Gregor Polančič

To bridge the gap between the digital and physical worlds, we need systems that can effectively transform reality into computable signals. This perspective paper examines key challenges in such transformation related to the gap between fine-grained sensor signals and activity-level events used in process intelligence tools. We examine these challenges along two perspectives. The first perspective considers two ways on how sensor data is entered into the event log—either sensor readings are abstracted to create new event information, or event information is already present, and sensor data enriches it with new context. The second perspective concerns the maturity of the operating process itself, considering how process maturity may influence the feasibility, reliability and potential usefulness of IoT integration. Integration is therefore not only a technical question of how sensor data becomes process events, but also a prior question of whether and when it is justified. We propose a conceptual perspective on this relationship and identify candidate assessment areas that could form a basis for a future IoT-enabled process mining maturity model; these areas are not empirically validated in this study. We close by considering auditable event logs as a basis for accountability as autonomous systems become more widespread.

The Case Management Model and Notation (CMMN) supports the modeling of dynamic, semi-structured, and knowledge-intensive processes, but its adoption remains limited due to conceptual and visual shortcomings. Using a Design Science Research Method (DSRM), this study introduces a notational variant of CMMN, termed CMMN+, comprising three structural and visual enhancements: explicit representation of activation logic, enriched data entity modeling through semantically grounded metadata and structured role assignments based on the RACI framework. Cognitive effectiveness is analytically evaluated using the nine principles of the Physics of Notations (PoN). The analysis demonstrates clear improvements in semiotic clarity, semantic transparency and perceptual discriminability, confirming enhanced interpretability of the proposed notational variant. As expected, trade-offs arise with respect to graphic economy, while principles such as cognitive fit require subsequent empirical validation. CMMN+ constitutes a conceptually and technically grounded notational advancement in case management modeling by systematically aligning language design with cognitive-effectiveness theory. The presented results establish a strong foundation for integrating more intuitive and semantically rich modeling support into practice.

As IoT environments continue to grow in scale and complexity, the increasing number of interconnected sensors and devices makes end-to-end system behaviour progressively harder to understand. Process mining offers strong potential to address this challenge by transforming sensor-driven event data into interpretable insights at the process level. Yet, current tools are typically designed for business processes, not sensor-driven IoT workflows, which raises questions about their suitability in the IoT context. This discrepancy is evident in existing comparative studies, which often rely on feature checklists, rarely consider usability and interaction effort, or fail to evaluate support for domain-specific analytical tasks. This study introduces a structured evaluation methodology that combines a functional capability assessment derived from vendor materials with a task-based evaluation grounded in 13 representative questions from an IoT-oriented smart factory scenario, focusing on clarity, ease of use, and the ability to address context-specific analytical needs. The results highlight notable strengths and trade-offs among the investigated tools, demonstrating substantial variation in usability, effort, and analytical coverage, and showing that no single tool fully supports the breadth of process-intelligence needs in IoT contexts. The proposed methodology provides a replicable foundation for evaluating process mining tools in domain-specific settings and supports more informed tool selection for IoT-driven analytical workflows.

Dostopne primerjave med orodji za rudarjenje procesov so pogosto zastarele ali ne vključujejo ocene iz uporabniške perspektive, kar otežuje izbiro primernega orodja.Namen prispevka je bil ponuditi primerjalno analizo štirih sodobnih orodij in tako omogočiti vpogled v njihove prednosti in slabosti. Cilj je bil ugotoviti, katera orodja so najbolj primerna za poslovne uporabnike iz vidikov razpoložljivosti, naprednostifunkcionalnosti in enostavnosti uporabe. Analiza se je izvedla z enotnim metodološkim pristopom, ki je vključeval pregled dokumentacije, praktično testiranje z dvema javno dostopnima podatkovnima nizoma ter ocenjevanjem po vnaprej določenih kriterijih. Ugotovljeno je bilo, da orodji Celonis in Apromore ponujata najbolj celovito podporo poslovnim uporabnikom. Obe orodji dosegata najvišjo oceno naprednosti v skoraj vseh sklopih funkcionalnosti, sta enostavni za uporabo in vključujeta umetno inteligenco. Na drugi strani ProM in PM4Py omogočata večjo prilagodljivost in preglednost analitičnih postopkov, vendar zahtevata tehnično znanje in zato nista primerna za široko uporabo brez ustreznega usposabljanja. S poudarkom na praktični uporabniški izkušnji in enostavnosti uporabe prispevek dopolnjuje obstoječe analize, ki se osredotočajo predvsem na seznam funkcionalnosti.

Case Management Model and Notation (CMMN) is a graphical notation used to model less predictable, highly flexible processes that may behave differently in each instance. It uses an event-centred approach and expands on what can be modelled with procedural modelling notations. Nearly a decade since the occurrence of CMMN, its practical use is questionable. We performed this research to identify possible reasons for this and to classify the potential advantages and disadvantages of CMMN. With the aforementioned objectives, we conducted a systematic literature review, which provided a broad insight into the state of the investigated object along with techniques for analysing qualitative data, coding, and successive approximation. From an initial set of 942 articles, 43 remain relevant. The results of the analysis and synthesis of the obtained data from relevant articles were generalised codes, which were used to explicitly answer the research questions. The results indicate that CMMN has good foundations in the declarative modelling approach and within the Case Management paradigm. Nevertheless, some issues were identified with the notation and elements of CMMN and with its complement—Business Process Model and Notation (BPMN).

Case Management Model and Notation (CMMN) is a graphical notation used to model less predictable, highly flexible processes that may behave differently in each instance. It uses an event-centred approach and expands on what can be modelled with procedural modelling notations. Nearly a decade since the occurrence of CMMN, its practical use is questionable. We performed this research to identify possible reasons for this and to classify potential advantages and disadvantages of CMMN. With the aforementioned objectives, our research method was a systematic literature review, which provided a broad insight into the state of the investigated object along with techniques for analysing qualitative data, coding and successive approximation. From an initial set of 942 articles, 43 remain relevant. The results of the analysis and synthesis of the obtained data from relevant articles were generalised codes, which were used to explicitly answer the research questions. Results indicate that CMMN has good foundations in the declarative modelling approach and within the Case Management paradigm. Nevertheless, some issues were identified with notation and elements of CMMN and with its complement - Business Process Model and Notation (BPMN).

Purpose: Due to a lack of event data, organizations using Business Process Management may struggle to update their process models whenever business process changes occur. As such, alternative data sources are needed to detect and monitor business process changes. Design/methodology/approach: We conducted interviews with domain experts to analyze real business processes and classify any identified changes using Reijers and Mansar's framework on business process redesign heuristics. Based on the results, we proposed a taxonomy of entity groups as well as a method for identifying entities in process models based on the taxonomy. With this method, we define how to create a mapping between entities and process models, forming a framework to identify outdated process models through monitoring the entities. Findings: The analyses of 25 business processes let us define three entity groups that form our taxonomy. We confirmed the feasibility of our entity identification method by classifying process elements of 85 pre-existing process models according to the taxonomy. Regarding the mapping that forms the basis of our framework, we found it necessary to define requirement recommendations to ensure its consistency and rigor. Originality/value: This study offers a novel approach to handling the challenges of business process change. By emphasizing the identification and use of entities in the analysis of business process changes, it provides a holistic approach to monitoring the work systems of an organization.

Monografija z naslovom »Sistematična analiza decentraliziranih družbenih medijev« naslavlja prepoznano raziskovalno vrzel preučevanja decentraliziranih družbenih medijev. Pri tem je posebni poudarek na konceptualnem vidiku, ki omogoča prepoznavanje logične zasnove, arhitekturnih značilnosti, potencialov in specifik družbenega medija ter primerjavo s centraliziranimi sorodnimi rešitvami. Predstavlja zbirko medsebojno primerljivih poglavij, ki opisno in analitično preučujejo najvidnejše predstavnike pokrajine decentraliziranih družbenih medijev v letu 2024. Poglavja so rezultat projektne naloge študentov Univerze v Mariboru, Fakultete za elektrotehniko, računalništvo in informatiko, ki so v okviru predmeta »Arhitektura družbenih medijev« sistematično in mentorirano preučevali izbrane decentralizirane družbene medije.

Unlike business process diagrams, where ISO/IEC 19510 (BPMN 2.0) prevails, high-level process landscape diagrams are being designed using a variety of standard- or semi-standard-based notations. Consequently, landscape diagrams differ among organizations, domains, and modeling tools. As (process landscape) diagrams need to be understandable in order to communicate effectively and thus form the basis for valid business decisions, this study aims to empirically validate the cognitive effectiveness of common landscape designs, including those BPMN-L-based, which represent a standardized extension of BPMN 2.0 specifically aimed at landscape modeling. Empirical research with 298 participants was conducted in which cognitive effectiveness was investigated by observing the speed, ease, accuracy, and efficiency of answering questions related to semantically equivalent process landscape diagrams modeled in three different notations: value chains, ArchiMate, and BPMN-L. The results demonstrate that BPMN-L-based diagrams performed better than value chain- and ArchiMate-based diagrams concerning speed, accuracy, and efficiency; however, subjects perceived BPMN-L-based diagrams as being less easy to use when compared to their counterparts. The results indicate that differences in cognitive effectiveness measures may result from the design principles of the underlying notations, specifically the complexity of the visual vocabulary and semiotic clarity, which states that modeling concepts should have unique visualizations.