Expert Systems with Applications 39 (2012) 5616–5624

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Expert Systems with Applications

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Semantic Web based innovative design knowledge modeling forcollaborative design

Kai Wang ⇑, Akio TakahashiFaculty of Knowledge Engineering, Tokyo City University, 1-28-1 Tamazutsumi, Setagaya-ku, Tokyo 158-8557, Japan

a r t i c l e i n f o

Keywords:Knowledge modelInnovative designSemantic WebCollaborative design

0957-4174/$ - see front matter � 2011 Elsevier Ltd. Adoi:10.1016/j.eswa.2011.11.056

⇑ Corresponding author.E-mail address: wangkjp@hotmail.com (K. Wang).

a b s t r a c t

This paper describes a study about how to use the Semantic Web technologies for innovative designknowledge modeling in a multi-agent distributed design environment. Semantic Web based knowledgemodeling for innovative design is proposed as prelude to the meaningful agent communication andknowledge reuse for collaborative work among multidisciplinary organizations. A model for innovativedesign is proposed at first, based on which a knowledge schema is brought forward. For sharing thedesign knowledge among an internet-based or distributed work team, even globally, A RDF-based knowl-edge model is presented to realize its representation on Semantic Web. A Semantic Web based repositoryfor innovative design and its API for topper Semantic Web applications have been also constructed. Theproposed knowledge modeling extends traditional product modeling with capabilities of innovativedesign, knowledge sharing and distributed problem solving, and is employed as a content languagewithin the messages in the proposed multi-agent system architecture. The proposed approach is viewedas a promising knowledge management method that facilitates the implementation of computer sup-ported cooperative work in innovative design of Semantic Web applications.

� 2011 Elsevier Ltd. All rights reserved.

1. Introduction Semantic Web, since the Semantic Web provides the across plat-

As engineering design becomes increasingly knowledge-inten-sive and collaborative (Zhen, Jiang, & Song, 2011), the need forcomputational design frameworks to support the representation,maintenance, and use of knowledge among distributed designersbecomes more critical (Ma & Mili, 2003). The modeling of the de-sign knowledge is the premise and fundamental for knowledgemanagement (KM) applications (Mili et al., 2001).

In today’s highly competitive and uncertain market environ-ment with short product life cycles, product development mustnot only satisfy the quality and speed of production, but it mustensure that products themselves have included innovative values.As innovation plays an important role in new product develop-ment, it can be utilized in search of novel ideas for innovative prod-uct design, and also can be regarded as a helpful tool in advancingnew product development output. The rationality of developinginnovation-oriented product design has been well recognized inboth academia and industry (Gero, 1996).

In addition, to support a geographically distributed work teamto fulfill a design task, or use the globally distributed Web re-sources of knowledge, more and more scholars have focused theirattention in KM system or platform based on Web, especially

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form media basis to exchange knowledge between distributedusers, while the current HTML-based web pages cannot reflect ma-chine-understandable semantics (Zhuge, 2002a, 2002b). Thesemantic enhancement to modeling and managing innovative de-sign knowledge facilitates the implementation of computer sup-ported cooperative work (CSCW) in design by allowing multipledesign agents to share a clear and common understanding to thedefinition of product design problem and the semantics of ex-changed design knowledge.

From the above two paragraphs, we could gain two key issues ofthe research in knowledge modeling: (1) how to model theknowledge for innovative design; and (2) how to make the designknowledge could be shared on Semantic Web for collaborativeproduct development. Therefore, this paper focuses on the knowl-edge modeling for the innovative design knowledge in the environ-ment of Semantic Web. Some related works done by other scholarsare briefly introduced in the next section. In Section 3, we provide amodel for innovative design based on Function-Behavior-Structure(FBS) framework. Section 4 is the knowledge modeling for thatinnovative design. To suit Semantic Web, a RDF-based knowledgemodel for innovative design is presented in Section 5. In Section 6,a repository based on the proposed knowledge model is built. As toimplementation of proposed knowledge model to support collabo-rative communication among multiple design agents, Section 7gives a detail introduction. Closing remark and summary are thenoutlined in the last section.

Fig. 1. The three subspaces constitute the state space of designs.

K. Wang, A. Takahashi / Expert Systems with Applications 39 (2012) 5616–5624 5617

2. Related works

The past decade has seen a strong emphasis on integrated prod-uct development knowledge modeling to support collaborativeknowledge sharing in engineering design projects (Zhen, Jiang, &Song, 2010, 2009). By integrating VRML-based models with con-ventional CAD packages, Roy et al. described an open collaborativedesign environment to access and manipulate both geometric andtechnological content of the product model through a single Inter-net interface (Roy & Kodkani, 1999). Bidarra et al. employed a cli-ent–server architecture to develop a Web-based collaborativefeature modeling system that provides feature validation, multipleviews, and sophisticated visualization facilities (Bidarra, Berg, &Brongsvoort, 2002). Bohm et al. adopted an XML data format to im-port and export the engineering design knowledge including arti-facts, functions, forms, behaviors, and flows from a designrepository, which supports product design knowledge archivaland Web-based search, display of the design model, and associatedtool generation (Bohm, Stone, & Szykman, 2003). As to knowledgemodeling for product design, a survey of knowledge modelingtechniques has been performed in 1999 (Devedzic, 1999). A knowl-edge model for fixture design process has been presented (Hunter,Vizan, Perez, & Rios, 2005). Using object-based knowledge model-ing approach, a model for design knowledge and its J2EE imple-mentation are brought forward to facilitate the automated onlinecode-checking process (Yang & Xu, 2004). As to concurrent design,distributed database are used to model a knowledge base to sup-port the design (Zhang & Xue, 2002).

Most researches on modeling of product or product designknowledge for distributed collaborative product development arebased on traditional WWW technologies. The basic architecturebehind the traditional WWW is insufficient to provide a dynamic,seamless and scalable framework required for an effective, large-scale implementation of collaborative design. Aiming at providinginformation for human understanding on the WWW and not formachine processing to information with well-defined meaning,the above product and knowledge modeling approaches cannotrigorously and unambiguously capture the semantics of exchangedengineering design knowledge, therefore prohibiting automatedreasoning in collaborative design environments.

The emerging Semantic Web possesses a huge potential to over-come knowledge modeling difficulties over the Web by modelingthe concepts in a knowledge domain with a high degree of granu-larity and formal structure including references to mutuallyagreed-upon semantic definitions in ontology (Lee, Handlers, &Lassila, 2001). The Semantic Web currently focuses on theResource Description Framework (RDF), Ontology Inference Layer(OIL), and DARPA Agent Markup Language (DAML) (Fensel, 2001;Hendler, 2001; Maedche & Staab, 2001). The XML-based RDFdefines the machine-understandable semantics of web resourcesby using the object-attribute-value model. The RDF schema en-hances the representation ability of the RDF through providingthe means to define the vocabulary, the class-based structure forexpressing the metadata about resource. An example of the useof above Semantic Web technologies in collaborative design is con-figuration knowledge representation (Felfernig, Friedrich, Jannach,Stumptner, & Zanker, 2003), which compares the requirements of ageneral configuration ontology with the logics chosen for theSemantic Web, and describes the specific extensions required forthe purpose of communicating configuration knowledge betweenstate-of-the-art configurators via Semantic Web languages OILand DAML + OIL. Aziz et al. proposed an ontological knowledgemodeling methodology for collaborative product development insmall to medium enterprises, which utilizes the Semantic Webinitiative data format RDF for encoding the knowledge base inproduct lifecycle management to allow the global identification

and contextual interpretation of the shared design knowledge(Aziz, Gao, Maropoulos, & Cheung, 2005).

Notwithstanding the promising results reported from existingresearch work for Semantic Web enabled collaborative design,the modeling frameworks are closely tied to a specific discipline,and they have not brought innovation into product developmentwith the advantage of multidisciplinary collaboration. Therefore,there is a need to develop an knowledge modeling framework thatsupports representation of multidisciplinary innovative designknowledge in an unambiguous yet flexible way, and that facilitatesautonomous deployment, reuse, and federation of design knowl-edge in a meaningful and scalable way.

3. A FBS-based model of innovative design

In the aspect of research in innovative design, Gero has made agreat contribution to research of creativity and its use in design(Gero, 1990; Gero & Maher, 1993). A creativity-based design pro-cess integrating some systematic design methodologies with adeveloped creativity tool has been proposed (Hsiao & Chou,2004). An innovated scheme for integrated product and process de-sign is proposed with the description from product visualization toprocess design and a view to directly generating an optimized pro-cess plan (Lau, Jiang, & Chan, 2002).

One useful way to provide a framework for design is throughthe conceptual schema design prototype (Gero, 1990) which artic-ulates a Function-Behavior-Structure framework. Thus, the statespace representation of designs has three subspaces or abstrac-tions: the structure space, S (often called the decision space); thebehavior space, B (often called the performance space); and thefunction space, F (which defines the product’s teleology). Fig. 1shows three subspaces which constitute the state space of designs(which is denoted by D).

Innovation and innovation in design, in particular, have manyinterpretations (Boden, 1991; Sternberg, 1988) Innovation, it hasbeen suggested, is not simply concerned with the introduction ofsomething new into a design. Rather, it should lead to results thatis unexpected (as well as being valuable). More formally we candescribe routing designing as following a defined schema wherethe expectation of what follows is defined by the schema. Innova-tive designing, which is part of non-routine designing, can be de-fined as perturbing the scheme to produce unexpected andincongruous results, for which there exist three kinds of ways:combination, analogy, and mutation (Gero & Maher, 1993). Thispaper adopts analogy as the basis for modeling the innovative de-sign process. Analogy is defined as the product of processes inwhich specific coherent aspects of conceptual structure of oneproblem of domain are matched with and transferred to anotherproblem of domain. Based on the nature of the analogy, we proposea model for innovative design shown in Fig. 2. Due to the theme ofthis paper, Fig. 2 emphasizes the use of knowledge in the innova-tive design process. In Fig. 2, different shapes denote differentkinds of knowledge, circle denotes the element in function domainknowledge, pentagon denotes behavior, and triangle denotes struc-ture; the double-arrowed lines represent the mapping relationshipbetween the elements of domain knowledge.

Firstly, according to the design demand, designers describe thedemand functions top-down by a hierarchy of sub-functions,

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which is the function domain of the target state space of design(denoted by FT in the Fig. 2). In this process, function domainknowledge, and F-F mapping relationship in the knowledge basewill support designers to fulfill an integrated hierarchy of functionsfor product. On the basis of the function domain of the target statespace of design, which is source for the following design process,the whole target state space of design could be constructed accord-ing to the mapping relationship including F-B, B-S, B-B, S-S map-ping. F-B and B-S mapping reflect the relationships betweendifferent domains; while B-B, S-S mapping reflect the relationshipinside a certain domain, which help to construct the hierarchy ofbehavior and structure domain.

In the second step, the most similar state space of design is re-trieved from the design cases repository according to the targetstate space and some predefined similarity rules, which could beclassified into 3 ways: (1) matching according to the function sim-ilarity, (2) behavior similarity, or (3) structure similarity. No matterwhich way designers choose, the gained similar state space of de-sign must make some conversion according to the target statespace. For the example in Fig. 1, one element in the behavior do-main of target state space, denoted by, has two sub-itemsand , while the similar state space dose not has them, so theyshould be added and form the new state space named source statespace of design. After the conversion, some new items may bebrought into the state space of design, so designers should checkthe whole state space to ensure all the elements in domains andtheir mapping relationships are supported by the present knowl-

Fig. 2. The model for innovative de

edge base, otherwise, further conversion will be performed, ornew knowledge should be constructed to support them. In Fig. 1,a new item in structure domain, denoted by , and a mapping rela-tionship, denoted by , emerge in the source state space ofdesign.

The last step is the evaluation for the final design schema. Inthis model, we adopt fuzzy-based evaluation way, in which a hier-archy of evaluation index is predefined, and as to each index, thereexist a set of fuzzy functions. The weights of index are also takeninto account to ensure the rationality of the evaluation.

4. Knowledge modeling for innovative design

To uniformly, normally and effectively model versatile knowl-edge is one of the key issues in developing knowledge-based inno-vative design system or platform. As illustrated in the Fig. 2, theknowledge involved in innovative design could be classified into4 categories: (1) domain knowledge, (2) mapping relationship,(3) design cases, and (4) evaluation rule, all of which are summa-rized in Fig. 3.

4.1. Domain knowledge

As the fundamental of the knowledge for innovative design, do-main knowledge describes a product in different views, which con-sists of 3 types:

sign based on FBS and analogy.

Fig. 3. The category chart of the kn

K. Wang, A. Takahashi / Expert Systems with Applications 39 (2012) 5616–5624 5619

(1) Function domain knowledgeFunction domain knowledge describes basic elements in thefunction hierarchy of a product, and it includes: functionname, function description, and so on. The ExtensibleMarkup language (XML) is eligible for specifying the struc-tural characteristic of resources. The following is the typicalXML-based function domain knowledge representation.

hFunction domain knowledgeihFunction nameihAction in functioniActionh/Action in functionihObject to actioniObjecth/Object to actionihModifier for actioniModifierh/Modifier for actionih/Function nameihFunction IDiIDh/Function IDihFunction descriptionihInput for functioniInputh/Input for functionihOutput for functioniOutputh/Output for functionihEffect of functioniEffecth/Effect of functionih/Function descriptionih/Function domain knowledgei

(2) Behavior domain knowledge

Behavior domain knowledge describes the theories of princi-ples corresponding to the items of domain knowledge andtheir sub-items. It may be more complex for behaviorknowledge to be represented since it sometimes needsgraphs to describe besides literal and numerical data. Thefollowing is the XML-based behavior domain knowledgerepresentation.

hBehavior domain knowledgeihBehavior nameihTool in behavioriToolh/Tool in behaviorihAction in behavioriActionh/Action in behaviorihObject to actioniObjecth/Object to actionihModifier for actioniModifier_Actionh/Modifier for actionihModifier for objectiModifier_Objecth/Modifier for objectih/Behavior nameihBehavior IDiIDh/Behavior IDihBehavior typeiTypeh/Behavior typeihBehavior descriptioniDescriptionh/Behavior nameih/Behavior domain knowledgei

(3) Structure domain knowledge

As the carriers of behavior domain knowledge, structure

owledge for innovative design.

domain knowledge is the description for a product in a viewof physic layout. It represents practical components toimplement corresponding theories or principles, and thenperform further functions. The following is the XML-basedstructure domain knowledge representation.

hStructure domain knowledgeihStructure nameiNameh/Structure nameihStructure IDiIDh/Structure IDihStructure entityiEntityh/Structure entityihStructure descriptioniDescriptionh/Structure descriptionih/Structure domain knowledgei

4.2. Mapping relationships

After the definition of the domain knowledge, which are the ba-sic elements involving in the knowledge for innovative design; therelationship among them also should be defined to construct hier-archies of domains and state space of designs for a certain product.The mapping relationships among domain knowledge could beclassified into 2 categories: (1) Relationship among the same do-main including: F-F, B-B, S-S mapping relationships, which linkthe domain knowledge to construct an integrated hierarchy for acertain domain. (2) Relationship among different domains includ-ing: F-B, B-S mapping relationships, which build bridges betweendifferent domains to construct an integrated state space of designs.No matter the type of the relationship, we use a uniform format todescribe them. Considering its virtue in representing structuralcharacteristic of resources, we adopt the XML to express mappingrelationship as follow.

hMapping relationshipihRelationship IDiIDh/Relationship IDihRelationship typeiTypeh/Relationship typeihExplanation for relationshipiExplanationh/Explanation forrelationshipihSource ID of mappingiID_Sourceh/Source ID of mappingihDestination ID List of mappingiID_List_Destinationh/Destination ID List of mappingihConstraint for relationshipiConstrainth/Constraint forrelationshipi

h/Mapping relationshipi

s with Applications 39 (2012) 5616–5624

Here, the source and destination of mapping relationship are re-lated to a certain item in domain knowledge, or a certain list of

items in domain knowledge respectively. Something more need toremark is that the relation among the list of destinations is ANDrather than OR, so we will use two or more mapping relationshipsto express OR situation.

4.3. Design cases

Case Base Reasoning (CBR), which is characterized by its capa-bility to capture past experience and knowledge for case matchingin various applications, is an emerging and well-accepted approachin the implementation of KM systems (Lau, Wong, Hui, & Pun,2003). Therefore, the design cases repository is the fundamentalfor analogy-based innovative design. During the process of design,the design cases will ‘grow’ as it ‘learns’ from experience and solv-ing new problems and designing new product. Its learning capabil-ities enhance product design’s skills, innovation and repository.Usually, case knowledge is difficult to represent due to cases’ com-plexity. Here, we use state space of design, which is mentionedabove, to model the design case knowledge. In fact, the designcases repository is a set of cases’ state space of designs. Its XML-based representation is shown as follow.

hDesign cases repositoryihCase 1: State space of designihFunction domain of caseiFunction of case 1h/Function

domain of caseihBehavior domain of caseiBehavior of case 1h/ Behavior

domain of caseihStructure domain of caseiStructure of case 1h/ Structure

domain of caseihMapping relationship of caseiMapping relationship of

case 1h/Mapping relationship of case ih/Case 1: State space of design i. . .. . .

hCase n: State space of designihFunction domain of caseiFunction of case nh/Function

domain of caseihBehavior domain of caseiBehavior of case nh/ Behavior

domain of caseihStructure domain of caseiStructure of case nh/ Structure

domain of caseihMapping relationship of caseiMapping relationship of

case nh/Mapping relationship of case ih/Case n: State space of design ih/Design cases repositoryi

5620 K. Wang, A. Takahashi / Expert System

4.4. Evaluation rules

In order to ensure the designing product is qualified to the ori-ginal design demands and embody its innovation, the evaluationfor the final design schema is essential in the process of productdesign. To this end, a method based on the analytic hierarchy in-dex is adopted in this paper. The hierarchies of the evaluation cri-teria are set up according to design demands and characteristicsof innovative design. It mainly consists of a hierarchy of evalua-tion index, fuzzy functions for each index; the weights of indexare also taken into account to ensure the rationality of theevaluation.

5. RDF-based knowledge model for innovative design

To support a geographically distributed work team to fulfill adesign task, or use the globally distributed Web resources ofknowledge, more and more attention have focused in KM system

or platform based on Web, especially Semantic Web, since theSemantic Web aims at providing services based on the ma-chine-understandable Web resources, and provides the acrossplatform media basis to exchange knowledge between distributedusers.

The XML-based RDF defines machine-understandable Web re-sources (which also includes the innovative design knowledge)using the object-attribute-value model. The ability to exchangeinformation between different applications means that the infor-mation may be made available to applications other than thosefor which it was originally created. Therefore, using RDF to mod-el the knowledge for innovative design, it will make the knowl-edge available for the applications on other sites rather thanonly local site. The knowledge will be shared by anyone whoneeds them. RDF Schema (RDFS) provides a type system forRDF. Then we could use the RDFS to model the knowledge forinnovative design.

5.1. Definition of classes and their relations

Before using RDFS to model knowledge, we should assign anamespace URI for the innovative design knowledge. Here, we as-signed it to prefix ‘‘idk:’’.

Xmlns:idk = http://nova-design-kdg.org/schemas; (note: inno-vation is marked by ‘nova’ for short)

In RDFS, a class is any resource having an rdf:type propertywhose value is the resource rdfs:Class. So the innovative designknowledge class would be described by assigning the class a URI-ref, say idk:Nova_Design and describing that resource with anrdf:type property whose value is the resource rdfs:Class. That is,nova-design-kdg.org would write the RDF statement in triplesform:

idk:Nova_Design rdf:type rdfs:Class (note: Nova_Design denotesclass of knowledge for innovative design)

Similarly, we could define the rule, constraint, formula, proce-dure, case classes as follow:

idk:Domian_kdg rdf:type rdfs:Class (note: Domian_kdg denotesclass of domain knowledge)idk:Mapping_kdg rdf:type rdfs:Class (note: Mapping _kdgdenotes class of mapping relationship)idk:Case_kdg rdf:type rdfs:Class (note: Case _kdg denotes class ofdesign cases)idk:Evaluation_kdg rdf:type rdfs:Class (note: Evaluation_kdgdenotes class of evaluation rules)

This kind of specialization relationship between two classes isdescribed using the predefined rdfs:subClassOf property to relatethe two classes. That is, nova-design-kdg.org would write theRDF statement:

idk:Domian_kdg rdfs:subClassOf idk:Nova_Designidk: Mapping_kdg rdfs:subClassOf idk:Nova_Design. . .. . .

RDF provides XML syntax for writing down and exchanging RDFgraphs, called RDF/XML. Unlike triples, which are intended as ashorthand notation, RDF/XML is the normative syntax for writingRDF. The definition of classes for engineering design using RDF/XML is shown as follow:

K. Wang, A. Takahashi / Expert Systems wit

h?xml version=’’1.0’’?ih!DOCTYPE rdf:RDF [h!ENTITY xsd ’’http://www.w3.org/2001/

XMLSchema#’’i]ihrdf:RDF xmlns:rdf=‘http://www.w3.org/1999/02/22-rdf-

syntax-ns#xmlns:rdfs=’’http://www.w3.org/2000/01/rdf-schema#’’xml:base=’’http://nova-design-kdg.org/schemas’’ihrdfs:Class rdf:ID=’’Nova_Design’’/ihrdfs:Class rdf:ID=’’Domain_kdg’’ihrdfs:subClassOfrdf:resource=’’# Nova_Design’’/i

h/rdfs:Classihrdfs:Classrdf:ID=’’Function_Domain_kdg’’ihrdfs:subClassOfrdf:resource=’’# Domain_kdg ‘‘/ih/rdfs:Classihrdfs:Classrdf:ID=’’Behavior_Domain_kdg’’ihrdfs:subClassOfrdf:resource=’’# Domain_kdg ‘‘/ih/rdfs:Classi. . .. . .

hrdfs:Class rdf:ID=’’Mapping_kdg’’ihrdfs:subClassOfrdf:resource=’’# Nova_Design’’/ih/rdfs:Classihrdfs:Class rdf:ID=’’Case_kdg’’ihrdfs:subClassOfrdf:resource=’’# Nova_Design’’/ih/rdfs:Classi. . .. . .

h/rdf:RDFi

5.2. Description for knowledge instance

To refer to these classes in RDF instance data located elsewhere,nova-design-kdg.org would need to identify the classes either bywriting absolute URIrefs, by using relative URIrefs together withan appropriate xml:base declaration. An instance for class offunction domian knowledge (idk:Function_Domain_kdg class) isdefined as follow:

h?xml version=’’1.0’’?ihrdf:RDF xmlns:rdf =’’http://www.w3.org/1999/02/22-rdf-syntax-ns#’’

xmlns:ex = http://nova-design-kdg.org/schemas#xml:base=’’http://nova-design-kdg.org/instances’’ihex: Function_Domain_kdgrdf:ID=’’Domain_function_1101’’/i

h/rdf:RDFi

5.3. Definition for attributes in knowledge classes

In addition to describing the specific classes of things they wantto describe, we also need to describe specific properties that char-acterize those classes of knowledge. In RDFS, properties are de-scribed using the RDF class rdf:Property, and the RDFS propertiesrdfs:domain, rdfs:range, and rdfs:subPropertyOf. Then, we alsouse function domian knowledge (idk:Function_Domain_kdg class)as an example:

hrdf:Property rdf:ID=’’Function name’’ihrdfs:domain rdf:resource=’’#Function_Domain_kdg’’/ihrdfs:range rdf:resource=’’& xsd:string’’/ih/rdf:Propertyihrdf:Property rdf:ID=’’Function ID’’ihrdfs:domain rdf:resource=’’#Function_Domain_kdg’’/ihrdfs:range rdf:resource=’’& xsd:string’’/ih/rdf:Propertyihrdf:Property rdf:ID=’’Function description’’ihrdfs:domain rdf:resource=’’#Function_Domain_kdg’’/ihrdfs:range rdf:resource=’’& xsd:string’’/ih/rdf:Propertyi

The corresponding RDF triples are:

idk:Function name rdf:type rdf:Propertyidk:Function name rdfs:domian idk: Function_Domain_kdgidk:Function name rdfs:range xsd:string. . .. . .

Other types of innovative design knowledge would be defended asabove similarly. Due to the limited space, other definitions areomitted

5.4. An example for a knowledge case based on RDF/XML

We use an example, an F-B mapping relationship, to illustratethe method for knowledge expression. The simple example of F-Bmapping relationship relates the different ways for luminescence,including: high intensity discharge (HID), light emitting diode(LED), and so on. Here, we just enumerate 2 sorts to explain aboveproposed method.

Suppose, the URI of the F-B mapping relationship is:

‘‘http://nova-design-kdg.org/instances/F-B_mapping_2101’’

The F function domain element (luminescence) is an instancebelong to class of function domian knowledge (Func-tion_Domain_kdg); while the two behavior domain elements(HID, LED) are instances belong to class of behavior domain knowl-edge (Behavior_Domain_kdg). Their URIs are:

‘‘http://nova-design-kdg.org/instances/Domain_function_1101’’‘‘http://nova-design-kdg.org/instances/Domain_behavior_1201’’‘‘http://nova-design-kdg.org/instances/Domain_behavior_1202’’

Then, the F-B mapping relationship is described using RDF/XMLas follow:

h?xml version=’’1.0’’?ihrdf:RDF xmlns:rdf = http://www.w3.org/1999/02/22-rdf-

syntax-ns#xmlns:s=’’http://nova-design-kdg.org/schemas#’’ixml:base=’’http://nova-design-kdg.org/instances’’ihrdf:Description rdf:about=’’http://nova-design-kdg.org/

instances/F-B_mapping_2101’’hs:ID_Sourceihrdf:Bagihrdf:li rdf:resource=’’# Domain_function_1101’’/ih/rdf:Bagih/s:ID_Sourceihs:ID_List_Destinationihrdf:Bagihrdf:li rdf:resource=’’# Domain_behavior_1201’’/ihrdf:li rdf:resource=’’# Domain_behavior_1202’’/ih/rdf:Bagih/s: ID_List_Destinationi. . .. . .

h/rdf:Descriptionih/rdf:RDFi

h Applications 39 (2012) 5616–5624 5621

6. Construction of the repository for semantic web application

The construction of the repository is one of key issues involvingin knowledge modeling, and it is the implementation of knowledgerepresentation in a view of physical layout. How to store theseknowledge, in which forms, and how to design the ApplicationInterface (API) for the upper applications, all of which should be

Fig. 4. The framework for the innovative design KM system on Semantic Web.

Table 2URI numbered table.

id URI

. . .. . .

00007 http://www.w3.org/1999/02/22-rdf-syntax-ns/type. . .. . .

00011 http://www.w3.org/1999/02/22-rdf-syntax-ns/Property. . .. . .

00101 http://nova-design-kdg.org/schemas/Functionname00102 http://nova-design-kdg.org/schemas/FunctionID. . .. . .

5622 K. Wang, A. Takahashi / Expert Systems with Applications 39 (2012) 5616–5624

determined in the process of building the repository. It will pavethe way for developing innovative design knowledge managementsystem on Semantic Web. The Fig. 4 illustrates its general frame-work; this section mainly focuses on the construction of the lower2 lays on the basis of the knowledge model mentioned in abovesections.

6.1. Text files storage: A text-form repository

After the engineering knowledge is represented using RDFS,method for the knowledge storage in the web-based applicationneeds to be determined. Since the RDF/XML code is a kind ofXML file, we usually choose text file as the RDFS-formatting knowl-edge storage. However, text file storage is not as good as the data-base storage in the aspects of volume, security etc.

As to the above web-based applications, they need a interface toconnect the text file storage. The interface would transform theRDF/XML text files into RDF triples using the RDF Parsers.

6.2. Database storage: A database-form repository

RDF is very similar with database, as the properties in RDF cor-respond to the columns in database tables. However, if we storethe RDFS-formatting knowledge in that way, it will make the data-base table contain huge amounts of columns since we must bringall the properties referred in all the records into the table as col-umns. In addition, the database table would be sparse becauseeach record is only related to a few columns. Therefore, databasestorage in above way will be wasteful and impractical.

We adopt another way that is storing the RDF triples directly,which just contain subject, predicate, and object, so the databasetable just also contains 3 columns: subject column, predicate col-umn, and object column, as shown in Table 1. In fact, each subject,predicate, and object is a URI ref, so the units in database table con-tain only URI Ref. Considering the repetition and length of URI ref,we assign a number to each URI ref and build another table to storethe numbered lists, as shown in Table 2. Then, as to the above RDFtriples table, each unit only needs to store numbers rather than along URI Ref. It would be both space-saving and convenient forsearch.

For example:idk:Function name rdf:type rdf:Propertyidk:Function ID rdf:type rdf:Property

Table 1RDF triples table.

Subject Predicate Object

. . .. . .

00101 00007 0001100102 00007 00011. . .. . .

6.3. API for the RDF-based repository

After constructing the RDF-formatting repository, we should fo-cus on the bridge between the repository and the above SemanticWeb based applications. Take account of different formats forknowledge storage, we choose the RDF triples as the media inthe process of transforming data, since the triple is the intrinsicformat for RDF. The Fig. 5 illustrates the detail of API as follow.

The data stored in text file will be transformed to RDF triplesthrough RDF parser, while the data in the database need no trans-formation. As to the above web-based application, the key problemlies in the data model for RDF-format knowledge. The RDF_CoreDa-ta in the Fig. 5 is the bridge between the RDF triples and aboveSemantic Web based application. It is a class, and consists of 3 sub-classes: RDF_Class Class, RDF_Property Class, RDF_Instance Class.Their definitions are shown as follow:

Class RDF_Class::RDF_CoreData{

RDF_Property property (Note: the properties involved in theclass)

. . .. . .

}Class RDF_Property::RDF_CoreData{

RDF_ Class domain (Note: the classes which the propertybelong to)

RDF_ Class range (Note: the type of the property). . .. . .

}Class RDF_Instance::RDF_CoreData{

RDF_ Class class (Note: the classes which the instancebelong to)

. . .. . .

}

Fig. 5. The data transformation in RDF API.

K. Wang, A. Takahashi / Expert Systems with Applications 39 (2012) 5616–5624 5623

The 3 classes represent the classes, properties, instances definedin the RDF Model. For example, idk:Function_Domain_kdg (class‘‘function domain knowledge’’) is related to RDF_Class Class;idk:Function name (the property ‘‘Function name’’ in the class‘‘function domain knowledge’’) is related to RDF_Property Class;Domain_function_1001 (an instance of class ‘‘function domainknowledge’’) is related to RDF_Instance Class.

7. Knowledge model’s application for distributed collaborativedesign

Considering above knowledge modeling to the innovative de-sign knowledge on the Semantic Web as a prelude to the mean-ingful agent communication for collaborative work amongmultidisciplinary organizations, this paper brings out a multi-agent system architecture for distributed collaborative design.The multi-agent system architecture mainly include middlewarelayer, agent layer, ontology layer, service layer, and interfacelayer.

The middleware layer supports distributed application agentscollocated within the collaborative virtual agent level and seman-tically integrated within a FIPA-compliant Java Agent DevelopmentEnvironment (JADE) (Bellifemine, Poggi, & Rimassa, 2001), whichprovides an agent middleware to support agent representation,agent management, and agent communication. For example, thecontrol agent is responsible for managing operation on Web ser-vices such as enhancement of system security and reconciliationof resource competition; the case agent is responsible for distrib-uted case base management; and the knowledge agent managesthe distributed knowledge hierarchy.

A meaningful communication in a multi-agent distributedcollaborative design system is possible only in the case thatthe communicating agents achieve their knowledge interopera-bility. Agent Communication Languages (ACLs) provide agentswith a means of knowledge interchange format. The two mostwidely used ACLs are the Knowledge Query and ManipulationLanguage (KQML) and, more recently, the Foundation for Intelli-gent Physical Agents-Agent Communication Language (FIPA-ACL)(Foundation for Intelligent Physical Agents, 2002). The work de-scribed in this paper adopts FIPA-ACL, which enables agents tocollaborate with each other by setting out encoding, semanticsand pragmatics of the communicating messages. The format ofFIPA-ACL mainly consists of the message type, the identities ofthe sender and receiver agents, the language to express the con-tent of messages exchanged between agents, the ontology toprovide terms for giving a meaning to the symbols in the con-tent expression, the protocol to specify the interaction protocolthat the sending agent employs, and the content to representthe product innovative design knowledge exchanged betweenagents.

This paper seeks to apply the Semantic Web technologies tohelp develop the multi-agent architecture based on innovativedesign knowledge modeling, which will support knowledge ex-change and sharing in the process of innovative design basedon a common ontological foundation, and be used as a contentlanguage within the FIPA-ACL messages. The query request forinnovative design knowledge ontology at the ontology layer canbe transformed from FIPA-ACL messages into OWL-QL format(Fikes, Hayes, & Horrocks, 2003), while the innovative designknowledge ontology with OWL format can be encapsulated intoFIPA-ACL messages to facilitate communication and sharingamong multiple agents. Following codes illustrate an example ofFIPA-ACL messages in which design agent_1 informs designagent_2 that an instance of compressor cylinder with convert-motion function is retrieved.

(inform: sender (agent-identifier

: name design-agent1@fketcu.com: addresses (sequence http://fketcu.com:6671/jade))

: receiver (set (agent-identifier: name design-agent2@ fketcu.com: addresses (sequence http://fketcu.com:6670/jade)))

: languageOWL: ontologyhttp://www.owl-ontologies.com/innovative-

design-ontology.owl: protocol (fipa-inform): contenthrdf:RDF

xmlns:rdf=’’ http://nova-design-kdg.org/schemas#’’xmlns:xsd=’’http://www.w3.org/2001/XMLSchema#’’xmlns:rdfs=’’http://www.w3.org/2000/01/rdf-schema#’’xmlns=’’http://www.owl-ontologies.com/innovative-design-ontology.owl#’’xml:base=’’http://www.owl-ontologies.com/innovative-design-ontology.owl’’ihowl:Ontology rdf:about=’’’’/owl:imports = n’’http://www.owl-ontologies.com/innovative-design-ontology.owl’’/i. . .. . .

hCompressor-cylinder rdf:ID=’’compressor-cylinder-SM06’’ihAchieves rdf:resource=’’#Convert-motion’’/ihOuter-diameter

rdf:datatype=’’http://www.w3.org/2001/XMLSchema#string’’i55 mmh/Outer-diameterihAir-consumption

rdf:datatype=’’http://www.w3.org/2001/XMLSchema#string’’i300cm3h/Air-consumptionihPressure

rdf:datatype=’’http://www.w3.org/2001/XMLSchema#string’’i0.1–0. 7 MPah/PressureihStroke

rdf:datatype=’’http://www.w3.org/2001/XMLSchema#string’’i25–300 mmh/StrokeihSignal-pressure

rdf:datatype=’’http://www.w3.org/2001/XMLSchema#string’’i0.02–0. 1 MPah/Signal-pressureihPower rdf:datatype=’’http://www.w3.org/2001/XMLSchema#string’’i50 Wh/PowerihMax-force

rdf:datatype=’’http://www.w3.org/2001/XMLSchema#string’’i30 Wh/Max- forceihEnviron-temp

rdf:datatype=’’http://www.w3.org/2001/XMLSchema#string’’i5–60degreeh/Environ-tempihPistol-diameter

rdf:datatype=’’http://www.w3.org/2001/XMLSchema#string’’i30 mmh/Pistol-diameterih/Compressor-cylinderi. . .. . .

h/rdf:RDFi)

The interface layer provides a graphic front-end such as navi-gation structures, knowledge visualizations, and semantic brows-

ers to the distributed designers and supports the incrementaldevelopment of user queries in a graphic and semantic way. Theinterface layer also provides a back-end to access various ontol-ogy-based Web services such as semantic annotation service,ontology registration service, aggregate directory service, ontologytransformation service, knowledge query service, knowledgereasoning service and inference service at the service layer to

5624 K. Wang, A. Takahashi / Expert Systems with Applications 39 (2012) 5616–5624

facilitate knowledge consumption, reuse and supply on theSemantic Web.

8. Discussion and summary

Comparing with the previous research work of other scholars,the major differences consist of four aspects:

(1) A detail knowledge model is brought out for innovativedesign, while others’ research mainly focus on generalknowledge model, or just related to general form of design,usually the design in detail stage rather than innovativedesign.

(2) A Semantic Web based knowledge representation method isemployed to model the knowledge involved in innovativedesign. Generally, majority of scholars concern SemanticWeb based knowledge representation framework for generalknowledge, Web source, or documents and so on; few ofthem is related to engineering design knowledge, especiallythe innovative design knowledge.

(3) This paper brings forward a detail and comprehensivescheme for repository construction, which can store theRDF-based knowledge in normal relational database in a cre-ative way. This aspect of work is often neglected in others’research.

(4) The proposed innovative design knowledge modeling extendstraditional product modeling with capabilities of innovativedesign, knowledge sharing and distributed problem solving,and is employed as a content language within the messagesin the proposed multi-agent system architecture.

Innovation is becoming more and more crucial in engineeringdesign, and a geographically distributed collaborative work modeis becoming prevalent. Moreover, the Semantic Web is a trendfor the evolution of internet, and knowledge management (KM)is hotspot in academia. As to the developing the Semantic Webbased innovative design KM applications, this paper made a preli-minary attempt at using the Semantic Web technologies for inno-vative design knowledge modeling in a multi-agent distributeddesign environment. The proposed approach is viewed as a prom-ising knowledge management method that facilitates the imple-mentation of computer supported cooperative work in innovativedesign of Semantic Web applications.

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