Program
14:00 - 14:15 |
Welcome |
14:15 - 15:00 |
Keynote: Process in the Large - From Enterprise Process Wikis to Crowdsourced Process Designs |
15:00 - 15:30 |
A Framework for Business Process Model Repositories |
15:30 - 16:00 |
Coffee Break |
16:00 - 16:30 |
Metric Trees for Efficient Similarity Search in Large Process Model Repositories |
16:30 - 17:00 |
Process Model Analysis using Related Cluster Pairs |
17:00 - 17:30 |
Closing discussion: Process in the Large - Status and Future Work |
Abstracts
Keynote: Process in the Large - From Enterprise Process Wikis to Crowdsourced Process Designs
Michael zur Muehlen
A Framework for Business Process Model Repositories
Zhiqiang Yan and Paul Grefen
Large organizations often run hundreds or even thousands of business processes. Managing such large collections of business processes is a challenging task. Intelligent software can assist in that task by providing common repository functions such as storage, search and version management. They can also provide advanced functions that are specific for managing collections of process models, such as managing the consistency of public and private processes and extracting knowledge from existing processes to better design new processes. This paper, by analyzing existing business process model repositories, proposes a framework for repositories that assist in managing large collections of business process models. The framework consists of a management model and a reference architecture. The management model lists the functionality that can be provided by business process model repositories. The reference architecture presents the components that provide this functionality and their interconnections. The framework provides a reference model for analysis and extension of existing repositories and design of new repositories.
Metric Trees for Efficient Similarity Search in Large Process Model Repositories
Matthias Kunze and Mathias Weske
Due to the increasing adoption of business process management and the key role of process models, companies are setting up and maintaining large process model repositories. Repositories containing hundreds or thousands of process models are not uncommon, whereas only simplistic search functionality, such as text based search or folder navigation, is provided, today. On the other hand, advanced methods have recently been proposed in the literature to ascertain the similarity of process models. However, due to performance reasons, an exhaustive similarity search by pairwise comparison is not feasible in large process model repositories. This paper presents an indexing approach based on metric trees, a hierarchical search structure that saves comparison operations during search with nothing but a distance function at hand. A detailed investigation of this approach is provided along with a quantitative evaluation thereof, showing its suitability and scalability in large process model repositories.
Process Model Analysis using Related Cluster Pairs
Michael Niemann, Melanie Siebenhaar, Julian Eckert and Ralf Steinmetz
Due to changing market conditions and resulting exibility requirements, the reference-conform implementation of processes in companies increasingly gains importance. The internal assessment of the realisation of reference processes (process conformance) is a resourceintensive task in terms of time and cost. The paper at hand presents a process model analysis method to address this issue using a combined structural and semantic comparison and analysis approach. The method provides decision support for process analysts concerning the adjustment of processes to reference processes in IT Governance contexts.