International Symposium on Collaborative Technologies and Systems, CTS 2007, May 21-25, Orlando, USA
Interoperability Requirement Challenges- Future Trends
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Prof. Vesa Salminen1, Prof. Balan Pillai2
Lappeenranta University of Technology, Lappeenranta, Finland, Email:
[email protected] 2 The Seoul National University, South Korea, Email:
[email protected]
ABSTRACT The objective of this article is to introduce, an interoperability concept; in “Intelligent and electronic ( i & e) – manufacturing system integration for semantic web. It demonstrates as to how to make use of the Semantic Web Infrastructure in the event of an Industry. We come-up with a methodology, that needed to try out (or in fact already a portion is tested) in live industrial environment. Interoperability design is extensively spoken out; and to some degree is trying to specify generally the requirements and challenges. But, what is the scenery of this revolt in technology? And what new technical challenges will it present? The ubiquity of computation and communication is not the only symptom of the insurgency. Much of this emerging computation is embedded; the processors in your phones, cars, personal digital assistants, and home appliances. Increasingly they are in concert with other computational fundamentals as part of a larger ensemble. This broad span of capabilities represents a fresh pattern of computing. Accurately when we realize that the ubiquity of communication bandwidths over and over again; makes it possible to position computational mission at whatsoever point in this chain of command; makes the most sense. We can do better – let us watch-out! KEYWORDS: Infrastructure for Collaborative Enterprise (CE)s, Requirement Engineering in CE, Knowledge Factory, Ontologies and Ethnographic Approaches, Semantic Web Infrastructure for Intelligent and Electronic ( i & e) Manufacturing
1. INTRODUCTION “If I have seen farther, it is by standing on the shoulders of giants,” wrote Isaac Newton in a letter to Robert Hooke in 1676 [1]. While Newton was referring to his discoveries in optics rather than his more important work on gravity and the laws of motion, it is an appropriate comment on how science, and unquestionably the whole of civilization, is a
series of incremental advances, each structure on what went before. This is the fascinating theme; which uses the interoperability concept, to trace the evolution of today’s picture of the businesses; from the avant-garde state of Internet liberation. There is a dramatic gap between capabilities of current collaboration and the networked requirements of businesses. The businesses are looking for scalable, adaptive, costeffective, collective, and pin-pointed solutions [2]. Clearly, there is a need to develop a systematic and holistic approach rapidly to form Virtual Enterprises; based on ubiquitous (anywhere, anytime), and affordable (easy and cheap) collaborative environments; in maintaining securely interoperable entity infrastructure; within a multiculturalcum-multilingual perspective. Ultimate goal is to realize; the vision of turning “inside-out” enterprises, as a plug-and-play Internet business community [3]. Actual Extended or Virtual Enterprise approaches create a big dilemma because each time a new partner is entering results in increasing exponentially management and integration costs. This is mostly due to disparate visions, understandings and other interpretations which are disabling collaboration capabilities among trading partners. Recently there has been a great interest in the Semantic Web and issues related to specification and exploration of semantics on the WWW. Berners-Lee, the initiator of the World Wide Web [www], lays stress on the importance of the “Semantic Web” for machine-understandable web contents and emphasizes the need for ontology [4]. Though a self-describing protocol eXtended Mark-up Language [xml] is in charge of the syntax of the web contents, clear definitions of the semantics of the domain knowledge required to implement machine-understandable contents. Ontology and ontological analysis needed fundamentally to represent knowledge about the domain and be able to share the information [5]. In specific the shared ontologies are being proposed for representing the core knowledge that forms the foundation for semantic information on the Web. We identify broad thrust related to ontologies: • Approaches to standardize the formal semantics of information to enable machine processing. Work is to be done as a part of the W3C working group.
International Symposium on Collaborative Technologies and Systems, CTS 2007, May 21-25, Orlando, USA
At a deeper level, we believe that Semantic Web is an opportunity to shrink the "formalization gap" between engineering disciplines. We argue that overcoming this gap is the fundamental change in engineering society. This discontinuity in formalization between human connected information process and the machine code necessary to accomplish comparable ends begins at a very high descriptive level and it is not itself a concern of computer science. If this concern is to be given a name at all, it must
We summarize the vision of the change of Technology Roadmap. It visions a timeframe for 5 years. The mission accomplishes to such a suitable level at 2010, when Semantic Web becomes a reality in industry. Figure 1 describes an onion model of the roadmap towards enterprise integration and full use of semantic infrastructure in open system architecture with interoperability and plug and play capability. n: eb s io W e Vi ntic pris a ter on m i Se r En grat fo nte I
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We have seen in this light, change, even a large amount of change, will be a feature of successful formal terminology, or ontology. We hope to demonstrate the feasibility and utility of this approach. The challenge in the context of the Semantic Web is to choose a representation for change that makes it explicit. We assume that the engineering tool kit viewed in this way the Semantic Web would be part of the semantics. The challenge with this approach is the formulation of the units of change and the creation of ontology of these change units. Making change part of the Semantic Web would preserve that consistency. One way to focus the development of the desired units, interrelationships, and uses is to solve real problems and gain experience from deployments of these solutions; we propose to do this by formulating, deploying, and evaluating what we now call "The New Engineering Transaction." This transaction needs to supply reverse engineering; operating schemes and control information systems with the requisite formal definition of a new "insert", given a reference model or application, and do so at Web scale. The main challenge is how to do this in a way that first avoids breaking working applications that use the engineering tool kit terminology and second preserves the longitudinal value of existing and future engineering innovations of implementation.
2. TECHNOLOGY ROADMAP
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Creating standards, especially standards that generate information industry infrastructure, is difficult, timeconsuming and at constant risk for irrelevance and failure. One way to mitigate this risk, and secure the participation of the diverse interest groups required making such standards a success is to focus on process -- as in the process that produces and maintains a good standard. This is in contrast to an approach that says some existing artifact selected from a list will be the standard, and all the others will not be the standard. An observation that we attribute is that it doesn' t matter where you start, that is, it does not much matter which terminology or terminologies one selects as a starting point, instead what does matter is the process by which the proposed standard evolves to achieve and sustain the desired degree of quality, comprehensiveness, and functionality. The process is what determines where the standard ends up.
be regarded as concerning engineering applications, and it is increasingly being referred to as "engineering information science" in Finland and "Engineering Informatics" in Europe and the US. It will be the task of this new discipline to better understand and define the engineering information processes we have considered here, in order that appropriate activities will be chosen for computerization, and to improve the man-machine system for better interoperability.
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Figure 1: Technology Roadmap towards Enterprise Integration Architecture, tools, and the local enhancements Implicit in much that has been written here is the architectural notion of engineering vocabulary servers, or in this context, formal terminology, or ontology servers. That is, such servers "normalize" terminology functions for enterprises, some at Web scale. We believe that such servers will be essential to the support of the Semantic Web, and as usual on the Web, the challenge will be how to maintain them in loose synchrony as appropriate. A clear result of experience gathered shows that terminology development, especially formal terminology development cannot be undertaken for long without non-trivial supporting tools and software. Foremost among the required tools is a scalable terminology editing workstation. The fact that formal terminologies will almost always be constructed and
International Symposium on Collaborative Technologies and Systems, CTS 2007, May 21-25, Orlando, USA
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Figure 2: The architecture of Engineering Ontology Here the builder uses an object-oriented knowledge representation model based on and compatible with knowledge model and is designed to use the best practices from other frame-based systems. This is assumed to supports operations on classes, slots, facets, and individuals. Interoperability, knowledge sharing, and reuse are important goals and works as a fully compliant server. This should support a metaclass architecture that is in an Open Environment to allow introduction of flexible and customizable behaviors into an engineering ontology. It is able to predefine certain system constants, classes, and primitives in a default upper engineering ontology that can extend or refine to change the knowledge model and behaviors within the system.
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This article is a summary and continuation of the completed project “Feasibility Study on an Open System Architecture in Distributed Networking, COMPLEX”. During the project we have developed methodology for Product, Service, and Complexity Management and experienced few implementations. The reason to continue by methodology development was emerged from the industry that are interested to implement more on application level and benefit the created good cooperation with The National Institute of Standards and Technology (NIST), Gaithersburg, Maryland and Massachusetts Institute of Technology (MIT), Boston, USA. Companies are able to establish better understanding of their immediate needs that are missing now in their system approach. There is a great need for most of the businesses to develop their product and service management in Open System Architecture. A sustainable growth of the business lies on services that Corporations are offering [6]. Products are increasingly embedding intelligent; therefore the role of product architecture is becoming important. The best possible product architecture for the optimized product platform is thus very important. It is recognized through product modeling and dependency management. In some cases, it is to be re-engineered to achieve an optimum cash return. The methodology phase contains freshly created new knowledge. It is attributing the redundancy or not. This phase draw ups the possibilities of self-integrating schemes. This includes the manufacturing system integrations and netting them into Business environment and thus creating B2B platform to serve B2C. Figure 3 introduces the agent mechanisms for Internet based i & e manufacturing. AGENT SYSTEMS FOR INTERNET-BASED MANUFACTURING
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By threading the vision the study may in future concentrate on cutting-edge at industry cases. A flash search will be conducted on the Industry needs and their product development capability and Systems. While surveying the requirements of the industry, we penetrate to verify the capabilities of Finnish Industries. We mirror them with US-industries and their peers, such as government and universities. We try to include the funding practices, product development sequences, and industry concentrations. It also foresees the innovation cycles and patented cases. The survival mechanisms and life cycle of individual projects in product development schemes are assumed to be the part of the study.
3. METHODOLOGY EXPERIMENTAL
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maintained by geographically separated domain experts implies additional requirements for "configuration management," conflict resolution and the like. One shortterm reality is the need for what we call "local enhancement". Ontology builder and server are in need of business requirements in electronic commerce and Business-to-Business, B2B applications. Architecture can be drawn for simplifying the concept (figure 2).
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Figure 3: Agent-Based Mechanisms over Internet Browser for i & e- Manufacturing
International Symposium on Collaborative Technologies and Systems, CTS 2007, May 21-25, Orlando, USA
Furthermore, figure 4 below describes the self-integration environment by using semantic infrastructure. METHODOLOGY TO i & e-MANUFACTURING Object Management Group
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Figure 6: Methodology on i & e - manufacturing system integration for semantic web.
Figure 4: Self-Integration Environment Figure 5 explains the connectivity of Semantic Web into i & e - manufacturing concept. The methodology of this is outlined in figures 5 and 6. Intelligent and Electronic Manufacturing System requires building of foundation that route for Semantic Web by “Plug- and-Play” format. The repository system feeds the strong linguistic representation through modeling and connecting between structures and classes. Internal search engine mechanism shall simulate and fractionate through re-framing the engineering entities into an understandable semantics. Semantic Infrastructure for Plug and Play Collaboration was created at National Institute of Standards and Technology, NIST on Testbed or so called information platform. Process Semantic Language, PSL, was also implemented on the test bed (figure 6).
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The time this methodology was introduced for applying at the Testbed facility, was too early. It is tempting to say that sheer speed will no longer suffice, and that more knowledge of chess, or something else, is needed. What this sketch shows is that a state transition must be represented as a pair forward >< backward, where forward is information about how to get to the state from the immediately preceding state, and backward is information about how to undo forward, that is how to go back to the immediately preceding state. A procedure was initiated through this sketch. Process specification language and the semantic impacts were tried to coin by adding a modeling tool. This tool models the context into machine understandable language; thus pinning a representation that adds value to this new standard. In practice, it has proven that it doesn’t rule the goof. The purpose was a methodological evaluation when building Semantic infrastructure adding functionality with PSL. The representation needs to be evaluated before one could bring more functionality. In this case we were proposing a requirement analyzing and mapping tool called Optiwise®. We have also experimented in adding RDF (Resource Description Format) with Ontology standpoints to bring Representation at the Application layer.
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International Symposium on Collaborative Technologies and Systems, CTS 2007, May 21-25, Orlando, USA
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Figure 7: Identify the tags (mechanical, process, control). Here the tag associated is to mean that it belongs to structural identification that should belong to either Mechanical, Process or Control properties and are associated to service, product and or both. This is a theoretical model. This can be developed to prove remarkably robust in the face of multi-disciplinary and multi-institutional inspection and sample instantiations. Its content will be to represent portions of various engineering tool kits and formularizes used or common application based public and private vocabularies. The process - embracing change and making it explicit The model presented in figure 7 above is little more than an academic exercise without accompanying productive terminology management. As a result, there is no warehouse of engineering tool-kit descriptions that can be reached over time. The changes across in the terminologies used; to formalize a solution, to the common understanding through the web. The engineering tool-kit description repositories that support such "timetravel" no two or three do so in the same manner and none use existing or proposed standards. An explicit goal of this project is to begin to overcome this shortfall at least in the context of engineering. The first step in making formal terminology changes into a terminology/ontology "thing" or unit is to create a unit of change that has the same general properties as any other "thing-ness" unit. For example, given the appropriate reference taxonomies, used to (in the Structural Logic sense) "classify" an engineering notion, one can create the desired reference terminology -- by adding the definition of each application, one application at a time. Frequently, new application come with new mechanisms of action and new indications (implementation) and thus the corresponding "new thing" may need to update the reference taxonomies before adding the definition of the
new thing. To make the simple case more tangible, here is one potential near term future of the kind of "new thing" that does not require updating the reference: • New thing "publish", as XML, a newly "structured" version of the package insert or, "label", designed to "explain" that the new thing to both human and computers. • This will further process and enhance the parts of the label that can be processed usefully by computers and then "publish" it, once again in XML. The "enhancements" may include connections to the mechanical, process and control engineering literature, related to terminology and foreign language names. • Applications or servers electing to process the new thing transaction will see that the XML indicates that is an "add", the simplest kind of transaction to process. That is, the transaction will add a new concept -- the new thing, the appropriate relationships to other concepts influence on the various reference taxonomies, and attributes. It is not hard to imagine that most applications would be relevant of such insertion and subsequently "do the right action." However, the problem with this simple form of the new thing transaction is that, as described by domain experts, most new things represent "changes in understanding", and it is not at all clear how existing applications can deal with such changes in understanding automatically, or know when they need help from humans. In the context, "changes in understanding" is represented by changes in the reference taxonomies, e.g. for mechanical properties, process diversities, control citations or maintenance use. An engineering Ontology - Formulation Principles When we view a formal terminology or ontology as a corpus of "facts" or assertions, collected over time, then one can contemplate ontology of such facts, or changes. The goal is to evaluate and adapt semantic web infrastructure and implement ontologies for B2B processes for engineering systems [7]. B2B of engineered products is very complex and has no foundation for easy sharing of product, process, or production information. The opportunity is a new semantic language by encoding meaning, which is being developed for the web. This is the basis for B2B of engineered products and services. Professor Thomas R Gruber, Stanford University, California, USA, well defined the "Ontology is an explicit specification of a conceptualization". The difficulty is defining and implementing the semantics to be attached to each type of change unit. One step toward such semantics is the simple expedient of tagging
International Symposium on Collaborative Technologies and Systems, CTS 2007, May 21-25, Orlando, USA
each terminological unit -- concept, term, relationship, and attribute - with a "start entity" and "end entity". More disciplined and complete forms of such semantics are what are needed to preserve the longitudinal functionality of systems that use the ontology, and what will be needed to transfer knowledge gained from a successful test of the new thing transaction to the Semantic Web. Thus, even when the user interface returns an exact equivalent for the casual term, users may choose a "better" formal term from the displayed semantic neighborhood. The simple explanation of this phenomenon is that humans are better at recognition than recall. Those developing ontologies will be familiar with the phenomenon; once domain experts can "see" a domain model they can almost always make it better. We conclude by incorporating a recent draft from Doumeingts, G, et al regarding the CEN framework on Interoperability Schemes [8]. Figure 9 confronted with the same approach as we exploded elsewhere in this article.
commonly called “middleware”. This middleware is the connectivity element; who joins applications through communication mechanisms creating transparency, scalability, and interoperability. It lies between the software applications it assists and the platform it is based on. Middleware classically resides; in a layer built directly on other layers of middleware; characteristically forming higher abstractions with each additional layer. Middleware must be designed by the API (Application Programming Interface) it provides to applications that utilize it and the protocol(s) it supports [9]. In concluding, we say; there are many numbers of approaches and paradigm combination to explore the Semantic Web Infrastructure. We use; a basic perceivereason-act artificial intelligence approach [10] as a building-block; to categorize a distinctive set of needs, link up some wants, and define desirable uniqueness one might regard as in the future trends.
REFERENCES [1] Hawking, S.: On the shoulders of Giants – The Great Works of Physics and Astronomy, Penguin Books, UK, 2002.
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[2] CE-NET-report: Concurrent Enterprising Network of Excellence. Concurrent Engineering Roadmap Vision 2010. http://www.ce-net.org.
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[3] Pallot M, Salminen V, Pillai B, Kulvant P, Business Semantics: The Magic Instrument Enabling Plug & Play Collaboration?, ICE 2004, June 14-16, 2004.
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[4] Berners-Lee, T, Hendler, J, & Lassila, O: The Semantic Web, Scientific American, 2001. [5] Chandrasekharan, B, Josephson, J.R & Benjamins, V.R.: What are Ontologies, and Why Do we need them? IEEE Intelligence Systems, 14 (1), 1999, p. 20-26.
Figure 9: CEN Framework for Enterprise Interoperability – Adopted with Courtesy of the Network Enabled Abilities CWA draft 9 - N 27 Research Roadmap Working Group.
4. CONCLUSION This article intended; to offering a realistic groundwork; in designing interoperability schemes; at the industrial environment for the future. We specified the requirements; and its challenges. Manufacturing industry has numerous setbacks; in developing systems and software for a smart environment is daunting task. There is sensor hardware and software perceiving the environment; application software that interprets and reasons about that perception data; and the effecter control software acting on the environment; as well as many support systems; makes the challenges to standards in posting them to Semantic Infrastructure or per se Semantic Web. This software is
[6] Salminen V., Pillai B., Integration of Products and Services – Towards System and Performance. International Conference on Engineering Design, ICED 05, Melbourne, August 15 -18, 2005. [7] Pillai B, Salminen V, Trends in Design and Connectivity to Broadband: 14th CIRP Design 2004, Cairo, Egypt, May 16-18, 2004. [8] Doumeingts, G, Li, M-S, Piddington, C & Ruggaber, R: Enterprise Interoperability – Research Roadmap document, version 1, December 2005. [9] Bernstein, P.A.: Middleware: a model for distributed system services. Communication of the ACM, 39(2), 1996, p.86 – 98. [10] Russell, S.J. & Norvig, P.: Artifical Intelligence: A Modern Approach. Prentice Hall, Upper Saddle River, New Jersey, 1995.