Carolina Ming Chiao
University of Ulm
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Publication
Featured researches published by Carolina Ming Chiao.
database and expert systems applications | 2008
Lucinéia Heloisa Thom; Manfred Reichert; Carolina Ming Chiao; Cirano Iochpe; Guillermo Nudelman Hess
Recently, a variety of workflow patterns has been proposed focusing on specific aspects like control flow, data flow, and resource assignments. Though these patterns are relevant for implementing Business Process Modeling (BPM) tools and for evaluating the expressiveness of BPM languages, they do not contribute to reduce redundant specifications of recurrent business functions when modeling business processes. Furthermore, contemporary BPM tools do not support process designers in defining, querying, and reusing activity patterns as building blocks for process modeling. Related to these problems this paper proposes a set of activity patterns, evidences their practical relevance, and introduces a BPM tool for the modeling of business processes based on the reuse of these activity patterns. Altogether our approach fosters reuse of business function specifications and helps to improve the quality and comparability of business process models.
2013 IEEE 1st International Workshop on Communicating Business Process and Software Models Quality, Understandability, and Maintainability (CPSM) | 2013
Carolina Ming Chiao; Vera Künzle; Manfred Reichert
Process- and data-centric software systems require a tight integration of processes, functions, data, and users. Thereby, the behavioral perspective is described by process models, while the information perspective is captured in a data model. Eliciting and capturing requirements of such software systems in a consistent way is a challenging task, demanding that both process and data model are well aligned and consistent with each other. While traditional software modeling languages do not allow for an explicit integration of data and process models, activity-centric process modeling languages tend to neglect the role of data as a driver of process execution; i.e., business objects are usually outside the control of the process, normally stored in external databases. To overcome this drawback, PHILharmonicFlows provides a comprehensive framework for enabling object-aware process support. In addition, a sound specification of process- and object-centric software systems becomes possible. In this paper, we present a requirements modeling approach that provides methodological guidance for modeling large process-and data-centric software systems based on PHILharmonicFlows. Such guidance will foster the introduction of respective software systems in the large scale.
enterprise distributed object computing | 2014
Carolina Ming Chiao; Vera Kuenzle; Manfred Reichert
Although the popularity of activity-centric process management systems (PrMS) has increased during the last decade, there still exist business processes that cannot be adequately supported by these PrMS. A common characteristic of these processes, which is neglected by current activity-centric PrMS, is their need for object-awareness, i.e., the explicit processing of business data and business objects respectively. In the PHILharmonicFlows project, characteristic properties of object-aware processes were identified and an advanced framework for their proper support was designed. In this paper, we present a proof-of-concept prototype implementing some of the fundamental concepts of the PHILharmonicFlows framework. Overall, this initiative will result in a new generation of process management technology.
business process management | 2013
Semra Catalkaya; David Knuplesch; Carolina Ming Chiao; Manfred Reichert
Making the right decisions in time is one of the key tasks in every business. In this context, decision theory fosters decision-making based on well-defined decision rules. The latter evaluate a given set of input parameters and utilize evidenced data in order to determine an optimal alternative out of a given set of choices. In particular, decision rules are relevant in the context business processes as well. Contemporary process modeling languages, however, have not incorporated decision theory yet, but mainly consider rather simple, guard-based decisions that refer to process-relevant data. To remedy this drawback, this paper introduces an approach that allows embedding decision problems in business process models and applying decision rules to deal with them. As a major benefit, it becomes possible to automatically determine optimal execution paths during run time.
business process management | 2012
Carolina Ming Chiao; Vera Künzle; Manfred Reichert
Enabling process flexibility is crucial for any process-aware information system (PAIS). In particular, implemented processes may have to be frequently adapted to accommodate to changing environments and evolving needs. When evolving a PAIS, corresponding process schemas have to be changed in a controlled manner. In the context of object-aware processes, which are characterized by a tight integration of process and data, PAIS evolution not only requires process schema evolution, but the evolution of data and user authorization schemas as well. Since the different schemas of an object-aware PAIS are tightly integrated, modifying one of them usually requires concomitant changes of the other schemas. This paper presents a framework for object-aware process support and discusses major requirements and challenges for enabling schema evolution in object-aware PAIS.
international conference on ehealth telemedicine and social medicine | 2012
Carolina Ming Chiao; Vera Künzle; Manfred Reichert
international conference on enterprise information systems | 2008
Lucinéia Heloisa Thom; Manfred Reichert; Carolina Ming Chiao; Cirano Iochpe
SIMPDA | 2013
Carolina Ming Chiao; Vera Künzle; Manfred Reichert
Revista Brasileira de Sistemas de Informação (iSys) | 2008
Lucinéia Heloisa Thom; Cirano Iochpe; Manfred Reichert; Barbara Weber; Droop Matthias; Gleison Samuel do Nascimento; Carolina Ming Chiao
Archive | 2013
Carolina Ming Chiao; Vera Künzle; Manfred Reichert