Integration of Data Flows of the Construction Project Life Cycle to Create a Digital Enterprise Based on Building Information Modeling

This study is devoted to the problem of digital transformation in the construction industry. To solve the proposed emerging approach for integrating information flows based on Building information modeling (BIM). This research describes the advanced methodology for creating a unified information model in construction, which combines architectural, design, engineering, cost and depreciation models of a construction object, raises a number of problems of reorganizing business processes at enterprises. The novelty of the research lies in the model of adapted common data environment based on life cycle of a construction project by stages of implementation and emergence of information. The proposed architecture is a platform for intelligent parametric modeling as intelligent CAD, which allows linking all elements of the model "Digital Enterprise".The result of the study is a conceptual mechanism for improving the efficiency of enterprise management processes based on the architectural approach in terms of digitalization of construction. Emerging technology in the study is the architecture of the intelligent decision support system in construction based on 5D BIMtechnology and Digital Enterprise. The main advantage of the proposed approach is the possibility of multiple reuse of information by all participants in the development and implementation of an investment and construction project without changes and distortions of data about the construction object. Keywords — Building Information Modeling, BIM, Digital Enterprise, Common Data Environment, life cycle of construction project, digitalization of construction

Understanding the Determinants of Big Data Analytics Adoption

This article aims to empirically investigate the factors that affects the adoption of big data analytics by firms (adopters and non-adopters). The current study is based on three feature that influence BDA adoption: technological context (relative advantage, complexity, compatibility), organizational context (top management support, technology readiness, organizational data environment), and environmental context (competitive pressure, and trading partner pressure). A structured questionnaire-based survey method was used to collect data from 231 firm managers. Relevant hypotheses were derived and tested by partial least squares. The results indicated that technology, organization and environment contexts impact firms' adoption of big data analytics. The findings also revealed that relative advantage, complexity, compatibility, top management support, technology readiness, organizational data environment and competitive pressure have a significant influence on the adopters of big data analytics, whereas relative advantage, complexity and competitive pressure have a significant influence on the non-adopters of big data analytics.

PROTECTION OF PRIVACY AND PERSONAL DATA IN THE BIG DATA ENVIRONMENT OF SMART CITIES

The project of smart cities has emerged as a response to the challenges of twenty-first- century urbanization. Solutions to the fundamental conundrum of cities revolving around efficiency, convenience and security keep being sought by leveraging technology. Notwithstanding all the conveniences furnished by a smart city to all the citizens, privacy of a citizen is intertwined with the benefits of a smart city. The development processes which overlook privacy and security issues have left many of the smart city applications vulnerable to non-conventional security threats and susceptible to numerous privacy and personal data spillage risks. Among the challenges the smart city initiatives encounter, the emergence of the smartphone-big data-the cloud coalescence is perhaps the greatest, from the viewpoint of privacy and personal data protection. As our cities are getting digitalized, information comprising citizens' behavior, choices, and mobility, as well as their personal assets are shared over smartphone-big data-the cloud coalescences, thereby expanding cyber-threat surface and creating different security concerns. This coalescence refers to the practices of creating and analyzing vast sets of data, which comprise personal information. In this paper, the protection of privacy and personal data issues in the big data environment of smart cities are viewed through bifocal lenses, focusing on social and technical aspects. The protection of personal data and privacy in smart city enterprises is treated as a socio-technological operation where various actors and factors undertake different tasks. The article concludes by calling for novel developments, conceptual and practical changes both in technological and social realms.

Medieval manuscripts and their migrations: Using SPARQL to investigate the research potential of an aggregated Knowledge Graph

Although the RDF query language SPARQL has a reputation for being opaque and difficult for traditional humanists to learn, it holds great potential for opening up vast amounts of Linked Open Data to researchers willing to take on its challenges. This is especially true in the field of premodern manuscripts studies as more and more datasets relating to the study of manuscript culture are made available online. This paper explores the results of a two-year long process of collaborative learning and knowledge transfer between the computer scientists and humanities researchers from the Mapping Manuscript Migrations (MMM) project to learn and apply SPARQL to the MMM dataset. The process developed into a wider investigation of the use of SPARQL to analyse the data, refine research questions, and assess the research potential of the MMM aggregated dataset and its Knowledge Graph. Through an examination of a series of six SPARQL query case studies, this paper will demonstrate how the process of learning and applying SPARQL to query the MMM dataset returned three important and unexpected results: 1) a better understanding of a complex and imperfect dataset in a Linked Open Data environment, 2) a better understanding of how manuscript description and associated data involving the people and institutions involved in the production, reception, and trade of premodern manuscripts needs to be presented to better facilitate computational research, and 3) an awareness of need to further develop data literacy skills among researchers in order to take full advantage of the wealth of unexplored data now available to them in the Semantic Web.

Assessing the Duration of the Lead Appointed Party Coordination Tasks and Evaluating the Appropriate Team Composition on BIM Projects

This paper addresses critical success factors for the delivery of BIM projects. The lack of experience with BIM projects on both the demand and supply side often leads to insufficient project teams, unsatisfied clients, schedule, and cost overruns. In order to better structure and control the information delivery in BIM projects requirements, planning and delivery must be standardized. The latter was achieved by EIR (Exchange Information Requirements), new BIM roles, BEP (BIM Execution Plan), and specified digital handover, which must be supported by a common data environment (CDE). This paper provides an analysis of the characteristics of BIM project delivery and duration in Architectural and Engineering companies in Slovakia. The analysis is based on the web survey of BIM managers and coordinators, which reveals that a significant amount of BIM project efforts must be executed by BIM specialists. The results also graphically depict the scope of critical BIM activities across project phases. The presented study is relevant for various project stakeholders and allows for a deeper understanding of the resources needed for the successful delivery of BIM projects in terms of adequate project team capacity, capability, organization, and planning.