Agora-Speech-Act-Based Adaptive Case Management. - Tenschert, Johannes; Lenz, Richard (BPM (Demos), 2016)

An Algebra for Pattern Matching, Time-aware Aggregates and Partitions on Relational Data Streams - Herbst, Sebastian; Pollner, Thomas Niko; Tenschert, Johannes; Lauterwald, Frank; Endler, Gregor; Meyer-Wegener, Klaus (DEBS '15 Proceedings of the 9th ACM International Conference on Distributed Event-Based Systems, 2015)
Keywords: animal tracking; complex event processing; continuous queries; data stream processing; disjoint union; object tracking; pattern matching; stream algebra; stream partitioning; time-aware aggregates

An Architecture for Continuous Data Quality Monitoring in Medical Centers - Endler, Gregor; Schwab, Peter; Wahl, Andreas Maximilian; Tenschert, Johannes; Lenz, Richard (MEDINFO 2015: eHealth-enabled Health, 2015)
In the medical domain, data quality is very important. Since requirements and data change frequently, continuous and sustainable monitoring and improvement of data quality is necessary. Working together with managers of medical centers, we developed an architecture for a data quality monitoring system. The architecture enables domain experts to adapt the system during runtime to match their specifications using a built-in rule system. It also allows arbitrarily complex analyses to be integrated into the monitoring cycle. We evaluate our architecture by matching its components to the well-known data quality methodology TDQM.
UnivIS-Import:2015-10-26:Pub.2015.tech.IMMD.IMMD6.anarch
Keywords: Medical Informatics; Data Quality; Quality Control; Quality Improvement; Data Collection; Databases; Factual; Group Practice

Anfragesprache für Workflowmodelle - Tenschert, Johannes (2012)
Für die Simulation medizinischer Arbeitsabläufe ist eine Vielzahl von Datensätzen nötig, die sehr häufig einzelnen Arbeitsschritten zugeordnet werden können. Es wurden daher zunächst als Modell für Arbeitsabläufe UML-Aktivitätsdiagramme gewählt, die in RDF formuliert, deren Zustände mit Zeitangaben und Kosten und deren Transitionen mit Bedingungen annotiert werden. In dieser Arbeit wird die Workflow Query Language (WQL), eine Anfragesprache für Workflowmodelle, entwickelt. Diese verwendet das Konzept der Fallakten, d.h. über mehrere Abfragen verfügbare und über ihren Namen identifizierbare Sammlungen von Variablen, Zeitangaben und Entscheidungen für Workflows und unterstützt vier verschiedene Anfragearten sowie Operationen zur Verwaltung von Workflows und Fallakten. Die vorgestellte Heuristik zur Pfadverarbeitung der WQL kann dabei mit Verzweigungen, Parallelität und Zyklen umgehen. Abschließend wird die Sprache nach vorher ausgearbeiteten Anforderungen evaluiert.
UnivIS-Import:2018-09-06:Pub.2012.tech.IMMD.IMMD6.anfrag
Keywords: Workflow Query Language; Workflow Management; Domain-specific Language

A Query Language for Workflow Instance Data - Baumgärtel, Philipp; Lenz, Richard; Tenschert, Johannes (New Trends in Databases and Information Systems, 2014)
UnivIS-Import:2015-04-16:Pub.2014.tech.IMMD.IMMD6.aquery

Design Principles for Comprehensible Process Discovery in Process Mining - Stierle, Matthias; Zilker, Sandra; Dunzer, Sebastian; Tenschert, Johannes; Karagegova, Gergana (28th European Conference on Information Systems - Liberty, Equality, and Fraternity in a Digitizing World, ECIS 2020, Marrakech, Morocco, June 15-17, 2020, 2020)

Detecting Bats Behavior with the Help of Event Stream Processing Systems - Herbst, Sebastian; Tenschert, Johannes; Meyer-Wegener, Klaus (SP1: Special Session - DFG Research Unit 'BATS' - Dynamically Adaptive Applications for Bat Localization using Embedded Communicating Sensor Systems, 2015)
UnivIS-Import:2017-12-18:Pub.2015.tech.IMMD.IMMD6.detect

Enterprise System Capabilities for Organizational Change in the BPM Life Cycle - Tenschert, Johannes; Tang, Willi; Matzner, Martin (Business Process Management Workshops, 2020)

Evaluation of WfMC Awards for Case Management: Features, Knowledge Workers, Systems - Tenschert, Johannes; Lenz, Richard (International Conference on Business Process Management, 2018)
In recent years, many production case management (PCM) and adaptive case management (ACM) systems have been introduced into the daily workflow of knowledge workers. In many research papers and case studies, the claims about the nature and requirements of knowledge work in general seem to vary. While choosing or creating a case management (CM) solution, typically one has the target knowledge workers and their domain-specific requirements in mind. But knowledge work shows a huge variety of modes of operation, complexity, and collaboration. We want to increase transparency on which features are covered by well-known and award-winning systems for different types of knowledge workers and different classes of systems. This may not unveil gaps between requirements and offered solutions, but it can uncover differences in solutions for varying user bases. We performed a literature review of 48 winners of the WfMC Awards for Excellence in Case Management from 2011 to 2016 and analyzed case studies in regard to targeted knowledge workers, advertised features, and type of system. Different types of knowledge workers showed a different bias on certain system types and features in regard to collaboration and variability of processe
Keywords: Adaptive Case Management; Process Management; Production case management Knowledge-intensive business process Knowledge work

Flexibility, Adherence, and Guidance for Regulated Processes with Case Management - Tenschert, Johannes; Hormesch, Michelle (BPM 2020 Industry Forum Proceedings, 2020)
Knowledge-intensive processes in regulated domains show high requirements in regard to documenting processes and their instances, but inherently as knowledge-intensive also in flexibility. This typically leads to a lack of automation, manual documentation, and the process being scattered across many support systems. At Pertuniti, we combine the flexibility of social software and adaptive case management with subprocess modeling for aspects that can be modeled and automated. This way, we can provide one transparent system of record that allows implicit documentation of structured and ad-hoc activities, managing and linking all case artifacts, and an iterative approach on which aspects are modeled. We cope with drastically varying requirements on process support with a flexible and adaptable data model, and by facilitating low-code implementations of changes and transparently deviating from models.
Keywords: adaptive case management; quality management; subprocess modeling; knowledge-intensive business process; process flexibility

Notation-agnostic Subprocess Modeling for Adaptive Case Management - Tenschert, Johannes; Dunzer, Sebastian; Matzner, Martin (Lecture Notes in Information Systems and Organisation, 2021)
Even though knowledge work comprises tasks that cannot be modeled a priori, some structure for routine work or an outlined course of action is often necessary. Knowledge workers perform structured and ad-hoc activities – and a wide range of requirements typically yields many tools. To avoid redundant and scattered process information, a single system of record capable of consolidating flexibility and modeling of different aspects of processes is desirable. For knowledge-intensive processes, we outline how to combine process models for structured routine aspects with the ad-hoc activities and flexibility of social software in the same context. Therefore, a case comprises modeled subprocesses as well as ad-hoc activities and artifacts. The shared context allows to transparently combine aspects and deviate from predefined models. We prototypically implement our approach and show that ad-hoc project management and different notations can be applied within the same case.<br
CRIS-Team Scopus Importer:2021-11-26
Keywords: adaptive case management; subprocess modeling; knowledge-intensive business process; process flexibility

Pertuniti: Subprocess Modeling and Hierarchic Case Management - Tenschert, Johannes; Marmaridis, Sophia (BPM 2020 Demo, 2020)
Knowledge-intensive processes are typically scattered across many systems with no clear system of record. Support systems have to consider informational relations of process instances on different granularities, and different aspects of the work require different characteristics in regard to flexibility. Today, adaptive case management is typically either tailored towards flexible process models or ad-hoc activities for a lot size of 1. Pertuniti connects both approaches by implementing cases as a set primarily of groupware artifacts for complete flexibility, subprocess modeling to automate aspects of the work, and flexible case data management considering hierarchies of cases. This way, we can reduce routine work or guide through regulated activities, while deviations and ad-hoc activities remain traceable.
Keywords: adaptive case management; subprocess modeling; data modeling; knowledge-intensive business process; process flexibility

Predictive business process deviation monitoring - Weinzierl, Sven; Dunzer, Sebastian; Tenschert, Johannes; Zilker, Sandra; Matzner, Martin (Proceedings of the 29th European Conference on Information Systems, 2021)
Business processes run at the core of an organisation’s value creation and are often the target of optimisation efforts. Organisations aim at adhering to their optimised processes. However, deviations from the optimised process still occur and may potentially impede efficiency in process executions. Conformance checking can provide valuable insights regarding past process deviations, but it cannot identify deviations before they occur. Outcome-oriented predictive business process monitoring (PBPM) provides a set of methods to predict process outcomes, e. g. key performance indicators. We propose an outcome-oriented PBPM method for predictive deviation monitoring using conformance checking and deep learning to draw the most out of the two domains. By leveraging early intervention, the method supports the proactive handling of deviations, i.e., inserted and missing events in process instances, to reduce their potential harm. Our evaluation shows that the method can predict business process deviations with high predictive quality, particularly for processes with fewer variants. <br
Keywords: predictive business process monitoring; conformance checking; deep learning; process mining

Speech-Act-Based Adaptive Case Management - Tenschert, Johannes (Friedrich-Alexander-Universität Erlangen-Nürnberg, 2019)
With a focus on their pragmatic intention, speech acts have been proposed to improve the design of interactive systems for decades. Yet, early prototypes were isolated applications with limited inferencing capabilities. Alongside, the share of knowledge work in the workforce rapidly increased, and knowledge-intensive processes became customary. The objectives, interactions, intermediate results, and final outcomes of knowledge-intensive processes are typically scattered across many systems. Often, important information is not documented at all. Adaptive case management is intended for emerging, knowledge-intensive processes, where the course of action unfolds as more information becomes available. We apply speech act theory in adaptive case management, since the representation of interactions considers the context they are performed in, regardless of whether this context is a structured, semi-structured, or ad-hoc process. This common representation enables inference regardless of whether an interaction or activity is modeled a priori or documented ad hoc, and ultimately helps in resolving the issue of scattered process information that is loosely coupled by the knowledge workers performing the process. This thesis verifies that speech acts are prevalent and diverse in actual business processes. Moreover, it substantiates that a manageable set of common speech acts for modeling and ad-hoc documentation is applicable in representative knowledge work domains. It investigates the requirements and expectations of adaptive case management in a more fine-grained classification of the knowledge workers to be supported. This way, for complex work with high interdependence, it results in a speech-act-based approach of adaptive case management, that does not require a predefined process model for knowledge-intensive processes or cases. It initially expects activities to be ad hoc, and additional models to simplify or automate routine work can be introduced on demand. It establishes speech-act-based techniques for semantic annotation, modeling, and business rules for compliance monitoring as well as for integration. Thereby, the approach combines structured, semi-structured, and ad-hoc work, while providing guard rails, and line markings for one consolidated, knowledge-intensive process.<br
Keywords: Adaptive Case Management; Business Process Management; Speech Act Theory; Knowledge-Intensive Processes

Speech Acts in Actual Processes: Evaluation of Interfaces and Triggers in ITIL - Tenschert, Johannes; Rehse, Jana Rebecca; Fettke, Peter; Lenz, Richard (Proceedings of the 10th Workshop on Social and Human Aspects of Business Process Management, 2017)
Today's organizations are socio-technical systems in which human workers increasingly perform knowledge work. Interactions between knowledge workers, clerks, and systems are essentially speech acts controlling the necessity and flow of activities in semi-structured and ad-hoc processes. IT-support for knowledge work does not necessarily require any predefined process model, and often none is available. To capture what is going on, a rising number of approaches for process modeling, analysis, and support classify interactions and derive processrelated information. The frequency and diversity of speech acts has only been examined within delimited domains, but not in the larger setting of a reference model covering different types of work and domains, multiple stakeholders, and interacting processes. Therefore, we have investigated interactions in the IT Infrastructure Library (ITIL). ITIL is a collection of predefined processes, functions, and roles that constitute best practices in the realm of IT service management (ITSM). For ITIL-based processes, we demonstrate the importance, prevalence, and diversity of interactions in triggers, and that further abstraction of interactions can improve the reusability of process patterns. Hence, at least in ITSM, applying speech act theory bears great potential for process improvemen

Speech Acts in Actual Processes: Evaluation of Interfaces and Triggers in ITIL - Tenschert, Johannes; Rehse, Jana Rebecca; Fettke, Peter; Lenz, Richard (SPRINGER-VERLAG NEW YORK, MS INGRID CUNNINGHAM, 175 FIFTH AVE, NEW YORK, NY 10010 USA, 2018)
Today's organizations are socio-technical systems in which human workers increasingly perform knowledge work. Interactions between knowledge workers, clerks, and systems are essentially speech acts controlling the necessity and flow of activities in semi-structured and ad-hoc processes. IT-support for knowledge work does not necessarily require any predefined process model, and often none is available. To capture what is going on, a rising number of approaches for process modeling, analysis, and support classify interactions and derive processrelated information. The frequency and diversity of speech acts has only been examined within delimited domains, but not in the larger setting of a reference model covering different types of work and domains, multiple takeholders, and interacting processes. Therefore, we have investigated interactions in the IT Infrastructure Library (ITIL). ITIL is a collection of predefined processes, functions, and roles that constitute best practices in the realm of IT service management (ITSM). For ITIL-based processes, we demonstrate the importance, prevalence, and diversity of interactions in triggers, and that further abstraction of interactions can improve the reusability of process patterns. Hence, at least in ITSM, applying speech act theory bears great potential for process improvement.
Keywords: Speech act theory; ITIL Knowledge-intensive business process; Adaptive case management Integration

Supporting Knowledge Work by Speech-Act Based Templates for Micro Processes - Tenschert, Johannes; Lenz, Richard (Business Process Management Workshops, 2016)
Speech acts have been proposed to improve the design of interactive systems for decades. Nevertheless, they have not yet made their way to common practice in software engineering or even process modeling. Various types of workflow management systems have been successful to support or even automate mostly predictable schema based process patterns without the explicit use of speech acts as design primitives. Yet, todays work is increasingly characterized by unpredictable collaborative processes, called knowledge work. Some types of knowledge work are supported by case management tools which typically provide regulated access to case-related information. But communicative acts are not supported sufficiently. Since knowledge workers are well aware of the pragmatic dimension of their communicative acts, we believe that bringing this awareness of the nature of a speech act to a case management tool will allow for better support of unregulated knowledge intensive processes. In this paper we propose a speech-act-based approach to improve the effectivity of knowledge work. We thereby enhance case management systems by making them aware of speech acts. Speech act related micro processes can then be used to prevent misunderstandings, increase process transparency and make useful inference
UnivIS-Import:2016-06-01:Pub.2015.tech.IMMD.IMMD6.suppor
Keywords: Adaptive case management; Speech Act Theory; Knowledge-intensive business process; Process template

Towards Speech-Act-Based Adaptive Case Management - Tenschert, Johannes; Lenz, Richard (Proc. 20th Int. Enterprise Distributed Object Computing Workshop, 2016)
UnivIS-Import:2017-12-18:Pub.2016.tech.IMMD.IMMD6.toward
Keywords: business data processing; knowledge management; United States; business process support systems; compliance monitoring; groupware; knowledge work; pragmatic intention; process transparency; socio-technical entities; speech act theory; speech-act-based adaptive case

Towards Speech-Act-Based Compliance - Tenschert, Johannes; Michelson, Georg; Lenz, Richard (Proc. 18th Conf. on Business Informatics, 2016)
UnivIS-Import:2018-09-06:Pub.2016.tech.IMMD.IMMD6.toward_9
Keywords: business data processing; knowledge management; law; organisational aspects; BPMS; CTL rules; JBoss Drools; LTL rules; US; ad-hoc interactions; compliance monitoring; cross-cutting concerns; daily business; knowledge work; legal requirements; organizations; rete-based b

Using Data-Stream and Complex-Event Processing to Identify Activities of Bats - Herbst, Sebastian; Tenschert, Johannes; Meyer-Wegener, Klaus (Datenbanksysteme für Business, Technologie und Web - Workshopband, 2015)
UnivIS-Import:2017-12-18:Pub.2015.tech.IMMD.IMMD6.usingd

Verarbeitung und Analyse von Positionsdatenströmen - Tenschert, Johannes (Friedrich-Alexander-Universität Erlangen-Nürnberg, 2014)
The DFG research group 1508 (BATS) develops a sensor network consisting of static and mobile sensors to monitor bats. This thesis elaborates techniques and notations to process and analyze position data streams. Abstractions for position data were elaborated: events and activities. Events are further divided into continuous queries interpreted as events and event patterns. Hence, the approach combines data stream processing and complex event processing. UML state charts were extended to be suitable for modeling activities. The definition of activities exploits Dynamic Bayesian networks to predict behavior. Adaptive predictions are proposed to increase precision of predictions if several hypotheses of dependencies are specified. Several state-of-the-art analyses, e.g. heatmaps and local convex hulls, as well as new analyses are implemented in the prototype. Techniques to predict activities additionally support inference on available Conditional Probability Tables as well as Conditional Tables for characteristics of activities. A possible definition of personality of animals is proposed. Finally, the approach and prototype is evaluated against the objectives as well as reliability of predictions, influence of data quality on analyses and expressiveness of presented notations.
UnivIS-Import:2018-09-06:Pub.2014.tech.IMMD.IMMD6.verarb
Keywords: complex event processing; data stream processing; position data stream; data engineering