Society Proceedings Format, and submitted in the Portable Document Format (.pdf). A submission can have at most 2 additional pages with a charge for these additional pages, if accepted.

Submissions:
The ICIT 2025 and associated workshops’ paper submission and review processes will be entirely electronic and will be conducted online using EasyChair: https://easychair.org/cfp/ICIT25

Programme Chairs:

Name	Title	Affiliation
Dr Zeeshan Tariq	Lecturer in Computer Science	Ulster University, UK
Prof Sally McClean	Professor of Mathematics	Ulster University, UK
Dr Abul Bashar	Assistant Professor in Computer Engineering	Prince Mohammad bin Fahd University, KSA

Programme Committee:

Name	e-mail address	Affiliation
Dr Bilal Ahmed	b.lodhi@ulster.ac.uk	Ulster University, UK
Dr Kevin Burke	kevin.burke@ul.ie	University of Limerick, Ireland
Dr Maqsood Mahmud	m.mahmud@ulster.ac.uk	Ulster University, UK
Dr Lalit Garg	lalit.garg@um.edu.mt	University of Malta, Malta
Dr Jun Liu	j.liu@ulster.ac.uk	Ulster University, UK
Dr Ian McChesney	ir.mcchesney@ulster.ac.uk	Ulster University, UK
Prof Adele Marshall	a.h.marshall@qub.ac.uk	Queen's University Belfast, UK
Dr Nazeeruddin Muhammad	nmohammad@pmu.edu.sa	Prince Mohammad bin Fahd University, KSA
Prof Chris Nugent	cd.nugent@ulster.ac.uk	Ulster University, UK
Dr Arshad Raza	s.raza@ulster.ac.uk	Ulster University, UK
Prof Bryan Scotney	bw.scotney@ulster.ac.uk	Ulster University, UK
Dr Atiq W Siddiqui	a_siddiqui@yu.edu.sa	Al Yamamah University Dammam, Saudi Arabia
Dr Ihsan Ullah	ihsan.ullah@nuigalway.ie	University of Galway, Ireland
Dr Suleman Yerima	syerima@dmu.ac.uk	Ulster University, UK
Prof Jane Zheng	h.zheng@ulster.ac.uk	Ulster University, UK

Registration:
https://icit.zuj.edu.jo/Home/Registrations.htm

Workshop Contacts
Dr Zeeshan Tariq: z.tariq@ulster.ac.uk
Prof Sally McClean: si.mcclean@ulster.ac.uk

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Next Workshop: Dr. Andrew Reeves