ABSTRACT
Log analysis and querying recently received a renewed interest from the research community, as the effective understanding of process behavior is crucial for improving business process management. Indeed, currently available log querying tools are not completely satisfactory, especially from the viewpoint of easiness of use. As a matter of fact, there is no framework which meets the requirements of easiness of use, flexibility and efficiency of query evaluation. In this paper, we propose a framework for graphical querying of (process) log data that makes the log analysis task quite easy and efficient, adopting a very general model of process log data which guarantees a high level of flexibility. We implemented our framework by using a flexible storage architecture and a user-friendly data analysis interface, based on an intuitive and yet expressive graph-based query language. Experiments performed on real data confirm the validity of the approach.
- van der Aalst, W.M.P., van Dongen, B.F., Herbst, J., Maruster, L., Schimm, G., Weijters, A.J.M.M.: Workow mining: a survey of issues and approaches. Data & Knowledge Engineering 47(2), 237--267 (2003) Google ScholarDigital Library
- Aalst, W.M.V.D.: A decade of business process management conferences: Personal reflections on a developing discipline. In: Business Process Management. pp. 1--16 (2012) Google ScholarDigital Library
- van der Aalst, W.M.P., de Beer, H.T., van Dongen, B.F.: Process mining and verification of properties: An approach based on temporal logic. In: Proc. of OTM Confederated Intl Conferences. pp. 130--147 (2005) Google ScholarDigital Library
- Balan, E., Milo, T., Sterenzy, T.: BP-Ex: a uniform query engine for business process execution traces. In: Proc. of EDBT. pp. 713--716 (2010) Google ScholarDigital Library
- Beheshti, S., Benatallah, B., Nezhad, H.R.M., Sakr, S.: A query language for analyzing business processes execution. In: Business Process Management, BPM. pp. 281--297 (2011) Google ScholarDigital Library
- Casati, F., Castellanos, M., Dayal, U., Salazar, N.: A generic solution for warehousing business process data. In: Proc. of VLDB. pp. 1128--1137 (2007) Google ScholarDigital Library
- Deutch, D., Milo, T.: A quest for beauty and wealth (or, business processes for database researchers). In: Proceedings of the Thirtieth ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems. pp. 1--12. PODS '11 (2011) Google ScholarDigital Library
- Deutch, D., Milo, T.: Type inference and type checking for queries over execution traces. The VLDB Journal 21(1), 51--68 (2012) Google ScholarDigital Library
- Fazzinga, B., Flesca, S., Furfaro, F., Masciari, E., Pontieri, L., Pulice, C.: A framework supporting the analysis of process logs stored in either relational or nosql dbmss. In: Foundations of Intelligent Systems - 22nd International Symposium, ISMIS 2015. pp. 52--58 (2015)Google Scholar
- Gao, X.: Towards the next generation intelligent bpm âĂŞ in the era of big data. In: Business Process Management. pp. 4--9 (2013) Google ScholarDigital Library
- Gentili, E., Milani, A., Poggioni, V.: Data summarization model for user action log files. In: Proc. of ICCSA. pp. 539--549 (2012) Google ScholarDigital Library
- Geppert, A., Tombros, D.: Logging and post-mortem analysis of workow executions based on event histories. In: Proc. of Conf. RIDS. pp. 67--82 (1997) Google ScholarDigital Library
- Grigori, D., Casati, F., Castellanos, M., Dayal, U., Sayal, M., Shan, M.C.: Business process intelligence. Comput. Ind. 53(3), 321--343 (Apr 2004) Google ScholarDigital Library
- Lee, C., Chung, C.: Efficient storage scheme and query processing for supply chain management using rfid. In: SIGMOD. pp. 291--302 (2008) Google ScholarDigital Library
- Masciari, E.: An end to end framework for building data cubes over trajectory data streams. Journal of Intelligent Information Systems (2015) Google ScholarDigital Library
- Momotko, M., Subieta, K.: Process query language: A way to make workow processes more flexible. In: Advances in Databases and Information Systems, ADBIS. pp. 306--321 (2004)Google Scholar
- Rogge-Solti, A., van der Aalst, W.M.P., Weske, M.: Discovering stochastic Petri nets with arbitrary delay distributions from event logs. In: Proc. of BPM Workshops. pp. 15--27 (2013)Google Scholar
- Schiefer, J., List, B., Bruckner, R.M.: Process data store: A real-time data store for monitoring business processes. In: Proc. of DEXA. pp. 760--770 (2003)Google ScholarCross Ref
- Wang, S., Lv, C., Wen, L., Wang, J.: Managing massive business process models and instances with process space. In: Proc. of the BPM Demo Sessions. p. 91 (2014)Google Scholar
- Wu, X., Lee, M., Hsu, W.: A prime number labeling scheme for dynamic ordered XML trees. In: Proc. of the 20th International Conference on Data Engineering, ICDE. pp. 66--78 (2004) Google ScholarDigital Library
- How, Who and When: Enhancing Business Process Warehouses By Graph Based Queries
Recommendations
Vishleshan: Performance Comparison and Programming Process Mining Algorithms in Graph-Oriented and Relational Database Query Languages
IDEAS '15: Proceedings of the 19th International Database Engineering & Applications SymposiumProcess-Aware Information System (PAIS) are IT systems that manages, supports business processes and generate large event logs from execution of business processes. Process Mining consists of analyzing event logs generated by PAISs and discover business ...
Answering "Why Empty?" and "Why So Many?" queries in graph databases
Graph databases provide schema-flexible storage and support complex, expressive queries. However, the flexibility and expressiveness in these queries come at additional costs: queries can result in unexpected empty answers or too many answers, which are ...
Schema mappings and data exchange for graph databases
ICDT '13: Proceedings of the 16th International Conference on Database TheoryData exchange and schema mapping management have received little attention so far in the graph database scenario, and tools developed in this context for relational databases have significant drawbacks in the context of graph-structured data. In this ...
Comments