An Approach for a Mutual Integration of the Web of Things with Business Processes View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2013

AUTHORS

Andreas Ruppen , Sonja Meyer

ABSTRACT

The vision of a multitude of heterogeneous, connected devices interacting with parts of its physical environment, known as the Internet of Things (IoT), has gained momentum over the last years. For traditional business information systems the integration of the IoT leads to the emergence of new value-added business processes that make use of its representative devices such as RFID, sensors and actuators, as entirely new resources. One promising approach in the IoT domain is a real-world service integration method based on Representational State Transfer (REST) principles expedited by the initiative Web of Things (WoT). The connection of classical Enterprise Resource Planning (ERP) systems commonly based on service oriented architectures coming with heavy-weight services and the resource oriented WoT coming with RESTful services for its limited devices is still a complex problem on both sides. In this paper, we propose a bi-directional integration approach of current Business Process Management (BPM)-based ERP systems and the WoT to provide a foundation to connect and analyze legacy systems as well as Future Internet applications. By following a three phase BPM-lifecycle, we investigate how the process metamodel of the industry standard Business Process Model and Notation (BPMN) can cover WoT specific components. Reversely, we examine how existing and useful business process information can be seamlessly included into the WoT respecting its essential architecture and applying a component-based approach. More... »

PAGES

42-56

Book

TITLE

Enterprise and Organizational Modeling and Simulation

ISBN

978-3-642-41637-8
978-3-642-41638-5

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-41638-5_3

DOI

http://dx.doi.org/10.1007/978-3-642-41638-5_3

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1000331372


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