Data-Driven Process Discovery and Analysis (Lecture Notes in Business Information Processing)

✍ Scribed by Paolo Ceravolo (editor), Maurice van Keulen (editor), María Teresa Gómez-López (editor)

• Publisher: Springer
• Year: 2020
• Tongue: English
• Leaves: 134
• Category: Library

✦ Synopsis

This book constitutes revised selected papers from the 8^th and 9^th IFIP WG 2.6 International Symposium on Data-Driven Process Discovery and Analysis, SIMPDA 2018, held in Seville, Spain, on December 13–14, 2018, and SIMPDA 2019, held in Bled, Slovenia, on September 8, 2019.

From 16 submissions received for SIMPDA 2018 and 9 submissions received for SIMPDA 2019, 3 papers each were carefully reviewed and selected for presentation in this volume. They cover theoretical issues related to process representation, discovery, and analysis or provide practical and operational examples of their application.

✦ Table of Contents

Preface
Organization
Contents
Designing Process-Centric Blockchain-Based Architectures: A Case Study in e-voting as a Service
Abstract
1 Introduction
2 Related Work
3 End to End Verifiability and Trust in HyperVote
4 HyperVote Process Centric Architecture
4.1 Vote Service Configurator (VSC)
4.2 Chaincode Catalogue (CC)
4.3 Hyperledger Configurator (HC)
4.4 Cloud Service Catalogue (CSC)
4.5 Cloud Deployer Orchestrator (CDO)
4.6 Match-Making Engine (MME)
4.7 Business Process Logs and Analytics
5 HyperVote Evaluation
6 Conclusion
References
Extracting Multiple Viewpoint Models from Relational Databases
1 Introduction
2 Related Work
2.1 Related Work: Extracting Event Data from Databases
2.2 Related Work: Representation of Artifact-Centric Models
2.3 Related Work: Discovery of Process Models Using Several Case Notions
3 Database Event Logs
4 Approach to Obtain MVP Models
5 Viewpoints: Retrieval of DFGs and Logs
5.1 Projection on a Directly-Follows Graph
5.2 Projection on a Log
6 Tool
7 Assessment
7.1 Comparison with Related Approaches
7.2 Evaluation of the Execution Time
7.3 Usability of the Approaches
7.4 Scalability of the Approach
7.5 Evaluation Using CRM Data
8 Conclusion
References
Standardizing Process-Data Exploitation by Means of a Process-Instance Metamodel
1 Introduction
2 Approach Overview and Contributions
2.1 Data Production Viewpoint
2.2 Data Consumption Viewpoint
3 Case Study
4 Process Instance Metamodel
4.1 Mapping the Metamodel and the Case Study Models
5 Proof of Concept Implementation
6 Related Work
6.1 Approaches that Consume Data for Reasoning
6.2 Approaches that Consume Data for Querying
6.3 Approaches that Consume Data for the Creation of Execution Traces
7 Conclusions and Further Work
References
Exploiting Event Log Event Attributes in RNN Based Prediction
1 Introduction
2 Related Work
3 Problem
4 Solution
4.1 Event Attributes
4.2 Formal Problem Definition
5 Test Framework
5.1 Training
5.2 Testing
6 Test Setup
7 Experiments
7.1 Threats to Validity
8 Conclusions
References
General Model for Tracking Manufacturing Products Using Graph Databases
1 Introduction
2 State-of-the-art
3 General Model for Tracking Manufacturing Products Using Graph Databases
3.1 Notation
3.2 Implementation
3.3 Use Cases
4 Discussion
5 Conclusions and Future Work
References
Supporting Confidentiality in Process Mining Using Abstraction and Encryption
1 Introduction
2 Related Work
3 Background
3.1 Process Mining
3.2 Discovering Social Networks
3.3 Cryptography
4 Problem Definition (Attack Analysis)
5 Approach
5.1 Internal Confidentiality Solution (ICS)
5.2 External Confidentiality Solution (ECS)
6 Evaluation
6.1 Correctness of the Approach
6.2 Performance
7 Conclusions
References
Author Index