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This paper aims to describe an interdisciplinary and innovative research conducted in Switzerland, at the Geneva School of Business Administration HES-SO and supported by the State Archives of Neuchâtel (Office des archives de l'État de Neuchâtel, OAEN). The problem to be addressed is one of the most classical ones: how to extract and discriminate relevant data in a huge amount of diversified and complex data record formats and contents. The goal of this study is to provide a framework and a proof of concept for a software that helps taking defensible decisions on the retention and disposal of records and data proposed to the OAEN. For this purpose, the authors designed two axes: the archival axis, to propose archival metrics for the appraisal of structured and unstructured data, and the data mining axis to propose algorithmic methods as complementary or/and additional metrics for the appraisal process.

Based on two axes, this exploratory study designs and tests the feasibility of archival metrics that are paired to data mining metrics, to advance, as much as possible, the digital appraisal process in a systematic or even automatic way. Under Axis 1, the authors have initiated three steps: first, the design of a conceptual framework to records data appraisal with a detailed three-dimensional approach (trustworthiness, exploitability, representativeness). In addition, the authors defined the main principles and postulates to guide the operationalization of the conceptual dimensions. Second, the operationalization proposed metrics expressed in terms of variables supported by a quantitative method for their measurement and scoring. Third, the authors shared this conceptual framework proposing the dimensions and operationalized variables (metrics) with experienced professionals to validate them. The expert’s feedback finally gave the authors an idea on: the relevance and the feasibility of these metrics. Those two aspects may demonstrate the acceptability of such method in a real-life archival practice. In parallel, Axis 2 proposes functionalities to cover not only macro analysis for data but also the algorithmic methods to enable the computation of digital archival and data mining metrics. Based on that, three use cases were proposed to imagine plausible and illustrative scenarios for the application of such a solution.

The main results demonstrate the feasibility of measuring the value of data and records with a reproducible method. More specifically, for Axis 1, the authors applied the metrics in a flexible and modular way. The authors defined also the main principles needed to enable computational scoring method. The results obtained through the expert’s consultation on the relevance of 42 metrics indicate an acceptance rate above 80%. In addition, the results show that 60% of all metrics can be automated. Regarding Axis 2, 33 functionalities were developed and proposed under six main types: macro analysis, microanalysis, statistics, retrieval, administration and, finally, the decision modeling and machine learning. The relevance of metrics and functionalities is based on the theoretical validity and computational character of their method. These results are largely satisfactory and promising.

This study offers a valuable aid to improve the validity and performance of archival appraisal processes and decision-making. Transferability and applicability of these archival and data mining metrics could be considered for other types of data. An adaptation of this method and its metrics could be tested on research data, medical data or banking data.

This paper aims to investigate the requirements for automating aspects of the appraisal process for digital objects. It explores these requirements in the context of automating re‐appraisal and questions many of the assumptions commonly made about appraisal and about automating the processes needed for life‐cycle management of digital objects.

The literature of digital preservation and curation and the experience of one of the authors in planning to implement a digital archive at the Wellcome Library are the basis of an exploration of issues.

The development of automated appraisal systems and associated tools is a worthwhile endeavour, although the complexity and cost associated with designing, developing and implementing them may be prohibitive in some situations. An automated appraisal system may, however, have only limited benefits in some contexts. The re‐appraisal of technical attributes of digital materials, which is an essential part of their management, is a prime contender for some level of automation. The approach proposed has limitations which arise from such factors as metadata requirements and trustworthiness.

The paper articulates assumptions made about automation and applies these in order to gain a better understanding of the requirements of automating aspects of appraisal in a digital archive.

Robots are still not used widely enough in the electrical and electronics industry, and the various reasons for this are explained.

This article’s purpose is to develop The Model for Smart, Self-learning and Adaptive Resilience Building (SARB).

Products and patents of methods and systems analysis was carried out in the fields of BIM application, Smart, Self-learning and Adaptive Resilience Building. Based on other researchers’ findings, The SARB Model was proposed.

Analysis of the literature showed that traditional decisions on the informational modelling do not satisfy all the needs of smart building technologies owing to their static nature. The SARB Model was developed to take care of its efficiency from the brief stage to the end of its service life.

The SARB Model was developed to take care of its efficiency from the brief stage to the end of its service life. The SARB Model does have some limitations: (1) the processes followed require the collection of much unstructured and semi-structured data from many sources, along with their analyses to support stakeholders in decision-making; (2) stakeholders need to be aware of the broader context of decision-making and (3) the proposal is process-oriented, which can be a disadvantage during the model’s implementation.

Two directions can be identified for the practical implications of the SARB Model. The initial expectation is the widespread installation of SARB Model within real estate and construction organisations. Furthermore, development of the SARB Model will be used to implement the ERASMUS+ project, “Advancing Skill Creation to ENhance Transformation—ASCENT” Project No. 561712-EPP-1-2015-UK-EPPKA2-CBHE-JP.

The practical implications of this paper are valuable.

The use of building information modelling (BIM) methodology has been increasing in the architecture, engineering, construction and operation sector, driven to a new paradigm of work with the use of three-dimensional (3D) parametric models. However, building information modelling (BIM) has been mostly used for as-built models of a building, not yet been widely used by designers during project and construction phases for occupational risks prevention and safety planning. This paper aims to show the capacity of developing tools that allow adding functionalities to Revit software to improve safety procedures and reduce the time spent on modelling them during the design phase.

To reach this objective, a structural 3D model of a building is used to validate the developed tools. A plugin prototype based on legal regulations was developed, allowing qualitative safety assessment through the application of job hazard analysis (JHA), SafeObject and checklists. These tools allow the automated detection of falls from height situations and the automated placement of the correspondent safety systems.

Revit application programming interface allowed the conception and addition of several functionalities that can be used in BIM methodology, and more specifically in the prevention of occupational risks in construction, contributing this paper to the application of a new approach to the prevention through design.

This paper is innovative and important because the developed plugins allowed: automated detection of potential falls from heights in the design stage; automated introduction of safety objects from a BIM Safety Objects Library; and the intercommunication between a BIM model and a safety database, bringing JHA integration directly on the project. The prototype of this work was validated for fall from height hazards but can be extended to other potentials hazards since the initial design stage.

The construction industry has been evolving in recent years through the adoption of smart tools such as building information modeling to reduce the complexity in the construction process and optimize the project's goals. This paper aims to identify and assess the key drivers for the implementation of smart sustainable practices in the construction industry.

Inferential and descriptive statistical techniques were employed in analyzing the data collected via an international empirical questionnaire survey deployed in soliciting the perceptions of 220 construction professionals across 21 countries. Factor analysis was used to categorize the identified key drivers into their underlying clusters for further discussion. Also, the data were analyzed based on the various groups and regions of the study's respondents.

The key drivers (KDs) are related to the technical competence of staff as well as knowledge and awareness level within the industry, issues related to organizational and project's strategy and policies, availability of financial resources and development of relevant standards and policies to aid its execution among others. A comparative analysis of the perceptions of the different respondents' groups was undertaken and discussed.

The analysis of the key drivers for the implementation of smart and sustainable practices in the construction industry is expected to aid the decision-making of the relevant stakeholders as well as serve as a consultation instrument for government agencies in their design of localized policies and guidelines to aid smart and sustainable urbanization. The findings revealed the gaps in the implementation of smart and sustainable practices in various climes and organization setups and provided useful and practical strategies for addressing the current hindrances during implementation.

The study has generated valuable insights into the significant drivers that can enhance the implementation of smart and sustainable practices across regions. It is evident that synergy among the relevant stakeholders in the built environment will help accelerate the implementation of smart sustainable practices in the construction industry. The study findings have provided profound contributions to theory and research as well as to industry practice.

Provides an overview of the implications of automation for staff training in libraries. Discusses the reported effects of automation on library personnel, and explains the significance of these for the planning of training. Considers the roles of the training organizer and the trainer. Outlines elements of the training programme, including timing, location, resources, methods, costs, evaluation, staff appraisal, and the need for continuity. Finally, raises considerations for suitable management style.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Index by subjects, compiled by K.G.B. Bakewell covering the following journals: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.

Compiled by K.G.B. Bakewell covering the following journals published by MCB University Press: Facilities Volumes 8‐18; Journal of Property Investment & Finance Volumes 8‐18; Property Management Volumes 8‐18; Structural Survey Volumes 8‐18.