Business process management employs process models and event logs to represent the behavior of the information systems under study. Traditional case-centric notions consider the order of activities and events in isolated process instances. The emerging field of object-centric processes challenges this assumption by putting objects in the center. Object-centric process mining and modeling approaches identify the structure of co-evolving data objects that influence the behavior of an information system to provide a comprehensive view of the system behavior. Object-centricity has been investigated independently in process modeling and in process mining, which resulted in the coexistence of seemingly contradictory assumptions and definitions. As a community effort, this research manifesto relates and aligns existing terminologies, definitions, and perspectives to provide a common ground for current and future research in object-centric business process management. Based on the current state of research, we propose a conceptualization that sets process models and event logs in relation to the information system’s behavior and the execution data it generates. The conceptualization aims at aligning different terminologies and, thus, providing a basis to model and analyze behavioral characteristics. Building on this common ground, we identify open research challenges along the most relevant research areas in object-centric process management. For each research area, its current status is investigated and an outline of the most relevant research challenges is presented.

Computational narratives embed data and the computations that process and visualize that data into a story. They introduce some challenges, such as they need to be structured to be easily adapted to a wide range of audiences and contexts, e.g., different technologies providing visual elements for communication. Model-Driven Engineering (MDE) is a paradigm that proposes the specification of models of a specific domain and transformations between them with many purposes. This work aims to analyze computational narratives from the perspective of MDE to address their challenges. We propose a narrative metamodel based on an existing conceptual model, and we explore the definition of model transformations for converting narrative models into HTML and Jupyter documents. We also exemplify the MDE approach using a real-life narrative referring to COVID-19 and provide some ideas for future research lines

Web applications are permanently being exposed to attacks that exploit their vulnerabilities. To detect and prevent misuse of the functionality provided by an application, it has become necessary to develop techniques that help discern between a valid user of the system and a malicious agent. In recent years, a technology that has been widely deployed to provide automated and non-invasive support for detecting web application attacks is Web Application Firewalls. In this work, we put forward and discuss the application of Process Mining techniques to detect deviations from the expected behavior of web applications. The objects of behavior analysis are logs generated by a widely deployed WAF called ModSecurity. We discuss experiments we have carried out applying our mining method on the well-known e-commerce platform Magento and using the ProM tool for the execution of the process mining techniques.

Business processes are usually enacted within a complex technological environment. Business processes data (e.g., cases, activity instances, variables, resources, etc.) is usually implicit in information systems and coupled with organizational data (e.g., clients, orders, payments, etc.). Even if processes are managed by a Business Process Management System, the link between both kinds of data is not easy to discover. In this context, a compartmentalized vision of process data on the one hand, and organizational data on the other, is not adequate to provide the organization with the evidence-based business intelligence necessary to improve their daily operation. In this paper, we deal with the integration of business process and organizational data as a basis for providing organizations with elements to allow a complete evaluation of the business process execution. We provide an analysis of scenarios for data integration and data matching problems, and we propose a model-driven approach for providing a unified view capturing all the pieces of data consistently for applying both process mining and data mining techniques.

Business processes are carried out to achieve business objectives within an organization. Sometimes, such processes accept variants depending on specific business requirements. Several proposals have emerged to deal with the variability of business processes with focus on the modeling of process families with variants, avoiding modeling each variant separately, which implies duplication and maintenance of the common parts. One of these proposals is the Common Variability Language (CVL), which allows to represent variability transparently in a host language. Deriving a process variant from the definition of a process family is a central and complex task, which is done manually in most of the approaches. The aim of this article is to explore the use of CVL together with the Business Process Model and Notation (BPMN 2.0) for modeling business process families, and the use of Model Driven Engineering (MDE) techniques for the automatic generation of process variants. We also present a graphical tool supporting these ideas and a qualitative evaluation of the variability approach by using the VIVACE framework.

Business Process Management System (BPMS) integrates several software modules to support the business process (BP) lifecycle. A process modeler, process engine, a web portal for interaction with users, and a REST/SOAP API which exposes operations from the engine are key ones. In previous works we have evaluated several BPMS identifying similarities in terms of the concepts they manage in their user portals and the APIs they expose, and how the user portals became highly coupled to the underlying process engine through the provided API. We proposed a generic user portal that makes invocations to a generic API decoupling the portal from the specific process engine it invokes, which can be exchanged through the generic API invocation to different process engines. In this paper we present an extension of this work by adding concepts to the generic API and data model, a comparative analysis between BPMS, as well as the implementation of adapters for three different engines to show its capabilities.

The Object Constraint Language (OCL) plays a central role in many Model-Driven Engineering (MDE) initiatives for expressing invariant conditions in models, among other uses. It is defined as a side-effect free language combining model-oriented and functional features. There are works that explore the use of the functional paradigm for the interpretation of OCL such that most of the functional infrastructure could be predefined and automatically generated. In this work we present the MDE-based automatic generation of such functional infrastructure based on Haskell. We also present how the infrastructure is connected with the Eclipse Modeling Framework for final users, allowing the internal complexity to be transparent to them. We provide a different perspective on the interpretation of OCL, together with a sandbox that allows to evaluate in a unified way several proposals that already exist in the scientific community, as well as to collaborate with the migration of functional aspects to the MDE paradigm.

Selecting a Business Process Management Systems (BPMS) for an organization is not a trivial task. It requires a thorough evaluation of its capabilities considering the whole support of the business process lifecycle and the organizational environment in which the BPMS will be used. In this context, in a previous work we have proposed a methodology for the systematic evaluation of BPMS, which was mostly focused on required functional and non-technical aspects. In this paper, we present the extension of our methodology with a detailed definition of non-functional aspects to be evaluated, and a set of test cases for their evaluation. We also performed a fine tuning of the methodology based on a comprehensive comparison with other existent methodologies and the provision of tool support. As a case study, we present an evaluation of open source and proprietary BPMS following our proposal.

Business processes may accept variants based on specific business requirements of an organization, leading to the definition of a process family. There are many proposals for the modeling of the common and variable parts of a process family, as well as to support the customization of each process variant (i.e., process configuration or tailoring). In this article, we present the results of a detailed study about the modeling and customization of process families based on the Business Process Model and Notation (BPMN 2.0) standard, and we introduce BPMNext, a novel approach devised for this purpose. The language is an adaptation of BPMN 2.0 based on the ideas provided by vSPEM, a language for the modeling of software processes families. We also present a supporting tool and its application to a real case study about the assignment of positions in exchange programs.

In a context of e-government, there are usually regulatory compliance requirements that the supporting systems should enforce. To this end, an appropriate processing of data coming from different sources is required, which presents an important challenge given the large volume of data that e-government systems handle. This volume of data is also increased with data coming from autonomous sensors (e.g. reporting carbon emission in protected areas) and from citizens providing information (e.g. illegal dumping) in a voluntary way. Complex Event Processing (CEP) technologies allow processing large amount of event data and detecting patterns from them. However, they do not provide support for geographic information which is essential for monitoring and controlling regulations which apply to specific geographical areas. This paper proposes a geospatial extension for CEP that allows monitoring environmental factors considering the geographic location of the processed data.