@article{MeyerPufahlBatoulisetal.2015,
  author    = {Meyer, Andreas and Pufahl, Luise and Batoulis, Kimon and Fahland, Dirk and Weske, Mathias},
  title     = {Automating data exchange in process choreographies},
  series = {Information systems},
  volume    = {53},
  journal   = {Information systems},
  publisher = {Elsevier},
  address   = {Oxford},
  issn      = {0306-4379},
  doi       = {10.1016/j.is.2015.03.008},
  pages     = {296 -- 329},
  year      = {2015},
  abstract  = {Communication between organizations is formalized as process choreographies in daily business. While the correct ordering of exchanged messages can be modeled and enacted with current choreography techniques, no approach exists to describe and automate the exchange of data between processes in a choreography using messages. This paper describes an entirely model-driven approach for BPMN introducing a few concepts that suffice to model data retrieval, data transformation, message exchange, and correlation four aspects of data exchange. For automation, this work utilizes a recent concept to enact data dependencies in internal processes. We present a modeling guideline to derive local process models from a given choreography; their operational semantics allows to correctly enact the entire choreography from the derived models only including the exchange of data. Targeting on successful interactions, we discuss means to ensure correct process choreography modeling. Finally, we implemented our approach by extending the camunda BPM platform with our approach and show its feasibility by realizing all service interaction patterns using only model-based concepts. (C) 2015 Elsevier Ltd. All rights reserved.},
  language  = {en}
}
@book{PufahlMeyerWeske2013,
  author    = {Pufahl, Luise and Meyer, Andreas and Weske, Mathias},
  title     = {Batch regions : process instance synchronization based on data},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-280-3},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-69081},
  publisher      = {Universit{\"a}t Potsdam},
  pages     = {18},
  year      = {2013},
  abstract  = {Business process automation improves organizations' efficiency to perform work. In existing business process management systems, process instances run independently from each other. However, synchronizing instances carrying similar characteristics, i.e., sharing the same data, can reduce process execution costs. For example, if an online retailer receives two orders from one customer, there is a chance that they can be packed and shipped together to save shipment costs. In this paper, we use concepts from the database domain and introduce data views to business processes to identify instances which can be synchronized. Based on data views, we introduce the concept of batch regions for a context-aware instance synchronization over a set of connected activities. We also evaluate the concepts introduced in this paper with a case study comparing costs for normal and batch processing.},
  language  = {de}
}
@book{MeyerSmirnovWeske2011,
  author    = {Meyer, Andreas and Smirnov, Sergey and Weske, Mathias},
  title     = {Data in business processes},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-144-8},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-53046},
  publisher      = {Universit{\"a}t Potsdam},
  pages     = {40},
  year      = {2011},
  abstract  = {Process and data are equally important for business process management. Process data is especially relevant in the context of automated business processes, process controlling, and representation of organizations' core assets. One can discover many process modeling languages, each having a specific set of data modeling capabilities and the level of data awareness. The level of data awareness and data modeling capabilities vary significantly from one language to another. This paper evaluates several process modeling languages with respect to the role of data. To find a common ground for comparison, we develop a framework, which systematically organizes process- and data-related aspects of the modeling languages elaborating on the data aspects. Once the framework is in place, we compare twelve process modeling languages against it. We generalize the results of the comparison and identify clusters of similar languages with respect to data awareness.},
  language  = {de}
}
@phdthesis{Meyer2015,
  author    = {Meyer, Andreas},
  title     = {Data perspective in business process management},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-84806},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xxi, 362},
  year      = {2015},
  abstract  = {Gesch{\"a}ftsprozessmanagement ist ein strukturierter Ansatz zur Modellierung, Analyse, Steuerung und Ausf{\"u}hrung von Gesch{\"a}ftsprozessen, um Gesch{\"a}ftsziele zu erreichen. Es st{\"u}tzt sich dabei auf konzeptionelle Modelle, von denen Prozessmodelle am weitesten verbreitet sind. Prozessmodelle beschreiben wer welche Aufgabe auszuf{\"u}hren hat, um das Gesch{\"a}ftsziel zu erreichen, und welche Informationen daf{\"u}r ben{\"o}tigt werden. Damit beinhalten Prozessmodelle Informationen {\"u}ber den Kontrollfluss, die Zuweisung von Verantwortlichkeiten, den Datenfluss und Informationssysteme. Die Automatisierung von Gesch{\"a}ftsprozessen erh{\"o}ht die Effizienz der Arbeitserledigung und wird durch Process Engines unterst{\"u}tzt. Daf{\"u}r werden jedoch Informationen {\"u}ber den Kontrollfluss, die Zuweisung von Verantwortlichkeiten f{\"u}r Aufgaben und den Datenfluss ben{\"o}tigt. W{\"a}hrend aktuelle Process Engines die ersten beiden Informationen weitgehend automatisiert verarbeiten k{\"o}nnen, m{\"u}ssen Daten manuell implementiert und gewartet werden. Dem entgegen verspricht ein modell-getriebenes Behandeln von Daten eine vereinfachte Implementation in der Process Engine und verringert gleichzeitig die Fehleranf{\"a}lligkeit dank einer graphischen Visualisierung und reduziert den Entwicklungsaufwand durch Codegenerierung. Die vorliegende Dissertation besch{\"a}ftigt sich mit der Modellierung, der Analyse und der Ausf{\"u}hrung von Daten in Gesch{\"a}ftsprozessen. Als formale Basis f{\"u}r die Prozessausf{\"u}hrung wird ein konzeptuelles Framework f{\"u}r die Integration von Prozessen und Daten eingef{\"u}hrt. Dieses Framework wird durch operationelle Semantik erg{\"a}nzt, die mittels einem um Daten erweiterten Petrinetz-Mapping vorgestellt wird. Die modellgetriebene Ausf{\"u}hrung von Daten muss komplexe Datenabh{\"a}ngigkeiten, Prozessdaten und den Datenaustausch ber{\"u}cksichtigen. Letzterer tritt bei der Kommunikation zwischen mehreren Prozessteilnehmern auf. Diese Arbeit nutzt Konzepte aus dem Bereich der Datenbanken und {\"u}berf{\"u}hrt diese ins Gesch{\"a}ftsprozessmanagement, um Datenoperationen zu unterscheiden, um Abh{\"a}ngigkeiten zwischen Datenobjekten des gleichen und verschiedenen Typs zu spezifizieren, um modellierte Datenknoten sowie empfangene Nachrichten zur richtigen laufenden Prozessinstanz zu korrelieren und um Nachrichten f{\"u}r die Prozess{\"u}bergreifende Kommunikation zu generieren. Der entsprechende Ansatz ist nicht auf eine bestimmte Prozessbeschreibungssprache begrenzt und wurde prototypisch implementiert. Die Automatisierung der Datenbehandlung in Gesch{\"a}ftsprozessen erfordert entsprechend annotierte und korrekte Prozessmodelle. Als Unterst{\"u}tzung zur Datenannotierung f{\"u}hrt diese Arbeit einen Algorithmus ein, welcher Informationen {\"u}ber Datenknoten, deren Zust{\"a}nde und Datenabh{\"a}ngigkeiten aus Kontrollflussinformationen extrahiert und die Prozessmodelle entsprechend annotiert. Allerdings k{\"o}nnen gew{\"o}hnlich nicht alle erforderlichen Informationen aus Kontrollflussinformationen extrahiert werden, da detaillierte Angaben {\"u}ber m{\"o}gliche Datenmanipulationen fehlen. Deshalb sind weitere Prozessmodellverfeinerungen notwendig. Basierend auf einer Menge von Objektlebenszyklen kann ein Prozessmodell derart verfeinert werden, dass die in den Objektlebenszyklen spezifizierten Datenmanipulationen automatisiert in ein Prozessmodell {\"u}berf{\"u}hrt werden k{\"o}nnen. Prozessmodelle stellen eine Abstraktion dar. Somit fokussieren sie auf verschiedene Teilbereiche und stellen diese im Detail dar. Solche Detailbereiche sind beispielsweise die Kontrollflusssicht und die Datenflusssicht, welche oft durch Aktivit{\"a}ts-zentrierte beziehungsweise Objekt-zentrierte Prozessmodelle abgebildet werden. In der vorliegenden Arbeit werden Algorithmen zur Transformation zwischen diesen Sichten beschrieben. Zur Sicherstellung der Modellkorrektheit wird das Konzept der „weak conformance" zur {\"U}berpr{\"u}fung der Konsistenz zwischen Objektlebenszyklen und dem Prozessmodell eingef{\"u}hrt. Dabei darf das Prozessmodell nur Datenmanipulationen enthalten, die auch in einem Objektlebenszyklus spezifiziert sind. Die Korrektheit wird mittels Soundness-{\"U}berpr{\"u}fung einer hybriden Darstellung ermittelt, so dass Kontrollfluss- und Datenkorrektheit integriert {\"u}berpr{\"u}ft werden. Um eine korrekte Ausf{\"u}hrung des Prozessmodells zu gew{\"a}hrleisten, m{\"u}ssen gefundene Inkonsistenzen korrigiert werden. Daf{\"u}r werden f{\"u}r jede Inkonsistenz alternative Vorschl{\"a}ge zur Modelladaption identifiziert und vorgeschlagen. Zusammengefasst, unter Einsatz der Ergebnisse dieser Dissertation k{\"o}nnen Gesch{\"a}ftsprozesse modellgetrieben ausgef{\"u}hrt werden unter Ber{\"u}cksichtigung sowohl von Daten als auch den zuvor bereits unterst{\"u}tzten Perspektiven bez{\"u}glich Kontrollfluss und Verantwortlichkeiten. Dabei wird die Modellerstellung teilweise mit automatisierten Algorithmen unterst{\"u}tzt und die Modellkonsistenz durch Datenkorrektheits{\"u}berpr{\"u}fungen gew{\"a}hrleistet.},
  language  = {en}
}
@article{HerzbergMeyerWeske2015,
  author    = {Herzberg, Nico and Meyer, Andreas and Weske, Mathias},
  title     = {Improving business process intelligence by observing object state transitions},
  series = {Data \& knowledge engineering},
  volume    = {98},
  journal   = {Data \& knowledge engineering},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0169-023X},
  doi       = {10.1016/j.datak.2015.07.008},
  pages     = {144 -- 164},
  year      = {2015},
  abstract  = {During the execution of business processes several events happen that are recorded in the company's information systems. These events deliver insights into process executions so that process monitoring and analysis can be performed resulting, for instance, in prediction of upcoming process steps or the analysis of the run time of single steps. While event capturing is trivial when a process engine with integrated logging capabilities is used, manual process execution environments do not provide automatic logging of events, so that typically external devices, like bar code scanners, have to be used. As experience shows, these manual steps are error-prone and induce additional work. Therefore, we use object state transitions as additional monitoring information, so-called object state transition events. Based on these object state transition events, we reason about the enablement and termination of activities and provide the basis for process monitoring and analysis in terms of a large event log. In this paper, we present the concept to utilize information from these object state transition events for capturing process progress. Furthermore, we discuss a methodology to create the required design time artifacts that then are used for monitoring at run time. In a proof-of-concept implementation, we show how the design time and run time side work and prove applicability of the introduced concept of object state transition events. (C) 2015 Elsevier B.V. All rights reserved.},
  language  = {en}
}
@article{WannickeFrindteGustetal.2015,
  author    = {Wannicke, Nicola and Frindte, Katharina and Gust, Giselher and Liskow, Iris and Wacker, Alexander and Meyer, Andreas and Grossart, Hans-Peter},
  title     = {Measuring bacterial activity and community composition at high hydrostatic pressure using a novel experimental approach: a pilot study},
  series = {FEMS microbiology ecology},
  volume    = {91},
  journal   = {FEMS microbiology ecology},
  number    = {5},
  publisher = {Oxford Univ. Press},
  address   = {Oxford},
  issn      = {0168-6496},
  doi       = {10.1093/femsec/fiv036},
  pages     = {15},
  year      = {2015},
  abstract  = {In this pilot study, we describe a high-pressure incubation system allowing multiple subsampling of a pressurized culture without decompression. The system was tested using one piezophilic (Photobacterium profundum), one piezotolerant (Colwellia maris) bacterial strain and a decompressed sample from the Mediterranean deep sea (3044 m) determining bacterial community composition, protein production (BPP) and cell multiplication rates (BCM) up to 27 MPa. The results showed elevation of BPP at high pressure was by a factor of 1.5 +/- 1.4 and 3.9 +/- 2.3 for P. profundum and C. maris, respectively, compared to ambient-pressure treatments and by a factor of 6.9 +/- 3.8 fold in the field samples. In P. profundum and C. maris, BCM at high pressure was elevated (3.1 +/- 1.5 and 2.9 +/- 1.7 fold, respectively) compared to the ambient-pressure treatments. After 3 days of incubation at 27 MPa, the natural bacterial deep-sea community was dominated by one phylum of the genus Exiguobacterium, indicating the rapid selection of piezotolerant bacteria. In future studies, our novel incubation system could be part of an isopiestic pressure chain, allowing more accurate measurement of bacterial activity rates which is important both for modeling and for predicting the efficiency of the oceanic carbon pump.},
  language  = {en}
}
@book{MeyerPufahlFahlandetal.2013,
  author    = {Meyer, Andreas and Pufahl, Luise and Fahland, Dirk and Weske, Mathias},
  title     = {Modeling and enacting complex data dependencies in business processes},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-245-2},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-65103},
  publisher      = {Universit{\"a}t Potsdam},
  pages     = {40},
  year      = {2013},
  abstract  = {Enacting business processes in process engines requires the coverage of control flow, resource assignments, and process data. While the first two aspects are well supported in current process engines, data dependencies need to be added and maintained manually by a process engineer. Thus, this task is error-prone and time-consuming. In this report, we address the problem of modeling processes with complex data dependencies, e.g., m:n relationships, and their automatic enactment from process models. First, we extend BPMN data objects with few annotations to allow data dependency handling as well as data instance differentiation. Second, we introduce a pattern-based approach to derive SQL queries from process models utilizing the above mentioned extensions. Therewith, we allow automatic enactment of data-aware BPMN process models. We implemented our approach for the Activiti process engine to show applicability.},
  language  = {en}
}
@book{MeyerWeske2014,
  author    = {Meyer, Andreas and Weske, Mathias},
  title     = {Weak conformance between process models and synchronized object life cycles},
  number    = {91},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-303-9},
  issn      = {1613-5652},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-71722},
  publisher      = {Universit{\"a}t Potsdam},
  pages     = {31},
  year      = {2014},
  abstract  = {Process models specify behavioral execution constraints between activities as well as between activities and data objects. A data object is characterized by its states and state transitions represented as object life cycle. For process execution, all behavioral execution constraints must be correct. Correctness can be verified via soundness checking which currently only considers control flow information. For data correctness, conformance between a process model and its object life cycles is checked. Current approaches abstract from dependencies between multiple data objects and require fully specified process models although, in real-world process repositories, often underspecified models are found. Coping with these issues, we introduce the concept of synchronized object life cycles and we define a mapping of data constraints of a process model to Petri nets extending an existing mapping. Further, we apply the notion of weak conformance to process models to tell whether each time an activity needs to access a data object in a particular state, it is guaranteed that the data object is in or can reach the expected state. Then, we introduce an algorithm for an integrated verification of control flow correctness and weak data conformance using soundness checking.},
  language  = {en}
}