Mayflower - Explorative Modeling of Scientific Workflows with BPEL

Using workflows for scientific calculations, experiments and simulations has been a success story in many cases. Unfortunately, most of the existing scientific workflow systems implement proprietary, non-standardized workflow languages, not taking advantage of the achievements of the conventional business workflow technology. It is only natural to combine these two research branches in order to harness the strengths of both. In this demonstration, we present Mayflower, a workflow environment that enables scientists to model workflows on the fly using extended business workflow technology. It supports the typical trial-and-error approach scientists follow when developing their experiments, computations or simulations and provides scientists with all crucial characteristics of the workflow technology. Additionally, beneficial to the business stakeholders, Mayflower brings additional simplification in workflow development and debugging

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

Koostööäriprotsesside läbiviimine plokiahelal: süsteem

Tänapäeval peavad organisatsioonid tegema omavahel koostööd, et kasutada ära üksteise täiendavaid võimekusi ning seeläbi pakkuda oma klientidele parimaid tooteid ja teenuseid. Selleks peavad organisatsioonid juhtima äriprotsesse, mis ületavad nende organisatsioonilisi piire. Selliseid protsesse nimetatakse koostööäriprotsessideks. Üks peamisi takistusi koostööäriprotsesside elluviimisel on osapooltevahelise usalduse puudumine. Plokiahel loob detsentraliseeritud pearaamatu, mida ei saa võltsida ning mis toetab nutikate lepingute täitmist. Nii on võimalik teha koostööd ebausaldusväärsete osapoolte vahel ilma kesksele asutusele tuginemata. Paraku on aga äriprotsesside läbiviimine selliseid madala taseme plokiahela elemente kasutades tülikas, veaohtlik ja erioskusi nõudev. Seevastu juba väljakujunenud äriprotsesside juhtimissüsteemid (Business Process Management System – BPMS) pakuvad käepäraseid abstraheeringuid protsessidele orienteeritud rakenduste kiireks arendamiseks. Käesolev doktoritöö käsitleb koostööäriprotsesside automatiseeritud läbiviimist plokiahela tehnoloogiat kasutades, kombineerides traditsioonliste BPMS- ide arendusvõimalused plokiahelast tuleneva suurendatud usaldusega. Samuti käsitleb antud doktoritöö küsimust, kuidas pakkuda tuge olukordades, milles uued osapooled võivad jooksvalt protsessiga liituda, mistõttu on vajalik tagada paindlikkus äriprotsessi marsruutimisloogika muutmise osas. Doktoritöö uurib tarkvaraarhitektuurilisi lähenemisviise ja modelleerimise kontseptsioone, pakkudes välja disainipõhimõtteid ja nõudeid, mida rakendatakse uudsel plokiahela baasil loodud äriprotsessi juhtimissüsteemil CATERPILLAR. CATERPILLAR-i süsteem toetab kahte lähenemist plokiahelal põhinevate protsesside rakendamiseks, läbiviimiseks ja seireks: kompileeritud ja tõlgendatatud. Samuti toetab see kahte kontrollitud paindlikkuse mehhanismi, mille abil saavad protsessis osalejad ühiselt otsustada, kuidas protsessi selle täitmise ajal uuendada ning anda ja eemaldada osaliste juurdepääsuõigusi.Nowadays, organizations are pressed to collaborate in order to take advantage of their complementary capabilities and to provide best-of-breed products and services to their customers. To do so, organizations need to manage business processes that span beyond their organizational boundaries. Such processes are called collaborative business processes. One of the main roadblocks to implementing collaborative business processes is the lack of trust between the participants. Blockchain provides a decentralized ledger that cannot be tamper with, that supports the execution of programs called smart contracts. These features allow executing collaborative processes between untrusted parties and without relying on a central authority. However, implementing collaborative business processes in blockchain can be cumbersome, error-prone and requires specialized skills. In contrast, established Business Process Management Systems (BPMSs) provide convenient abstractions for rapid development of process-oriented applications. This thesis addresses the problem of automating the execution of collaborative business processes on top of blockchain technology in a way that takes advantage of the trust-enhancing capabilities of this technology while offering the development convenience of traditional BPMSs. The thesis also addresses the question of how to support scenarios in which new parties may be onboarded at runtime, and in which parties need to have the flexibility to change the default routing logic of the business process. We explore architectural approaches and modelling concepts, formulating design principles and requirements that are implemented in a novel blockchain-based BPMS named CATERPILLAR. The CATERPILLAR system supports two methods to implement, execute and monitor blockchain-based processes: compiled and interpreted. It also supports two mechanisms for controlled flexibility; i.e., participants can collectively decide on updating the process during its execution as well as granting and revoking access to parties.https://www.ester.ee/record=b536494

Linguistic Refactoring of Business Process Models

In the past decades, organizations had to face numerous challenges due to intensifying globalization and internationalization, shorter innovation cycles and growing IT support for business. Business process management is seen as a comprehensive approach to align business strategy, organization, controlling, and business activities to react flexibly to market changes. For this purpose, business process models are increasingly utilized to document and redesign relevant parts of the organization's business operations. Since companies tend to have a growing number of business process models stored in a process model repository, analysis techniques are required that assess the quality of these process models in an automatic fashion. While available techniques can easily check the formal content of a process model, there are only a few techniques available that analyze the natural language content of a process model. Therefore, techniques are required that address linguistic issues caused by the actual use of natural language. In order to close this gap, this doctoral thesis explicitly targets inconsistencies caused by natural language and investigates the potential of automatically detecting and resolving them under a linguistic perspective. In particular, this doctoral thesis provides the following contributions. First, it defines a classification framework that structures existing work on process model analysis and refactoring. Second, it introduces the notion of atomicity, which implements a strict consistency condition between the formal content and the textual content of a process model. Based on an explorative investigation, we reveal several reoccurring violation patterns are not compliant with the notion of atomicity. Third, this thesis proposes an automatic refactoring technique that formalizes the identified patterns to transform a non-atomic process models into an atomic one. Fourth, this thesis defines an automatic technique for detecting and refactoring synonyms and homonyms in process models, which is eventually useful to unify the terminology used in an organization. Fifth and finally, this thesis proposes a recommendation-based refactoring approach that addresses process models suffering from incompleteness and leading to several possible interpretations. The efficiency and usefulness of the proposed techniques is further evaluated by real-world process model repositories from various industries. (author's abstract

Investigating the process of process modeling and its relation to modeling quality : the role of structured serialization

Lately, the focus of organizations is changing fundamentally. Where they used to spend almost exclusively attention to results, in terms of goods, services, revenue and costs, they are now concerned about the efficiency of their business processes. Each step of the business processes needs to be known, controlled and optimized. This explains the huge effort that many organizations currently put into the mapping of their processes in so-called (business) process models. Unfortunately, sometimes these models do not (completely) reflect the business reality or the reader of the model does not interpret the represented information as intended. Hence, whereas on the one hand we observe how organizations are attaching increasing importance to these models, on the other hand we notice how the quality of process models in companies often proves to be insufficient. The doctoral research makes a significant contribution in this context. This work investigates in detail how people create process models and why and when this goes wrong. A better understanding of current process modeling practice will form the basis for the development of concrete guidelines that result in the construction of better process models in the future. The first study investigated how we can represent the approach of different modelers in a cognitive effective way, in order to facilitate knowledge building. For this purpose the PPMChart was developed. It represents the different operations of a modeler in a modeling tool in such a way that patterns in their way of working can be detected easily. Through the collection of 704 unique modeling executions (a joint contribution of several authors in the research domain), and through the development of a concrete implementation of the visualization, it became possible to gather a great amount of insights about how different people work in different situations while modeling a concrete process. The second study explored, based on the discovered modeling patterns of the first study, the potential relations between how process models were being constructed and which quality was delivered. To be precise, three modeling patterns from the previous study were investigated further in their relation with the understandability of the produced process model. By comparing the PPMCharts that show these patterns with corresponding process models, a connection was found in each case. It was noticed that when a process model was constructed in consecutive blocks (i.e., in a structured way), a better understandable process model was produced. A second relation stated that modelers who (frequently) moved (many) model elements during modeling usually created a less understandable model. The third connection was found between the amount of time spent at constructing the model and a declining understandability of the resulting model. These relations were established graphically on paper, but were also confirmed by a simple statistical analysis. The third study selected one of the relations from the previous study, i.e., the relation between structured modeling and model quality, and investigated this relation in more detail. Again, the PPMChart was used, which has lead to the identification of different ways of structured process modeling. When a task is difficult, people will spontaneously split up this task in sub-tasks that are executed consecutively (instead of simultaneously). Structuring is the way in which the splitting of tasks is handled. It was found that when this happens consistently and according to certain logic, modeling became more effective and more efficient. Effective because a process model was created with less syntactic and semantic errors and efficient because it took less time and modeling operations. Still, we noticed that splitting up the modeling in sub-tasks in a structured way, did not always lead to a positive result. This can be explained by some people structuring the modeling in the wrong way. Our brain has cognitive preferences that cause certain ways of working not to fit. The study identified three important cognitive preferences: does one have a sequential or a global learning style, how context-dependent one is and how big one’s desire and need for structure is. The Structured Process Modeling Theory was developed, which captures these relations and which can form the basis for the development of an optimal individual approach to process modeling. In our opinion the theory has the potential to also be applicable in a broader context and to help solving various types of problems effectively and efficiently