Methods for Representing and Accessing Material Property Data and

Chapter 28

Methods for Representing and Accessing Material Property Data and Its Use With Decision Support Systems

Downloaded by EAST CAROLINA UNIV on January 3, 2018 | http://pubs.acs.org Publication Date: April 15, 1999 | doi: 10.1021/bk-1999-0722.ch028

Lawrence J. Kaetzel National Institute of Standards and Technology, Building 226, B350, Gaithersburg, M D 20899

Improved methods are needed to access and understand coating knowledge that is stored in computers. Today, a proliferation of the Internet allows organizations to distribute information efficiently. However, shortcomings exist in the ability to assess its validity, quality, and completeness. This paper presents activities of the coating industry and government organizations that will improve decision-making for coating systems through improved understanding of the material properties and predicted performance.

Introduction The coating industry is represented by a diverse collection of entities including raw material suppliers, coating manufacturers, facility owners, researchers, and trade associations. This diversity creates difficult problems for managing and sharing knowledge, in part, due to the sheer volume of information, the capability to provide convenient access and timely delivery, the ability to interpret content and formats (compatibility), and data quality issues. The need to address these problems and develop new strategies for representing and sharing knowledge is never more apparent then when seeking and retrieving information from the Internet. The Internet's capabilities and content are often overstated and in many instances provide the user with little to show for the time invested in searching and interpreting knowledge. Several factors are responsible for this dilemma: • • • •

search capabilities are inadequate due to inconsistencies in the way knowledge is stored and displayed; computer hardware and software are often incongruous; users lack confidence in the developer or content; results are out-of-context or the terminology used is inconsistent; and

U . S . government w o r k . Published 1999 A m e r i c a n C h e m i c a l Society

Bauer and Martin; Service Life Prediction of Organic Coatings ACS Symposium Series; American Chemical Society: Washington, DC, 1999.

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user interfaces can be cumbersome to use (not logically organized or performance is lacking).

The National Institute of Standards and Technology (NIST) has initiated an activity to address the construction industry's information needs. The ComputerIntegrated Knowledge System (CIKS) Network, along with industry and government partners, is developing solutions for construction industry knowledge users. CIKS is an activity of the NIST, Building and Fire Research Laboratory, High-Performance Construction Materials and Systems Program. Planning for the development of CIKS was initiated at a workshop held in June of 1996. Participants at the workshop identified pilot projects and opportunities for collaboration. The results of the workshop were published in a NIST report [1]. An Internet World Wide Web [W ] is operational where the CIKS workshop report can be viewed on-line, as well as other CIKS information. The W address is: http://www.ciks.nist.gov During the CIKS workshop, a coating material working group was established and this working group is currently involved in the development of several pilot projects that will be described in detail later in this article. 3

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CIKS collaborative efforts include interactions with construction industry groups such as the Civil Engineering Research Foundation's (CERF), CONMAT (CONstruction MATerials) Council. In 1994, a CERF Coating Industry Working Group identified major research projects that address coating industry knowledge. These projects were described in a CERF report [2]. The Coating Industry Working Group identified Data and Cost Analysis and Technology Transfer as knowledge related areas that are important to the coating industry. These projects involve the development of standard data formats, engineering management systems, and the development of standard guides and procedures for successful use of highperformance coating systems. The report also identifies specific government agencies, private industry associations, and companies that have the expertise to address the research projects. Accomplishing the goals will require partnerships among the organizations. Figure 1 shows the interactive framework that has been established for CIKS and is currently being used as a framework for construction industry interactions.

An Overview of CIKS The term "computer-integrated knowledge system" indicates that the scope of CIKS is broader than just compiling data and developing application programs. The CIKS system involves establishing a sound information infrastructure for consistent terminology, information standards, and interoperable systems that apply across construction industry disciplines and a variety of construction industry activities. Figure 2 shows a hierarchy and CIKS components. A meta model has been developed for the CIKS activity. For the purpose of this article, a "meta model" is a high-level representation of processes, knowledge formats and sources, and interfaces that describe a logical framework for CIKS. Describing the meta model is a complex exercise and would extend beyond the scope of this article. For readers



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Figure 1: CIKS Partners and working groups. who wish to gain a more complete understanding of the CIKS meta model, a detailed description can be found in a NIST Internal Report [3]. Implementation of CIKS includes making available prototype knowledgebased systems, developed jointly by NIST and industry, and testing existing production systems for interoperability. Construction industry practitioners, such as building designers, contractors, materials engineers, and specifiers are the intended users of CIKS.

Figure 2: CIKS components and their hierarchy.


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CIKS knowledge-based prototype systems incorporate virtually all forms of knowledge, from raw data to high-level human expert facts and rules-of-thumb. Knowledge sources involve both the public and private sector. Forms of generic and project knowledge to be represented in CIKS include computer-based models, databases, decision-support systems, standards, images, catalogues, handbooks, manuals, and integrated project knowledge bases. When complete, CIKS will incorporate features such as cataloguing, indexing, intelligent searching, retrieval, routing, browsing, query and interpretation, presentation systems, distance learning, help facilities, and collaborative authoring. CIKS computerized systems use enabling information technologies that provide an open-systems framework that will ensure interoperability. Examples include intelligent search engines or agents that can find data in context on the Internet W and multimedia capabilities that incorporate visual information that enhances knowledge interpretation. Standards developed by the International Standards Organization (ISO), the American National Standards Institute (ANSI), and the American Society for Testing and Materials (ASTM) will play a vital role in the implementation of CIKS. 3

The established goals for CIKS include developing: • universal electronic access to distributed knowledge, information and data; • application systems (prototype and production) that use the data, information, and knowledge to aid in (1) construction materials design, processing, selection and testing, and (2) facility design, construction (or installation and application), operation, maintenance, and repair; • an open test bed at NIST for industry, academia, and government partners to build prototype systems , evaluate existing production systems, and to test enabling information technologies; and • the implementation of commercial-scale systems, developed, deployed, and maintained by industry.

To meet these goals, new methods must be implemented that will bring about more coherent and reusable systems. This must start with the establishment of a consistent terminology for defining terms, such as those used by the coating industry when specifying products and equipment. Once a terminology base is established, process and data models must be developed. Process models or activity models, as they are often called, describe how knowledge is used. Data models show the data sources and data types for a process or activity model. These two types of models fall into a category described in the CIKS Meta Model as Data Management. Two activities and areas that involve the investigation and development of information models are Ontologies (process and data models), and the ISO, Standard for Product Data Exchange (STEP) [4,5]. Efforts to organize and communicate information


431 using Ontologies are being addressed by the artificial intelligence community [6]. An example of this work can be found at the Stanford University, Knowledge Systems Laboratory in the development of the Ontolingua server [7]. The Ontolingua server allows collaborative authoring of ontologies via the Internet W and may be useful in the development of CIKS. 3


The STEP effort has focused primarily on defining protocols for the exchange of computer aided design information (e.g., drawings and product specifications). However, to date, no significant work has involved construction materials knowledge. The use of Ontologies and STEP are being investigated to assess their application within the CIKS meta model. For CIKS to achieve its goals within the projected 5-year timeframe, new collaborative agreements and partnerships with industry will be required. The test bed that has been established at NIST will play an important role. Opportunities will be provided for industry and organizations to test existing and prototype systems. This will involve on-site guest researcher appointments as well as remote access to the test bed via the Internet. A variety of computing platforms and information technologies will be involved in the testing. The capabilities currently operational in the test bed include multi-platform computer systems such Unix© and Microsoft NT operating systems. Database management systems for designing, storing, and retrieving database information via the W is operational. Information standards, such as Remote Data Access (RDA) [8] and ANSI SQL database standard [9] were used in the development of the computerized systems. Specific examples include the implementation of a paint proficiency sample database administered by the American Association of State Highway and Transportation Officials (AASHTO) Materials Reference Laboratory (AMRL). Members of the AMRL staff are currently extending the capabilities of the computerized system by developing new W applications through the use the CIKS test bed. The new on-line capabilities will enhance the representation and communication of information involving proficiency sample tests for the AASHTO State Department of Transportation member agencies by providing more timely data acquisition and retrieval. 1

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Another prototype CIKS has been developed for high-performance concrete and is described in a report published by NIST [10]. An example of an implementation of a CIKS high-performance concrete system was described in a recent article in Concrete International [11]. The system uses an Internet W as an interface, and multiple forms of knowledge, such as computer-based models, material property databases, and bibliographic information. It is designed to predict the service life of chloride-exposed steel-reinforced concrete. Additional databases containing coating product data and asphalt materials are being considered for development at this time. Future applications will involve the use of intelligent 3

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The mention of commercial products and services in this paper does not constitute an endorsement of the National Institute o f Standards and Technology. Their purpose is to show clarity and provide examples. © is a registered trademark licensed exclusively by Xopen Company Limited.


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agents, decision support systems, and a common user interface strategy for distributed systems. Many of these efforts will be carried out through collaboration with the CIKS Material Working Groups. The CIKS network will potentially serve the whole range of stakeholders within the construction community, and the benefits to the construction industry should be considerable. The increased access to knowledge, coupled with improved materials and facility design, construction, and operation and maintenance should help reduce project delivery time, increase the service life of constructed facilities, and reduce maintenance and repair costs. Moreover, CIKS should help reduce cost increases/overruns and lost time caused by change orders, rework, and reengineering. It will have a far-reaching impact on activities such as the development and issuance of standards and guides to the establishment of criteria for evaluating data. Perhaps most importantly, CIKS will provide an increased access to education and training and should raise the overall skill level of the construction industry's workforce and create a market-pull for innovative materials, technologies, and practices.

Knowledge Applications for the Coating Industry Examples of Coating Industry Knowledge-Based Systems. Computerized Knowledge-Based Systems (KBS) are widespread among the coating industry. Examples of systems developed for construction industry application are identified in a selected bibliography later in this paper. Many of these systems are prototypes and were developed when information technologies (e.g. expert system shells, neural networks) were in their infancy. Features lacking in these systems include the ability to integrate with the business process and the ability to operate with computerized systems across different disciplines (e.g. designers, maintenance and operation staff) and processes (e.g., material and product selection, and cost analysis). Many KBS are developed for in-house use. Examples include databases on coating products and services, research data, cost estimating, and decision-support systems. Many of these systems are rarely distributed to others, in formal or commercial formats. Reasons include their proprietary nature, lack of an incentive for distribution (marketability), and costs related to development and maintenance. In fact, many systems are developed and maintained by personnel responsible for developing the knowledge and their existence may be unrecognized by their colleagues. Computerized systems designed for distribution, such as commercial products, require more effort to develop and maintain. These tend to be more formal systems where marketing strategies, distribution mechanisms, and customer (user) assistance are essential for a successful product and to return the development investment. Often knowledge content is the driving force for these systems. The Journal of Protective Coatings & Linings, "JPCL Archives II" is an example of such a product. Future versions of this product could be made available on-line via the


433 Internet, while still providing income to the publisher/distributor. Solutions currently being developed to allow electronic commerce and intellectual property distribution on the Internet will accelerate this method. 3

The Internet W has altered thinking on how an organization's knowledge is kept. For example, through the use of an Intranet (an internal W ), access to knowledge can be provided to personnel within an organization (e.g. marketing, testing, and research departments). Use of an Intranet results in benefits such as shorter development times, lower costs, and improved computer security. Although the Intranet is useful within organizations, use of the Internet will benefit organizations as new capabilities such as electronic commerce mature and increased network traffic capacity increases. To remain competitive, Internet-based information is no longer a convenience, but a necessity.


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Perhaps the most significant constraint affecting the distribution of organizational and commercial knowledge-based systems is the lack of interoperability. Quite simply, interoperability means the ability to use knowledge and software among computerized systems. Incompatible data formats and computer hardware and software, incomplete or subjective data, inconsistent terminology, and the lack of electronic access are examples of specific factors that prohibit widespread use. Solving these problems will require collaboration by industry and government. Agreement must be reached on a common terminology, standard knowledge formats, criteria for establishing data quality, and common computer interfaces that provide seamless integration of knowledge to the user. The CIKS activity will address these issues. The Society for Protective Coatings/Computer-Integrated Knowledge System (SSPC/CIKS) Joint Coating Working Group One group that is currently addressing coating industry knowledge issues is the SSPC/CIKS Joint Coating Working Group. The Working Group comprises members from the SSPC Committee C.4.10 on "Knowledge-Base Systems for Coatings," and a CIKS Coating Industry Working Group formed during the CIKS June 1996 workshop. SSPC's Executive Director, Bernard Appleman chairs the group. Members of the group include public and private sector organizations representing coating formulators, consultants and engineers, facility owners, and researchers. Figure 3 shows a diagram of the group's interaction with the CIKS test bed and its role in the development of CIKS. Collaboration with other industry and standards setting committees such as ASTM D-l on "Paint and Related Coatings, Materials and Applications " and Committee E-49 on "Computerization of Material and Chemical Property Data" will be necessary. These collaborations will result in consistent terminology and standards for identifying, representing, and sharing coating material knowledge. Specific focus areas of the SSPC/CIKS Joint Coating Working Group include:



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Figure 3: SSPC/CIKS Coating Working Group role in CIKS development.

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developing guides to assist coating industry knowledge users in using and integrating the Internet in business practice; improving the communication of computer-based information such as messages, computer-stored files, and access to application systems; developing standard formats for representing and exchanging coating product data; developing state-of-the-art reports describing current practice and enabling information technologies that have application within the coating industry.

Future projects requiring longer lead-times (2-years) to implement include the development of case-based reasoning (decision-making based on documented observations of coating performance), data dictionaries, and expert systems. Products from the Working Group will be disseminated in the form of SSPC Technology Updates, Guides, and the SSPC Coating Knowledge Center. The draft "Guide for the Identification and Use of Industrial Coating Material in Computerized Product Databases" exemplifies the Working Group's effort to develop standard guides and methods for representing coating material knowledge. Table 1 shows examples of the data elements proposed in the guide. The draft document is being proposed as a SSPC Guide and would be used by coating manufactures, specifiers, and users (facility owners) for the communicating of coating product data. Figure 4 represents a diagram of the use of coating product data using the W . Product data sheets are now used to communicate this information. However, variations exist among manufacturers 3


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Data segment Product description Intended use

Physical properties


Mixing and application

Key performance parameters Safety Manufacturer supplemental information

Example Data elements Product name, product identification, generic type, system component Common application, substrate type, exposure environment, compatible undercoat and topcoat Volume solids, solids by weight, mixed density, test methods Minimum and maximum dry film application thickness, theoretical coverage per volume, dew point, induction time, pot life Corrosion resistance, weathering, abrasion resistance, test methods NFPA health hazard, flammability Manufacturer comments

Table 1: Example of product data segments and data elements. when describing product data content, such as terms used and the type of data reported. As more companies use computerized systems such as the W to disseminate information, standards such as the proposed coating product data guide will provide improved understanding (through consistent terminology and data elements). The ability to integrate product data among diverse computerized systems, such as company and facility owner project databases will be realized. Another benefit of the guide will be an increased understanding of coating material performance and data quality through the reporting of data elements such as those described in the "Key Performance Parameters" data segment. These parameters will be substantiated through the identification of test methods used to develop parameter values. 3

Figure 4: Diagram showing the generation and use of coating product data.


436 Current NIST Effort to Establish the CIKS Test Bed NIST as an organization, is seeking to improve the delivery of its research results. The CIKS test bed will be a useful tool in providing construction material knowledge. The previously mentioned AMRL Paint Proficiency Sample Program is an example of the use of the test bed to provide access to technical data. Technical databases and decision-support systems are methods that have received the greatest attention thus far. Material property databases for cement and coatings can now be accessed through the W . The Uniform Resource Locator (URL) address for accessing the NIST technical databases is: http://ciks.nist.gov Downloaded by EAST CAROLINA UNIV on January 3, 2018 | http://pubs.acs.org Publication Date: April 15, 1999 | doi: 10.1021/bk-1999-0722.ch028

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Two decision-support systems have been developed by NIST during the past several years. The first of the two systems is the Highway Concrete Expert System (HWYCON). This system is designed to assist highway engineers in the diagnosis, selection, and repair and rehabilitation of highway concrete structures. It includes knowledge related to concrete pavements, bridges, and support structures. Several universities are also using the system as part of their material science and civil engineering curriculum. The Transportation Research Board sells HWYCON. The computerized system requires the Microsoft operating system, Windows version 3 or Windows '95. The distribution package contains a set of floppy diskettes and a report describing the design, installation, and operation of the system [12,13]. The second system called the Coating Expert Advisory System-I (COEX-I) [14] contains coating material knowledge and is designed to assist in the analysis of coating failures and selection of coating systems for stationary military structures. An overview of the COEX-I is described later.

Technical Databases Technical databases contain many different types of data (see Figure 5). Examples include; product databases that describe material properties and manufacturer data, laboratory performance measurements, and outdoor exposure test results. It was stated earlier that significant differences occur among databases due to designer/developer preferences. These differences take the form of; inconsistent field names and contents; choice of computer hardware; and software that does not allow interoperability. The proposed SSPC Guide on coating product data formats is only the first step in providing compatible databases that can be used among computerized systems. To realize the full benefit of distributed database exchange, standard methods must be used to implement and disseminate the data. The steps in developing interoperable distributed databases include: • • • •

establishing consistent database formats and terminology; establishing a logical schema to represent the physical data in the database; implementing of the database (acquire, computerize) using a database management system; providing electronic access through media distribution or electronically, via the Internet W . 3



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Figure 5: Examples of technical coating databases.

Significant operational enhancements can be achieved through electronic publication of databases using the W . Interfacing database standards such as SQL (Structured Query Language) and the W client interface (e.g. WEB browser) reduces the need to develop multiple user interfaces for different computer platforms and can significantly reduce software development and maintenance costs. Access to databases can be provided in a more timely, and convenient manner. Figure 6 contains a diagram of the components of a distributed technical database system designed for W access. This model can be applied to virtually any type of database. The client (user) is provided the functionality of submitting queries (questions) to the database in an interactive mode. Typically, this is done using a W browser program. The process of converting input from the client involves converting the query into a SQL statement. In the instance shown in Figure 7, this is accomplished using the ISO Standard 9579 [8], "Remote Data Access" (RDA). This standard is a generic model providing database access and has been implemented at NIST for the purpose of interfacing W clients to SQL databases. The RDA standard was implemented using the C Programming Language. After receiving the SQL statement, the database management system retrieves the data from the physical database and produces a table containing the data elements (fields) and their values. This information is returned to the RDA component that formats the information for output in the Hyptertext Markup Language (HTML) and displays the information using the W client's browser. Added capabilities have been developed to also produce graphical plots. An interface has been developed to the NIST Dataplot Statistical and Graphical Analysis system [15]. This permits the graphical display of database information, interactively. Since the construction industry is comprised of companies with varying degrees of personnel and funding resources. It is necessary 3

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Figure 6: W implementation for technical databases. to test knowledge system development using multiple platforms. Figures 7 and 8 show two methods that are used in the CIKS test bed to implement distributed technical databases using ISO, ANSI and de-facto standards for database storage, query, and retrieval. The use of newer, more flexible de-facto standards in the form of Microsoft Internet Information Server and the "Access" database management system, created opportunity for less costly hardware and software resources. For example, hardware and software costs for the resources shown in Figure 7 range from $50K to $75K dollars. Hardware and software costs for the resources shown in Figure 8 rangefrom$5K to $10K dollars.

Figure 7: W database implementation, using an engineering workstation platform, ISO, and ANSI standards.



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Figure 8: W database implementation, using microcomputer platform and de-facto standards.

Decision-Support Systems For the purpose of this article, decision-support systems or as they are sometimes called, expert systems, are defined as follows: "Computerized systems that can contain virtually any type of coating data and knowledge, such as technical databases, photographs, expert guidance, video and sound, computer-based models, and a logic module to operate (direct the logical instruction sequence) on the knowledge and provide an interface to the user." Many attempts to develop decision-support systems have occurred in technical areas during the past 15 to 20 years. Examples of decision-support systems developed for construction materials users can be found in the bibliography at the end of this article. There are relatively few commercial decision-support systems available today. The most successful are operational within organizations that are committed to develop, maintain, and operate them within the organization. Historically, complex systems that cover a wide-interest area and involve high-level expert knowledge are costly to develop and maintain. However, advances in decision-support system development tools during the mid-1980's provided more cost effective development tools. These tools use the object-oriented programming [16] architecture and advanced techniques for the representation and use of knowledge, such as video, sound, and hypertext links. The result is a significant reduction in development time. Additional benefits in using object-oriented development tools include: • •

ability to reuse data, knowledge, and procedures; relationships can be established among data and knowledge (inheritance); Bauer and Martin; Service Life Prediction of Organic Coatings ACS Symposium Series; American Chemical Society: Washington, DC, 1999.

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efficient graphical user interfaces are included in the tool; improved interfaces to external knowledge and programming modules.

COEX-I: An Object-Oriented Decision-Support System. One benefit of implementing decision-support systems is their ability to provide a systematic approach to problem-solving and knowledge dissemination. By incorporating the knowledge of expert(s) or specialists in coating materials and practices, improved levels of decision-making can result. For example, experts residing in a central location can extend or replicate their knowledge to field staff who need to evaluate the condition of coated structures, and perform repair and maintenance duties. Guidance for these individuals is typically found in printed form represented in manuals, guides, and standards. Computerizing the knowledge to include photographs, sound and video, and the guidance on the use of the guide significantly enhances knowledge understanding, resulting in cost savings and improved facility performance. The COEX-I expert system was developed by a team of coating experts who had previously written the Military Handbook, "Handbook for Paints and Protective Coatings for Facilities" [17]. The group includes representatives from Department of Defense facilities who are involved in maintaining coated facilities. The group decided to develop a prototype decision-support system to assist military staff in analyzing coating failures that occur on stationary military structures such as water towers, buildings, and bridges. Section 11 of the guide covers the Analysis of Paint Failures and includes a decision tree that is designed to assist the user of the handbook. From this decision tree, rules (logic) were computerized in the form of question-and-answers. The rules provide a hierarchical structure to the knowledge and guide the user in problem solving,fromthe identification of visual observations found on the structure to recommendations given by the system. Recommendations include the identification of the coating failure, its cause, and guidance on remedial action(s). An additional capability was added to allow the user to specify criteria for coating system selection where total replacement is necessary for structural steel that shows blistering to the substrate. Figure 9 shows a diagram of the COEX-I system. COEX-I is a prototype decision-support system that is being distributed for review and comment. Although the system is based on military structures, parts of the knowledge base apply to structural steel that is present in highway bridges. Examples include corrosion failures and videos contained in the system that provide guidance and inspection procedures for blistering and corrosion causes. Development tools used in the development of COEX-I are being applied to a new system designed to assist Federal Highway Administration (FHWA) and State Department of Transportation Engineers in the selection of coating systems for highway steel bridges. Knowledge contained in the system was developed through



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Figure 9: COEX-I system diagram.

various FHWA projects during the past decade. FHWA and NIST are developing the system, jointly, under FHWA, Turner-Fairbank Research Center sponsorship. It will be operational in 1998. Summary This article has presented an overview of an approach to solving industry wide information needs for the coating industry, and through examples, has described several knowledge-based activities and applicable standards. The extreme diversity in user needs and variations in problem solving using computerized systems dictate the need for collaboration in the development of CIKS. These collaborations must occur between private sector companies, academia, and government agencies, and should result in a sound architecture that will enable a much greater degree of information sharing (interoperability), improved decision-making, and improved data quality. The CIKS test bed will provide opportunities to test new paradigms and prototype systems, information standards, and existing knowledge-based systems. A set of common terms and formats will permit seamless user interfaces that will result in shorter development times and cost savings for coating material users. Increased understanding of the performance of coating material will be realized through the identification of coating material properties and increased data quality. A realization of the SSPC Coating Knowledge Center will be accelerated. References [1] Clifton, J.R. and Sunder, S.S., "A Partnership for a National Computer-Integrated Knowledge Systems Network for High-Performance Construction Materials and Systems: Workshop Report" NISTIR 6003, National Institute of Standards and Technology, Gaithersburg, MD 1997.


442 [2] "Materials for Tomorrow's Infrastructure: A Ten-Year Plan for Deploying HighPerformance Construction Materials and Systems," Civil Engineering Research Foundation, Washington, DC, 1994, Report #94-5011.


[3] Kurihara, T.Y. and Kaetzel, L.J., "Computer Integrated Knowledge System (CIKS) for Construction Materials, Components, and Systems: Proposed Framework, National Institute of Standards and Technology, Gaithersburg, MD, September 1997, NIST Internal Report 6071. [4] W. Danner, "Standard for the Exchange of Product Model Data Development Methods: Specification of Semantics for Information Sharing,", National Institute of Standards and Technology, Gaithersburg, MD, September 1992, NIST Internal Report 4915. [5] Carpenter, J. and Rumble, J., "STEP for Materials," in ASTM Standardization News, American Society for Testing and Materials, Conshohocken, PA, April 1997, Volume 25, Number 4, pp. 26-30. [6] Falasconi, S., Lanzola, G. and Stefanelli, M., "Using Ontologies in Multi-Agent Systems," in Tenth Knowledge Acquisition for Knowledge-Based Systems Workshop (KAW '96), University of Pavia, Pavia, Italy, November 1996. [7] Farquhar, A., Fikes, R. and Rice, J., "The Ontolingua Server: A Tool for Collaborative Ontology Construction Knowledge Systems Laboratory, "Stanford University, Berkeley, CA September 1996. [8] Brady, K. and Sullivan, J., "User's Guide for RDA/SQL Validation Tests,", National Institute of Standards and Technology, Gaithersburg, MD, December 1996, NIST Internal Report 5725. [9] "Database Language SQL," Federal Information Processing Standard (FIPS) 1272, National Institute of Standards and Technology, Gaithersburg, MD, June 1993. [10] Clifton, J.R., Bentz, D.P., and Kaetzel, L.J., "Computerized Integrated Knowledge Based System for High-Performance Concrete: An Overview,", National Institute of Standards and Technology, Gaithersburg, MD, February 1997, NIST Internal Report 5947. [11] Bentz, D.P., Clifton, J.R., and Snyder, K.A., "Predicting Service Life of Chloride-Exposed Steel-Reinforced Concrete," in Concrete International, American Concrete Institute, Farmington Hills, MI, December 1996,Volume 18, No. 12, pp. 42-47. [12] Kaetzel, L.J., Clifton, J.R., and Snyder, K.A., "Users Guide to the Highway Concrete (HWYCON) Expert System," Strategic Highway Research Program, National Research Council, Washington, DC, 1994, SHRP-C-406.


443 [13] Kaetzel, L.J., Clifton, J.R., Kleiger, P., and Snyder, K.A., "Highway Concrete (HWYCON) Expert System User Reference and Enhancement Guide," National Institute of Standards and Technology, Gaithersburg, M D , May 1993, NIST Internal Report 5184.


[14] "COEX-I Expert System for Steel Protection," in Building and Fire Research Laboratory, Research Update, National Institute of Standards and Technology, Gaithersburg, M D , 1996, Volume 2, Number 3. [15] Filliben, J., "Dataplot Introduction and Overview", National Institute of Standards and Technology, Gaithersburg, M D , June 1984, NBS Special Publication 667. [16] Henderson, P., "Object-Oriented Specification and Design with C++," McGrawHill Book Company, New York, N Y , 1993. [17] "Military Handbook: Handbook for Paints and Protective Coatings for Facilities," U.S. Department of Defense, Naval Facilities Engineering Command, Lester, PA, January 1995, MIL-HDBK-1110/1. Selected Bibliography of Knowledge-Based Systems H. Adeli, (Ed.), "Expert Systems in Construction and Structural Engineering," Chapman and Hall, New York, N Y , 1988. "Interactive Education: Transitioning CD-ROMS to the Web," in Computer Networks and ISDN Systems, Elsevier Science, 1994, No. 27, pp. 267-272. "Chemistry Sites Proliferate on the Internet's World Wide Web," in Construction and Engineering News, November 1995, pp. 35-46. "Developing Expert Systems," Federal Highway Administration, U.S. Department of Transportation, McLean, V A , December 1988, Publication No. FHWA-TS-88-022. Colin, L.F. and Harris, R.A., "Knowledge Based Expert Systems in Transportation: A Synthesis of Highway Practice," Transportation Research Board, Washington, DC, September 1992, National Cooperative Highway Research Program Synthesis 183. Clifton, J.R. and Kaetzel, L.J., "Expert Systems in Concrete Construction," in Concrete International, American Concrete Institute, Farmington Hills, MI, November 1988. Kuo, S.S., Clark, D.A., and Kerr, R., "Complete Package for Computer Automated Bridge Inspection Process," Transportation Research Board, Washington, DC, 1988. "Knowledge Acquisition for Expert Systems in Construction," U.S. Army Corp's of Engineers, Construction Engineering Research Laboratory, Champaign, IL, September 1988, USACERL Special Report M-89/10.


444 Kaetzel, L.J. and McKnight, M.E., "Enhancing Coatings Diagnostics, Selection, and Use Through Computer Based Knowledge Systems," Proceedings of SSPC '95, The Society for Protective Coatings, Pittsburgh, PA, November 1995, SSPC 95-09, pp. 287-295.


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