Synopsis
While classic data management focuses on the data itself, research on Business Processes also considers the context in which this data is generated and manipulated, namely the processes, users, and goals that this data serves. This provides the analysts a better perspective of the organizational needs centered around the data. As such, this research is of fundamental importance. Much of the success of database systems in the last decade is due to the beauty and elegance of the relational model and its declarative query languages, combined with a rich spectrum of underlying evaluation and optimization techniques, and efficient implementations. Much like the case for traditional database research, elegant modeling and rich underlying technology are likely to be highly beneficiary for the Business Process owners and their users; both can benefit from easy formulation and analysis of the processes. While there have been many important advances in this research in recent years, there is still much to be desired: specifically, there have been many works that focus on the processes behavior (flow), and many that focus on its data, but only very few works have dealt with both the state-of-the-art in a database approach to Business Process modeling and analysis, the progress towards a holistic flow-and-data framework for these tasks, and highlight the current gaps and research directions. Table of Contents: Introduction / Modeling / Querying Business Processes / Other Issues / Conclusion
About the Author
Tova Milo received her Ph.D. degree in Computer Science from the Hebrew University, Jerusalem, in 1992. After graduating she worked at the INRIA research institute in Paris and at University of Toronto and returned to Israel in 1995, joining the School of Computer Science at Tel Aviv university where she is now a full Professor and Department head. Her research focuses on advanced database applications such as data integration, XML and semi-structured information, Web-based applications and Business Processes, studying both theoretical and practical aspects. Tova served as the Program Chair of several international conferences, including PODS, ICDT, VLDB, XSym, and WebDB. She is a member of the VLDB Endowment and the ICDT executive board and is an editor of TODS, the VLDB Journal, and the Logical Methods in Computer Science Journal. She has received grants from the Israel Science Foundation, the US-Israel Binational Science Foundation, the Israeli and French Ministry of Science, and the European Union. She is a recipient of the 2010 ACM PODS Alberto O. Mendelzon Test-of-Time Award and of the prestigious EU ERC Advanced Investigators grant. Daniel Deutch is an Assistant Professor in the Computer Science Department of Ben Gurion University. He received his Ph.D. in Computer Science from Tel Aviv University in 2010 and was a Postdoc at the University of Pennsylvania (UPenn), and at the INRIA research institute. His research interests include, among other areas, web data management, data provenance, and inference in database systems. During his Ph.D. studies, Daniel received a number of awards for his research, including the Israeli Ministry of Science Eshkol grant and ICDT best student paper award. Daniel has been a member of the program committee of various international conferences and workshops (including WWW, ICDT, PODS). Daniel’s research is funded by grants from the US-Israel Binational Science Foundation and the Israeli Ministry of Science.
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