EFFICIENT SYSTEM INTEGRATION USING  SEMANTIC REQUIREMENTS AND CAPABILITY MODELS - An Approach for Integrating Heterogeneous Business Services

Sunindyo

et al. 2010

Canadian Semantic Web

Self Cite

In a service-oriented environment business processes flexibly build on software services provided by systems in a network. A key design challenge is the semantic matchmaking of business processes and software services in two steps: 1. Find for one business process the software services that meet or exceed the BP requirements; 2. Find for all business processes the software services that can be implemented within the capability constraints of the underlying network, which poses a major problem since even for small scenarios the solution space is typically very large. In this chapter we analyze requirements from mission-critical business processes in the Air Traffic Management (ATM) domain and introduce an approach for semi-automatic semantic matchmaking for software services, the "System-Wide Information Sharing" (SWIS) business process integration framework. A tool-supported semantic matchmaking process like SWIS can provide system designers and integrators with a set of promising software service candidates and therefore strongly reduces the human matching effort by focusing on a much smaller space of matchmaking candidates. We evaluate the feasibility of the SWIS approach in an industry use case from the ATM domain.

Section: Semantic Integration With Semantic Web Servicesmentioning

confidence: 99%

“…The SWIS framework explicitly models the semantics of integration requirements and capabilities using a machine-understandable notation (semantic integration) [35]; and the connectors and transformations between heterogeneous legacy systems (technical integration) to simplify systems integration (business process support) [34].…”

Section: Introductionmentioning

confidence: 99%

Semantic Service Matchmaking in the ATM Domain Considering Infrastructure Capability Constraints

Sunindyo

et al. 2010

Canadian Semantic Web

Self Cite

“…The SEEK approach, described in [19] in more details, consists of 6 process steps: 1. legacy system description, 2. domain knowledge description, 3. model QA, 4. derivation and selection of integration partners, 5. generation of transformation instructions, and 6. configuration QA. For a typical systems integration scenario, the problem space is described as integration requirements and capabilities, the solution space consists of connectors and data transformation instructions between legacy systems, while the bridging process between both spaces is concerned with finding feasible integration solutions, e.g., with minimal integration costs.…”

Section: Objectives and Contributionmentioning

confidence: 99%

“…The data-driven SEEK approach [19] has been developed in order to explicitly model the semantics of the problem space, the solution space, and provide a process to bridge problem and solution spaces. The SEEK approach, described in [19] in more details, consists of 6 process steps: 1. legacy system description, 2. domain knowledge description, 3. model QA, 4. derivation and selection of integration partners, 5. generation of transformation instructions, and 6. configuration QA.…”

Section: Objectives and Contributionmentioning

confidence: 99%

“…The overall process for systems integration consists of three phases (see [19]): 1. the elicitation and validation of systems integration requirements (problem space knowledge); 2. the description of the architecture and the modeling of the capabilities of technical solution candidates (solution space knowledge) [17]; and 3. the bridging of the knowledge models of problem and solution space to identify the most suitable solution candidates [20].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Efficient Integration of Complex Information Systems in the ATM Domain with Explicit Expert Knowledge Models

Complex Intelligent Systems and Their Applications

Mikula

et al. 2010

Self Cite

Abstract. The capability to provide a platform for flexible business services in the Air Traffic Management (ATM) domain is both a major success factor for the ATM industry and a challenge to integrate a large number of complex and heterogeneous information systems. Most of the system knowledge needed for integration is not available explicitly in machine-understandable form, resulting in timeconsuming and error-prone human integration tasks. In this chapter we introduce and evaluate a knowledge-based approach, "Semantically-Enabled Externalization of Knowledge" for the ATM domain (SEEK-ATM), which explicitly models a) expert knowledge on specific heterogeneous systems and integration requirements; and b) allows mapping of the specific knowledge to the general ATM problem domain knowledge for semantic integration. The domain-specific modeling enables a) to verify the integration knowledge base as requirements specification for later design of technical systems integration and b) to provide an application program interface (API) to the problem space knowledge to facilitate tool support for efficient and effective systems integration. Based on an industry case study, we evaluate effects of the proposed SEEK-ATM approach in comparison to traditional system integration approaches in the ATM domain. Major advantages of the novel approach are the efficient derivation of technical configurations and automated quality assurance of the expert knowledge models.

Making Expert Knowledge Explicit to Facilitate Tool Support for Integrating Complex Information Systems in the ATM Domain

2009 International Conference on Complex, Intelligent and Software Intensive Systems

Mikula

et al. 2009

Self Cite

The capability to provide a platform for flexible business services in the Air Traffic Management (ATM) domain is both a major success factor for the ATM industry and a challenge to integrate a large number of complex and heterogeneous information systems. Most of the system knowledge needed for integration is not available explicitly in machineunderstandable form, resulting in time-consuming and error-prone human tasks.In this paper we propose a knowledge-based approach, "Semantically-Enabled Externalization of Knowledge" for the ATM domain (SEEK-ATM), which explicitly models a) expert knowledge on specific heterogeneous systems and integration requirements; and b) allows mapping of the specific knowledge to the general ATM problem domain knowledge for semantic integration. The domain-specific modeling enables a) to verify the integration knowledge base as requirements specification for later design of technical systems integration and b) to provide an API to the problem space knowledge to facilitate tool support for efficient and effective systems integration.Based on an industry case study, we evaluate effects of the proposed SEEK-ATM approach in comparison to traditional system integration approaches in the ATM domain.