This book constitutes the refereed proceedings of the 31st International Conference on Advanced Information Systems Engineering, CAiSE 2019, held in Rome, Italy, in June 2019. The 41 full papers presented in this volume were carefully reviewed and selected from 206 submissions. The book also contains one invited talk in full paper length.
The papers were organized in topical sections named: information system engineering; requirements and modeling; data modeling and analysis; business process modeling and engineering; information system security; and learning and mining in information systems.
Abstracts on the CAiSE 2019 tutorials can be found in the back matter of the volume.

Inhalt
Invited Talk.- Direct and reverse rewriting in data interoperability.- Information System Engineering.- Efficient Engineering Data Exchange in Multi-Disciplinary Systems Engineering Enterprises.- Bing-CF-IDF+: A Semantics-Driven News Recommender System.- Methodological Framework to Guide the Development of Continual Evolution Methods.- Inter-organizational integration in the AEC/FM industry: Exploring the "addressed" and "unaddressed" information exchange needs between stakeholders.- A Lightweight Framework for Multi-Device Integration and Multi-Sensor Fusion to Explore Driver Distraction.- Exhaustive Simulation and Test Generation Using fUML Activity Diagrams.- A Block-Free Distributed Ledger for P2P Energy Trading: Case with IOTA.- Profile Reconciliation through Dynamic Activities across Social Networks.- Requirements and Modeling.- Towards an Ontology-based Approach for Eliciting Possible Solutions to Non-Functional Requirements.- Using a Modelling Language to Describe the Quality of Life Goals of People Living with Dementia.- Multi-Platform Chatbot Modeling and Deployment with the Jarvis Framework.- Information Systems Modeling: Language, Verification, and Tool Support.- Expert2Vec: Experts Representation in Community Question Answering for Question Routing.- A Pattern Language for Value Modeling in ArchiMate.- Paving Ontological Foundation for Social Engineering Analysis.- Improving Traceability Links Recovery in Process Models through an Ontological Expansion of Requirements.- Requirements Engineering for Cyber Physical Production Systems.- Data modeling and Analysis.- A Fourth Normal Form for Uncertain Data.- Revealing the Conceptual Schemas of RDF Datasets.- Modeling and In-Database Management of Relational, Data-Aware Processes.- D2IA: Stream Analytics on User-Defined Event Intervals.- Business Process Modeling and Engineering.- Extracting Declarative Process Models from Natural Language.- From Process Models to Chatbots.- Dynamic Role Binding in Blockchain-Based Collaborative Business Processes.- 3D virtual world BPM training systems: process gateway experimental results.- Deriving and Combining Mixed Graphs from Regulatory Documents Based on Constraint Relations.- A Method to Improve the Early Stages of the Robotic Process Automation Lifecycle.- Generation and Transformation of Compliant Process Collaboration Models to BPMN.- GameOfFlows: Process Instance Adaptation in Complex, Dynamic and Potentially Adversarial Domains.- Information System Security.- Security Vulnerability Information Service with Natural Language Query Support.- Automated Interpretation and Integration of Security Tools Using Semantic Knowledge.- An Assessment Model for Continuous Security Compliance in Large Scale Agile Environments.- Learning and Mining in Information Systems.- Proactive Process Adaptation using Deep Learning Ensembles.- Using Machine Learning Techniques for Evaluating the Similarity of Enterprise Architecture Models.- Efficient Discovery of Compact Maximal Behavioral Patterns from Event Logs.- Discovering Responsibilities with Dynamic Condition Response Graphs.- Fifty Shades of Green: How Informative is a Compliant Process Trace.- Solution Patterns for Machine Learning.- Managing and Simplifying Cognitive Business Operations using Process Architecture Models.- A Constraint Mining Approach to Support Monitoring Cyber-Physical Systems.- Behavior-Derived Variability Analysis: Mining Views for Comparison and Evaluation.