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.

In recent years, the use of information systems has become increasingly important in organizations, generating vast amounts of heterogeneous data from various sources. Data Science encompasses data mining and process mining disciplines, among others, that allow the management, analysis, and discovery of valuable information from this data. However, these disciplines are often applied independently, over different datasets obtained from heterogeneous data sources which are not necessarily integrated, and thus can lead to partial views when analyzing the results. To address this issue, this research proposes a unified approach to data mining and process mining over process and organizational integrated data, which enables a comprehensive view of the daily operation of organizations for evidence-based decision making. In this paper we present a proposal for carrying out such integrated analysis, and a proof of concept prototype developed to support it. We also present an example of application with process and organizational data from a real university process.

Abstract Business processes can have variants depending on specific business requirements, which lead to the definition of a so-called business process family. Since conventional business process modeling languages, e.g., the Business Process Model and Notation (BPMN), do not explicitly support variants’ specification, several proposals have emerged to deal with it. However, they mainly focus on languages’ definition, while less emphasis is made on providing complete variability management. This article presents a Model-Driven Engineering approach for managing BPMN-based business process families composed of a metamodel for conceptualizing process families, a high-level process for managing them (involving model transformations for the configuration of variants), and tool support for the complete approach. We validated the proposal using a real-world example from a university and an empirical study with real users. Users rated the support tool’s principal functional suitability and usability features as very good. Many improvement opportunities were detected, e.g., version control, collaborative work, and error reporting. We also provide a literature review and thorough evaluation of BPMN-based business process families’ proposals using the VIVACE framework.

Enterprise architecture has become an important driver to facilitate digital transformation in companies, since it allows to manage IT and business in a holistic and integrated manner by establishing connections among technology concerns and strategical/motivational ones. Enterprise architecture modelling is critical to accurately represent business and their IT assets in combination. This modelling is important when companies start to manage their enterprise architecture, but also when it is remodelled so that the enterprise architecture is realigned in a changing world. Enterprise architecture is commonly modelled by few experts in a manual way, which is error-prone and time-consuming and makes continuous realignment difficult. In contrast, other enterprise architecture modelling proposal automatically analyses some artefacts like source code, databases, services, etc. Previous automated modelling proposals focus on the analysis of individual artefacts with isolated transformations toward ArchiMate or other enterprise architecture notations and/or frameworks. We propose the usage of Knowledge Discovery Metamodel (KDM) to represent all the intermediate information retrieved from information systems' artefacts, which is then transformed into ArchiMate models. Thus, the core contribution of this paper is the model transformation between KDM and ArchiMate metamodels. The main implication of this proposal is that ArchiMate models are automatically generated from a common knowledge repository. Thereby, the relationships between different-nature artefacts can be exploited to get more complete and accurate enterprise architecture representations.

Since the beginning of 2020, COVID-19 has had a strong impact on the health of the world population. Tracing the contacts of infected people is one of the main strategies for controlling the pandemic. Given the high rates of contagion, which makes difficult an effective manual tracing, multiple initiatives arose for developing digital proximity tracing technologies. In this paper, we discuss in depth the security and personal data protection requirements that these technologies must satisfy, and we present an exhaustive and detailed list of the various applications that have been deployed globally. In particular, we identify potential threats that could undermine the satisfaction of the analyzed requirements, violating hegemonic personal data protection regulations.

The daily operation of organizations leaves a trail of the execution of business processes (BPs) including activities, events and decisions taken by participants. Compliance requirements add specific control elements to process execution, e.g. domain and/or country regulations to be fulfilled, enforcing order of interaction messages or activities, or security checks on roles and permissions. As the amount of available data in organizations grows everyday, using execution data to detect compliance violations and its causes, can help organizations to take corrective actions for improving their processes and comply to applying rules. Compliance requirements violations can be detected at runtime to prevent further execution, or in a post mortem way using Process Mining to evaluate process execution data against the specified compliance requirements for the process. In this paper we present a BP compliance Requirements Model (BPCRM) defining generic compliance controls that can be used to specify specific compliance requirements over BPs, that are used as input to assess compliance violations with process mining. This model can be seen as a catalogue that includes a set of predefined compliance rules or patterns in one place, helping organizations to specify and evaluate the compliance of their processes.

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.

Implementing Business Processes (BPs) with services (and microservices) is nowadays the main way to support the execution of automated activities in processes, both within the organization itself, and externally interacting with customers, suppliers and other participants. In order to do so, it is important not only to model and implement services but also to define Quality of Service (QoS) characteristics for services, to monitor and evaluate their execution. Although there are many proposals for services monitoring and evaluation from the services point of view, there are not many from the BPs perspective. In this paper we present a reference architecture for service monitoring tools, along with a prototype implementation as an extension of the web services execution environment AXIS2. We show that existing service measures and new ones can be defined into the monitor to collect execution data and relate this data with BPs execution, to measure BPs and service execution in an integrated manner.

Modeling variability in software systems or processes promotes reuse of core assets.In particular, variability in software development processes allows customization of activities, artifacts, roles and other elements to specific projects, in what is called a process variant.Each process variant is derived from a base common process, called process tailoring, which is usually a tedious and error prone manual process.In the last years, there has been a growing interest in supporting the process variability approach, being v-SPEM a proposal that integrates and advanced view of variability into the SPEM standard.In this paper we present an extension of v-SPEM support for final users, with automated generation of variants, to help during process tailoring.The use of automatic mechanisms reduces errors and simplifies the tailoring process by hiding the details to the end users.

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.

The process of building Data Warehouses (DW) is well known with well defined stages but at the same time, mostly carried out manually by IT people in conjunction with business people. Web Warehouses (WW) are DW whose data sources are taken from the web. We define a flexible WW, which can be configured accordingly to different domains, through the selection of the web sources and the definition of data processing characteristics. A Business Process Management (BPM) System allows modeling and executing Business Processes (BPs) providing support for the automation of processes. To support the process of building flexible WW we propose a two BPs level: a configuration process to support the selection of web sources and the definition of schemas and mappings, and a feeding process which takes the defined configuration and loads the data into the WW. In this paper we present a proof of concept of both processes, with focus on the configuration process and the defined data.

A Web Warehouse (WW) is a Data Warehouse which consolidates data from the Web. The goal of these systems is to act as an intermediary between data publication and the user, pre-processing data and adding value to them. This pre-processing involves data integration, data aggregation, data re-structuring and data quality measurement and improvement. A Business Process (BP) model helps us to specify the users, activities, precedence relations between activities and restrictions, that have to be carried out in order to obtain the desired output. In this paper we present a two level BP specification approach for constructing a WW which has two distinctive characteristics: it manages data quality and it is configurable. The first level BP model is focused on helping the user to configure the web data sources and the desired data quality characteristics, the second level BP uses the defined configuration to generate the WW. Quality characteristics are also defined for the intermediate data sources used to populate the WW.

Business Process Management (BPM) promotes in organizations a horizontal vision based on the processes they perform to reach their objectives, and on the systems that support them. These systems are "aware" of the business processes they integrate, which guide the system execution (Process Aware Information Systems, PAIS). Automating pieces of these processes by means of services orchestration (mainly web services) allows to integrate to process execution the invocation of legacy systems, systems from other organizations (clients, providers, partners, etc.) and newly developed systems. In this article we present a proposal for the automatic generation of this kind of systems to support business processes with services. The proposal is based on models and transformations between them, from the specification of the business process model in BPMN2, through the services model in SoaML, to the code generated for invoking services from process execution. In particular, the paper provides details on the generation of code in Java EE and Web Services.