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Enterprise Interoperability
Enterprise integration is a domain of research developed since 1990s as the extension of Computer Integrated Manufacturing (CIM). Enterprise integration research is mainly carried out within two distinct research communities: Enterprise Modelling and Information Technology (Panetto and Molina, 2008). In the context of Enterprise Modelling, the enterprise integration concerns the set of methods, models and tools that one can use to analyze, to design and to continually maintain an enterprise in an integrated state. An integrated state can be achieved ensuring constantly the interactions between enterprise entities necessary to achieve domain objectives. Enterprise interoperability refers to the ability of performing these interactions between enterprise systems (exchange of information and services). Then, it is a means to achieve integration (Chen and Vernadat, 2002; Panetto, 2007). ISO 14258 considers that interoperation between two (or more) entities can been achieved in three ways:
– Integrated: where there is a standard format for all constituent systems. Diverse enterprise models are interpreted in the standard format.
– Unified: where there is a common meta-level structure across constituent models, providing a means for establishing semantic equivalence.
– Federated: where models must be dynamically accommodated rather than having a predetermined meta-model: mapping between concepts could be done at an ontology level to formalise the interoperability semantics.
Integration is generally considered to go beyond mere interoperability to involve some degree of functional dependence. While interoperable systems can function independently, an integrated system loses significant functionality if the flow of services is interrupted. An integrated family of systems must, of necessity, be interoperable, but interoperable systems need not be integrated (Panetto, 2007). Integration also deals with organisational issues, in possibly a less formalised manner due to dealing with people, but integration is much more difficult to solve, while interoperability is more of a technical issue. Compatibility is something less than interoperability. It means that systems/units do not interfere with each other’s functioning. But it does not imply the ability to exchange services. Interoperable systems are by necessity compatible, but the converse is not necessarily true. To realize the power of networking through robust information exchange, one must go beyond compatibility.
In sum, interoperability lies in the middle of an “Integration Continuum” between compatibility and full integration. While compatibility is clearly a minimum requirement, the degree of interoperability/integration desired in a joint family of systems or units is driven by the underlying operational level of those systems.
Then, classifying interoperability problems may help in understanding the degree of development needed to solve, at least partially, these problems (Panetto, 2007).
Levels of interoperability
There are several possible levels of interoperability (Euzenat, 2001):
• encoding: being able to segment the representation in characters.
• lexical: being able to segment the representation in words (or symbols).
• syntactic: being able to structure the representation in structured sentences (or formulas or assertions).
• semantic: being able to construct the propositional meaning of the representation.
• semiotic: being able to construct the pragmatic meaning of the representation (or its meaning in context).
Each level cannot be achieved if the previous levels have not been completed. The encoding, lexical and syntactic levels are the most effective solutions, but not sufficient, to achieve a practical interoperability between computerized systems using existing technologies such as XML (eXtensible Mark-up Language) (W3C, 2004a), and its related applications (SOAP (Simple Object Access Protocol) (W3C, 2003), WSDL (Web Services Description Language) (W3C, 2004b), ebXML (Electronic Business XML Initiative) (OASIS , 2002), to name a few). In that sense, standardisation initiatives (ISO 14528, 1999; IEC 62264, 2002; ISO EN DIS 19440, 2004) try to cope with this issue by defining generic constructs focusing on the domain concepts definitions. The semiotic level requires complex processing more related to artificial intelligence domain.
Aspects of Interoperability
Interoperability between two organisations is a multifaceted problem since it concerns both technical and organisational issues, which are intertwined and complex to deal with, but not only. According to the European Interoperability Framework (EIF, 2004), there are three aspects of interoperability:
1. Organisational Interoperability: This aspect of interoperability is concerned with defining business goals, modelling business processes and bringing about the collaboration of administrations that wish to exchange information and may have different internal structures and processes. Moreover, organisational interoperability aims at addressing the requirements of the user community by making services available, easily identifiable, accessible and user-oriented.
2. Semantic Interoperability: This aspect of interoperability is concerned with ensuring that the precise meaning of exchanged information is understandable by any other application that was not initially developed for this purpose. Semantic interoperability enables systems to combine received information with other information resources and to process it in a meaningful manner. Semantic interoperability is therefore a prerequisite for the front-end multilingual delivery of services to the user.
3. Technical Interoperability: This aspect of interoperability covers the technical issues of linking computer systems and services. It includes key aspects such as open interfaces, interconnection services, data integration and middleware, data presentation and exchange, accessibility and security services.
Interoperability maturity models
The problems of enterprise interoperability can be defined according to various points of view and perspectives. Table 1 below shows the overlap and alignment between the various maturity models (Panetto, 2007). The main purpose of their framework is to provide an organized mechanism so that concepts, problems and knowledge on enterprise interoperability can be represented in a more structured way, in terms of diagrams, text and formal rules. They are not representation of operational processes, data, organizational structure, etc., but define the modelling constructs that are necessary to describe enterprise systems so that models achieved are consistent and easy integrated.
Existing projects
Two main initiatives relating to interoperability development exist: ATHENA Integrated Project (IP) (ATHENA, 2003) and INTEROP Network of Excellence (NoE) (INTEROP, 2003). The roadmap of these projects was defined by Interoperability Development of Enterprise Applications and Software (IDEAS) network, which was the first initiative carried out in Europe under the Fifth Framework Programme, to address enterprise and manufacturing interoperability.
Advanced Technologies for Interoperability of Heterogeneous Enterprise Networks and their Applications (ATHENA) is a programme that consists of a set of projects dealing with gaps-closing activities considered as priorities in IDEAS roadmaps and lead to prototypes, technical specifications, guidelines and best practices that form a common European repository of knowledge (ATHENA, 2003).
Interoperability Research for Networked Enterprises Applications and Software (INTEROP) aims at integrating expertise in relevant domains for sustainable structuration of European Research on Interoperability of Enterprise applications (INTEROP, 2003). More than 50 research entities (Universities, Institutes,…) and up to 150 researchers and 100 Doctorate students from 15 EU countries have worked within INTEROP NoE.
In other word, the gaps analysis and roadmaps resulted from IDEAS have led to the definition of R&D research projects to carry out by ATHENA. Dispersed and fragmented knowledge on interoperability and related research activities was integrated and restructured by INTEROP. The three initiatives form a coherent and complementary approach to enterprise interoperability.
Standard-based approach to enterprise interoperability
Because companies have been using heterogeneous information systems, they primarily have used standard-based approaches for large scale information sharing.
Various existing standards can be classified into two categories:
1. supporting infrastructures, architectures, and languages (e.g. CORBA, FIPA, KQML, and NIIIP, etc.).
2. standards for information exchange and sharing (e.g. STEP, KIF, and XML, etc.).
However, the standard-based approaches have raised several issues and problems, such as (Oh and Yee, 2008).
1. they force whole trading partners to follow a single unified standard, ignoring the heterogeneous nature inherent in business partners’ environments.
2. it is significantly inefficient and difficult to fit, customize, and integrate complex industrial standards. Many enterprise applications schemas mismatches, such as terminology, structure, data organization, and data granularity, even though they share the same semantics at higher abstract level.
3. because these standards allow flexibility in terms of message contents and their processes composed, a significant effort is required to implement precisely business transactions (Kotinurmi, 2005), even though the partners agreed to use them.
4. an excessive lead-time is required to accept new partners and connect them to existing partners;
5. the traditional standardization process cannot manage semantics of messages effectively. Most of the standard-based solutions only provide commonly agreed sets of labels, entity definitions and relationships for interchanging heterogeneous information or for defining project models. But they usually do not support broad ranges of explicit definitions for the terminologies and concepts used in their schemas.
As these standard schemas lack rich, formal and explicit semantic descriptions, they cannot ensure the consistent interpretation and understanding of application semantics across disciplines. Simply sharing the common labels and standard data structures is not sufficient to achieve semantic interoperability.
To address the issues and problems of the standard-based approaches, and to achieve semantic interoperability, different technologies have been introduced. Besides the interoperability standardization approach, ontology engineering is recognized as another key technology to deal with the semantic interoperability problems.
Ontology-based approach for semantic enterprise interoperability
Semantics can be broadly defined as the meaning associated with a terminology in a particular context (Patil et al., 2005). Semantic interoperability is the ability of enabling heterogeneous multi-disciplinary enterprise applications to understand and utilize semantics of enterprise systems and meanings of model data, and to map between commonly agreed concepts to establish a semantically compatible information interchange and sharing environment.
Ontologies are often considered to be a most powerful means to solve the problem of efficient storing and retrieving knowledge, because they are constructed to specify the conceptual model of an information and knowledge domain explicitly. For this reason, they can be used in supporting information and knowledge exchange between different organizations and then they are very useful in solving semantic interoperability problem.
Ontologies specify the semantics of terminology systems in a well-defined and unambiguous manner (Guarino, 1998), by formally and explicitly representing shared understanding about domain concepts and relationships between concepts. In an ontology-based approach, intended meanings of terminologies and logical properties of relations are specified through ontological definitions and axioms in a formal language, such as OWL (Web Ontology Language) (W3C, 2005) or RDF (Resource Description Framework) Schema (www.w3.org/TR/2000/CR-rdf-schema-20000327).
Table of contents :
INTRODUCTION: PROBLEM STATEMENT, RESEARCH OBJECTIVES AND METHODOLOGIES
1. PROBLEM STATEMENT
1.1. The Interoperability Problem
1.2. The Interoperability standards
2. RESEARCH OBJECTIVES
3. RESEARCH METHODOLOGIES
4. STRUCTURE OF THE THESIS
5. REFERENCES OF THE CHAPTER
CHAPTER 1: INTEROPERABILITY IN MANUFACTURING SYSTEMS
1. INTRODUCTION
2. INTEROPERABILITY: GENERAL ISSUES
2.1. Enterprise Interoperability
2.2. Levels of interoperability
2.3. Aspects of Interoperability
2.4. Interoperability maturity models
2.5. Existing projects
3. INTEROPERABILITY IN MANUFACTURING SYSTEMS
3.1. Enterprise Systems
3.2. Standard-based approach to enterprise interoperability
4. ONTOLOGY-BASED APPROACH FOR SEMANTIC ENTERPRISE INTEROPERABILITY
5. CONCLUSIONS
6. REFERENCES OF THE CHAPTER
CHAPTER 2: PRODUCT ONTOLOGY
1. INTRODUCTION
2. ONTOLOGY: GENERAL ISSUES
2.1. Types of ontologies
2.2. Ontology Languages
2.3. Application Area
2.4. Tools
2.5. Open issues
3. PRODUCT ONTOLOGIES
4. STANDARDS FOR PRODUCT DATA
4.1. Product Development Standards
4.2. Product Production Interoperability Standards
4.3. Product Use Interoperability Standards
5. CONCLUSIONS
6. REFERENCES OF THE CHAPTER
CHAPTER 3: PROPOSAL OF A ONTOLOGICAL MODEL FOR
PRODUCT-CENTRIC INFORMATION SYSTEMS INTEROPERABILITY
1. INTRODUCTION
3
2. STANDARD MODELS ANALYSIS
3. THE METHODOLOGY
3.1. The scenario
4. MAPPING FORMALIZATION
4.1. FOL formalisation of UML conceptual models
5. SEMANTICS OF PRODUCT DATA IN STANDARD MODELS
6. MAPPING FORMALIZATION
7. ONTOLOGICAL MODEL
8. CONCLUSION
9. REFERENCES OF THE CHAPTER
CHAPTER 4: VALIDATION OF THE ONTOLOGICAL MODEL
1. INTRODUCTION
2. USE CASE
2.1. The general context
2.2. The scenario
2.3. Application of proposed model
3. CONCLUSION
4. REFERENCES OF THE CHAPTER
CONCLUSIONS AND FUTURE RESEARCH
1. SUMMARY
2. LIMITS AND ADVANTAGES OF THE PROPOSED MODEL
3. FURTHER DEVELOPMENTS
4. REFERENCES
4
ANNEX I: FIRST ORDER LOGIC (FOL)
1. FOL: SYNTAX
2. FOL: SEMANTICS
3. REFERENCES
ANNEX II: DATA MODELLING USING EXPRESS-G
ANNEX III: DATA MODELLING USING UML
LIST OF THE REFERENCES
LIST OF THE ACRONYMS
FIGURE INDEX
TABLE INDEX
