Schema Evolution in Process Management Systems

Continuously arising new trends in information technology and developments at the (e-business) market let companies crave for automated business process support. Process management systems offer the promising possibility to (electronically) define, control, and monitor business processes. However, if this technology shall be applicable in practice it must be possible to change running business processes even at runtime. Basically, such process changes can take place at two levels - the process type level and the process instance level. If a process type is modified a new version of the respective process type schema is created. Then, at minimum, the process instances running according to the old process type schema version must be able to finish without being disturbed. However, this simple versioning approach is only sufficient for short-running business processes. For long-running ones like, for example, car leasing contracts or medical treatment processes which may last from 3 up to 5 years, it must be possible to apply the process type changes to the collection of running process instances as well, but without causing inconsistencies or errors in the sequel. Apart from process schema evolution and change propagation a flexible process management system must also enable instance-specific (ad-hoc) changes, for example, if exceptional situations occur. If then a process type change takes place the challenging question arises how to adequately deal with the interplay of process type and process instance changes

Change Support in Process-Aware Information Systems - A Pattern-Based Analysis

In today's dynamic business world the economic success of an enterprise increasingly depends on its ability to react to changes in its environment in a quick and flexible way. Process-aware information systems (PAIS) offer promising perspectives in this respect and are increasingly employed for operationally supporting business processes. To provide effective business process support, flexible PAIS are needed which do not freeze existing business processes, but allow for loosely specified processes, which can be detailed during run-time. In addition, PAIS should enable authorized users to flexibly deviate from the predefined processes if required (e.g., by allowing them to dynamically add, delete, or move process activities) and to evolve business processes over time. At the same time PAIS must ensure consistency and robustness. The emergence of different process support paradigms and the lack of methods for comparing existing change approaches have made it difficult for PAIS engineers to choose the adequate technology. In this paper we suggest a set of changes patterns and change support features to foster the systematic comparison of existing process management technology with respect to process change support. Based on these change patterns and features, we provide a detailed analysis and evaluation of selected systems from both academia and industry. The identified change patterns and change support features facilitate the comparison of change support frameworks, and consequently will support PAIS engineers in selecting the right technology for realizing flexible PAIS. In addition, this work can be used as a reference for implementing more flexible PAIS

ADEPT - Next Generation Process Management Technology

In the ADEPT project we have been working on the design and implementation of a next generation process management technology for several years. Based on a conceptual framework for dynamic process changes, on innovative process support functions, and on advanced implementation concepts, the developed system enables the realization of adaptive, process-aware information systems (PAIS). Basically, process changes can take place at the process type as well as the process instance level: Changes of single process instances may have to be carried out in an ad-hoc manner (e.g., to deal with an exceptional situation) and must not affect system robustness and consistency. Process type changes, in turn, must be quickly accomplished in order to adapt the PAIS to business process changes. This may also include the migration of (thousands of) instances to the new process schema (if desired). Important requirements are to perform respective migrations on-the-fly, to preserve correctness, and to avoid performance penalties

Designing Traceability into Big Data Systems

Providing an appropriate level of accessibility and traceability to data or process elements (so-called Items) in large volumes of data, often Cloud-resident, is an essential requirement in the Big Data era. Enterprise-wide data systems need to be designed from the outset to support usage of such Items across the spectrum of business use rather than from any specific application view. The design philosophy advocated in this paper is to drive the design process using a so-called description-driven approach which enriches models with meta-data and description and focuses the design process on Item re-use, thereby promoting traceability. Details are given of the description-driven design of big data systems at CERN, in health informatics and in business process management. Evidence is presented that the approach leads to design simplicity and consequent ease of management thanks to loose typing and the adoption of a unified approach to Item management and usage.Comment: 10 pages; 6 figures in Proceedings of the 5th Annual International Conference on ICT: Big Data, Cloud and Security (ICT-BDCS 2015), Singapore July 2015. arXiv admin note: text overlap with arXiv:1402.5764, arXiv:1402.575

Evolving NoSQL Databases Without Downtime

NoSQL databases like Redis, Cassandra, and MongoDB are increasingly popular because they are flexible, lightweight, and easy to work with. Applications that use these databases will evolve over time, sometimes necessitating (or preferring) a change to the format or organization of the data. The problem we address in this paper is: How can we support the evolution of high-availability applications and their NoSQL data online, without excessive delays or interruptions, even in the presence of backward-incompatible data format changes? We present KVolve, an extension to the popular Redis NoSQL database, as a solution to this problem. KVolve permits a developer to submit an upgrade specification that defines how to transform existing data to the newest version. This transformation is applied lazily as applications interact with the database, thus avoiding long pause times. We demonstrate that KVolve is expressive enough to support substantial practical updates, including format changes to RedisFS, a Redis-backed file system, while imposing essentially no overhead in general use and minimal pause times during updates.Comment: Update to writing/structur