Organisational challenges of the semantic web in digital libraries: A Norwegian case study

This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2009 Emerald Group Publishing LimitedPurpose – The purpose of this paper is to examine from a socio-technical point of view the impact of semantic web technology on the strategic, organisational and technological levels. The semantic web initiative holds great promise for the future for digital libraries. There is, however, a considerable gap in semantic web research between the contributions in the technological field and research in the organisational field. Design/methodology/approach – A comprehensive case study of the National Library of Norway (NL) is conducted, building on two major sources of information: the documentation of the digitising project of the NL; and interviews with nine different stakeholders at three levels of NL's organisation during June to August 2007. Top managers are interviewed on strategy, middle managers and librarians are interviewed regarding organisational issues and ICT professionals are interviewed on technology issues. Findings – The findings indicate that the highest impact will be at the organisational level. This is mainly because inter-organisational and cross-organisational structures have to be established to address the problems of ontology engineering, and a development framework for ontology engineering in digital libraries must be examined. Originality/value – ICT professionals and library practitioners should be more mindful of organisational issues when planning and executing semantic web projects in digital libraries. In particular, practitioners should be aware that the ontology engineering process and the semantic meta-data production will affect the entire organisation. For public digital libraries this probably will also call for a more open policy towards user groups to properly manage the process of ontology engineering

An analysis of the requirements traceability problem

In this paper1, we investigate and discuss the underlying nature of the requirements traceability problem. Our work is based on empirical studies, involving over 100 practitioners, and an evaluation of current support. We introduce the distinction between pre-requirements specification (pre-RS) traceability and post-requirements specification (post-RS) traceability, to demonstrate why an all-encompassing solution to the problem is unlikely, and to provide a framework through which to understand its multifaceted nature. We report how the majority of the problems attributed to poor requirements traceability are due to inadequate pre-RS traceability and show the fundamental need for improvements here. In the remainder of the paper, we present an analysis of the main barriers confronting such improvements in practice, identify relevant areas in which advances have been (or can be) made, and make recommendations for research

COBOL to Java and Newspapers Still Get Delivered

This paper is an experience report on migrating an American newspaper company's business-critical IBM mainframe application to Linux servers by automatically translating the application's source code from COBOL to Java and converting the mainframe data store from VSAM KSDS files to an Oracle relational database. The mainframe application had supported daily home delivery of the newspaper since 1979. It was in need of modernization in order to increase interoperability and enable future convergence with newer enterprise systems as well as to reduce operating costs. Testing the modernized application proved to be the most vexing area of work. This paper explains the process that was employed to test functional equivalence between the legacy and modernized applications, the main testing challenges, and lessons learned after having operated and maintained the modernized application in production over the last eight months. The goal of delivering a functionally equivalent system was achieved, but problems remained to be solved related to new feature development, business domain knowledge transfer, and recruiting new software engineers to work on the modernized application.Comment: 4 pages, Accepted to be Published in: Proceedings of the 2018 IEEE International Conference on Software Maintenance and Evolution (ICSME), September 23-29, 2018, Madrid, Spai

Construction safety and digital design: a review

As digital technologies become widely used in designing buildings and infrastructure, questions arise about their impacts on construction safety. This review explores relationships between construction safety and digital design practices with the aim of fostering and directing further research. It surveys state-of-the-art research on databases, virtual reality, geographic information systems, 4D CAD, building information modeling and sensing technologies, finding various digital tools for addressing safety issues in the construction phase, but few tools to support design for construction safety. It also considers a literature on safety critical, digital and design practices that raises a general concern about ‘mindlessness’ in the use of technologies, and has implications for the emerging research agenda around construction safety and digital design. Bringing these strands of literature together suggests new kinds of interventions, such as the development of tools and processes for using digital models to promote mindfulness through multi-party collaboration on safet

Intelligent systems in manufacturing: current developments and future prospects

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial Intelligence (AI) techniques to be considered and then shows how these AI techniques are used for the components of IMS

Automation from lean perspective-potentials and challenges

The competitive climate of production and high labour cost, motivate western companies to use technologies like automation as a mean to increase manufacturing competitiveness. On the other hand companies are aware about cost reductive policies like lean production which has shown noticeable achievement, consequently some manufacturers tend to follow such system. In this situation, in order to have lean enterprise, it is vital to find a clear picture of challenges and potentials of implementing automation within a lean environment. So, finding the right level and type of automation becomes vital for companies, and achieving this is not possible without a lean development of automation. The paper presents an overview of automation development from a lean perspective. The focus is on manufacturing and a case study in the automotive industry is presented. Challenges and potentials of automation are pinpointed and some suggestions regarding automation development is given

Continuous maintenance and the future – Foundations and technological challenges

High value and long life products require continuous maintenance throughout their life cycle to achieve required performance with optimum through-life cost. This paper presents foundations and technologies required to offer the maintenance service. Component and system level degradation science, assessment and modelling along with life cycle ‘big data’ analytics are the two most important knowledge and skill base required for the continuous maintenance. Advanced computing and visualisation technologies will improve efficiency of the maintenance and reduce through-life cost of the product. Future of continuous maintenance within the Industry 4.0 context also identifies the role of IoT, standards and cyber security

Organizational challenges of the semantic web in digital libraries

The Semantic Web initiative holds large promises for the future. There is, however, a considerable gap in Semantic Web research between the contributions in the technological field and the research done in the organizational field. This paper examines, from a socio-technical point of view the impact of Semantic Web technology on the strategic, organizational and technological levels. Building on a comprehensive case study at the National Library in Norway our findings indicate that the highest impact will be at the organizational level. The reason is mainly because inter-organizational and cross-organizational structures have to be established to address the problems of ontology engineering, and a development framework for ontology engineering in digital libraries must be examined

Analysis framework for the interaction between lean construction and building information modelling

Building with Building Information Modelling (BIM) changes design and production processes. But can BIM be used to support process changes designed according to lean production and lean construction principles? To begin to answer this question we provide a conceptual analysis of the interaction of lean construction and BIM for improving construction. This was investigated by compiling a detailed listing of lean construction principles and BIM functionalities which are relevant from this perspective. These were drawn from a detailed literature survey. A research framework for analysis of the interaction between lean and BIM was then compiled. The goal of the framework is to both guide and stimulate research; as such, the approach adopted up to this point is constructive. Ongoing research has identified 55 such interactions, the majority of which show positive synergy between the two

Big Data and the Internet of Things

Advances in sensing and computing capabilities are making it possible to embed increasing computing power in small devices. This has enabled the sensing devices not just to passively capture data at very high resolution but also to take sophisticated actions in response. Combined with advances in communication, this is resulting in an ecosystem of highly interconnected devices referred to as the Internet of Things - IoT. In conjunction, the advances in machine learning have allowed building models on this ever increasing amounts of data. Consequently, devices all the way from heavy assets such as aircraft engines to wearables such as health monitors can all now not only generate massive amounts of data but can draw back on aggregate analytics to "improve" their performance over time. Big data analytics has been identified as a key enabler for the IoT. In this chapter, we discuss various avenues of the IoT where big data analytics either is already making a significant impact or is on the cusp of doing so. We also discuss social implications and areas of concern.Comment: 33 pages. draft of upcoming book chapter in Japkowicz and Stefanowski (eds.) Big Data Analysis: New algorithms for a new society, Springer Series on Studies in Big Data, to appea