Ontology-Based Querying of Composite Services

Smith, Fabrizio; Missikoff, Michele; Proietti, Maurizio

doi:10.1007/978-3-642-32439-0_10

Cited by 21 publications

(13 citation statements)

References 18 publications

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“…Two query languages [57,58] that focus on pattern-based graph matching techniques are proposed. Other relevant work include: semantic querying of process structural characteristics [59], a querying technique used for BPMN process models annotated with crosscutting concerns [60], a visual model query artifact [61], and a descriptive language to query and change the structural aspect of process models [62]. ○ Behavioral querying focuses on behaviors induced by activity models.…”

Section: Literature Analysis and Evaluationmentioning

confidence: 99%

Process querying: Enabling business intelligence through query-based process analytics

Polyvyanyy

Ouyang

Barros

et al. 2017

Decision Support Systems

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The volume of process-related data is growing rapidly: more and more business operations are being supported and monitored by information systems. Industry 4.0 and the corresponding industrial Internet of Things are about to generate new waves of process-related data, next to the abundance of event data already present in enterprise systems. However, organizations often fail to convert such data into strategic and tactical intelligence. This is due to the lack of dedicated technologies that are tailored to effectively manage the information on processes encoded in process models and process execution records. Process-related information is a core organizational asset which requires dedicated analytics to unlock its full potential. This paper proposes a framework for devising process querying methods, i.e., techniques for the (automated) management of repositories of designed and executed processes, as well as models that describe relationships between processes. The framework is composed of generic components that can be configured to create a range of process querying methods. The motivation for the framework stems from use cases in the field of Business Process Management. The design of the framework is informed by and validated via a systematic literature review. The framework structures the state of the art and points to gaps in existing research. Process querying methods need to address these gaps to better support strategic decision-making and provide the next generation of Business Intelligence platforms.

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Section: Literature Analysis and Evaluationmentioning

confidence: 99%

Process querying: Enabling business intelligence through query-based process analytics

Polyvyanyy

Ouyang

Barros

et al. 2017

Decision Support Systems

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“…We show how a BPS is specified by means of an example. The full definition can be found in (Smith et al, 2012). Let us consider the BP depicted in Figure 1, where the handling of a purchase order is represented using the BPMN notation.…”

Section: Business Process Schemasmentioning

confidence: 99%

“…In this work we focus on functional annotations and on their interaction with the control flow to define the behavior of a BPS, thus extending the framework presented in (Smith et al, 2012) where terminological annotations only were considered.…”

Section: Merging Behaviorsmentioning

confidence: 99%

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Rule-based Behavioral Reasoning on Semantic Business Processes

Smith

Proietti

2013

Proceedings of the 5th International Conference on Agents and Artificial Intelligence

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We propose a rule-based framework for representing and reasoning about business processes from both the procedural and ontological point of views. To this end we define a rule-based procedural semantics for a relevant fragment of BPMN, a very popular graphical notation for specifying business processes. Our semantics defines a state transition system by following an approach similar to the Fluent Calculus, and allows us to specify state change in terms of preconditions and effects of the enactment of activities. Then we show how the procedural process knowledge can be seamlessly integrated with the domain knowledge specified by using the OWL-RL rule-based ontology language. Our framework provides a wide range of reasoning services by using standard logic programming inference engines. In particular, we can perform very sophisticated reasoning tasks by combining both procedural and domain dependent knowledge. A preliminary implementation shows that our approach is effective in practice.

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“…Process models produced by healthcare experts are represented as formal rules, providing a framework that allows their semantic enrichment. Whilst some progress in this direction has been made in recent research (Jafarpour et al, 2011;Peek et al, 2011 andSmith et al, 2012], the integration of data from literature, business processes and decision trees through workflows that cover the full cycle of health care, from diagnosis to prognosis and treatment, has not been presented before.…”

Section: Introductionmentioning

confidence: 99%

Medical-treatment Recommendation and the Integration of Process Models into Knowledge-based Systems

Subirats

Ceccaroni

Maroto

et al. 2014

Proceedings of the 6th International Conference on Agents and Artificial Intelligence

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Decision making based on evidence other than human reasoning is becoming increasingly important in healthcare. Valuable evidence is in the form of treatment processes used by healthcare institutions and this paper presents a new framework for representing and modeling knowledge from these processes. Specifically, it presents the integration of data from literature, business processes and decision trees through workflows that cover the full cycle of health care, from diagnosis to prognosis and treatment. With respect to patient status, as single instants cannot convey sufficient information, time series are analyzed and classified to improve decision-making ability. The elicitation of new knowledge takes into account international standards, ontologies, information models, nomenclatures and multiple types of indicators. The integration of formal process-modeling in knowledge-based systems is exemplified by a real-world recommendation scenario. After evaluation with a medical-rehabilitation data set, results show a strong correspondence between treatment recommended by the proposed system and clinical practice.

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Ontology-Based Querying of Composite Services

Cited by 21 publications

References 18 publications

Process querying: Enabling business intelligence through query-based process analytics

Process querying: Enabling business intelligence through query-based process analytics

Rule-based Behavioral Reasoning on Semantic Business Processes

Medical-treatment Recommendation and the Integration of Process Models into Knowledge-based Systems

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