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IoTDM4BPMN: An IoT-Enhanced Decision Making Framework for BPMN 2.0
Full text linkThe relevance of the Internet of Things (IoT) for Business Process Management (BPM) support is increasing. IoT devices enable the collection and exchange of data over the Internet, whereby each physical device is uniquely identifiable through its embedded computing system. BPM, in turn, is concerned with analyzing, discovering, modeling, executing, and monitoring (digitized) business processes. By enhancing BPM systems with IoT capabilities, real-world data can be gathered and considered during process execution to enhance process monitoring as well as IoT-driven decision making. In this context, the aggregation of low-level IoT data into high-level process-relevant data constitutes a fundamental step towards IoT-driven decisions in business processes. This paper presents IoT Decision Making for Business Process Model and Notation (IoTDM4BPMN) a webbased framework for modeling, executing, and monitoring IoTdriven decisions in real-time. We give insights into the design and implementation of IoTDM4BPMN and provide a case study as a first validation that applies IoTDM4BPMN to the modeling, executing, and monitoring of a real-world IoT-driven decision process
LAMP: a monitoring framework for mHealth application research
Full text linkThe usage of mobile applications in healthcare has gained popularity in recent years. In 2018, at least, 10,000 apps related to mental health could be downloaded in the app stores. The popularity of healthcare apps, especially in the field of mental health, is based on in their simplicity in large-scale data collection scenarios used for the improvement of health-related services or research. For these apps, instruments to quantify the quality of an app and repositories for app quality ratings have emerged in recent years. What is rarely considered, however, is the degree of functional correctness of an app, which can have a serious impact on the data collection process and thus on data quality. The increasing restrictions of background services are a challenge for app developers, who need to implement recurring tasks reliably in the background, like the collection of longitudinal data based on questionnaires or sensor measurements. In this paper, we present a monitoring framework to investigate the degree of functional correctness regarding the background service implementation of apps based on notification events. With this framework, we want to enable the large-scale collection of app execution data in the wild to gain more insights into the execution of apps in different execution environments and configurations. The gained knowledge shall help to improve existing applications in the field of mental health and eventually to improve the degree of functional correctness of those apps
Data-Driven Evolution of Activity Forms in Object- and Process-Aware Information Systems
Full text linkAbstract. Object-aware processes enable the data-driven generation of forms based on the object behavior, which is pre-specified by the respective object lifecycle process. Each state of a lifecycle process comprises a number of object attributes that need to be set (e.g., via forms) before transitioning to the next state. When initially modeling a lifecycle process, the optimal ordering of the form fields is often unknown and only a guess of the lifecycle process modeler. As a consequence, certain form fields might be obsolete, missing, or ordered in a non-intuitive manner. Though this does not affect process executability, it decreases the usability of the automatically generated forms. Discovering respective problems, therefore, provides valuable insights into how object- and process-aware information systems can be evolved to improve their usability. This paper presents an approach for deriving improvements of object lifecycle processes by comparing the respective positions of the fields of the generated forms with the ones according to which the fields were actually filled by users during runtime. Our approach enables us to discover missing or obsolete form fields, and additionally considers the order of the fields within the generated forms. Finally, we can derive the modeling operations required to automatically restructure the internal logic of the lifecycle process states and, thus, to automatically evolve lifecycle processes and corresponding forms
Deriving Event Logs from Legacy Software Systems
Full text linkAbstract. The modernization of legacy software systems is one of the key challenges in software industry, which requires comprehensive system analysis. In this context, process mining has proven to be useful for understanding the (business) processes implemented by the legacy software system. However, process mining algorithms are highly dependent on both the quality and existence of suitable event logs. In many scenarios, existing software systems (e.g., legacy applications) do not leverage process engines capable of producing such high-quality event logs, which hampers the application of process mining algorithms. Deriving suitable event log data from legacy software systems, therefore, constitutes a relevant task that fosters data-driven analysis approaches, including process mining, data-based process documentation, and process-centric software migration. This paper presents an approach for deriving event logs from legacy software systems by combining knowledge from source code and corresponding database operations. The goal is to identify relevant business objects as well as to document user and software interactions with them in an event log suitable for process mining
Visual Decision Modeling for IoT-Aware Processes
Full text linkThe enactment of real-world-aware business processes involves multiple interconnected devices. While the latter form the basis of the Internet of Things (IoT) and enable the exchange and collection of physical data via the Internet, Business Process Management (BPM) enables analyzing, modeling, implementing, executing, and monitoring business processes. In IoT-aware processes decision making may depend on the data provided by multiple IoT devices, which results in decision rules of complex structure. In this paper, we present two approaches for the visual modeling of decisions in IoT-aware processes. The first approach allows for the visual representation of complex decision rules by extending Business Process Model and Notation (BPMN) 2.0. The second approach separates decision logic from process logic using a drag&drop modeler. With both these approaches, IoT involvement in decision making becomes apparent and complex decisions can be represented in an intuitive and simple manner
Analysis and Reengineering of the Mobile Health App Database
No full textDas MHAD-Backend wurde entwickelt um geschulten Experten eine technische Lösung bereitzustellen, systematische Bewertungen von Gesundheitsapps zu erstellen und Patienten und Behandlern damit eine informierte Entscheidung bei der Wahl der geeigneten Anwendung zu ermöglichen. Während der Verwendung des Systems meldeten die Benutzer verschiedene Schwachstellen und Funktionserweiterungswünsche, die auf eine geringe User Experience hinwiesen.
Im Rahmen dieser Arbeit wurde eine tiefgreifende Analyse des Systems durchgeführt um diese Probleme zu identifizieren und anschließend Methoden entwickelt, sie beheben. Dazu wurde eine Möglichkeit zum Caching der Systemdaten eingebaut und die Datenbankaufrufe optimiert um eine abnehmende Systemperformance zu verhindern. Zusätzlich wurde die automatisierte Suche innerhalb der App-Stores erweitert und die Architektur und Ablauf der Forschungsprojekte an den Leitfaden des PRISMA-Flussdiagramms angepasst um die Arbeiten am System zu erleichtern
Progress Determination of a BPM Tool with Ad-Hoc Changes: An Empirical Study
Full text linkOne aspect of monitoring business processes in real-time is to determine their current progress. For any real-time progress determination it is of utmost importance to accurately predict the remaining share still to be executed in relation to the total process. At run-time, however, this constitutes a particular challenge, as unexpected ad-hocchanges of the ongoing business processes may occur at any time. To properly consider such changes in the context of progress determination, different progress variants may be suitable. In this paper, an empirical study with 194 participants is presented that investigates user acceptance of different progress variants in various scenarios. The study aims to identify which progress variant, each visualised by a progress bar, isaccepted best by users in case of dynamic process changes, which usually effect the current progress of the respective progress instance. Theresults of this study allow for an implementation of the most suitablevariant in business process monitoring systems. In addition, the study provides deeper insights into the general acceptance of different progress measurements. As a key observation for most scenarios, the majority of the participants give similar answers, e.g., progress jumps within a progress bar are rejected by most participants. Consequently, it can be assumed that a general understanding of progress exists. This underlines the importance of comprehending the users’ intuitive understanding of progress to implement the latter in the most suitable fashion
Enabling Conformance Checking for Object Lifecycle Processes
Full text linkAbstract. In object-aware process management, processes are represented as multiple interacting objects rather than a sequence of activities, enabling data-driven and highly flexible processes. In such flexible scenarios, however, it is crucial to be able to check to what degree the process is executed according to the model (i.e., guided behavior). Conformance checking algorithms (e.g., Token Replay or Alignments) deal with this issue for activity-centric processes based on a process model (e.g., specified as a petri net) and a given event log that reflects how the process instances were actually executed. This paper applies conformance checking algorithms to the behavior of objects. In object-aware process management, object lifecycle processes specify the various states into which corresponding objects may transition as well as the object attribute values required to complete these states. The approach accounts for flexible lifecycle executions using multiple workflow nets and conformance categories, therefore facilitating process analysis for engineers
Konzeption und Implementierung einer kollaborativen Multiplayer-Komponente in einem Base-Building-Spiel
No full textNeonCity ist ein Multiplayer-Spiel, welches dem Spieler erlaubt seine eigene Basis mit verschiedenen
Objekten auszubauen und zu verstärken. Hierbei ist jede Stadt von bis zu 6 weiteren
Spielern umgeben. Die Spieler haben die Möglichkeit frei zu entscheiden, ob sie mit den
benachbarten Städte koexistieren oder Kämpfe ausführen.
Dabei dienen die aktuellen Methoden, Vorgehensweisen und Techniken der Spieleindustrie
als Grundlage für dieses Projekt.
Die Ergebnisse dieser Arbeit und Implementierung dienen als Proof-of-Concept, welche
die Spielmechanik und den Technologiestack als Basis zur Verfügung stellt, sodass auf dieser
Testgruppen das Spiel beurteilen können und darauf aufbauend die Anwendung zum Produkt
abzuschließen zu können
Design and Implementation of an Empirical Eye Tracking Study regarding the Validation of Existing Guidelines for the Proper Comprehension of Process Models
Full text linkBusiness Process Management hat in den letzten Jahren immer mehr an Bedeutung
gewonnen. Gründe hierfür sind unter anderem die Erhöhung der Produktivität,
die Verringerung von Kosten und auch die Automatisierung von Routineaufgaben.
Ein wichtiger Bestandteil des Business Process Managements bildet die Erstellung
von Geschäftsprozessen. Damit diese Prozesse von allen verstanden werden und
auch von hoher Qualität sind, wurden im Laufe der Jahre immer wieder neue Modellierungsrichtlinien
entworfen. Unter anderem auch die „Seven Process Modeling
Guidelines“. Diese einfach formulierten Richtlinien sollen dabei helfen, dass auch
Menschen mit weniger Erfahrung im Bereich der Prozessmodellierung gute und vor
allem verständliche Prozesse modellieren können. In dieser Arbeit wurde der Frage
nachgegangen, ob diese Guidelines tatsächlich zu einer höheren Verständlichkeit
der Prozesse beitragen. Um dies zu untersuchen, wurde ein Eye Tracking Experiment
implementiert. Insgesamt bestand das Experiment aus zwei Gruppen. Eine
Gruppe bekam dabei nur Prozessmodelle zu sehen, die ohne Hilfe der Richtlinien
erstellt wurden und die andere Gruppe bekam nur die Modelle zu sehen, die mit
Hilfe der genannten Richtlinien erstellt wurden. In der Studie wurde die Performance,
der Cognitive Load und das Level of Acceptability der Teilnehmer gemessen.
Diese Daten dienten am Schluss zur statistischen Analyse und zur Beantwortung
der Forschungsfrage. Obwohl es ein paar signifikante Unterschiede gab, konnte im
Allgemeinen keine der aufgestellten Hypothesen bestätigt werden. Überraschenderweise\ud
konnten die Seven Process Modeling Guidelines in dieser Studie nicht zu
einer höheren Verständlichkeit von Prozessmodellen beitragen