Business Process as a Service (BPaaS): The Smart BPaaS Design Environment
2016, Woitsch, Robert, Hinkelmann, Knut, Juan Ferrer, Ana Maria, Yuste, Joaquin Iranzo, Karagiannis, Dimitris, Schlamberger, Niko
This paper introduces the project idea of Business Processes as a Services (BPaaS) that is worked out in the H2020 project CloudSocket. Concept models and semantics are used to align domain specific business processes with executable workflows that are deployed and in production in a multi-cloud environment. The Business Process Management System Paradigm (BPMS) is requesting the functional capabilities of the so-called BPaaS Environments (i) design, (ii) allocation, (iii) execution and (iv) evaluation, which technically compose the CloudSocket Broker platform. This paper introduces first findings of aligning customers’ business needs with BPaaS cloud offerings using a model-based approach.
A Modelling Environment for Business Process as a Service
2016, Kurjakovic, Sabrina, Lammel, Benjamin, Woitsch, Robert, Kritikos, Kyriakos, Hinkelmann, Knut, Krogstie, John, Mouratidis, Haralambos, Su, Jianwen
Business processes can benefit from cloud offerings, but bridging the gap between business requirements and technical solutions is still a big challenge. We propose Business Process as a Service (BPaaS) as a main concept for the alignment of business process with IT in the cloud. The mechanisms described in this paper provide modelling facilities for both business and IT levels: (a) a graphical modelling environment for processes, workflows and service requirements, (b) an extension of an enterprise ontology with cloud-specific concepts, (c) semantic lifting of graphical models and (d) SPARQL querying and inferencing for semantic alignment of business and cloud IT.
A viewpoint-based case-based reasoning approach utilising an enterprise architecture ontology for experience management
2016-03-28, Martin, Andreas, Emmenegger, Sandro, Hinkelmann, Knut, Thönssen, Barbara
The accessibility of project knowledge obtained from experiences is an important and crucial issue in enterprises. This information need about project knowledge can be different from one person to another depending on the different roles he or she has. Therefore, a new ontology-based case-based reasoning (OBCBR) approach that utilises an enterprise ontology is introduced in this article to improve the accessibility of this project knowledge. Utilising an enterprise ontology improves the case-based reasoning (CBR) system through the systematic inclusion of enterprise-specific knowledge. This enterprise-specific knowledge is captured using the overall structure given by the enterprise ontology named ArchiMEO, which is a partial ontological realisation of the enterprise architecture framework (EAF) ArchiMate. This ontological representation, containing historical cases and specific enterprise domain knowledge, is applied in a new OBCBR approach. To support the different information needs of different stakeholders, this OBCBR approach has been built in such a way that different views, viewpoints, concerns and stakeholders can be considered. This is realised using a case viewpoint model derived from the ISO/IEC/IEEE 42010 standard. The introduced approach was implemented as a demonstrator and evaluated using an application case that has been elicited from a business partner in the Swiss research project.
Workplace Learning - Providing Recommendations of Experts and Learning Resources in a Context-sensitive and Personalized Manner
2016, Emmenegger, Sandro, Laurenzi, Emanuele, Thönssen, Barbara, Zhang Sprenger, Congyu, Hinkelmann, Knut, Witschel, Hans Friedrich
Support of workplace learning is increasingly important as change in every form determines today's working world in industry and public administrations alike. Adapt quickly to a new job, a new task or a new team is a major challenge that must be dealt with ever faster. Workplace learning differs significantly from school learning as it should be strictly aligned to business goals. In our approach we support workplace learning by providing recommendations of experts and learning resources in a context-sensitive and personalized manner. We utilize user s' workplace environment, we consider their learning preferences and zone of proximal development, and compare required and acquired competencies in order to issue the best suited recommendations. Our approach is part of the European funded project Learn PAd. Applied research method is Design Science Research. Evaluation is done in an iterative process. The recommender system introduced here is evaluated theoretically based on user requirements and practically in an early evaluation process conducted by the Learn PAd application partner.
Run-Time Planning of Case-based Business Processes
2016, Hinkelmann, Knut, Sprovieri, Danillo, Diaz, Daniel, Mazo, Raul, Espana, Sergio, Ralyte, Jolita, Souveyet, Carine
Organizations act in highly competitive markets, which forces them to be flexible. Constantly changing business requirements require flexible business processes. Case Management Model and Notation (CMMN) supports modeling run-time flexibility of partially structured business process models, but does not fully specify the control flow. Objective: The goal is to develop a planning algorithm that supports the case worker in planning case-based business processes at run-time. Method: We identify the requirements of run-time planning of partly structured processes by analyzing the admission process for the master degree at FHNW. To plan the process instance, we develop a planning algorithm. Our planning algorithm is evaluated using concrete cases provided by FHNW in order to demonstrate real application. Results: The planning algorithm reflects the requirements for serializing tasks at run-time. Conclusion: Our planning algorithm allows to automatically deriving context-specific execution plans for CMMN models at run-time.
KPIs 4 Workplace Learning
2016, Emmenegger, Sandro, Thönssen, Barbara, Hinkelmann, Knut, Witschel, Hans Friedrich, Ana, Fred, Aveiro, David
Enterprises and Public Administrations alike need to ensure that newly hired employees are able to learn the ropes fast. Employers also need to support continuous workplace learning. Work-place learning should be strongly related to business goals and thus, learning goals should direct-ly add to business goals. To measure achievement of both learning and business goals we pro-pose augmented Key Performance Indicators (KPI). In our research we applied model driven engineering. Hence we developed a model for a Learning Scorecard comprising of business and learning goals and their KPIs represented in an ontology. KPI performance values and scores are calculated with formal rules based on the SPARQL Inferencing Notation. Results are presented in a dashboard on an individual level as well as on a team/group level. Requirements, goals and KPIs as well as performance measurement were defined in close co-operation with Marche Region, business partner in Learn PAd.