Semantic Policies for Modeling Regulatory Process Compliance

Business process management (BPM) as a paradigm for enterprise planning and governance is nowadays a core discipline of information systems management. Growing up from the first process re-engineering initiatives in the 1980’s, BPM technologies now seek to span all of the organizational silos of enterprises, and also expand vertically from the strategy layers where visions and goals are defined to the lower data transaction layers. Ensuring the compliance of processes to the guidance and control provided to the business by regulations is an obligation to every enterprise. In this work, we motivate the need for automation in compliance management and propose the use of policies as a modeling concept for regulations. We introduce the CASE model for structuring regulatory compliance requirements as policies. Policies shall allow to model regulations at abstraction levels adequate to implementing platform independent mechanisms for policy verification. We describe the CASE model and explain how it can be used to structure and model policies extracted from regulations. This chapter also defines a policy modeling ontology that we propose as a language for formally modeling CASE policies. The basic CASE model and the corresponding policy modeling ontology support compliance of enterprise processes to regulations by enabling automation to compliance checking (verification). The utilization of the CASE method as well as the policy ontology is showcased using an example of resource access control in business processes.

Automated Planning of Process Models

Companies need to adapt their processes quickly in order to react to changing customer demands or new regulations, for example. Process models are an appropriate means to support process setup but currently the (re)design of process models is a time-consuming manual task. Semantic Business Process Management, in combination with planning approaches, can alleviate this drawback. This means that the workload of (manual) process modeling could be reduced by constructing models in an automated way. Since existing, traditional planning algorithms show drawbacks for the application in Semantic Business Process Management, we introduce a novel approach that is suitable especially for the Semantic-based Planning of process models. In this chapter, we focus on the semantic reasoning, which is necessary in order to construct control structures, such as decision nodes, which are vital elements of process models. We illustrate our approach by a running example taken from the financial services domain. Moreover, we demonstrate its applicability by a prototype and provide some insights into the evaluation of our approach.

Semantic Integration of Structured and Unstructured Data in Data Warehousing and Knowledge Management Systems

Nowadays, increasing information in enterprises demands new ways of searching and connecting the existing information systems. This chapter describes an approach for the integration of structured and unstructured data focusing on the application to Data Warehousing (DW) and Knowledge Management (KM). Semantic integration is used to improve the interoperability between two well-known and established information systems in the business context of nowadays enterprises. The objective is to introduce a semantic solution in the field of Business Intelligence based on ontology integration. The main focus of this chapter is not to provide a complete literature review of all existing approaches or just to point put the motivation for such an approach. In fact, it presents, under consideration of the most important research approaches, a solution for how a Semantic Integration could be technically achieved in this specific application area. After pointing out the motivation, a short introduction to Semantic Integration, the problems and challenges occurring from it, and the application area of Knowledge Management and Data Warehousing are given. Besides the basic ideas of ontologies and ontology integration are introduced. The approach itself starts with a short overview on the determined requirements, followed by a concept for generating an ontology from a Data Warehouse System (DWS) to be finally integrated with Knowledge Management Systems (KMS) ontology. Finally SENAGATOR, an exemplarily system for semantic navigation based on integrated ontologies, is shortly introduced.

Ontologies and Controlled Vocabulary

This chapter presents an analytical study about methodology and methods to build ontologies and controlled vocabularies, compiled by the analysis of a literature about methodologies for building ontologies and controlled vocabularies and the international standards for software engineering. Through theoretical and empirical research it was possible to build a comparative overview which can help as a support in the defining of methodological patterns for building ontologies, using theories from the computer science and information science.

Semantically Enhanced Business Process Modeling Notation

Semantic Business Process Management (SBPM) bridges the gap between business and IT by taking advantage of the Semantic Web technologies. The foundation for SBPM is the detailed ontological description of enterprise models. These models encompass also business processes taking place in enterprises. Within this chapter, we show how the process-oriented knowledge may be captured for the needs of SBPM. For this reason, we describe semantically enhanced Business Process Modeling Notation (sBPMN) being a conceptualization of one of the main process modeling notations with the fast growing popularity among the tool vendors, namely BPMN. The sBPMN ontology is based on the BPMN specification and may be used as a serialization format by the BPMN modeling tools, thus, making creation of annotations invisible to users. In this chapter, we also present an example of a process model description.

Heterogeneous Text and Numerical Data Mining with Possible Applications in Business and Financial Sectors

Nowadays, many world-wide universities, research centers, and companies share their own data electronically. Naturally, these data are from heterogeneous types such as text, numerical data, multimedia, and others. From user side, this data should be accessed in a uniform manner, which implies a unified approach for representing and processing data. Furthermore, unified processing of the heterogeneous data types can lead to richer semantic results. In this chapter, we present a unified pre-processing approach that leads to generation of richer semantics of qualitative and quantitative data.

Ontological Evaluation of Scheer’s Reference Model for Production Planning and Control Systems

Within the information systems field, reference models have been known for many years. A reference model is a conceptual framework and may be used as a blueprint for information systems development. Despite the relevance of reference model quality, little research has been undertaken on their systematical analysis and evaluation. In this chapter, we evaluate Scheer’s reference model for production planning and control systems from an ontological point of view. The evaluation is based on the Bunge-Wand-Weber ontology. Several ontological anomalies are found in Scheer’s reference model. The obtained knowledge is useful for selecting, applying, and extending the reference model.

Functional Components Specification in the Semantic SOA-Based Model

Semantic Web Services are providing means for (semi-) automatic discovery, composition, and execution of Web Services. However, these new emerging semantic techniques seem to be inaccurate to be used in terms of semanticizing the capabilities of Web Services and the requests of Web Services consumers. This comes from the blurred representation of their involved ontologies. This chapter presents a semantic Web-Service-based reference model that is mainly relying on the idea of applying lightweight semantics to Web Services in order to have an efficient solution for different business domains. The model advances the reusability of its components and reduces the necessity of data transformation functions in business process descriptions. Furthermore, technical aspects about the core prototypical implementation are described.

EPCs Annotated with Lexical and Semantic Labels to Bridge the Gap between Human Understandability and Machine Interpretability

Labels of EPC functions and events are the key to understanding EPC models by humans and by machines. Empirical studies show that the current labeling practice of model elements is conducted rather arbitrarily which inherently causes potential threats for understanding by humans. Thus, refactoring of model element labels is suggested either human-driven or with automated support while semantic annotation using domain-ontologies is well-recognized to approach the understanding of model elements by machines. Current research either focuses on improving the quality of labels or on semantic annotation to facilitate machine interpretability. To the best of our knowledge, there is a significant lack of approaches that facilitate to exploit the potentials and benefits arising from bridging the gap between approaches that improve human understandability and that facilitate machine interpretability. This work introduces a comprehensive, formalized approach that enables the modeling tasks automated refactoring of model elements and automated semantic annotation by bridging the gap between informal and formal representation of model elements.

Semantic-Enabled Compliance Management

A lot of companies are nowadays obliged to follow regulations and to integrate specific policies from these regulations into their business processes. Implementing compliance automation concepts is crucial for companies because of the dependencies between compliance policies, IT-infrastructure and business process management. Nowadays in many companies there exist either no compliance automation concepts at all, or automation is limited to simply integrating hard-coded checks into standard software with no linkage to the business processes. In the scientific community in the past years, some concepts for compliance automation based on business processes, workflow technology, and semantic technologies have been developed. Semantic technologies seem to be a promising approach where implemented regulations are expressed by means of ontologies. In this chapter we present an approach for a semantics-based configuration of a service package with respect to Service Level Agreements, which capitalizes on the principles and use cases of the EU-project, plugIT. This chapter discusses the approach in detail, shows the economical benefits, and concludes with an outlook for the next steps.