Modeling of IoT devices in Business Processes: A Systematic Mapping Study

[EN] The Internet of Things (IoT) enables to connect the physical world to digital business processes (BP). By using the IoT, a BP can, e.g.: 1) take into account real-world data to take more informed business decisions, and 2) automate and/or improve BP tasks. To achieve these benefits, the integration of IoT and BPs needs to be successful. The first step to this end is to support the modeling of IoT-enhanced BPs. Although numerous researchers have studied this subject, it is unclear what is the current state of the art in terms of current modeling solutions and gaps. In this work, we carry out a Systematic Mapping Study (SMS) to find out how current solutions are modelling IoT into business processes. After studying 600 papers, we identified and analyzed in depth a total of 36 different solutions. In addition, we report on some important issues that should be addressed in the near future, such as, for instance the lack of standardization.This research has been funded by Internal Funds KU Leuven (Interne Fondsen KU Leuven) and the financial support of the Spanish State Research Agency under the project TIN2017-84094-R and co-financed with ERDF.Torres Bosch, MV.; Serral, E.; Valderas, P.; Pelechano Ferragud, V.; Grefen, P. (2020). Modeling of IoT devices in Business Processes: A Systematic Mapping Study. IEEE. 221-230. https://doi.org/10.1109/CBI49978.2020.00031S22123

Lifecycle Management for Business Process Variants

This chapter deals with advanced concepts for the configuration and management of business process variants. Typically, for a particular business process, different variants exist. Each of them constitutes an adjustment of a master process (e.g., a reference process) to specific requirements building the process context. Contemporary Business Process Management tools do not adequately support the modeling and management of such process variants. Either the variants have to be specified in separate process models or they are expressed in terms of conditional branches within the same process model. Both methods can result in high model redundancies, which make model adaptations a time-consuming and error-prone task. In this chapter, we discuss advanced concepts of our Provop approach, which provides a flexible and powerful solution for managing business process variants along their lifecycle. Such variant support will foster more systematic process configuration as well as process maintenance

Software modelling languages: A wish list

© 2015 IEEE. Contemporary software engineering modelling tends to rely on general-purpose languages, such as the Unified Modeling Language. However, such languages are practice-based and seldom underpinned with a solid theory-be it mathematical, ontological or concomitant with language use. The future of software modelling deserves research to evaluate whether a language base that is compatible with these various elements as well as being philosophically coherent offers practical advantages to software developers

Can process mining automatically describe care pathways of patients with long-term conditions in UK primary care? A study protocol

Introduction In the UK, primary care is seen as the optimal context for delivering care to an ageing population with a growing number of long-term conditions. However, if it is to meet these demands effectively and efficiently, a more precise understanding of existing care processes is required to ensure their configuration is based on robust evidence. This need to understand and optimise organisational performance is not unique to healthcare, and in industries such as telecommunications or finance, a methodology known as ‘process mining’ has become an established and successful method to identify how an organisation can best deploy resources to meet the needs of its clients and customers. Here and for the first time in the UK, we will apply it to primary care settings to gain a greater understanding of how patients with two of the most common chronic conditions are managed. Methods and analysis The study will be conducted in three phases; first, we will apply process mining algorithms to the data held on the clinical management system of four practices of varying characteristics in the West Midlands to determine how each interacts with patients with hypertension or type 2 diabetes. Second, we will use traditional process mapping exercises at each practice to manually produce maps of care processes for the selected condition. Third, with the aid of staff and patients at each practice, we will compare and contrast the process models produced by process mining with the process maps produced via manual techniques, review differences and similarities between them and the relative importance of each. The first pilot study will be on hypertension and the second for patients diagnosed with type 2 diabetes

Designing the Didactic Strategy Modeling Language (DSML) From PoN: An Activity Oriented EML Proposal

[EN] This paper presents the design of the didactic strategy modeling language (DSML) according to the principles of Physics of Notations (PoN). The DSML is a visual and activity-oriented language for learning design characterized by the representation of different activities according to the nature of the task. Once the language is designed, a blind interpretation study is conducted to validate the semantic transparency of the learning activity iconography. The results of the paper allow to refine the icons. In addition to this, an authoring tool for DSML, which is integrated to an LMS, is presented. As a result, a model driven course was designed as a DSML pre-validation.Ruiz, A.; Panach Navarrete, JI.; Pastor López, O.; Giraldo-Velásquez, FD.; Arciniegas, JL.; Giraldo, WJ. (2018). Designing the Didactic Strategy Modeling Language (DSML) From PoN: An Activity Oriented EML Proposal. IEEE-RITA: Latin-American Learning Technologies Journal. 13(4):136-143. https://doi.org/10.1109/RITA.2018.2879262S13614313