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To provide a selective bibliography for researchers and practitioners interested in database modeling of engineering information with sources which can help them develop engineering information systems.

Identifies the requirements for engineering information modeling and then investigates how current database models satisfy these requirements at two levels: conceptual data models and logical database models.

Presents the relationships among the conceptual data models and the logical database models for engineering information modeling viewed from database conceptual design.

Currently few papers provide comprehensive discussions about how current engineering information modeling can be supported by database technologies. This paper fills this gap. The contribution of the paper is to identify the direction of database study viewed from engineering applications and provide a guidance of information modeling for engineering design, manufacturing, and production management.

Facilitating the information exchange and interoperability between stakeholders during the life-cycle of an asset can be one of the fundamental necessities for developing an enhanced information exchange framework. Such a framework can also improve the successful accomplishment of building projects. This paper aims to use Semantic Web technologies for facilitating information exchange within existing building projects.

In real-world building projects, the construction industry’s information supply chain may initiate from near scratch when new building projects are started resulting in diverse data structures represented in unstructured data sources, like Excel spreadsheets and documents. Large-scale data generated throughout a building's life-cycle requires exchanging and processing during an asset's Operation and Maintenance (O&M) phase. Building information modelling (BIM) processes and related technologies can address some of the challenges and limitations of information exchange and interoperability within new building projects. However, the use of BIM in existing and retrofit assets has been hampered by the challenges surrounding the limitations of existing technologies.

The aim of this paper is twofold. Firstly, it briefly outlines the framework previously developed for generating semantically enriched 3D retrofit models. Secondly, a framework is proposed focussing on facilitating the information exchange and interoperability for existing buildings. Semantic Web technologies and standards, such as Web Ontology Language and existing AEC domain ontologies are used to enhance and improve the proposed framework.

The proposed framework is evaluated by implementing an example application and the Resource Description Framework data produced by the previously developed framework. The proposed approach makes a valuable contribution to the asset/facilities management (AM/FM) domain. It should be of interest to various FM practices for existing assets, such as the building information/knowledge management for design, construction and O&M stages of an asset’s life-cycle.

The purpose of this paper is to propose a framework of decision making to aid practitioners in modeling and optimization experimental data for improvement quality of industrial processes, reinforcing idea that planning and conducting data modeling are as important as formal analysis.

The paper presents an application was carried out about the modeling of experimental data at mining company, with support at Catholic University from partnership projects. The literature seems to be more focussed on the data analysis than on providing a sequence of operational steps or decision support which would lead to the best regression model given for the problem that researcher is confronted with. The authors use the concept of statistical regression technique called generalized linear models.

The authors analyze the relevant case study in mining company, based on best statistical regression models. Starting from this analysis, the results of the industrial case study illustrates the strong relationship of the improvement process with the presented framework approach into practice. Moreover, the case study consolidating a fundamental advantage of regression models: modeling guided provides more knowledge about products, processes and technologies, even in unsuccessful case studies.

The study advances in regression model for data modeling are applicable in several types of industrial processes and phenomena random. It is possible to find unsuccessful data modeling due to lack of knowledge of statistical technique.

An essential point is that the study is based on the feedback from practitioners and industrial managers, which makes the analyses and conclusions from practical points of view, without relevant theoretical knowledge of relationship among the process variables. Regression model has its own characteristics related to response variable and factors, and misspecification of the regression model or their components can yield inappropriate inferences and erroneous experimental results.

Changes in market and production profiles require a more flexible concept in manufacturing. Computer integrated manufacturing (CIM) describes an integrative concept for joining business and manufacturing islands. In this context, database technology is the key technology for implementing the CIM philosophy. However, CIM applications are more complex and thus more demanding than traditional database applications such as business and administrative applications. Systematically analyses the database requirements for CIM applications including business and manufacturing tasks. Special emphasis is given on integration requirements due to the distributed, partly isolated nature of CIM applications developed over the years. An illustrative sampling of current efforts in the database community to meet the challenge of non‐standard applications such as CIM is presented.

A survey of current work on database systems is presented. The area is divided into three main sectors: data models, data languages and support for database operations. Data models are presented as the link between the database and the real world. Languages range from formal algebraic languages to attempts to use a dialogue in English to formulate queries. The support includes hardware for content addressing, database machines and software techniques for optimizing and evaluating group expressions. Mathematical models are used to organize this support. Throughout there is a tutorial component and evaluation, which in both cases is related to the application of database ideas to documentation.

The purpose of this paper is to propose a new deep learning-based model to carry out better maintenance for naval propulsion system.

This model is constructed by integrating different deep learning algorithms. The basic idea is to change the connection structure of the deep neural network by introducing a residual module, to limit the prediction output to a reasonable range. Then, connect the Deep Residual Network (DRN) with a Generative Adversarial Network (GAN), which helps achieve data expansion during the training process to improve the accuracy of the assessment model.

Study results show that the proposed model achieves a better prediction effect on the dataset. The average performance and accuracy of the proposed model outperform the traditional models and the basic deep learning models tested in the paper.

The proposed model proved to be better performed naval propulsion system maintenance than the traditional models and the basic deep learning models. Therefore, our model may provide better maintenance advice for the naval propulsion system and will lead to a more reliable environment for offshore operations.

The purpose of this paper is to conceptualize data quality (DQ) in the context of business process management and to propose a DQ oriented approach for business process modeling. The approach is based on key concepts and metrics from the data quality management domain and supports decision‐making in process re‐design projects on the basis of process models.

The paper applies a design oriented research approach, in the course of which a modeling method is developed as a design artifact. To do so, method engineering is used as a design technique. The artifact is theoretically founded and incorporates DQ considerations into process re‐design. Furthermore, the paper uses a case study to evaluate the suggested approach.

The paper shows that the DQ oriented process modeling approach facilitates and improves managerial decision‐making in the context of process re‐design. Data quality is considered as a success factor for business processes and is conceptualized using a rule‐based approach.

The paper presents design research and a case study. More research is needed to triangulate the findings and to allow generalizability of the results.

The paper supports decision‐makers in enterprises in taking a DQ perspective in business process re‐design initiatives.

The paper reports on integrating DQ considerations into business process management in general and into process modeling in particular, in order to provide more comprehensive decision‐making support in process re‐design projects. The paper represents one of the first contributions to literature regarding a contemporary phenomenon of high practical and scientific relevance.

In this paper we discuss an area of information systems management and development that appears to have been practised by many major European and US organisations: the area of corporate data modelling. However, rather suprisingly perhaps, it is clear that there is little theoretical or empirical literature devoted to this important issue. There is little empirical evidence to indicate the actual scale of adoption of this practice, and there is certainly little analytical material devoted to questions of the efficacy of this activity or considerations of good practice in this area. The main aim of this paper is to begin to offer some early empirical and analytical material on corporate data modelling. We have been conducting a study of a number of organisation’s experience of corporate data modelling in the UK. We would hope that an examination of the current corporate experience of corporate data modelling will stimulate a clearer discussion of the purposes and practices of this important area of modern information systems planning.

Electronic product catalogues and brochures are gaining popularity, but there is little agreement on content, format, and searching methods. This limits their usability and integration with existing construction software tools. This paper examines a product‐modelling approach to delivering building product information and describes a proposed multi‐tier client‐server environment. ISO/STEP and IAI/IFC building product models are considered to facilitate representation, exchange, and sharing of product information. The proposed architecture incorporates scalability with middleware components that would provide single or few points of entry to integrated product information. This paper is part of a research project that builds on the results of related projects including Construct IT Strategy, PROCAT‐GEN, Active Catalog, COMBINE, and ARROW, towards implementing the required software components.

In data engineering, view formalisms are used to provide flexibility to users and user applications by allowing them to extract and elaborate data from the stored data sources. Conversely, since the introduction of EXtensible Markup Language (XML), it is fast emerging as the dominant standard for storing, describing, and interchanging data among various web and heterogeneous data sources. In combination with XML Schema, XML provides rich facilities for defining and constraining user‐defined data semantics and properties, a feature that is unique to XML. In this context, it is interesting to investigate traditional database features, such as view models and view design techniques for XML. However, traditional view formalisms are strongly coupled to the data language and its syntax, thus it proves to be a difficult task to support views in the case of semi‐structured data models. Therefore, in this paper we propose a Layered View Model (LVM) for XML with conceptual and schemata extensions. Here our work is three‐fold; first we propose an approach to separate the implementation and conceptual aspects of the views that provides a clear separation of concerns, thus, allowing analysis and design of views to be separated from their implementation. Secondly, we define representations to express and construct these views at the conceptual level. Thirdly, we define a view transformation methodology for XML views in the LVM, which carries out automated transformation to a view schema and a view query expression in an appropriate query language. Also, to validate and apply the LVM concepts, methods and transformations developed, we propose a viewdriven application development framework with the flexibility to develop web and database applications for XML, at varying levels of abstraction.