Research of Ontology Modeling in Structure Engineering Grid LONG Hao1,2, LU Hai1, Di Rui-Hua1

1.School of Computer Science,Beijing University of Technology,Beijin,100124,China 2.School of Software,JiangXi Normal University,Nanchang , 330022,China

hhlong@emails.bjut.edu.cn

Abstract—Combining ontology with grid technology and applying them into the structure engineering is an inevitable trend and demand for engineers and researchers. Concerned with the semantic conflicts during resource integration and sharing, an ontology-based framework of the structure engineering grid is introduced, a method for designing the ontology model of the structure engineering grid is proposed, which consists of three types of ontology concept: Data types of Ontology, Core Ontology and Grid service Ontology, and the particular description of their functions and relations are given. The framework and the model are flexible and suitable for structural experimental resource integrating and searching.

Keywords: Semantic Grid; Framework; ontology model; resource integrating & searching

1 INTRODUCTION

Grid is an innovative computing paradigm appeared in 1990s, during the past 10 years, it has been developing into an advanced technology and an important research, increasing popular in E-world, profiting from the developing of WWW science and technology, their infrastructures and academe effort[1,2]. Grid systems usually integrate large numbers of heterogeneous and distributed resources, which leads to a lot of semantic conflicts during information integration and sharing, many researchers made contributions to put semantics into grid technology, aiming to provide intelligent information understanding and retrieval for the users. Because of its high accessibility, nice operational flexibility, and good extensibility for dynamic and distributed resources, intelligent information sharing and collaboration, semantic grid has had many successful stories in different scientific domains.

This paper intends to apply semantic grid technology into structure engineering to support collaborative experiments for researchers and engineers. Firstly, an ontology-based framework of the structure engineering grid is introduced, a method for designing the ontology model of the structure engineering grid is proposed, where three types of ontology concept are defined; Data types of Ontology, Core Ontology and Grid service Ontology, and the particular description of their functions, constitutes and relations with each other are given. Then an ontology-based resource integration model is introduced. The model is flexible and extensible, and is suitable for execution of collaborative

structure engineering experiments. This paper is organized as follows. Section 2 reviews

the related works. In section 3, we describe the ontology-based framework of the structure engineering grid, Section 4 discusses the ontology model. Finally Section 5 concludes the paper and outlines the future work.

2 RELATED WORKS

2.1 GRID TECHNOLOGY IN STRUCTURE ENGINEERING

Structure is the framework of the buildings, any structure damage induced by faulty design or bad maintenance implies great threaten to public security. The designer must do experiments to verify the structure before construction, and the owner need evaluate the building’s structure performance frequently. With the wide use of sensor, automation and simulation technologies in structure engineering, engineers and researchers are inclined to combine distributed personnel and experimental resources(including data, simulation system, spot devices and related software) to execute collaborative experiment or monitoring, surely semantic grid is an eligible choice.

Many grid projects have been launched to establish networked structure laboratory. The most successful attempt might be NEES[3,4](Network for Earthquake Engineering Simulation). The infrastructure of NEES provides the experimental equipment, the analytical modeling tools and the network interface to conduct simultaneous testing of multiple large-scale experimental substructures and complex numerical models using distributed resources on the Internet[5,6]. Inspired by NEES, an ambitious project, KOCED (Korean Construction Engineering Development) was started in Korea to build and connect 12 large testing facilities at the major universities distributed over the country using high performance information network[7]. In Taiwan, a platform, called ISEE(Internet-based Simulations for Earthquake Engineering),has been developed for collaborative networked structural experiments among distributed structural laboratories. Similar testing platform also has been developed in Japan. In China some researchers also made great efforts. Hunan University, Tsinghua University and Harbin Institute of technology cooperated to develop a remote collaborative experiment demonstration system called HQH-NSER[8],in 2003 China Earthquake Administration and China Aerospace Science&Industry

2009 Fourth ChinaGrid Annual Conference

978-0-7695-3818-1/09 $26.00 © 2009 IEEE

DOI 10.1109/ChinaGrid.2009.33

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Corp. sponsored CEDA Grid(China Earthquake Disaster Alleviation and Simulation Grid)[9]. From 2006 we began to construct a networked experimental system called ESESGrid(Engineering Structure Experiment and Simulation Grid), in literature [10], a service-oriented, multi-layer framework and the key implementation technologies of ESESGrid were discussed. Now a demo system of ESESGrid is under testing in a structure engineering center. Its efficiency and feasibility are proved with good performance, with it structure engineers and researchers can handle and operate different physical experimental instruments remotely, distributed resources can be connected together to support complex structure experiments, and experimental results can be visualized in front of interested participators instantly.

2.2 ONTOLOGY AND OWL-S

Ontology provides a formal, shared specification of concepts, their relationships, and other realities of some domain, which can reduce or eliminate confusion of terminologies, enable computers to process domain knowledge more precisely and conveniently. Since 1990s, ontology has developed from AI field to computer field, and becomes a popular research topic in various communities such as knowledge engineering, natural language processing, intelligent information integration and knowledge management, etc. The existing famous ontologies are CYC, WordNet, CIAWorld FactBook, (KA)2 and Tourism.

Various kind of formal languages are used for representing ontology, such as Description Logics, Frame-Logic, and special languages for Semantic Web such as OXL, OWL and OIL, etc. OWL-S is defined as a W3C standard to provide a computer-interpretable description of the services, service access and service composition using OWL ontologies. Building on SOAP and WSDL, the OWL-S services can be dynamic executed on the web.

OWL-S Upper Ontology is composed by three elements: ServiceProfile, ServiceModel, and Service Grounding. The ServiceProfile tells “what the service does” including description of what is accomplished by the service, limitations on service applicability and quality of service. The ServiceModel tells “how to use the service”, also detailing, where necessary, the step by step processes leading to the outcomes(Control/Data flows). The Service Grounding specifies the details of how the service can be accessed, typically a grounding will specify a communication protocol, message formats ,and other service-specified details.

3 THE ONTOLOGY-BASED FRAMEWORK OF THE STRUCTURE ENGINEERING GRID

To solve semantic conflicts during resource integrating

and ensure intelligent information searching, an ontology-based framework of the structure engineering grid is proposed based on previous work, which is a four-layer hierarchical architecture, including Resource Layer, grid service Layer, semantic service layer and Application Layer. As showed in figure 1.

Resource Layer consists of all distributed structure engineering experimental resources, such as physical experimental instruments and equipments(Data acquiring systems, Shaking Table Array, Multi-function Electro-Hydraulic Loading System, etc.), simulation programs and virtual structure models, history experimental databases, ontology knowledge repository, and calculating , storage , network resources, etc.

Grid service Layer provides a running environment for grid services associated with experimental resources. It utilizes those public grid services in CGSP(ChinaGrid Support Platform), including indexing, monitoring, scheduling, deploying and registering functions, moreover, it make some improvements to support structure engineering applications.

Semantic layer supports uniform data and knowledge integration to avoid semantic conflicts. Here heterogeneous domain acknowledge and data from distributed locations is organized and defined uniformly. According to the mapping rules between ontology and real resources or data, Ontology-based query is parsed and appointed to the grid services in the grid service layer.

Application layer provides interface between the users and the system. Here users can access resources using ontology-based query, without caring the difference between resources.

Figure 1 the ontology-based framework of the structure engineering grid

4 the Ontology Model of Structure Engineering Grid

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4.1 THE ONTOLOGY MODEL

A goal of designing the ontology model of the structure engineering grid is to satisfy distributed and collaborative experimental resource sharing with flexible, reusable, dynamic features in higher level, and allow user to discover, access, integrate and disseminate knowledge in distributed environments. The capability of the model would cover access, descriptive, functional and structural features. Figure 2 shows the stack model that includes three ontologies:

Data types ontology: Describing the data types that the domain ontology uses.

Core ontology: Defining the knowledge representation entities that includes domain ontology, SLA(Service Level Agreement)[11] ontology, spatial ontology, access control ontology at the knowledge level.

Semantic Grid service ontology: Describing encapsulated structure engineering experimental resources concepts with OWL language, normally these resources are programmed as web services, therefore their internal structure and functional features are presented here.

Figure 2 the ontology model of the structure engineering grid

4.2 CORE ONTOLOGY Core ontology describes the basic knowledge, the

concept and relation of resource representation. Core ontology is showed in figure 2. as Figure 3 shows, it consists of four parts: structure engineering ontology, SLA ontology, spatial ontology, and access control ontology. In this project, we directly reuse the SLA ontology in literature [12], other ontologies is described below in detail.

ACCESS CONTROL ONTOLOGY In the structure engineering grid, heterogeneous

resources belong to different organizations with diverse access control policies, the Access Control Ontology is designed to represent such information. The Permission concept describes different privileges of the system and different resources, which are further specified by the SystemPermission concept and the GridResourcePermission concept respectively. The Role concept describes a set of

privileges. The User concept specify the grid users, managers and resources providers, they can be classified by the UserGroup concept. Any role and single permission can be assigned to certain user and user group.

SPATIAL ONTOLOGY In structure engineering grid some resources are

connected with physical experimental equipments, which usually are called location-based services. Their positional information is important in resource searching, equipment management and experiment scheduling. The Location concept describes the positional information of grid resources, organizations or users, which can be administrative(the AdministrativeLocation concept) or geographical(the GeographicalLocation concept), sometimes an administrative location is linked with a given geographical location. The Organization concept can be viewed as a special administrative location. In this paper we use DNS and URI to represent geographical and administrative position respectively.

STRUCTURE ENGINEERING ONTOLOGY This ontology contains descriptions about the domain

knowledge and data that used in structure engineering experiments, which describe experimental activities(Project, Experiment, Trial), methodology(Experimental Method), objective(Structure Component, Material), facility(Grid Resource Group, Grid Resource, Grid Resource Configuration, Load Equipment, Measure Equipment, Channel Group, Channel, Sensor ),result(Output, Processed Output).

The Project concept describes a collection of structure engineering experiments carried out by certain organizations or users and designed to achieve specific goals. A project includes one or more related experiments and can be sponsored by one or more funding sources. The Experiment concept describes an independent task belonging to a particular project and is configured with a structure component, a group of equipments, an experimental method and an output scheme, it can be a dynamic, static, pseudo-dynamic, or pseudo-static one and can be executed many times. Each an execution process of any experiment is described by the Trail concept.

The Structure Component concept describes the component producing policy and other information of experimental objects, their constitution is specified by the Material concept.

The Grid Resource Group concept describes resource set, and the Grid Resource concept describes its members, possibly it is a load equipment, or a measure equipments, and its default setting is specified by the Configuration concept. Physically each measure equipment is linked with several sensors, each sensor is called a channel, they are described by the Sensor concept, the Channel Group

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concept and the Channel concept respectively. The Load Strategy concept and the Measure Strategy

concept prescribe load equipment operating policy and measure equipment setting policy for experiment and trail.

The Output concept describes the acquired data of an experiment, which normally is stored as a whole, identified with a location tag and can be further processed.

Figure 3 Core ontology

4.3 SEMANTIC GRID SERVICE ONTOLOGY Semantic grid service ontology provides uniform

semantic knowledge mainly replicates the OWL-S ontology’s upper-level concepts, moreover, some grid service features and related concepts are appended. The Semantic Grid Service Ontology is showed in figure 4.

The grid resource concept extends the service concept of OWL-S, it represents grid resource object, and it’s a kind of state grid resource, its configurable lifecycle is specified by the Grid Resource life Time concept, its properties are described by the Grid resource configuration concept and the resource property concept.

The semantic grid service concept is a subclass of grid service representing encapsulated grid service with ontology, it can be primitive or composite, and is described

by the semantic grid service grounding concept, the semantic grid service profile concept and the semantic grid resource process concept.

The semantic grid service profile concept specifies its ability, including functional features(service specification, classification, responsibility, etc.)and nonfunctional features(input, output, precondition, result, etc. ).

The semantic grid resource process concept specifies the execution process of the service, including exposed operations, their relations, and operating parameters.

The semantic grid service grounding concept is a subclass of serviceModel in OWL-S, it realizes the parameter mapping and binding between transforming messages and WSDL messages, and enables locating of grid service and accessing to resource state properties.

Figure 4 Semantic Grid Service Ontology

4.4 ONTOLOGY USAGE EXAMPLE In this paper we use Protégé3.3.1 to develop structure

engineering ontology model, it is described by OWL DL and stored as OWL documents. And we use embedded reasoner model “Infmodel” in Jana[13] to realize reasoning. Each relation is specified by a triple composed of a subject, a predicate, and an object, where the subject and the object are represented by “Resource”, the predicate is represented by “Property”. By specifying the subject and the predicate, the corresponding objects can be inferred. Figure 5 gives an example of reasoning equivalent class of “Material”.

Property predicate= infmodel.getProperty( "http://www.w3.org/2002/07/owl#equivalentClass"); Resourcesubject=infmodel.getResource( "http://www.owl-ontologies.com/Material.owl#Material"); StmtIterator i = infmodel.listStatements(subjec，predicate，null)

Figure 5 an example of reasoning Semantic grid service is the basic component which is

capable of realizing some kind function of the grid, and it relying on a certain structure engineering experimental facility, presently many such facilities are windows

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platform-based(for example, DAQ system as CronPL, Cansas). To support semantic technology they are firstly encapsulated as grid web services using C#, we use Protégé3.3.1 and OWL-S plugin to describe their interfaces, processes, interactions and other specifications with OWL-S.

5 CONCLUSION AND FUTURE WORK

Semantic grid will acquire much more attention from public because it can provide users better service quality with its understanding of knowledge. Structure engineers and researchers will profit from the exploration of this paper. Because our work is still in base section, many questions, such as ontology matching efficiency, searching quality, etc. require more efforts

ACKNOWLEDGEMENT

This research is supported by National Natural Science Foundation of China under Grant No. 007000548108. the Foundation of Beijing institute of Education under Grant No.JJ007011200901. REFERENCES [1] De Roure, D.Hendler, J.A, E-Science: the grid and the Semantic Web. IEEE Intelligent Systems, 2004,19(1),pp.65-71

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