Automatic support for product based workflow design : generation of process models from a product data model

Product Based Workflow Design (PBWD) is one of the few scientific methodologies for the (re)design of workflow processes. It is based on an analysis of the product that is produced in the workflow process and derives a process model from the product structure. Until now this derivation has been a manual task and is therefore a time-consuming and error-prone exercise. Automatic support would enhance the use of the PBWD methodology. In this paper we propose several algorithms to automatically generate process models from a product structure and we present a software tool (implemented in ProM) to support this. Finally, the properties of the resulting process models are analysed and discussed

Understanding Business Process Quality

Abstract Organizations have taken benefit from quality management prac-tices in manufacturing and logistics with respect to competitiveness as well as profitability. At the same time, an ever-growing share of the organizational value chain centers around transactional administrative processes addressed by business process management concepts, e.g. in finance and accounting. Integrating these fields is thus very promising from a management perspec-tive. Obtaining a clear understanding of business process quality constitutes the most important prerequisite in this respect. However, related approaches have not yet provided an effective solution to this issue. In this chapter, we consider effectiveness requirements towards business process quality concepts from a management perspective, compare existing approaches from various fields, deduct a definition framework from organizational targets, and take initial steps towards practical adoption. These steps provide fundamental in-sights into business process quality, and contribute to obtain a clear grasp of what constitutes a good business process.

Open data from the third observing run of LIGO, Virgo, KAGRA, and GEO

The global network of gravitational-wave observatories now includes five detectors, namely LIGO Hanford, LIGO Livingston, Virgo, KAGRA, and GEO 600. These detectors collected data during their third observing run, O3, composed of three phases: O3a starting in 2019 April and lasting six months, O3b starting in 2019 November and lasting five months, and O3GK starting in 2020 April and lasting two weeks. In this paper we describe these data and various other science products that can be freely accessed through the Gravitational Wave Open Science Center at https://gwosc.org. The main data set, consisting of the gravitational-wave strain time series that contains the astrophysical signals, is released together with supporting data useful for their analysis and documentation, tutorials, as well as analysis software packages