ABSTRACT：

The ability to quickly respond to change is critical to many organizations for a variety of reasons: staying competitive in the marketplace, legal compliance, device and IT upgrades, re-organization, etc. Therefore the underlying business processes (BPs) must be able to deal with uncertainty, exceptional situations, and environmental changes. Runtime process flexibility is required when execution decisions have to be made at runtime, or detailed specifications of some tasks cannot be fully defined at design time, or when business rules or policies change. The real challenge in managing BP changes is to provide a systematic and integrated support for the BP designer to specify how a BP would react to various run-time changes and for the BP to evolve gracefully in a controlled, incremental, and predictable manner. In this talk we will examine the core issues involved in BP change management and the technical solutions available currently and the potential new technical solutions ahead.

BIOGRAPHY:

Dr. Jian Yang is a full professor at Department of Computing, Macquarie University. She received her PhD from The Australian National University in 1995. Before she joined Macquarie University, she worked as an associate professor at Tilburg University, Netherlands (2000-2003), a senior research scientist at the Division of Mathematical and Information Science, CSIRO, Australia (1998-2000), and as an assistant professor at The Australian Defence Force Academy, University of New South Wales (1993-1998). Dr. Yang has published about 200 papers in the international journals and conferences such as IEEE transactions, Information Systems, Data & Knowledge Engineering, CACM, VLDB, ICDCS, CAiSE, CoopIS, CIKM, etc. She is the co-founder of the International Conference on Service Oriented Computing and now serving as a steering committee member. She has served as program committee co-chairs and general chair of in various international conferences. She is also a regular reviewer for journals such as IEEE Transactions on Knowledge & Data Engineering, Data & Knowledge Engineering, VLDB Journal, IEEE Internet Computing, etc.

Her main research interests are: web service technology; business process management; interoperability, trust and security issues in digital libraries and e-commerce; social network.

ABSTRACT：

Formal modeling is one of the most important research practices of computer scientists. This talk tries to explain why we need it and how to do it. A three steps methodology is introduced here. The steps are Abstraction, Representation and Method respectively, and thus it is named ARM. Two examples are used for illustration: BPM as a whole and insurance claim in particular. ARM has led to all our research achievements ever since it became mature, including what was introduced in our paper titled “A Three layer model for business processes – process logic, case semantics and workflow management”.

BIOGRAPHY:

袁崇义教授 1964年南京大学数学系毕业，入中科院数学所为研究生。1975年开始计算机软件领域的研究工作。1992年调入北大计算机系，教授，博导。2005年退休。

在科学院数学所期间，1977年至1979年先后在加拿大多伦多大学与滑铁卢大学进修计算机•软件两年余。1984年至1990年在德国（波恩）数学研究院（GMD）访问4次共3年余。访问期间在Carl Adam Petri 的研究所学习Petri网。1989年至2013年期间共出版4本Petri网专著，包括2005年电子工业出版社的《Petri网原理与应用》及2013年科学出版社的《Petri网应用》。主要论文有软件学报英文版2007年< A three layer model for business process -- process logic, case semantics and workflow management > 及近几年关于程序语言及形式语义(OESPA)的若干文章。

ABSTRACT：

Both database management (DBM) and business process management (BPM) are critical for an organization. How to make these two types of management systems work more closely is important yet challenging. In the past, the community of DBM has made impact on BPM, e.g., transactional workflows, process evolution and versioning, view mechanism, and resource management. However, all these functions are provided at the process level, not at the data level in traditional activity-centric BPM systems, where data is treated as a second-class citizen. In an artifact-centric BPM model, business artifacts become first-class citizen and their supports from DBM are improved. Nevertheless, the gap between BPM and DBM still exists. In the BigData era, how to effectively and efficiently manage and process complex, diversified, dynamic and large volume of business data becomes even more challenging and the closer collaboration between DBM and BPM will need to further investigated.

BIOGRAPHY:

Dr. Chengfei Liu is a full professor at the Department of Computer Science and Software Engineering, Faculty of Science, Engineering and Technology, Swinburne University of Technology, Australia. He is the leader of Web and Data Engineering research group and the focus area leader of Knowledge and Data Intensive Systems in the Swinburne University tier-1 Centre for Computing and Engineering Software Systems (SUCCESS). Prior to joining Swinburne, he taught at the University of South Australia and the University of Technology Sydney, and was a Research Scientist at Cooperative Research Centre for Distributed Systems Technology (DSTC), Australia. He also held visiting positions at the Chinese University of Hong Kong, the University of Aizu in Japan, and IBM Silicon Valley Lab in USA. His current research interests include keyword search over structured data, query processing and refinement, XML and RDF databases, graph data management, community discovery, big data management, workflow management, web services, and advanced transaction management. He has published 180 peer-reviewed papers in various journals and conference proceedings and has served in over 100 organizing committees and program committees in international conferences/workshops in the areas of databases and business process management. He has received 4M research fund in the past 10 years, including 8 ARC (Australia Research Council) grants in the areas of database and business process management. He was the recipient of the 2007 Vice-Chancellor's Award for Research Excellence at Swinburne University of Technology.