Distributed Ontology Architecture for Knowledge Management in Highway Construction

The ongoing plethora of rehabilitation in the infrastructure domain requires more planning and integration during design and construction. To achieve this, there is a need for developing and using semantic (ontology-based) mechanisms for the exchange of development knowledge among all project stakeholders. This paper presents a distributed ontology architecture for knowledge management in highway construction. With every other utility tied to the highway geometry, the architecture is intended to be the base for a cross-discipline knowledge exchange in the infrastructure domain. The architecture presents highway knowledge on three levels: domain knowledge (an umbrella for infrastructure shared knowledge), application knowledge (representation of highway-specific knowledge), and user knowledge (an enterprise-specific representation of highway knowledge). The proposed architecture models highway concepts using six major root concepts: project, process, product, actor, resources, and technical topics (attributes and constraints). The architecture was developed using rigorous knowledge acquisition and ontology development techniques. It was developed as an extension for the e-COGNOS ontology. The architecture was validated through input from domain experts.     

E-Society Portal: Integrating Urban Highway Construction Projects into the Knowledge City

Community involvement is an important factor for sustainable highway construction. Information and communication technologies provide a new and more effective approach to facilitate community involvement. However, there are too many parameters with conflicting and subjective definitions related to sustainability and too many stakeholders with varying degrees of interest and sophistication. There is a need for an effective tool to communicate project impacts on sustainability to local communities. This paper presents an ontology for stakeholder management and sustainability in highway construction. An ontology is a conceptual semantic model that attempts to capture human knowledge (both explicit and tacit) in a consistent manner. Ontologies include three main elements: a taxonomy (common vocabulary presented in concept trees), set of relationships (linking concepts across trees), and axioms (limitation/constraints on the behavior of concepts). The ontology was used to develop a portal for broadcasting highway design features to local communities. By browsing through the portal, a user can learn about project elements, the impacts of each element on sustainability issues, who is sponsoring such element, and what efforts have been made to reduce any impacts of such elements on local communities.     

Merging Architectural, Engineering, and Construction Ontologies

Ontologies have emerged as a means of facilitating semantic interoperability among computer systems. However, recognizing that no single universally agreed-on ontology can ever be defined for a domain, a tool that allows ontologies to interoperate becomes essential to semantic interoperability. This paper presents an ontology integrator (Onto-Integrator) for facilitating ontology interoperability within the architectural, engineering, and construction (AEC) domain. The Onto-Integrator offers a heuristic for ontology merging, including the merging of concept taxonomies, relations, and axioms. Unlike existing tools, the integrator addresses ontology merging requirements that are specific to the AEC domain. The integrator heuristic was implemented into a prototype Web-based tool and was evaluated through a focus group.     

Automated Classification of Construction Project Documents

The number of documents generated in a construction project and stored in interorganizational information systems is significant. Since a large percentage of these project documents are generated in text format, methods for organizing and improving access to the information contained in these types of documents become essential to construction information management. Information classification schemes can be used for this purpose. They provide a common framework to enact document organization and information exchange among project members. Current systems for document management rely on manual classification methods controlled by human experts. Due to the widespread use of information technologies for construction, the increasing availability of electronic documents, and the development of systems based on project object models, manual classification becomes unfeasible. This paper presents a unique way to improve information organization and access in interorganizational systems based on automated classification of construction project documents according to their related project components. Machine learning methods were used for this purpose. A prototype of a document classification system was developed to provide easy deployment and scalability to the classification process.     

Domain Ontology for Processes in Infrastructure and Construction

With the increasing demands for domain-wide integrated construction and infrastructure development, there is a need for developing a domain ontology to build a knowledge model that describes the multistakeholder project development process. This paper presents a domain ontology for supporting knowledge-enabled process management and coordination across various stakeholders, disciplines, and projects. The ontological model is composed of concepts, relations, and axioms. Concepts represent the “things” in the domain of interest; relations establish the interconcept links; and axioms specify the definitions of concepts and relations and constraints on their behavior and interpretation. The ontology models the most fundamental concepts in the domain in a structured, extendable, and flexible format to facilitate future evolution and extension of the ontology for representing application-specific and/or enterprise-specific knowledge. The ontology was evaluated through technical evaluation and user evaluation. User evaluation was conducted through one-to-one expert evaluation interviews.     

Ontology-Centered Knowledge Management Using Information Retrieval Techniques

The paper argues that an effective solution to information and knowledge management (KM) needs of practitioners in the construction industry can be found in the provision of an adapted knowledge environment that makes use of user profiling and document summarization techniques based on information retrieval sciences. The conceptualization of the domain through ontology takes a pivotal role in the proposed knowledge environment and provides a semantic referential to ensure relevance, accuracy, and completeness of information. A set of KM services articulated around the selected ontology have been developed, using the Web services model, tested, and validated in real organizational settings. This provided the basis for formulating recommendations and key success factors for any KM project development.     

Taxonomy of Knowledge Requirements for Construction Executives

Construction projects are achieved through a “project format” where the focus of management is on the planning and control of resources. While this aspect of the construction industry receives significant focus, less attention is paid to the broader concerns of construction organizations, or enterprise management. This lack of focus is resulting in few construction professionals' acquiring the breadth of knowledge required to sufficiently address enterprise management issues. In response to this issue, a taxonomy of knowledge requirements for construction executives has been developed to serve as a map of knowledge areas for construction industry executives. Based on a study of internationally recognized journals, a content analysis methodology was used to gauge the current state of management topics. Based on this content analysis, the paper presents the eight focal areas of knowledge for construction executives and the accompanying emerging topics from management researchers.     

Dynamic Knowledge-Based Process Integration Portal for Collaborative Construction

There is a need to support collaborative coordinated construction through the integration of work processes across various stakeholders, disciplines, and projects. Due to the fast-growing complexities of domain-wide coordination and collaboration, coupled with the emerging opportunities of knowledge sharing, a knowledge-based approach is believed to be the way to go. Knowledge-based process integration takes into account explicit and formal semantics (meaning) of processes. It aims at supporting seamless integration of knowledge-carrying processes. This paper presents a prototype collaborative portal for domain-wide process integration. The portal is ontology-based: semantic process representation is enabled through ontologies, and knowledge-based process integration is facilitated through an ontology merger. The portal aims at offering an efficient value-adding collaboration platform through multidimensional process integration for producing a common workflow that goes beyond listing of processes to a knowledge-enabled view. The prototype was evaluated through a focus group.     

Formalism for Applying Domain Constraints in Domain-Oriented Schema Matching

Exchanging data between different software systems is a critical requirement in the architecture, engineering, and construction industry, where task specific data models and public data exchange standards have been applied for data representation and exchange. Matching two data models effectively and efficiently is a challenging task, especially when performed manually, due to the large size and the complexity of today’s data schemas. Some existing computer-aided approaches have attempted to automate matching of different schemas. These approaches work and reduce human effort under specific conditions; however, they do not always result in an accurate matching of two schemas. Achieving schema matching result comparable in accuracy to manual matching requires leveraging domain specific knowledge. Yet utilization of domain knowledge for schema matching rarely has been incorporated in prior studies. In this paper, we present a semiautomated approach that leverages domain knowledge to improve the schema matching process. Compared to a generic schema matching approach, the approach discussed in this paper is able to generate more accurate results due to the incorporation of domain specific constraints, which are represented and reasoned with to create a match between data models. A prototype was developed to validate this approach through a number of real world test cases, including the matching of two publicly-available data exchange standards.     

From syntactic-semantic tagging to knowledge discovery in medical texts

In the GALEN project, the syntactic-semantic tagger MultiTALE is upgraded to extract knowledge from natural language surgical procedure expressions. In this paper, we describe the methodology applied and show that out of a randomly selected sample of such expressions coming from the procedure axis of Snomed International, 81% could be analysed correctly. The problems encountered fall in three different categories: unusual grammatical configurations within the Snomed terms, insufficient domain knowledge and different categorisation of concepts and semantic links in the domain and linguistic models used. It is concluded that the Multi-TALE system can be used to attach meaning to words that not have been encountered previously, but that an interface ontology mediating between domain models and linguistic models is needed to arrive at a higher level of independence from both particular languages and from particular domains.     

Expert Systems for Construction Project Monitoring

Potential applications of knowledge based expert systems in the area of construction project monitoring and control are described. Originally developed from research in artificial intelligence, these systems are computer programs that can undertake intelligent tasks currently performed by highly skilled people. While some project monitoring can be accomplished by algorithmic procedures, the capability of knowledge based expert systems to deal with illstructured problems and to be extensively modified over time make them desirable for application in this area. Sample applications and heuristic rules in scheduling and inventory control are provided.     

Concept Relation Extraction from Construction Documents Using Natural Language Processing

The objective of this research is to present an innovative technique for managing the knowledge contained in construction contract documents to facilitate quick access and efficient use of such knowledge for project management and contract administration tasks. Knowledge Management has become the focus of a lot of scientific research during the second half of the 20th century as researchers discovered the importance of the knowledge resource to business organizations. Despite early expectations of improved document management techniques, document management systems used in the construction industry have failed to deliver the anticipated performance. Recent research attempts to utilize analysis of the contents of documents to improve document categorization and retrieval functions. It is hypothesized that natural language processing can be effectively used to perform document text analysis. The proposed system, technique for concept relation identification using shallow parsing (CRISP), utilizes a shallow parser to extract semantic knowledge from construction contract documents which can be used to improve electronic document management functions such as document categorization and retrieval. When compared with human evaluators, CRISP achieved almost 80% of the average kappa score attained by the evaluators, and approximately 90% of their F-measure score.     

Integrated Schedule and Cost Model for Repetitive Construction Process

Several efforts have been made by many researchers to develop a model for schedule and cost integration in construction projects, but it is difficult to integrate and manage schedule and cost in an actual construction site using such a model. The integrated schedule and cost model developed in this study (1) enables the planning and control of repetitive construction processes and (2) can be used by a project manager in an actual construction site. Furthermore, an integrated schedule and cost model for the core wall construction, which is an important repetitive process in the recently booming high-rise building construction in terms of scheduling, was developed using the integration model developed in this study. It is expected that the integrated schedule and cost model developed can allow project managers to integrate the schedule and cost of repetitive construction processes more effectively and support the project managers’ decision-making.     

Master Builder Project Delivery System and Designer Construction Knowledge

The master builder system for designing and building construction projects was the dominant project delivery system in the construction industry during the early part of the 20th century. Master builders were generally charged with both design and construction services for a project. During the last half of the 20th century, many different systems for project delivery with fragmented responsibilities have replaced the master builder system. Reducing the use of the master builder system has led to the creation of elaborate systems for managing projects in the construction industry. In order to investigate the use of the master builder delivery system and other systems, a research project was conducted that included reviewing (1) the history of the construction industry, (2) project delivery systems, (3) constructability issues, (4) construction industry fragmentation, (5) the results of a survey of architecture, engineering, and construction professionals from the San Francisco Bay Area in California on the current processes they use for training engineers and architects, (6) an analysis of the survey results, (7) construction industry recommendations, and (8) conclusions based on the survey results and analysis. The information obtained from the research project, including the survey and an analysis of the results, is included in this document. The results of the research indicate that reduction in the use of the master builder project delivery system and the rise of numerous fragmented delivery systems have limited the designer’s knowledge of construction processes.     

Formalization of Construction Sequencing Rationale and Classification Mechanism to Support Rapid Generation of Sequencing Alternatives

Resequencing construction activities is a critical task for project planners for effective project control. Resequencing activities require planners to determine the impact or “role” an activity has on successor activities. They also need to determine the status of activities, i.e., which activities may or may not be delayed. Distinguishing the role and status of activities in turn requires planners to understand the rationale for activity sequences. The current critical path method (CPM) framework, however, represents sequencing rationale using precedence relationships and distinguishes activities only with respect to their time-criticality. Thus, planners find it difficult to keep track of individual sequencing logic, and manually inferring the role and status of activities becomes practically prohibitive in complex project schedules. The research presented in this paper addressed this limitation of the CPM framework by formalizing a constraint ontology and classification mechanism. The ontology allows planners to describe their rationale for activity sequences in a consistent and intuitive way, whereas the classification mechanism leverages the ontology to automatically infer the role and status of activities. The ontology and mechanisms were implemented in a prototype tool. With this tool, users can quickly verify which activities to delay to expedite critical milestone or bottleneck activities, thus making it possible to quickly evaluate and generate sequencing alternatives in CPM-based schedules.     

基于本体理论的冶金设备分类编码方法

随着冶金信息化建设的不断发展,物资采购管理、设备资产管理、工程建设管理的改革在不断深化,冶金设备以及备品备件信息的规范化、科学化管理亟待解决,构建标准化的冶金设备“统一分类与编码”体系迫在眉睫。运用本体理论和方法,对冶金设备信息进行了概念、属性的定义,构建了冶金设备领域本体,在此基础上,提出了更加科学和实用的基于本体理论的冶金设备分类编码构想,满足了冶金设备信息共享和重用的需求。     

Construction Energy Use

A method has been developed for classification of energy use associated with the delivery process for a construction project. A study has been conducted for a large civil works project to identify the areas of major consumption of energy. An energy estimating procedure has been developed for projects to identify the imbedded energy content of in‐place end products and in‐process components of the construction end products. The procedure has been applied to a sample project to identify major areas of energy use and opportunities for better energy utilization and conservation. The opportunities identified have been classified in a manner paralleling the classification scheme developed.     

Building Integrated Architecture/Engineering/Construction Systems Using Smart Objects: Methodology and Implementation

Integrated project systems hold the promise for improving the quality while reducing the time and cost of architecture/engineering/construction (AEC) projects. A fundamental requirement of such systems is to support the modeling and management of the design and construction information and to allow the exchange of such information among different project disciplines in an effective and efficient manner. This paper presents a methodology to implement integrated project systems through the use of a model-based approach that involves developing integrated “smart AEC objects.” Smart AEC objects are an evolutionary step that builds upon past research and experience in AEC product modeling, geometric modeling, intelligent CAD systems, and knowledge-based design methods. Smart objects are 3D parametric entities that combine the capability to represent various aspects of project information required to support multidisciplinary views of the objects, and the capability to encapsulate “intelligence” by representing behavioral aspects, design constraints, and life-cycle data management features into the objects. An example implementation of smart objects to support integrated design of falsework systems is presented. The paper also discusses the requirements for extending existing standard data models, specifically the Industry Foundation Classes (IFC), to support the modeling of smart AEC objects.     

Empire State Building Project: Archetype of “Mass Construction”

Analysis of historical projects, with the dual benefits of hindsight and modern concepts of construction systems, can help fill the gaps in our theoretical understanding of production in construction, which have increasingly been identified as a barrier to progress in improving construction project management. The richness of the historical record describing construction of the Empire State Building provides a unique opportunity to analyze and compare it with the paradigms of craft, industrialized, and lean construction. Its size and its record rate of construction, which has not been broken since for tall buildings, make it of prime interest. The project progress was reconstructed using line-of-balance software and its different flows were assessed. The results lead to the conclusion that it is an archetypal example of what we propose be called “mass construction.” This enables a richer understanding of the taxonomy of production systems in construction, and should aid theoreticians and practitioners alike to devise better production systems for construction projects.