6,389 research outputs found
Advancements and Challenges in Object-Centric Process Mining: A Systematic Literature Review
Recent years have seen the emergence of object-centric process mining
techniques. Born as a response to the limitations of traditional process mining
in analyzing event data from prevalent information systems like CRM and ERP,
these techniques aim to tackle the deficiency, convergence, and divergence
issues seen in traditional event logs. Despite the promise, the adoption in
real-world process mining analyses remains limited. This paper embarks on a
comprehensive literature review of object-centric process mining, providing
insights into the current status of the discipline and its historical
trajectory
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A monitoring approach for runtime service discovery
Effective runtime service discovery requires identification of services based on different service characteristics such as structural, behavioural, quality, and contextual characteristics. However, current service registries guarantee services described in terms of structural and sometimes quality characteristics and, therefore, it is not always possible to assume that services in them will have all the characteristics required for effective service discovery. In this paper, we describe a monitor-based runtime service discovery framework called MoRSeD. The framework supports service discovery in both push and pull modes of query execution. The push mode of query execution is performed in parallel to the execution of a service-based system, in a proactive way. Both types of queries are specified in a query language called SerDiQueL that allows the representation of structural, behavioral, quality, and contextual conditions of services to be identified. The framework uses a monitor component to verify if behavioral and contextual conditions in the queries can be satisfied by services, based on translations of these conditions into properties represented in event calculus, and verification of the satisfiability of these properties against services. The monitor is also used to support identification that services participating in a service-based system are unavailable, and identification of changes in the behavioral and contextual characteristics of the services. A prototype implementation of the framework has been developed. The framework has been evaluated in terms of comparison of its performance when using and when not using the monitor component
OC-PM: Analyzing Object-Centric Event Logs and Process Models
Object-centric process mining is a novel branch of process mining that aims
to analyze event data from mainstream information systems (such as SAP) more
naturally, without being forced to form mutually exclusive groups of events
with the specification of a case notion. The development of object-centric
process mining is related to exploiting object-centric event logs, which
includes exploring and filtering the behavior contained in the logs and
constructing process models which can encode the behavior of different classes
of objects and their interactions (which can be discovered from object-centric
event logs). This paper aims to provide a broad look at the exploration and
processing of object-centric event logs to discover information related to the
lifecycle of the different objects composing the event log. Also, comprehensive
tool support (OC-PM) implementing the proposed techniques is described in the
paper
Preventing Object-centric Discovery of Unsound Process Models for Object Interactions with Loops in Collaborative Systems: Extended Version
Object-centric process discovery (OCPD) constitutes a paradigm shift in
process mining. Instead of assuming a single case notion present in the event
log, OCPD can handle events without a single case notion, but that are instead
related to a collection of objects each having a certain type. The object types
constitute multiple, interacting case notions. The output of OCPD is an
object-centric Petri net, i.e. a Petri net with object-typed places, that
represents the parallel execution of multiple execution flows corresponding to
object types. Similar to classical process discovery, where we aim for
behaviorally sound process models as a result, in OCPD, we aim for soundness of
the resulting object-centric Petri nets. However, the existing OCPD approach
can result in violations of soundness. As we will show, one violation arises
for multiple interacting object types with loops that arise in collaborative
systems. This paper proposes an extended OCPD approach and proves that it does
not suffer from this violation of soundness of the resulting object-centric
Petri nets. We also show how we prevent the OCPD approach from introducing
spurious interactions in the discovered object-centric Petri net. The proposed
framework is prototypically implemented
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