FNet: An Index for Advanced Business Process Querying

Yan, Zhiqiang; Dijkman, Remco; Grefen, Paul

doi:10.1007/978-3-642-32885-5_20

Cited by 12 publications

(10 citation statements)

References 22 publications

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“…When searching for process models, one often starts by performing a filtering step, e.g., filtering out those models that do not contain tasks with labels of interest [9,10]. Afterwards, computation intensive methods, either structural or behavioral, cf.…”

Section: Discussionmentioning

confidence: 99%

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Indexing and Efficient Instance-Based Retrieval of Process Models Using Untanglings

Polyvyanyy

Rosa

Hofstede

2014

Advanced Information Systems Engineering

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Abstract. Process-Aware Information Systems (PAISs) support executions of operational processes that involve people, resources, and software applications on the basis of process models. Process models describe vast, often infinite, amounts of process instances, i.e., workflows supported by the systems. With the increasing adoption of PAISs, large process model repositories emerged in companies and public organizations. These repositories constitute significant information resources. Accurate and efficient retrieval of process models and/or process instances from such repositories is interesting for multiple reasons, e.g., searching for similar models/instances, filtering, reuse, standardization, process compliance checking, verification of formal properties, etc. This paper proposes a technique for indexing process models that relies on their alternative representations, called untanglings. We show the use of untanglings for retrieval of process models based on process instances that they specify via a solution to the total executability problem. Experiments with industrial process models testify that the proposed retrieval approach is up to three orders of magnitude faster than the state of the art.

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Section: Discussionmentioning

confidence: 99%

“…[2,3,8,9,10]. Given a query specified as a structural pattern, or a structural template with wildcards, these techniques are capable of retrieving process models which are formalized as structures that match the pattern, or fit the template.…”

Section: Related Workmentioning

confidence: 99%

Indexing and Efficient Instance-Based Retrieval of Process Models Using Untanglings

Polyvyanyy

Rosa

Hofstede

2014

Advanced Information Systems Engineering

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“…The role of model querying is more clearly defined in BPM than in MBSD: queries are used to verify standards compliance, identify refactoring candidates, and identify process templates representing candidates for re-use [8]. Approaches proposed for querying business process models are not all targeted at the same modeling language: while some primarily address the BPMN notation [3,7,15], others focus on different visual or textual representations of business processes [5,11,14,28,6].…”

Section: Related Workmentioning

confidence: 99%

“…BP-QL has been implemented, but is restricted both conceptually and practically to querying WS-BPEL models. Another queryby-example approach is presented in [28], where a featurebased search is adopted with the goal of improving query processing times. Both models and queries are represented in a custom graph-based notation: Process Graphs, and Query Process Graphs, respectively.…”

Section: Related Workmentioning

confidence: 99%

Querying business process models with VMQL

Störrle

Acretoaie

2013

Proceedings of the 5th ACM SIGCHI Annual International Workshop on Behaviour Modelling - Foundations and Applications

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The Visual Model Query Language (VMQL) has been invented with the objectives (1) to make it easier for modelers to query models effectively, and (2) to be universally applicable to all modeling languages. In previous work, we have applied VMQL to UML, and validated the first of these two claims. In this paper, we apply VMQL to the Business Process Modeling Notation (BPMN) to evaluate the second claim. We explore the adaptations required, and re-evaluate the usability of VMQL in this context. We find similar results to earlier work, thus both supporting our claims and establishing the usability of VMQL beyond the realm of UML.

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“…While scanning is efficient through in-memory database technology, the explosive growth of "big data" through event streaming applications, e.g., sensor data streams in Internet of Things applications, nonetheless warrants the use of indexing, e.g., B-Tree or R-Tree, to be created for process data, as alternative access paths to sequential process repository scans. Proposals for dedicated indexing strategies for processes involve indexing activity traces and subgraph isomorphism algorithms [24,25]. We include under the banner of "indexing" pragmatic considerations of pre-processing data, e.g., prejoining, to reduce computational latency and support rapid retrieval.…”

Section: Non-functional Requirements Of Process Queryingmentioning

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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FNet: An Index for Advanced Business Process Querying

Cited by 12 publications

References 22 publications

Indexing and Efficient Instance-Based Retrieval of Process Models Using Untanglings

Indexing and Efficient Instance-Based Retrieval of Process Models Using Untanglings

Querying business process models with VMQL

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

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