A Semantically-Enhanced Modelling Environment for Business Process as a Service

Abstract

In this paper we present a hybrid modeling approach which supports the continuous alignment of business and IT in the cloud. Business Process as a Service provides the end-to-end cloud support for business processes instead of single applications. A graphical modelling environment allows nontechnical modelers to design business processes and to specify requirements in human-interpretable way. Via semantic lifting, the graphical models can be annotated with classes and values from an enterprise ontology. The BPaaS Ontology contains the relevant classes for the smart Business and IT-Cloud alignment. It supports the modeler in using a standard terminology and thus ensures consistent modeling.

Towards an Agile and Ontology-Aided Modeling Environment for DSML Adaptation

“…The adaptation of a modeling language can be done by applying a set of operators on the Language Ontology. In order to determine an initial set of operators, we build on lessons learned from the work of recent research projects, Patient-Radar [6,26] and CloudSocket 5 [27,28]. Thus, the following set of operators were derived to be performed on the Language Ontology, which implies a theoretical foundation based on ontology formalism.…”

Towards Business-to-IT Alignment in the Cloud

“…Models abstract away from complex realities and become fit to their purpose, i.e., to precisely model the respective intended domain. In [13] we already adopted a model-driven approach where an extension of BPMN 2.0 allows modeling both business process requirements in a business language and workflows/cloud services in a technical language. The approach includes the translation of the business language into the technical one enabling the comparison between process requirements and workflow/cloud service specifications.…”

“…Semantic Lifting shifts the purpose of modelling beyond transparency and communication [14]. The interpretable knowledge base (i.e., ontology) allows for automation on models [13]. For example, in [8] it is described an ontologybased early warning system for automating the assessment of supply chain risks, while in [7] ontologies are combined with a case-based reasoning approach to automate the support on workplace learning.…”

“…Benefits of domain-specific conceptualizations are well established within the modeling community [25] [17] [10]. Secondly, this work builds upon the findings in [13] but adopts a different perspective of Business-to-IT alignment in the Cloud. Namely, there is a shift from the language translation to the mapping of values between requirements and specifications on both the business and IT dimensions, separately.…”

“…The Business Matchmaker allows specifying requirements in a more user centric approach than the one in [13]. It relies on a context-adaptive questionnaire that guides the user via a set of questions that reflect BP functional and nonfunctional requirements.…”