Workflow mining: a survey of issues and approaches
Data & Knowledge Engineering
Survey of graph database models
ACM Computing Surveys (CSUR)
Monitoring business processes with queries
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Structural Matching of BPEL Processes
ECOWS '07 Proceedings of the Fifth European Conference on Web Services
Performance of compressed inverted list caching in search engines
Proceedings of the 17th international conference on World Wide Web
Querying business processes with BP-QL
Information Systems
Process spaceship: discovering and exploring process views from event logs in data spaces
Proceedings of the VLDB Endowment
Deriving Protocol Models from Imperfect Service Conversation Logs
IEEE Transactions on Knowledge and Data Engineering
The Open Provenance Model: An Overview
Provenance and Annotation of Data and Processes
Extending SPARQL with regular expression patterns (for querying RDF)
Web Semantics: Science, Services and Agents on the World Wide Web
Semantics preserving SPARQL-to-SQL translation
Data & Knowledge Engineering
A query language for analyzing networks
Proceedings of the 18th ACM conference on Information and knowledge management
Tolkien: an event based storytelling system
Proceedings of the VLDB Endowment
Managing and Mining Graph Data
Managing and Mining Graph Data
Correlation patterns in service-oriented architectures
FASE'07 Proceedings of the 10th international conference on Fundamental approaches to software engineering
A framework for querying graph-based business process models
Proceedings of the 19th international conference on World wide web
Codebook: discovering and exploiting relationships in software repositories
Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 1
RDFProv: A relational RDF store for querying and managing scientific workflow provenance
Data & Knowledge Engineering
Relational processing of RDF queries: a survey
ACM SIGMOD Record
HyperGraphDB: a generalized graph database
WAIM'10 Proceedings of the 2010 international conference on Web-age information management
Process Mining: Discovery, Conformance and Enhancement of Business Processes
Process Mining: Discovery, Conformance and Enhancement of Business Processes
Event correlation for process discovery from web service interaction logs
The VLDB Journal — The International Journal on Very Large Data Bases
FNet: an index for advanced business process querying
BPM'12 Proceedings of the 10th international conference on Business Process Management
A framework and a language for on-line analytical processing on graphs
WISE'12 Proceedings of the 13th international conference on Web Information Systems Engineering
Modeling and query language for hospitals
HIS'13 Proceedings of the second international conference on Health Information Science
Enabling the analysis of cross-cutting aspects in ad-hoc processes
CAiSE'13 Proceedings of the 25th international conference on Advanced Information Systems Engineering
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The execution of a business process (BP) in today's enterprises may involve a workflow and multiple IT systems and services. Often no complete, up-to-date documentation of the model or correlation information of process events exist. Understanding the execution of a BP in terms of its scope and details is challenging specially as it is subjective: depends on the perspective of the person looking at BP execution. We present a framework, simple abstractions and a language for the explorative querying and understanding of BP execution from various user perspectives. We propose a query language for analyzing event logs of process-related systems based on the two concepts of folders and paths, which enable an analyst to group related events in the logs or find paths among events. Folders and paths can be stored to be used in follow-on analysis. We have implemented the proposed techniques and the language, FPSPARQL, by extending SPARQL graph query language. We present the evaluation results on the performance and the quality of the results using a number of process event logs.