5,915 research outputs found
Automatic vs Manual Provenance Abstractions: Mind the Gap
In recent years the need to simplify or to hide sensitive information in
provenance has given way to research on provenance abstraction. In the context
of scientific workflows, existing research provides techniques to semi
automatically create abstractions of a given workflow description, which is in
turn used as filters over the workflow's provenance traces. An alternative
approach that is commonly adopted by scientists is to build workflows with
abstractions embedded into the workflow's design, such as using sub-workflows.
This paper reports on the comparison of manual versus semi-automated approaches
in a context where result abstractions are used to filter report-worthy results
of computational scientific analyses. Specifically; we take a real-world
workflow containing user-created design abstractions and compare these with
abstractions created by ZOOM UserViews and Workflow Summaries systems. Our
comparison shows that semi-automatic and manual approaches largely overlap from
a process perspective, meanwhile, there is a dramatic mismatch in terms of data
artefacts retained in an abstracted account of derivation. We discuss reasons
and suggest future research directions.Comment: Preprint accepted to the 2016 workshop on the Theory and Applications
of Provenance, TAPP 201
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
Ensuring the semantic correctness of a BAUML artifact-centric BPM
Context: Using models to represent business processes provides several advantages, such as facilitating the communication between the stakeholders or being able to check the correctness of the processes before their implementation. In contrast to traditional process modeling approaches, the artifact-centric approach treats data as a key element of the process, also considering the tasks or activities that are performed in it. Objective: This paper presents a way to verify and validate the semantic correctness of an artifact-centric business process model defined using a combination of UML and OCL models - a BAUML model. Method: We achieve our goal by presenting several algorithms that encode the initial models into first-order logic, which then allows to use an existing satisfiability checking tool to determine their correctness. Results: An approach to verify and validate an artifact-centric BPM specified in BAUML, which uses a combination of UML and OCL models. To do this, we provide a method to translate all BAUML components into a set of logic formulas. The result of this translation ensures that the only changes allowed are those specified in the model, and that those changes are taking place according the order established by the model. Having obtained this logic representation, these models can be validated by any existing reasoning method able to deal with negation of derived predicates. Moreover, we show how to automatically generate the relevant tests to validate the models. We also show the feasibility of our approach by implementing a prototype tool and applying it to a running example. Conclusion: It is feasible to ensure the semantic correctness of an artifact-centric business process model in practice.Peer ReviewedPostprint (author's final draft
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