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The purpose of this paper is to put forward a Ultra-high Frequency Radio Frequency Identification (UHF-RFID) data model construction scheme for university libraries, hoping to realize the opening, uniform, compatible and interoperable RFID application between different libraries and manufacturers.

This article uses the practical application needs of university libraries as the starting point, and proposes the UHF-RFID data model construction scheme for university libraries based on the study of applicable standards, such as ISO 28560.

Based on practical application demand of university libraries and some international standards, the paper puts forward an UHF-RFID data model construction scheme for university libraries. First, the scheme explains and defines six user data elements different from ISO28560: version, owner library identifiers, temporary item location, subject, International Standard Serial Number (ISSN) and International Standard Book Number (ISBN). Furthermore, different encoding rules for electronic product code (EPC) data area and user data area are designed to achieve maximum work efficiency.

This paper tries to bring forward a set of referential UHF-RFID data model standards for university libraries. Hopefully, this standard will offer uniform data models for university libraries to comply with, integrate the disordered market and further make the opening, unified, compatible and interoperable RFID application possible.

Although there are several formally published RFID standard documents, they are primarily designed for high frequency RFID technology. Concerning UHF-RFID technology, there are still no internationally unified data model standards. Hence, this paper brings forward the UHF-RFID data model construction scheme for university libraries.

The purpose of this paper is to review and provide recommendations to extend the current open standard data models for describing monitoring systems and circular economy precepts for built assets. Open standard data models enable robust and efficient data exchange which underpins the successful implementation of a circular economy. One of the largest opportunities to reduce the total life cycle cost of a built asset is to use the building information modelling (BIM) approach during the operational phase because it represents the largest share of the entire cost. BIM models that represent the actual conditions and performance of the constructed assets can boost the benefits of the installed monitoring systems and reduce maintenance and operational costs.

This paper presents a horizontal investigation of current BIM data models and their use for describing circular economy principles and performance monitoring of built assets. Based on the investigation, an extension to the industry foundation classes (IFC) specification, recommendations and guidelines are presented which enable to describe circular economy principles and asset monitoring using IFC.

Current open BIM data models are not sufficiently mature yet. This limits the interoperability of the BIM approach and the implementation of circular economy principles. An overarching approach to extend the current standards is necessary, which considers aspects related to not only modelling the monitoring system but also data management and analysis.

To the authors’ best knowledge, this is the first study that identifies requirements for data model standards in the context current linear economic model of making, using and disposing is growing unsustainably far beyond the finite limits of planet of a circular economy. The results of this study set the basis for the extension of current standards required to apply the circular economy precepts.

There have been major efforts to develop the technology for integrated construction environments and the mechanisms needed to improve the collaboration between construction professionals. Evidently, the development and usage of such an environment is a complicated task. The two issues that can be among the main contributors to this are: the development of the technology and its effective implementation. These two issues are addressed separately in this paper. The paper first explains the approaches of sharing project information, followed by a review of a recent project in this area, the result of which is a distributed integrated construction environment based on the industry foundation class (IFC), capable of supporting a number of construction applications. This environment is capable of supporting a construction team to work collaboratively over the internet. It then discusses the difficulties facing the successful implementation of such environments in construction organisations. This is addressed within the context of two management models for effective implementation of IT: the resource‐based model and the Nolan model.

This paper presents an argument for automating data representations within the construction sector. It questions whether full automation and integration is feasible and achievable considering the complexity of the industry and supply chain problems. The paper starts by reviewing the research in the area of information automation, modelling and integration. A research prototype, GALLICON, is used as an example to demonstrate the levels of integration and automation that may be achieved with the current generation of technology.

Traceability of food is of paramount importance to the increasingly sustainability-conscious consumers. Several tracking and tracing systems have been developed in the AgriFood sector in order to prove to the consumers the origins and processing of food products. Critical challenges in realizing food's traceability include cooperating with multiple actors on common data sharing standards and data models.

This research applies a design science approach to showcase traceability that includes preharvest activities and conditions in a case study. The authors demonstrate how existing data sharing standards can be applied in combination with new data models suitable for capturing transparency information about plant production.

Together with existing studies on farm-to-fork transparency, our results demonstrate how to realize transparency from field to fork and enable producers to show a complete bill of sustainability.

The existing standards and data models address transparency challenges in AgriFood chains from the moment of harvest up to retail (farm-to-fork) relatively well, but not what happens before harvest. In order to address sustainability concerns, there is a need to collect data about production activities related to product quality and sustainability before harvesting and share it downstream the supply chain. The ability to gather data on sustainability practices such as reducing pesticide, herbicide, fertilizer and water use are crucial requirements for producers to market their produce as quality and sustainable products.

The purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index systems for the design optimization and inspection process. The research may form the basis for a rational, comprehensive evaluation and provide the most effective way of improving the quality of management decision-making. It is of practical significance to improve the rationality and reliability of the index system and provide standardized, scientific reference standards and theoretical guidance for the design and construction of the index system.

Using modern methods such as complex networks and machine learning, a system for the quality diagnosis of index data and the classification and stratification of index systems is designed. This guarantees the quality of the index data, realizes the scientific classification and stratification of the index system, reduces the subjectivity and randomness of the design of the index system, enhances its objectivity and rationality and lays a solid foundation for the optimal design of the index system.

Based on the ideas of statistics, system theory, machine learning and data mining, the focus in the present research is on “data quality diagnosis” and “index classification and stratification” and clarifying the classification standards and data quality characteristics of index data; a data-quality diagnosis system of “data review – data cleaning – data conversion – data inspection” is established. Using a decision tree, explanatory structural model, cluster analysis, K-means clustering and other methods, classification and hierarchical method system of indicators is designed to reduce the redundancy of indicator data and improve the quality of the data used. Finally, the scientific and standardized classification and hierarchical design of the index system can be realized.

The innovative contributions and research value of the paper are reflected in three aspects. First, a method system for index data quality diagnosis is designed, and multi-source data fusion technology is adopted to ensure the quality of multi-source, heterogeneous and mixed-frequency data of the index system. The second is to design a systematic quality-inspection process for missing data based on the systematic thinking of the whole and the individual. Aiming at the accuracy, reliability, and feasibility of the patched data, a quality-inspection method of patched data based on inversion thought and a unified representation method of data fusion based on a tensor model are proposed. The third is to use the modern method of unsupervised learning to classify and stratify the index system, which reduces the subjectivity and randomness of the design of the index system and enhances its objectivity and rationality.

Explores the use of extensible markup language (XML) to both store and enforce organizational data definitions, thus providing a synergetic framework for leveraging the potential of knowledge management (KM) tools. XML provides a flexible markup standard for representing data models. KM provides IT processes for capturing, maintaining, and using information. While the processes that comprise KM and the mechanisms that form XML differ greatly in concept, they both deal in a fundamental way with information. XML maintains the context of data (i.e. data model) which enables data to represent information. KM provides the framework for managing this information. Explores the vital role that XML can play to support an efficient corporate KM strategy.

The purpose of this paper is to describe the technical features, underlying concepts and implementation details of a novel Building Information Modeling (BIM)-integrated, graph-based platform developed to support BIM for facilities management through a usability driven visual representation of the construction operations building information exchange (COBie) spreadsheet data.

This paper is based on the iterative steps of design thinking and agile software development methodology. The conceptual development of the VisualCOBie platform is based on Gestalt’s principles of visual perception to facilitate usability and comprehension of the COBie data.

The paper demonstrates that Gestalt’s principles of visual perception provide a suitable conceptual as well as implementable basis for improving the usability and comprehension of COBie spreadsheets. The implemented BIM-integrated, graph-based VisualCOBie platform supports visual navigation and dynamic search, reducing the cognitive load of large spreadsheets that are common in facilities management software.

The usability, visual search and dependencies-based search of VisualCOBie can potentially transform how we implement and use facilities and information management systems in construction, where large spreadsheets are frequently used in conjunction with BIM and other tools. VisualCOBie also provides usability-based step towards BIM for facilities management.

The VisualCOBie approach provides a novel user interface and information management platform. This paper may also foster a potential paradigm shift in our approach to the representation and use of information exchange standards such as COBie, which are required to facilitate the research and practice on BIM for facilities management.

The purpose of this paper is to compare the use of two Object-Relational models against the use of a post-Relational model for a realistic application. Although real-world applications, in most cases, can be adequately modeled by the Entity-Relationship (ER) model, the transformation to the popular Relational model alters the representation of structures common in reality, like multi-valued and composite fields. Alternative database models have been developed to overcome these shortcomings.

Based on the ER model of a medical application, this paper compares the information representation, manipulation and enforcement of integrity constraints through PostgreSQL and Oracle, against the use of a post-Relational model composed of the Conceptual Universal Database Language (CUDL) and the Conceptual Universal Database Language Abstraction Level (CAL).

The CAL/CUDL pair, although more periphrastic for data definition, is simpler for data insertions, does not require the use of procedural code for data updates, produces clearer output for retrieval of attributes, can accomplish retrieval of rows based on conditions that address composite data with declarative statements and supports data validation for relationships between composite data without the need for procedural code.

To verify, in practice, the conclusions of the paper, complete implementation of a CAL/CUDL system is needed.

The use of the CAL/CUDL pair would advance the productivity of database application development.

This paper highlights the properties of realistic database-applications modelling and management that are desirable by developers and shows that these properties are better satisfied by the CAL/CUDL pair.

This paper aims to provide top-level design and basic platform for intelligent application in China high-speed railway.

Based on the analysis for the future development trends of world railway, combined with the actual development needs in China high-speed railway, The definition and scientific connotation of intelligent high-speed railway (IHSR) are given at first, and then the system architecture of IHSR are outlined, including 1 basic platform, 3 business sectors, 10 business fields, and 18 innovative applications. At last, a basic platform with cloud edge integration for IHSR is designed.

The rationality, feasibility and implementability of the system architecture of IHSR have been verified on and applied to the Beijing–Zhangjiakou high-speed railway, providing important support for the construction and operation of the world’s first IHSR.

This paper systematically gives the definition and connotation of the IHSR and put forward the system architecture of IHSR for first time. It will play the most important role in the design, construction and operation of IHSR.