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The ongoing problem of inconsistency in the stages of system development encourages the development and elaboration of approaches and methods aimed at eliminating the causes of their occurrence. According to the research community, one of the most promising approaches is to involve users in the development process. Six directions in the implementation of the approach to user involvement in the system development process were formed and analyzed in the article. The analysis of the applicability of such approaches and methods to the task of involving the user in the process of developing an information data model is carried out. The problems of this direction were highlighted. To solve these problems, the sensemaking approach principles which is a development of the methodology for sensemaking proposed by Brenda Dervin, are proposed to use. On the basis of the proposed sensemaking approach, the implementation of the proposed approach is shown with the help of the development of the method, a method for constructing the specification of the information model was developed. The steps of the method are represented by methods that implement the idea of involving the user in the development process by analyzing his work with elements of documentation support.

This paper presents approaches for the employment of non-contact sensing to enhance both the efficiency and reliability of numerical modelling of historic masonry. It commences with a thorough review of the high-level numerical modelling approaches of historic masonry. Following, the accuracy and cost-effectivity of available non-contact sensing techniques are reviewed for surveying masonry structures. These are: a) the total station; b) the laser tracker; c) Structure-from-Motion (SfM) photogrammetry; and d) terrestrial laser scanning (TLS). Then, strategies of automatically developing geometric models (i.e., numerical models before structural analysis) from geospatial data are reviewed, considering their potential for automation and usage. These were based on the employment of: a) point clouds; b) meshes; c) non-uniform rational basis splines (NURBSs); d) building information models (BIMs); e) orthoimages; and f) discrete points. Primarily, the review found that high-level numerical modelling approaches such as the continuum and block-based models are highly effective, but necessitate accurate geometric data for reliable results. To bridge this gap, the potential of emerging technologies such as SfM photogrammetry was found to significantly improve the efficiency and robustness of high-level structural analysis, through providing geometric data accurately and with a low cost. Moreover, the cloud-based (i.e., with a point cloud) and image-based (i.e., with an orthoimage) approaches of converting geospatial data into numerical models were also found the most effective, for continuum and block-based modelling respectively. This contribution demonstrates the potential to employ novel digital technologies such as non-contact sensing techniques to improve the efficiency and robustness of high-level numerical modelling approaches.

Higher education institutions are becoming increasingly complex and self-developing systems. Monitoring the activities of such systems requires a special approach and includes three main elements, that is, external monitoring, independent evaluation and internal monitoring. In the framework of this article, the main task of monitoring is the analysis and disclosure of internal patterns, causes and trends of the development processes of a university. In these conditions, the need to move to a broader model for solving and reducing complexity based on information and knowledge is revealed. The model reduces the uncertainty of the environment and thus provides more effective decision-making. The monitoring model includes changes in the strategic planning process that are consistent with the characteristics of the new organizational model. Ontologies, as a theory of content, which allow formalizing processes and knowledge, are a key element in this context.

The relevance of the study is conditioned by the need to strengthen the management function of an agricultural enterprise that focuses on the principles of sustainable development and aims to modernise accounting and analytical support for managing economic potential. The purpose of the study is to form a strategy for the desired improvement of accounting and analytical support of the enterprise with an emphasis on: reporting on sustainable development; expansion of the analytical complex of indicators of economic potential, capacity and performance of an agricultural enterprise; improvement of accounting and analytical support of enterprises using this information model through updating the documentation of control and audit. The theoretical and methodological basis was formed by scientific methods based on the dialectic of knowledge and objective laws of the development of the economy, nature, and society. Economic and mathematical modelling, systematisation and synthesis helped to develop a strategy to improve accounting and analytical support for managing the economic potential of agricultural enterprises, taking into account the principles of sustainable development. This type of modelling can help to effectively modernise accounting and analytical support for managing the economic potential for agricultural enterprises. The developed information model of selective adaptation helps managers of various levels to monitor the implementation of business processes for improving accounting and analytical support for economic potential management, assess the degree of achievement of priority goals and compliance with the principles of sustainable development. One of the steps of long-term modernisation of accounting and analytical support for agricultural enterprises through the introduction of sustainable development reporting is proposed, which should include indicators and documents on managing the economic potential, economic capacity, and performance of agricultural enterprises. The advantage of this information model is the ability to calculate the complexity index of transformation of accounting and analytical support for economic potential management using the principles of sustainable development, which shows the level of complexity of future modernisation of these aspects

Possibility theory is a computationally efficient framework for reasoning with imprecise probabilities. Before performing any possibilistic analysis, however, the (imprecise) probabilistic information about the experiment needs to be expressed in the form of a possibility distribution. In this paper, we propose a novel Imprecise Probability-to-Possibility Transformation. This method unifies many results in quantitative possibility theory concerning information modeling, data analysis, and the construction of joint distributions. Furthermore, we show how it enables new results about possibilistic information aggregation and how it may refine frequentist inference in (im-)precise statistical models. The approach is characterized by a clear distinction between the elementary events' well-known objective possibilities from quantitative possibility theory and the elementary events' subjective plausibilities, a reimagination of qualitative possibility measures, which helps overcome several non-uniqueness issues.

The aim of the study is to try to analyze the most common mechanisms of impulse noise impact on data transmitted in the symbols of single-carrier and multi-carrier modulation systems. The paper solves the problem of a qualitative analysis of the destructive effect of impulse noise on the possibility of restoring symbols of digital modulation systems operating on the basis of a copper cable infrastructure. The performed analysis uses induction as research methods, which allows extending isolated special cases of symbol distortion to the generalized procedures for degrading the transmitted information quality; an analogy involving the consideration of similar mechanisms for modifying data in a stream of modulated signals with one carrier and multiple ones. The novelty of the findings obtained consists in generalizing the process of decoding errors due to noise bursts to the systems with one carrier and several ones, as well as in differentiating the influence of the noise pulse duration and power on the transmitted symbols. As the main findings of the work, we can note the identification of the impact ambiguity of impulse noise on the transmission systems of digital subscriber lines, expressed in the necessity to take into account while analyzing both the parameters of the noise itself and the type of modulation, and the energy and time relationships between the useful signal and noise. Thus, the work shows that the destructiveness degree of the impulse noise impact on the transmission system of a digital subscriber line is determined by several characteristics that should be taken into account when developing mechanisms for the protection against interference, or, conversely, to justify the inappropriateness of their use.

With the advancement of information construction, as an important part of smart city, the construction of smart society is invested. As a new mode of social management innovation under the new situation, the advantage of smart society is that it can complete the full integration of existing public resources and infrastructure, realize the knowledge mining of appearance information, so as to make social services and management more information-based and intelligent based on the common needs of smart social management, this paper analyzes the overall function of social management system in detail, puts forward the architecture and simulation of social management service system based on internet of things information model, and realizes the smart social management system, so as to make social service more high-quality and efficient, and social management more standardized and scientific. This paper describes how to promote social management services, and the specific needs of social information as the research basis of this paper, realize the application of social information integrated management service platform, and then give play to the advantages of information technology, realize the transformation of social management work mode, facilitate the social management work, improve the overall quality of life of the community, and reduce the cost of management.

Recent technological developments in the construction industry are seeking to create smart cities by using Cyber-Physical Systems (CPSs) to enhance information models such as BIM. Currently, BIM models are commonly adopted to work with IoT-based systems and embrace smart technologies that offer interoperability in the communication layer. In future, it is envisioned that digital twins will provide new possibilities for cyber-physical systems via monitoring and simulation. However, rarely in this rapidly developing field is security fully considered. This paper reviews the relevant literature regarding the use of the IoT in the built environment and analyses current practices. It also presents examples of cities that use the IoT to improve construction and the lived experience. Finally, it reviews how digital twins factor in multiple layers defined in CPSs, from physical objects to information models. Based on this review, recommendations are provided documenting how BIM specifications can be expanded to become IoT compliant, enhancing standards to support cybersecurity, and ensuring digital twin and city standards can be fully integrated in future secure smart cities.

Condition monitoring (CM) is the escort of smart manufacturing, which guarantees safety, precision, and efficiency of production process. However, traditional CM capacities with limited storage and computing resources cannot follow the explosive growth of manufacturing data. Empowered by the emerging Internet of Things, cyber–physical system, and cloud computing, cloud manufacturing (CMfg) characterizes a new service-oriented technology, which is reshaping the CM paradigm into an agile, scalable, and interoperable mode. In this article, a CMfg-based CM platform for smart manufacturing is proposed. A 5G wireless communication network-based edge computing system is presented to achieve data acquisition, feature extraction, and emergency response with ultrareliability and low-latency communication. In order to deal with the issue of data management and analysis, a generic open platform communications unified architecture information model oriented to the workshop is proposed in the fog layer. The cloud monitoring platform is constructed encompassing message delivery, data storage, status visualization, and training of artificial intelligence models. Finally, a CMfg-based CM system and a CMfg-based tool wear estimation system are outlined as two industrial cases. The experiments verify the feasibility and effectiveness of the proposed platform.

In information modeling, it is important to determine the content, direction and form of information flows. Information flows of environmental education are formed in the visitor center, distributed across the territory of ecotourism and are aimed at forming an ecological mentality among various groups of visitors to the territory of ecotourism. The information system of environmental education and enlightenment, which forms a responsible attitude of tourists to their natural environment, is integrated into the tourist framework of the territory. The decomposition of the network of tourist routes in the Central part of Eastern Sayan made it possible to determine the field of influence of information centers and to identify the main characteristics: the general theme of expositions, environmental routes, a set of functions and architectural style. The territory of ecotourism is considered as a social space. The power of influence of information objects depends on their position in the social space, which is determined by the size of their social capital. The methodological approach to modeling the information content of the ecological and educational visit center is the concept of the social field of P. Bourdieu, where the ecological field seeks to maximize its influence. The institution that exerts this influence is the educational system. As a result, the author proposed a conceptual model of the environmental education system, the essence of which is that the content of the main theme of the visit center should correspond to its field of influence.

Current development and management of economic activity is largely associated with the implementation of the concept of the digital economy, which poses new challenges for business intelligence. The set of tasks is formed in order to develop business intelligence so that it matches the improved management of economic subjects, and to ensure the quality of business processes when digital technologies are introduced. Improved management based on the concept of the business environment implies that monitoring principles are used to analyze the behavior of external business environment participants with the purpose to build a rational partnership relationship. The digital economy creates information opportunities in this area, as it provides the access to Big Data and their processing using Big data analytics technologies. With regard to the requirements of management, the article analyzes the behavior of elements of the internal business environment to develop a management solution to improve the effectiveness of their behavior. The high quality of the solution is provided by the information model being a highly adequate image of a particular object under control and the ability of the control apparatus to fully realize the volume of its inherent functions. Under these conditions, the digital transformation of analytical processes is based on its own information platform, which should use breakthrough digital technologies. The research uses such methods as systemic analysis to generalize the modern concepts of economic system management, development of digital technologies and their introduction into management decision-making processes.

Current detection networks usually struggle to detect small-scale object instances due to spatial information loss and lack of semantics. In this paper, we propose a one-stage detector named LocalNet, which pays specific attention to the detailed information modeling. LocalNet is built upon our redesigned detection-oriented backbone called long neck ResNet, which aims to preserve more detailed information in the early stage to enhance the representation of small objects. Furthermore, to enhance the semantics in the detection layers, we propose a local detail-context module, which reintroduces the detailed information lost in the network and exploits the local context within a restricted receptive field range. Moreover, we explore a method for training detectors nearly or totally from scratch, which provides the potential to design network structures with more freedom. With nearly $$94\%$$ of the pretrained parameters randomly reinitialized in the backbone, our model improves the mAP of our baseline model from 75.0 to $$82.3\%$$ on the PASCAL VOC dataset with an input size of $$300\times 300$$ and achieves state-of-the-art accuracy. Even when trained from scratch, our model achieves $$80.8\%$$ mAP, which is $$5.8\%$$ greater than the mAP of our baseline model with a fully pretrained backbone.

The service information system is constantly transforming to a networked information model, and domestic hardware equipment is constantly updated. Independent controllability has also become the basic requirement of the new information age. With the development of the information age and the new era of independent control, more and more services and applications will also be deployed on autonomous and controllable cloud platforms. With the rapid development of Internet technology in the information age and the resulting changes in productivity, people can record, store, and transmit more and more information. When information becomes recordable, storage, and easy to transmit, information becomes modern meaning nowadays, an era of information explosion characterized by massive, volatile, timely transmission, and diverse forms has truly come, forming what is now called the “big data era”. This article mainly introduces the analysis of sports big data based on the cloud platform and the research on the impact on the sports economy and intends to provide ideas and directions for the analysis of sports big data and the research on the impact on the sports economy. This paper proposes a cloud platform-based sports big data analysis and research methods for its impact on the sports economy, including the use of Hadoop cloud platform big data processing systems and support vector regression algorithms for cloud platform-based sports big data analysis and sports economy. The experimental results of this paper show that the average correlation between sports big data analysis and sports economic development is 0.5155, and appropriate cloud platform-based sports big data analysis plays a positive role in promoting sports economic development.

This paper presents an indoor navigation support system based on the Building Information Models (BIM) paradigm. Although BIM is initially defined for the Architecture, Engineering and Construction/Facility Management (AEC/FM) industry, the authors believe that it can provide added value in this context. To this end, the authors will focus on the Industry Foundation Classes (IFC) standard for the formal representation of BIM. The approach followed in this paper will be based on the ifcOWL ontology, which translates the IFC schemas into Ontology Web Language (OWL). Several modifications of this ontology have been proposed, consisting of the inclusion of new items, SWRL rules and SQWRL searches. This way of expressing the elements of a building can be used to code information that is very useful for navigation, such as the location of elements related to the actions desired by the user. It is important to note that this design is intended to be used as a complement to other well-known tools and techniques for indoor navigation. The proposed modifications have been successfully tested in a variety of simulated and real scenarios. The main limitation of the proposal is the immense amount of information contained in the ifcOWL ontology, which causes difficulties involving its processing and the time necessary to perform operations on it. Those elements that are considered important have been selected, removing those that seem secondary to navigation. This procedure will result in a significant reduction in the storage and semantic processing of the information. Thus, for a system with 1000 individuals (in the ontological sense), the processing time is about 90 s. The authors regard this time as acceptable, since in most cases the tasks involved can be considered part of the system initialization, meaning they will only be executed once at the beginning of the process.

In this paper a semantic metalanguage is developed and designed to study the occurrence, spread and safe interaction of semantic processes in information modeling systems, including cognitive interference. An approach to construe a semantic network is proposed and based on a computational model in which both nodes and arcs are information processes. Concepts are represented by intensional objects within the framework of theories without types, and they, in turn, are considered as special counterparts of typed theories. Similar mixing was used in model studies for lambda calculus. To a contrast with them, in this paper, information processes correspond to parameterized metadata objects, which are variable domain constructs. Transformations of variable domains correspond to the spread of the process. Directional transformation provides the generation of metadata targets in the form of parameterized concepts. This simulates the development of the process, which corresponds to the spread of cognitive interference and allows the interpretation of a hidden time factor. The emerging model is purely process based and provides such a conceptual framework. The possibility of coding this framework with a system of interdependent lambda terms is reflected.

In the world of the Internet of Things (IoT), heterogeneous systems and devices need to be connected and exchange data with others. How data exchange can be automatically realized becomes a critical issue. An information model (IM) is frequently adopted and utilized to solve the data interoperability problem. Meanwhile, as IoT systems and devices can have different IMs with different modeling methodologies and formats such as UML, IEC 61360, etc., automated data interoperability based on various IMs is recognized as an urgent problem. In this paper, we propose an approach to automate the data interoperability, i.e. data exchange among similar entities in different IMs. First, similarity scores among entities are calculated based on their syntactic and semantic features. Then, in order to precisely get similar candidates to exchange data, a concept of class distance calculated with a Virtual Distance Graph (VDG) is proposed to narrow down obtained similar properties for data exchange. Through analyzing the results of a case study, the class distance based on VDG can effectively improve the precisions of calculated similar properties. Furthermore, data exchange rules can be generated automatically. The results reveal that the approach of this research can efficiently contribute to resolving the data interoperability problem.

The article is devoted to clarification of the structure of maintenance of low-intensity railways by optimising infrastructure maintenance operational personnel using the example of Mikunsky infrastructure section of the Northern Infrastructure Directorate of Russian Railways. As an example of the distance for operation of infrastructure, the article considers Berlin section of infrastructure of German railways. The task of organising the activities of the infrastructure linear enterprise of the track complex, including track section workers (PC), signalling, centralisation and blocking (SCB) maintenance section personnel working within enlarged teams and emergency repairs teams equipped with service trains and KamAZ vehicles, is considered. For the analysis of information uncertainty, an information model is proposed, for which the risk is considered in the form of determining losses. At the stage of preliminary calculations, a change in the number of maintenance personnel will make it possible to obtain a reduction in operating costs.

Online social networks (OSNs) have become so popular that it has changed the Internet to a more collaborative environment. Now, a third of the world’s population participates in OSNs, forming communities, and producing and consuming media in different ways. The recent boom of artificial intelligence technologies provides new opportunities to help improve the processing and mining of social data. In this article, an algorithm that can detect communities in the OSNs using the concepts of granular computing in rough sets is proposed. In this information model, a social network as a rough set granular social network (RGSN) is modeled. A new community detection algorithm named granular-based community detection (GBCD) is implemented. This article also defines and uses two measures, namely, a granular community factor and an object community factor. The proposed algorithm is evaluated on four real-world data sets as well as computer-generated data sets. The model is compared with other state-of-the-art community detection algorithms for the values of modularity, normalized mutual information (NMI), Omega index, accuracy, specificity, sensitivity, and $F1$ -measure. The cumulative performance of the GBCD algorithm is found to be 3.99, which outperforms other state-of-the-art community detection algorithms.

PurposeTo meet the emerging demand for fine-grained annotation and semantic enrichment of cultural heritage images, this paper proposes a new approach that can transcend the boundary of information organization theory and Panofsky's iconography theory.Design/methodology/approachAfter a systematic review of semantic data models for organizing cultural heritage images and a comparative analysis of the concept and characteristics of deep semantic annotation (DSA) and indexing, an integrated DSA framework for cultural heritage images as well as its principles and process was designed. Two experiments were conducted on two mural images from the Mogao Caves to evaluate the DSA framework's validity based on four criteria: depth, breadth, granularity and relation.FindingsResults showed the proposed DSA framework included not only image metadata but also represented the storyline contained in the images by integrating domain terminology, ontology, thesaurus, taxonomy and natural language description into a multilevel structure.Originality/valueDSA can reveal the aboutness, ofness and isness information contained within images, which can thus meet the demand for semantic enrichment and retrieval of cultural heritage images at a fine-grained level. This method can also help contribute to building a novel infrastructure for the increasing scholarship of digital humanities.

The paper describes the method of using laser scanning as a way to help identify problems and collisions that cannot be detected using 2D drawings. The study shows the advantages of creating an information model of a metro station using point clouds, compared to creating a model based only on ready-made drawings. The main goals of creating digital twins of underground complexes – metro stations-are listed in the paper and an algorithm for transferring a real object into a 3D model is considered. As an example for the study, an underground object was considered – a metro station that requires reconstruction and was built in the 1950s. As a result of processing the initial laser scanning data, a number of issues were found that need to be resolved: the object does not meet the standards for dimensions, it is not possible to place / bring equipment, and the station subsidence. It is concluded that the use of laser scanning to create a 3D model of underground complexes-metro stations helps to detect errors and potential problems at the design stage. Such problems cannot be identified using 2D drawings, so the availability of laser scanning results gives an advantage during construction and reconstruction.

The ease of software development, maintenance, commissioning and reconfiguration is paramount in industrial systems, because these must be adaptable to changes in customer demand and the evolution of production assets. Such adaptations are a core motivator in the fourth industrial revolution. Additionally, software applications should be able to communicate over the logical and geographical borders of production plants, regardless of software platforms and vendors. However, these issues remains unaddressed in current software tools, although a solution is reachable with a proper software toolkit. As a solution, this article introduces such a toolkit to support the development of industrial software systems. The toolkit implements a communication stack with both a communication protocol and an information model. The long-term goal is to enable all communication in industrial plants with such a toolkit regardless of software products, vendors and platforms. Additionally, the toolkit provides auxiliary tools to help in the development of industrial software, such as services to provide historical data for simulation purposes. As an outcome, the toolkit provides insight about the development needs of industrial communications. publishedVersion

For the development of OPC UA servers for machine tools the complex architecture of numeric controls and programmable logic controllers is often depicted in a structure focused on data. The information models provide access to a wide set of available data points but lack intuitive functions, such as handling of NC programs and controlling auxiliary systems, which would be used by machine operators in manual mode. The information model presented in this paper shows a possible solution to combine data and functionality of machine tools in an intuitive structure in order to simplify navigation for clients and users.

This paper presents a notation to model business processes in the context of B2B (Business to Business) systems. Data-awareness is a key asset of the notation: data is placed at the forefront of process representations and task execution is data-driven instead of control-driven. In addition to process models, the notation (B2BPN) includes three other types of models, i.e. the architectural model, the collaboration models and the information model of the process. Data can transit between B2B processes through the interactions defined in the collaboration models and such models represent the relationships between the companies taking part in B2B systems. The notation is illustrated with an example concerning the order management of a distributor.

The system development process is becoming increasingly complex as the systems themselves become more and more complex. At the same time, the various disciplines such as mechanical engineering, electrical engineering and software engineering are becoming increasingly intermixed, so that companies in one discipline are experiencing leaps and bounds in the complexity of their systems and their development. For this reason, this publication presents a concept of a virtual assistant that leads through a development phase. It shows that the software supporting the development needs an information model to store the data of the developed system and to connect it with the existing knowledge. This knowledge can either be available internally or on the web. The development process should therefore support cooperation so that the assistance software and engineers interact with each other.

Advanced manufacturing in the context of the digital thread has mainly focused on process information related to the integration of machining processes, tools, operations, and specific manufacturing parameters. However, no unified information model has been developed to represent specific manufacturing process in 3D printing. This work therefore proposes a STEP/STEP-NC-compliant process data model to define specific application objects and entities, to model manufacturing data relationships and constraints, and to standardize process parameters through extended 3D printing concepts in fused deposition modelling (FDM). This data model describes manufacturing layers, deposition operations and process parameters in the context of the digital thread. As a special feature, manufacturing layers provide geometric information to layered operations based on STEP/STEP-NC standards for additive manufacturing (AM). Deposition operations specify the definitions of print devices or headers, header paths, FDM technology and functions, and even deposition strategy. Process parameters mainly provide process information in the FDM process. Finally, a conformance testing process is developed, focussed on manufacturing layers and header paths and by means of information exchange.

A method for determining the parameters of heating systems for hydraulic presses is proposed, including: decomposition of the general problem into optimization tasks for elements of a heating system; mathematical formulations of optimization tasks and determination of information flows between them; the structural determination of automation system for selecting parameter values of hydraulic press heating systems and the functions of its elements; the development of mathematical models describing the functionality of heating systems elements for hydraulic presses along with corresponding information models for storing and processing information about the source data and results of solving optimization tasks; the formation of a relational database of heating system elements for hydraulic presses, whose tables are based on the analysis of information models representing the characteristics of press elements and sets of permissible values of the characteristics to be selected. Elements of the developed automation system for determining the parameters of heating systems were used to perform calculations of heating systems for industrial presses ordered by Tambovpolymermash Plant JSC and ARTI-Zavod JSC.

Constructing a fully mapped virtual world is the premise of establishing the digital twin system; thus, the integration of BIM (Building Information Modeling) and GIS (Geographic Information System) constitutes a fundamental part of the mature digital twin. Although quite a few theoretical unified data models of BIM and GIS integration have been presented in precedent research, the practical web-based applications and software support for real-world city information modeling are still difficult to achieve. One of the challenges is storage inefficiency. It thence leads to burdens in exchange and analysis, which hugely impede the realization of virtual-real fusion. To address that issue, in this research, we contribute to exploring an HDF- (Hierarchical Data Format-) based, innovative, and synthesized scheme with three significant technical processes. First, data reorganization trims the original data with efficient redundancy elimination and reordering for IFC-SPF (IFC STEP Physical File) and XML-encoded CityGML (City Geography Markup Language). Next, bidirectional transformation methods for BIM and GIS modeling data, images, and analytical data into HDF are proposed. They retain the entities and relationships in modeling data and can further improve the compactness and accessibility by ultimately 60%–80% which saves 497,612 KB from 565,152 KB in the test of ZhongChun transformation substation. Finally, data aggregation enhances the bond of the integrated model and heterogeneous data resources from the transformed HDF files. The case studies show that the approach proposed in this paper could reach high efficiency for practicability of the BIM + GIS integration model. This light-weight integration method can further improve the front-end service responsiveness in digital twin applications.

By providing a consolidated access point to information of devices and systems, digital twins enable new, data-intensive use cases for the industrial internet of things (IIoT) like predictive plant and product design. A digital twin is a digital representation of an entity, which is sufficient to meet the requirements of a set of use cases. However, the lack of interoperability between the digital twins of different companies hinders use cases that require information exchange between different organizations. Achieving interoperability among digital twins requires transforming the included information to other formats. In this paper, we present requirements as well as a solution to enable interoperable digital twins by flexibly transforming their information models. The solution enables file- and API-based information exchange of comprehensive information models in a bidirectional way. We illustrate how we applied our solution to a real-world application example in an industrial context by transforming ABB Ability™ digital twins to the asset administration shell format. We show that our customizable transformation system paves the way for on-demand interoperability and thereby enables advanced use cases in the IIoT. This includes smart use cases that connect industries as well as artificial intelligence in industry.

Data interoperability between domain-specific applications is a key prerequisite for building information modeling (BIM) to solidify its position as a central medium for collaboration and information sharing in the construction industry. The Industry Foundation Classes (IFC) provides an open and neutral data format to standardize data exchanges in BIM, but is often exposed to data loss and misclassifications. Concretely, errors in mappings between BIM elements and IFC entities may occur due to manual omissions or the lack of awareness of the IFC schema itself, which is broadly defined and highly complex. This study explored the use of geometric deep learning models to classify infrastructure BIM elements, with the ultimate goal of automating the prechecking of BIM-to-IFC mappings. Two models with proven classification performance, Multi-View Convolutional Neural Network (MVCNN) and PointNet, were trained and tested to classify 10 types of commonly used BIM elements in road infrastructure, using a dataset of 1496 3D models. Results revealed MVCNN as the superior model with ACC and F1 score values of 0.98 and 0.98, compared with PointNet's corresponding values of 0.83 and 0.87, respectively. MVCNN, which employs multiple images to learn the features of a 3D artifact, was able to discern subtle differences in their shapes and geometry. PointNet seems to lose the granularity of the shapes, as it uses points partially selected from point clouds.

An important part of the industry 4.0 concept is the horizontal and vertical integration of manufacturing systems. Information exchange in traditional production environments happens through interfaces that are connections between strictly defined senders and receivers. This limits the possibility for changing and extending the manufacturing system. A possible approach to enable the information exchange between all system entities uniformly are information models. Such models are semantic descriptions of the available data. The creation of these models needs to follow the manufacturing process, but also requires certain standardization to improve efficiency. Another challenge is the actual technical integration of the information into a common address space. This paper connects an approach for information modeling with a concept for dynamic aggregation. The approach is described with the help of a continuous example that uses OPC UA as a middleware technology.

Effective management for the maintenance of water dispensers dispersed throughout an academic campus is essential for ensuring the quality of drinking water. Conventionally, water dispenser maintenance is conducted approximately bimonthly or when a passive fault notice is obtained. This maintenance frequency usually results in ineffective allocation of maintenance staff and poor maintenance quality. This study proposes a new model for campus facility maintenance management that enables maintenance staff to maintain water dispensers at the optimal time and select the shortest maintenance path. The proposed model was developed using the maintenance information of the Construction Operations Building Information Exchange obtained from building information models of multiple buildings, water dispenser operation data from a water dispenser monitoring module, and an optimization algorithm developed by integrating Dijkstra’s algorithm, simulated annealing, and a genetic algorithm to identify the shortest maintenance path. The proposed model was tested on a campus in Northern Taiwan. The application results revealed that maintenance strategies could be systematically established to determine the optimal time to dispatch maintenance staff based on the lowest unit cost criterion; this approach was also used to identify the shortest maintenance path through multiple buildings.

A context-aware approach to intelligent decision support based on user digital traces is proposed. The concept of human digital life with regard to intelligent decision support is discussed. The aims of addressing this concept in diverse domains are clarified and approaches to modelling human digital life are identified. In the proposed approach, digital traces serve as a source of information to reveal user preferences and decision-making behaviour. Perspectives on decision support based on user digital traces are developed. The research outcomes are the specification of requirements to intelligent decision support based on user digital traces, the principles, conceptual framework and information model of such support. The principles form the basis for the conceptual framework of intelligent decision support based on user digital traces. Components of the conceptual model are user profiles; a user digital life model that structures information containing in the digital traces; group patterns that describe preferences and decision-making behavior shared by a user group; and a decision maker ontology. The information model defines information flows between the framework’s components, identifies tasks that require solutions to implement the framework and offers techniques for this. The novelties of the research are applying the concept of human digital life to intelligent decision support and context-dependent ontological inference of the type of user as a decision-maker, which determines a group of users sharing their preferences and behaviours with the active user, to predict a recommended decision. The paper contributes to the areas of modelling human digital life and intelligent decision support.

Introduction. Modeling serves as a methodological basis for modern science and a tool for cognitive activity. It can be considered as a thinking activity mediated and optimized through information models. In this case, logical operations of cognition and simulation techniques are applied to the information. Materials and Methods. The scientific research results on how knowledge is formed, stored and processed in a person's memory, how they interact with information representations are studied and summarized. Information models used in various subject domains are analyzed. The provisions on rational ways of presenting information under modeling are formulated, and computer tools for constructing such representations are indicated. Results. Methods and techniques for visualizing information on the object under study are specified. Software tools and services providing visualizations and research modeling procedures are given. Discussion and Conclusions. The results obtained can be used to optimize modeling procedures. Images, structures, relationships and connections of the object under study are visualized in special programs with the help of the described methods and techniques. They, in turn, mediate the process of mental modeling and broaden the basis for its implementation.

Use of electronic health record data is expanding to support quality improvement and research; however, this requires standardization of the data and validation within and across organizations. Information models (IMs) are created to standardize data elements into a logical organization that includes data elements, definitions, data types, values, and relationships. To be generalizable, these models need to be validated across organizations. The purpose of this case report is to describe a refined methodology for validation of flowsheet IMs and apply the revised process to a genitourinary IM created in one organization. The refined IM process, adding evidence and input from experts, produced a clinically relevant and evidence-based model of genitourinary care. The refined IM process provides a foundation for optimizing electronic health records with comparable nurse sensitive data that can add to common data models for continuity of care and ongoing use for quality improvement and research.

The rapid urbanization over the last decades is leading to intensive land exploitation, and thus to the degradation of the city environment and the surrounding areas. This reality that applies at a global level, challenges new needs for sustainable growth and new ways to protect and ensure land property. It is of great importance, for the viable growth of every organized social structure, to protect land ownership and land-use in an appropriate way. Therefore arises the need for continuous and valid update of the complex Rights, Restrictions and Responsibilities (RRRs) within a developing 3D urban environment. For this environment, the interest focuses on ensuring land properties by improved methods of 3D information management, within modern land administration systems. The integration of Building Information Models (BIMs) and Geographic Information Systems (GIS) is expected to produce various advantages and play an important role in constructing 3D city models that successfully deal with every challenge in the urban landscape. GIS, in one hand, can manage and provide information about the existing environment, while on the other hand, BIMs focus on information regarding the design, construction and maintenance of a building /or complex structure inside that environment. This paper discusses the development of an integrated GIS and BIM 3D data platform enriched with 3D cadastral information This is illustrated with two use cases, a city block (No 464) in the area of Chalandri, Athens, and a four-floor building (at Kithaironos 21 street, in the same buildings’ block), used for applying BIM technology.

An Information–Modeling Complex has been developed for the information support of managerial decision making in the field of rational use, protection, and restoration of reservoir ecosystems. The system successively implements three mathematical hydroenvironmental models of the system Nizhnekamskoe Reservoir Drainage Basin―the Nizhnekamskoe Reservoir―the Kuibyshev Reservoir. The complex of models is an effective tool for studying the response of the ecological conditions of reservoirs to natural changes and anthropogenic impact. The use of the complex as a tool for environmental forecast or an expert system in scenario simulation of natural processes is the most promising way to solving the problems of water quality management and reservoir production.

With the continuous development of modern life, people have paid more and more attention to the needs of healthy and comfortable outdoor activities. The traditional static recuperation mode has been impacted, and the modern dynamic leisure agricultural tourism health care mode is more and more popular. Horticultural therapy improves people’s cognitive, psychological and physiological functions and provides people with positive values through plant-related sensory activities and horticultural operations. Therefore, horticultural therapy has become a product of the idea that designers have been exploring new forms of landscape architecture, trying to create a more comfortable environment and maximize the benefits of people in landscape architecture. In recent years, the theoretical and empirical studies of complex networks provide an important means to reveal the complexity of complex systems. As a new and active field of scientific research, complex networks have been introduced into the empirical research of real-world networks for a long time. At present, more and more people pay attention to computer science, social science, biological science, management science and many other fields. This paper constructs a BIM horticultural therapy health environment analysis system based on complex network model. The experimental results show that the proposed method can effectively analyze the application of BIM horticultural therapy in healthy environment.

Purpose As the use of building information modeling (BIM) for facilities management (FM) continues to grow, questions remain around the quality and completeness of digital assets to support FM practices. This paper aims to examine the current gap between digital and physical assets in the absence of formal information requirements and its impact on the handover process. Design/methodology/approach An action-research was carried out with a large public organization to understand the challenges of their current FM processes and the steps required in developing an asset information model (AIM) from a project information model (PIM). A mixed method approach was employed with interviews, document analysis and an exploratory pilot case study. Findings This paper investigates the process, the challenges and the level of effort of the information commissioning process to create a fit-for-use AIM. Four distinct steps were identified in the process as follows: analyzing the handover PIM and documents, extracting FM-specific information, populating the model with the information and attaching operations and maintenance (O&M) documents. The research highlights the significant amount of effort that is required when no specific asset information requirements are formulated at the project onset. Practical implications The paper presents an information commissioning process that helps to develop an AIM from a PIM. Understanding the impact of the lack of requirements on the information commissioning process can help asset owners understand the importance of defining and articulating their information requirements up front. Originality/value This paper provides empirical evidence of the impact of the absence of formal information requirements on the development of a fit-for-use AIM.

Loss of productivity through on-site delays and disruptions is a significant problem in the construction industry. This can be caused by workforce, materials, and equipment clashes. A major need for the industry is to improve construction logistic efficiencies for materials and equipment from manufacture to the point of use by the workforce. The authors investigate the effectiveness and efficiency of integrated construction supply chain logistics (ICSCL) using 4D Building Information Models (BIM), via three information streams: literature, a case study of the Elephant and Castle project (E&C), and a survey from UK construction professionals. The results illustrate, although BIM of various levels is currently in use throughout the UK, 4D BIM for ICSCL is not extensively utilised due to an absence of strategy, perceived costs of IT, and training requirements. That use could potentially add value with a trusted supply chain and disciplined planning using a multiple stream logistic model.

Cyber–physical systems (CPSs) in the manufacturing domain can be deployed to support monitoring and analysis of production systems of a factory in order to improve, support, or automate processes, such as maintenance or scheduling. When a network of CPS is subject to frequent changes, the semantic interoperability between the CPSs is of special interest in order to avoid manual, tedious, and error-prone information model alignments at runtime. Ontologies are a suitable technology to enable semantic interoperability, as they allow the building of information models that lank machine-readable meaning to information, thus enabling CPSs to mutually understand the shared information. The contribution of this article is twofold. First, we present an ontology building method that is tailored toward the needs of CPSs in the manufacturing domain. For this purpose, we introduce the requirements regarding this method and discuss related research concerning ontology building. The method itself is designed to begin with ontological requirements and to yield a formal ontology. As the reuse of ontologies and other information resources (IRs) is crucial to the success of ontology building projects, we put special emphasis on how to reuse IRs in the CPS domain. Second, we present a reusable set of ontology design patterns that have been developed with the aforementioned method in an industrial use case and illustrate their application in the considered industrial environment. The contribution of this article extends the method introduced, as a postconference paper, by a detailed industrial application. Note to Practitioners —With growing digitalization in industry, the exchange and use of manufacturing-related data are becoming increasingly important to improve, support, or automate processes. Thus, it is necessary to combine information from different data sources that have been designed by different vendors and may, therefore, be heterogeneous in structure and semantics. A system that plans a maintenance worker’s daily schedule, for instance, requires information about the status of machines, production plans, and inventory, which resides in other systems, such as programmable logic controllers (PLCs) or databases. When creating such information systems, accessing, searching, and understanding the different data sources is a time-intensive and error-prone procedure due to the heterogeneities of the data sources. Even worse, this procedure has to be repeated for every newly built system and for every newly introduced data source. To allow for eased access, searching, and understanding of these heterogeneous data sources, ontology can be used to integrate all heterogeneous data sources in one schema. This article contributes a method for building such ontologies in the manufacturing domain. Furthermore, a set of ontology design patterns is presented, which can be reused when building ontologies for a domain.

The research is focused on the development of an approach to modeling and forecasting market good prices based on information changes. The process is described by the first order differential equations, and the solution of a corresponding Cauchy problem made it possible to develop an information pricing model. The proposed method is shown to be useful both for predicting asset prices on the stock and currency exchanges and on commodity electronic markets. Data preparation stage before modeling is presented too.

Envisioned 5G applications and services, such as Tactile Internet, Industry 4.0 use-cases, remote control of drone swarms, pose serious challenges to the underlying networks and cloud platforms. On the one hand, evolved cloud infrastructures provide the IT basis for future applications. On the other hand, networking is in the middle of a momentous revolution and important changes are mainly driven by Network Function Virtualization (NFV) and Software Defined Networking (SDN). A diverse set of cloud and network resources, controlled by different technologies and owned by cooperating or competing providers, should be coordinated and orchestrated in a novel way in order to enable future applications and fulfill application level requirements. In this paper, we propose a novel cross domain orchestration system which provides wholesale XaaS (Anything as a Service) services over multiple administrative and technology domains. Our goal is threefold. First, we design a novel orchestration system exploiting a powerful information model and propose a versatile embedding algorithm with advanced capabilities as a key enabler. The main features of the architecture include $i$ ) efficient and multi-purpose service embedding algorithms which can be implemented based on graph models, $ii$ ) inherent multi-domain support, $iii$ ) programmable aggregation of different resources, $iv$ ) information hiding together with flexible delegation of certain requirements enabling multi-operator use-cases, and $v$ ) support for legacy technologies. Second, we present our proof-of-concept prototype implementing the proposed system. Third, we establish a dedicated test environment spanning across multiple European sites encompassing sandbox environments from both operators and the academia in order to evaluate the operation of the system. Dedicated experiments confirm the feasibility and good scalability of the whole framework.

The ways of implementing the basic principles of «lean production» at certain stages of shipbuilding production and throughout the entire life cycle of shipbuilding products are considered. The article describes the main losses that occur at the production stage, as well as ways to improve shipbuilding production and directions for solving some problems of minimizing losses in relation to enterprises in the shipbuilding industry. The authors present an example of using CALS technologies in the process of production management, designing marine engineering facilities, communication between individual design organizations and the shipbuilding enterprise when creating complex projects; as well as ways to implement this task as the most promising in the world practice. The main purpose of using CALS in shipbuilding at all stages of the life cycle of a shipbuilding product is to create a unified information model, standardize the main methods for obtaining, storing and interpreting information, protect, certify and license the information used at all stages of the life cycle of shipbuilding products using computer-aided design systems. The article describes the main goals and directions of implementing CALS technologies as one of the stages of improving processes within the framework of the lean production concept. The ways of minimizing production losses in the development of planning and technological documentation and design and technological production preparation, production of working design documentation are considered. The purpose of creating a 3D ship model using volumetric scanning technology as a means of supporting the life cycle of marine equipment products at the stages of maintenance, repair and modernization is shown. The authors list the main ways to implement the assigned tasks at the shipbuilding enterprise, considering them from the point of view of implementing «lean production»; and the essential condition for its effective functioning is the joint use of CALS technologies at the enterprises of the shipbuilding industry, contractors and design organizations. The task of training and retraining specialists for the shipbuilding industry with appropriate professional competencies is outlined.

PurposeThe adoption of building information modelling (BIM) in managing built heritage is an exciting prospect, but one that presents complexities additional to those of modern buildings. If challenges can be identified and overcome, the adoption of historic BIM (HBIM) could offer efficiencies in how heritage buildings are managed.Design/methodology/approachUsing Durham Cathedral as a case study, we present the workflows applied to create an asset information model to improve the way this unique UNESCO World Heritage Site is managed, and in doing so, set out the challenges and complexities in achieving an HBIM solution.FindingsThis study identifies the need for a better understanding of the distinct needs and context for managing historic assets, and the need for heritage information requirements (HIR) that reflect this.Originality/valueThis study presents first-hand findings based on a unique application of BIM at Durham Cathedral, a UNESCO World Heritage Site. The study provides a better understanding of the challenges and drivers of HBIM adoption across the heritage sector and underlines the need for information requirements that are unique to historical buildings/assets to deliver a coherent and relevant HBIM approach.

Context. The article focuses on the question of automated decision-making analysis made by the operator in ergatic systems of critical infrastructures on the example of marine transport control in difficult navigation conditions. It is evident enough that the main criterion for an adequate perception of input information done by an operator is highly likely to predict the choice of behavioral decision-making strategies in discrete time conditions. However, the difficulty of modeling the operator’s actions is found to be lying in non-linear pattern of taking definite decisions in emergency situations and deviations from the Codes and Rules.Objective. The research purpose strategy of conducted investigation can be defined as the development of the mathematical platform for a decision support system (DSS) module with an aim to identify the class-forming set of atomic elements. In particular this issue determines the fact of distortion of the perception of information about navigation risks predicting the operator’s behavior pattern while having vessel running process. This is possible to have it depicted through formal analysis.Method. To capture the analysis of danger perception by the operator the paper introduces a mathematical model of data collection which identifies the fact of perception distortion in the form of attribute space of metadata obtained by the method of converting information from navigation devices. Besides, the factor of disorientation of the operator can be considered to be a shift on a displaced bridge which significantly affects on the analysis of information for adequate decision making. In addition, taking into account the failure of navigation equipment such as: RADAR, ARPA, AIS, ECDIS, especially while doing exit from the automatic control mode, a dangerous precedent can possibly be created for the operator not ready to perceive the complexity of the situation. To make it work a formal analysis was carried out using the extending risks possibility level tasks during the transition under these conditions. In addition to this item, a probabilistic model of perceiving the situation under the conditions of the error set is reported to have been constructed. So, as the result, the modeling process turned out to show the definite evidence of getting no way possibility to have the degree of criticality of the navigation situation determined without a clear identification of factors affecting the distortion of perception of the operator. Nevertheless, generalized statistical data are sure to be not enough and there is a special need of taking into account an individual information model of each operator for the effective work of DSS as this process faces real challenges. It must be significantly noticed that in order to analyze the perception of information by the operator a special test for defining preferences when choosing a strategy of control actions in the form of maneuvering under difficult navigation conditions purpose was created. Regarding the test results, as well as data on the passage of locations, certain attention is advised to be drawn to the classification analysis of 15 parameters using artificial neural networks having been carried out by our team and, as a consequence, the boundaries of deviations in the perception of navigational danger were found out and clarified. Additional superior item to be spoken about is certainly the introduction of rules and algorithms having been welcomed into the DSS core including the following: interaction field, RADAR and NIS synchronization tools; actual navigational hazard in a given cartographic area; ships trajectories and, as a result, simulations of probable deviations in the information perception of the operator.Results. In order to meet beneficial agreement between the effectiveness of the developed DSS with the proposed formalanalytical approaches an experiment was assumed to be appropriate to be conducted using the Navi Trainer 5000 navigation simulator (NTPRO 5000). Based on the foregoing, due to comprehensive results in experiment metadata for the 2.5 years of operation of navigation simulators and DSS software tools the identification of the deviation probabilities in the information perception of dangers was achieved and export the predicted data to new locations for the operator and cartographic areas was performed. Undoubtedly, the experimental investigation confirmed the hypothesis of the study and reflected completely the feasibility of using this DSS to make predictions of possible risks when control the vessel by analyzing the information model of the operator.Conclusions. Formal-analytical approaches presented in the study combined with the developed DSS software tools and the information itself made it possible to classify the decision-making strategies of the operator when control the vessel and to predict the probability of catastrophic consequences. The feasibility of the proposed models and methods was successfully revealed by carried out experiments.

There are heterogeneous problems between the CAD model and the assembly process document. In the planning stage of assembly process, these heterogeneous problems can decrease the efficiency of information interaction. Based on knowledge graph, this paper proposes an assembly information model (KGAM) to integrate geometric information from CAD model, non-geometric information and semantic information from assembly process document. KGAM describes the integrated assembly process information as a knowledge graph in the form of “entity-relationship-entity” and “entity-attribute-value”, which can improve the efficiency of information interaction. Taking the trial assembly stage of a certain type of aero-engine compressor rotor component as an example, KGAM is used to get its assembly process knowledge graph. The trial data show the query and update rate of assembly attribute information is improved by more than once. And the query and update rate of assembly semantic information is improved by more than twice. In conclusion, KGAM can solve the heterogeneous problems between the CAD model and the assembly process document and improve the information interaction efficiency.

This paper presents a systematic methodology to enable environmental sustainability and productivity performance assessment for integrated process and operation plans at the machine cell level of a manufacturing system. This approach determines optimal process and operation plans from a range of possible alternatives that satisfy the objectives and constraints. The methodology provides a systematic procedure to highlight parameters that have significant impact on both sustainability and productivity performance metrics. We developed models and applied them to analyze manufacturing life cycle scenarios for collecting and categorizing key concepts towards building a material information model for sustainability. Integration of process and operation plans allows globalized assessment of sustainability and productivity, while development of a multi-criteria decision-making method leads to optimization of process planning activities based on the impact of conflicting sustainability and productivity metrics. A case study is detailed to demonstrate the sustainability-focused methodology, wherein integrated simulation and optimization techniques are used to support analysis of candidate scenarios and selection of preferred alternatives from a finite set of alternate process and operation plans. A discrete event simulation tool is used to model evolution of sustainability metrics (e.g., energy consumption) and productivity metrics (e.g., production time, cost) of a shop floor. The outcomes of this work include determination of optimized feature sequence plans which optimize various key performance indicators depending on stakeholder interest based on time, sustainability and production cost.

Considering that each computer-aided design (CAD) system has independent geometric dimensioning and tolerancing modeling method, precision information model generated by different CAD systems is difficult to be shared and reused by the downstream precision analysis system. To tackle the problem that tolerance semantic information cannot be transmitted through data exchange standards, this paper aims to propose a novel semantic tolerance screening approach to represent precision information for assembly precision analysis (APA) in the design stage. Based on semantic correlation between tolerance propagation and accumulation, precision information of multi-parts is preliminarily screened out. Then by utilizing semantic web rule language rules to determine the type and position of tolerance zones, multiple tolerances existing on a precision feature surface are refinedly screened out. Finally, a formal tolerance screening ontology, named ToS-Ontology, is generated for performing APA of complex products. The effectiveness of the proposed approach is demonstrated by a practical example, which is to calculate center distance between two holes to ensure bolts can pass smoothly in the limit case.

The information explosion the world has witnessed in the last two decades has forced businesses to adopt a data-driven culture for them to be competitive. These data-driven businesses have access to countless sources of information, and face the challenge of making sense of overwhelming amounts of data in a efficient and reliable manner, which implies the execution of read-intensive operations. In the context of this challenge, a framework for the dynamic read-optimization of large dimensional datasets has been designed, and on top of it a workload-driven mechanism for automatic materialized view selection and creation has been developed. This paper presents an extensive description of this mechanism, along with a proof-of-concept implementation of it and its corresponding performance evaluation. Results show that the proposed mechanism is able to derive a limited but comprehensive set of views leading to a drop in query latency ranging from 80% to 99.99% at the expense of 13% of the disk space used by the base dataset. This way, the devised mechanism enables speeding up query execution by building materialized views that match the actual demand of query workloads.

The construction of smart cities in our country has received extensive attention. Under the situation that smart cities are vigorously promoted nowadays, compared with traditional construction and operation and maintenance methods, building information model (BIM) technology is more suitable to serve as an important foundation for intelligent management in the whole process of construction projects. BIM is an abbreviation for building information model. BIM relies on a variety of digital technologies, which can be used to realize information modeling of urban buildings and infrastructure. The efficiency of information exchange in the process of intelligence construction ensures the integrity and accuracy of information data exchange and maintains the consistency of information data exchange. Data and information have objectivity, applicability, transferability, and sharing. Geographic data is a digital representation of various geographical features and phenomena and their relationships. BIM is a digital representation of physical and functional characteristics of a facility. It can It is used as a shared knowledge resource for facility information. It becomes a reliable basis for facility life-cycle decision-making. Input BP neural network, and then learn and train by BP neural network.