Conceptual modelling of building regulation knowledge

doi:10.1016/S0954-1810(96)00043-X

Artificial Intelligence in Engineering

Volume 11, Issue 3, July 1997, Pages 273-284

https://doi.org/10.1016/S0954-1810(96)00043-X Get rights and content

Abstract

In recent years knowledge has become more and more a critical production factor for many organisations. Adequate performance of many activities depends on the availability of knowledge. However, volume and complexity of knowledge increase more and more. Consequently the accessibility of knowledge decreases.

Knowledge of fire-safety regulations is critical for architects to design fire-safe buildings and for local authorities to verify fire-safety of building designs. However, effective application of this knowledge in the Netherlands is a problem because of the volume, complexity and inaccessibility of the Dutch Fire-Safety Regulations. People in practice don't understand and consequently misinterpret the regulations. A solution to this lack of knowledge is the development of a knowledge based system.

In the development of knowledge based systems the conceptual modelling phase is an important one. In this phase knowledge of the application-domain is modelled using a conceptual modelling language.This paper describes criteria for selecting a suitable conceptual modelling language taking into account the nature of knowledge in a particular application-domain. Further it explains what the nature of building regulation knowledge is and which conceptual modelling language is most suitable to represent this knowledge. Finally the paper describes and shows some contents of a knowledge based system that advises architects to design fire-safe buildings conforming to the regulations and helps local authorities to verify building designs with respect to fire-safety regulations.

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Cited by (8)

A building regulation question answering system: A deep learning methodology
2020, Advanced Engineering Informatics
Citation Excerpt :
Thus, to provide additional computerized support to the users of regulations, representing regulation knowledge in a formal and computer-interpretable way is necessary [3]. A variety of modeling approaches have been applied to represent the logic of building regulations [6], which include object-oriented [7], rule-based [8], ontology-based [9] and semantic-based [10]. A detailed review of regulation knowledge modeling and automatic rule-based checking can be found in the works of Zhong et al. [3], Eastman et al.[8] and Pauwels et al.[10].
Regulations play an important role in assuring the quality of a building’s construction and minimizing its adverse environmental impacts. Engineers and the like need to retrieve regulatory information to ensure a building conforms to specified standards. Despite the availability of search engines and digital databases that can be used to store regulations, engineers, for example, are unable to retrieve information for domain-specific needs in a timely manner. As a consequence, users often have to deal with the burden of browsing and filtering information, which can be a time-consuming process. This research develops a robust end-to-end methodology to improve the efficiency and effectiveness of retrieving queries pertaining to building regulations. The developed methodology integrates information retrieval with a deep learning model of Natural Language Processing (NLP) to provide precise and rapid answers to user’s questions from a collection of building regulations. The methodology is evaluated and a prototype system to retrieve queries is developed. The paper’s contribution is therefore twofold as it develops a: (1) methodology that combines NLP and deep learning to be able to address queries raised about the building regulations; and (2) chatbot of question answering system, which we refer to as QAS4CQAR. Our proposed methodology has powerful feature representation and learning capability and therefore can potentially be adopted to building regulations in other jurisdictions.
Toward improving the quality compliance checking of urban private constructions in Iran: An ontological approach
2018, Sustainable Cities and Society
Citation Excerpt :
However, before that, the related studies in the field of QCC are discussed. With the emergence of BIM (Eastman, Eastman, Teicholz, Sacks, & Liston, 2011) along with research studies on the modeling of the regulation knowledge in the construction industry (de Gelder, 1997; Eastman, Lee, Jeong, & Lee, 2009; Zhou & El-Gohary, 2015), various research projects have been conducted in the field of compliance checking (Baumgärtel, Kadolsky, & Scherer, 2014; Solihin & Eastman, 2015; Zhang & El-Gohary, 2014; Zhang & El-Gohary, 2015; Zhong, Ding et al., 2012). Among these, the number of studies addressed the QCC in the construction industry.
City, as a complex system, needs to be managed as an integrated entity so that every encumbrance that slows its processes could be eliminated. However, developing a single mature model to integrate the whole processes of the various systems in the city is not practical. Yet, it is possible to develop purposeful and consistent models, for each specific system, that all together eventuate in the integrated management. In this regard, the mechanism of constructions quality compliance checking is one out of many systems in Iran that needs to be addressed for integration due to three main reasons; first, the multiplicity of problems in this section; secondly, the multidimensional significance of this section; and finally the ability to improve the status quo through using appropriate approach. Accordingly, the present study, by developing an ontology, which is named QA-ontology, as a missing chain, and using existent ontologies in previous studies, presents a conceptual model. This model takes advantages of the ability of ontologies in the information storing as a graph. This type of information storing provides the homogeneous information that is needed for both integration in the quality compliance checking of urban private constructions and assimilation into further extensions of integration in other mechanisms of a city.
Safety regulation: The lessons of workplace safety rule management for managing the regulatory burden
2015, Safety Science
Citation Excerpt :
The alternatives for developing an IT support system are either that companies in industry, trade associations, or professional associations could coordinate to finance the project or that government could see it as part of its duty of informing the regulated of their obligations. If two or more agencies regulate the same activity of the company, those regulations may overlap and even conflict (Lord Robens, 1972; de Gelder, 1997; Burman and Daum, 2009; Aagaard, 2011). Aagard shows that overlapping jurisdictions (he examines overlap between the Occupational Safety and Health Administration and the Environmental Protection Agency) need not cause problems if the overlap is explicitly managed by the two agencies.
There is a strong political consensus in a number of countries that occupational safety and health regulation is stifling industrial innovation and development and is feeding a culture of damaging risk aversion and petty bureaucracy. In a number of countries this has led to proposals to repeal regulations and reduce the regulatory burden. The authors were commissioned to prepare a discussion paper on this issue by the Mercatus Center of George Mason University in Arlington, Virginia, aimed particularly at an American audience. This paper is based on that report (Hale et al., 2011).
The paper is based on previous work of the first two authors, developing a framework of occupational safety rule management at the workplace level (Hale and Borys, 2012a,b). Based on a literature study, this paper analyses the similarities and differences between rules at the workplace level and the development, use and enforcement of regulations at the national level to influence and control organisational behavior. It traces the forces encouraging the growth of regulatory detail and hence the bureaucratic burden of compliance and the options open to reduce that burden without loosening control so much that the level of safety declines. The analysis uses the hierarchy of rules from goals, through process (risk management) rules to detailed action rules as framework for predicting the level of ownership and responsibility felt by the regulated.
Ontology-based semantic modeling of regulation constraint for automated construction quality compliance checking
2012, Automation in Construction
Citation Excerpt :
As Demir et al. pointed out, most regulations are presented as texts, whether paper or electronic, in order to give more computerized support to the users of regulations, it is necessary to represent the regulation knowledge in a formal and computer-interpretable way [12]. The review of regulation knowledge modeling and automatic rule-based checking (although dedicated in building design domain) can be obtained in refs. [12–14]. Previous research efforts mainly focused on the procedural implementation approach.
Regulations play an important role in assuring the construction quality. However, due to the large amount of regulation needs considered, the construction quality compliance checking against regulations can be cumbersome/time-consuming and error prone. In order to give more computerized support to the construction quality compliance checking against regulations, an ontology-based semantic modeling approach of regulation constraints is explored. A meta model for construction quality inspection and evaluation i.e. CQIEOntology is proposed in this paper. Based on CQIEontology, the regulation constraints are modeled into OWL axioms and SWRL rules. By these OWL axioms and SWRL rules, the regulation provisions imposed on construction quality inspection can be translated into a set of inspection tasks, and get associated with the specific construction tasks. Once the construction starts, the applicable inspection tasks, including a series of quality checking and evaluation, will be reminded and recommended. Obviously, the proposed approach facilitates taking the construction quality compliance checking as a paralleling activity to the construction rather than an afterthought, and helps the inspectors in quality inspection. Finally, the approach is demonstrated in Protégé 3.4.6 through case studies based on regulation examples taken from “Code for Acceptance of Construction Quality of Building Foundation (GB50202-2002) and the validation and discussion are given for it.”
The regulation constraint modeling and semantic inferring in construction quality checking
2013, Structural Survey
Ontology-based approach for automated quality compliance checking against regulation in metro construction project
2012, Lecture Notes in Electrical Engineering

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Artificial Intelligence in Engineering

Conceptual modelling of building regulation knowledge

Abstract

The state of knowledge-based systems

Communications of the ACM

Computer Science

I lied about the trees, or, defaults and definitions in knowledge representation

AI Magazine

Tabular decision logic for structural design

Journal of the Structural Division

A building regulation question answering system: A deep learning methodology

Toward improving the quality compliance checking of urban private constructions in Iran: An ontological approach

Safety regulation: The lessons of workplace safety rule management for managing the regulatory burden

Ontology-based semantic modeling of regulation constraint for automated construction quality compliance checking

The regulation constraint modeling and semantic inferring in construction quality checking

Ontology-based approach for automated quality compliance checking against regulation in metro construction project