Past, present and future of information and knowledge sharing in the construction industry: Towards semantic service-based e-construction

The paper reviews product data technology initiatives in the construction sector and provides a synthesis of related ICT industry needs. A comparison between (a) the data centric characteristics of Product Data Technology (PDT) and (b) ontology with a focus on semantics, is given, highlighting the pros and cons of each approach. The paper advocates the migration from data-centric application integration to ontology-based business process support, and proposes inter-enterprise collaboration architectures and frameworks based on semantic services, underpinned by ontology-based knowledge structures. The paper discusses the main reasons behind the low industry take up of product data technology, and proposes a preliminary roadmap for the wide industry diffusion of the proposed approach. In this respect, the paper stresses the value of adopting alliance-based modes of operation

Model Based Development of Quality-Aware Software Services

Modelling languages and development frameworks give support for functional and structural description of software architectures. But quality-aware applications require languages which allow expressing QoS as a first-class concept during architecture design and service composition, and to extend existing tools and infrastructures adding support for modelling, evaluating, managing and monitoring QoS aspects. In addition to its functional behaviour and internal structure, the developer of each service must consider the fulfilment of its quality requirements. If the service is flexible, the output quality depends both on input quality and available resources (e.g., amounts of CPU execution time and memory). From the software engineering point of view, modelling of quality-aware requirements and architectures require modelling support for the description of quality concepts, support for the analysis of quality properties (e.g. model checking and consistencies of quality constraints, assembly of quality), tool support for the transition from quality requirements to quality-aware architectures, and from quality-aware architecture to service run-time infrastructures. Quality management in run-time service infrastructures must give support for handling quality concepts dynamically. QoS-aware modeling frameworks and QoS-aware runtime management infrastructures require a common evolution to get their integration

Systematic mapping of power system models: Expert survey

The power system is one of the main subsystems of larger energy systems. It is a complex system in itself, consisting of an ever-changing infrastructure used by a large number of actors of very different sizes. The boundaries of the power system are characterised by ever-evolving interfaces with equally complex subsystems such as gas transport and distribution, heating and cooling, and, increasingly, transport. The situation is further complicated by the fact that electricity is only a carrier, able to fulfil demand for such things as lighting, heat or mobility. One specific and fundamental feature of the electricity system is that demand and generation must match at any time, while satisfying technical and economic constraints. In most of the world’s power systems, only relatively small quantities of electricity can be stored, and only for limited periods of time. A detailed analysis of supply and demand is thus needed for short time intervals. Mathematical models facilitate power system planning, operation, transmission and distribution, demonstrating problems that need to be solved over different timescales and horizons. The use of modelling to understand these processes is not only vital for the system’s direct actors, i.e. the companies involved in the generation, trade, transmission, distribution and use of electricity, but also for policy-makers and regulators. Power system models can provide evidence to support policy-making at European Union, Member State and Regional level. As a consequence of the growth in computing power, mathematical models for power systems have become more accessible. The number of models available worldwide, and the degree of detail they provide, is growing fast. A proper mapping of power system models is therefore essential in order to: - provide an overview of power system models and their applications available in, or used by, European organisations; - analyse their modelling features; - identify modelling gaps. Few reviews have been conducted to date of the power system modelling landscape. The mission of the Knowledge for the Energy Union Unit of the Joint Research Centre (JRC) is to support policies related to the Energy Union by anticipating, mapping, collating, analysing, quality checking and communicating all relevant data/knowledge, including knowledge gaps, in a systematic and digestible way. This report therefore constitutes: - From the energy modelling perspective, a useful mapping exercise that could help promote knowledge-sharing and thus increase efficiency and transparency in the modelling community. It could trigger new, unexplored avenues of research. It also represents an ideal starting point for systematic review activities in the context of the power system. - From the knowledge management perspective, a useful blueprint to be adopted for similar mapping exercises in other thematic areas. Finally, this report is aligned with the objectives of the European Commission's Competence Centre on Modelling, (1) launched on 26 October 2017 and hosted by the JRC, which aims to promote a responsible, coherent and transparent use of modelling to support the evidence base for European Union policies. In order to meet the objectives of this report, an online survey was used to collect detailed and relevant information about power system models. The participants’ answers were processed to categorise and describe the modelling tools identified. The survey, conducted by the Knowledge for the Energy Union Unit of the JRC, comprised a set of questions for each model to ascertain its basic information, its users, software characteristics, modelling properties, mathematical description, policy-making applications, selected references, and more. The survey campaign was organised in two rounds between April and July 2017. 228 surveys were sent to power system experts and organisations, and 82 questionnaires were completed. The answers were processed to map the knowledge objectively. (2) The main results of the survey can be summarised as follows: - Software-related features: about two thirds of the models require third-party software such as commercial optimisation solvers or off-the-shelf software. Only 14% of the models are open source, while 11% are free to download. - Modelling-related features: models are mostly defined as optimisation problems (78%) rather than simulation (33%) or equilibrium problems (13%). 71% of the models solve a deterministic problem while 41% solve probabilistic or stochastic problems. - Modelled power system problems: the economic dispatch problem is the most commonly modelled problem with a share of approximately 70%, followed by generation expansion planning, unit commitment, and transmission expansion planning, with around 40‒43% each. Most of the models (57%) have non-public input data while 31% of models use open input data. - Modelled technologies: hydro, wind, thermal, storage and nuclear technologies are widely taken into account, featuring in around 83‒94% of models. However, HVDC, wave tidal, PSTs, and FACTS (3) are not often found unless the analysis is specifically performed for those technologies. - Applicability in the context of European energy policy: more than half of the mapped models (56%) were used to answer a specific policy question. Of the five Energy Union strategic dimensions, integration of the European Union internal energy market was addressed the most often (27%), followed by climate action (23%), research, innovation and competitiveness (21%), and energy efficiency (15%). This report includes JRC recommendations based on the results of the survey, on future research avenues for power system modelling and its applicability within the Energy Union strategic dimensions. More attention should be paid, for example, to model uncertainty features, and collaboration among researchers and practitioners should be promoted to intensify research into specific power system problems such as AC (4) optimal power flow. The report includes factsheets for each model analysed, summarising relevant characteristics based on the participants’ answers. While this report represents a scientific result per se, one of the expected (and welcomed) outcomes of this mapping exercise is to raise awareness of power system modelling activities among European policy makers.JRC.C.7-Knowledge for the Energy Unio

Identifying reverse 3PL performance critical success factors

The reverse and third party logistics operational process is now well known and established to be a vital component of modern day supply chain and product / service-based organizations (Marasco, 2007). Apart from being a vital component of such enterprises, many researchers and practitioners have also been noting the importance of this approach and its impact on customer service, satisfaction, profitability and other key performance indicators (Autry et al., 2001). However, studies relating to reverse 3PL performance are still limited. This research attempts to examine the factors that influence the reverse logistics performance within 3PL, within a specific case study organization in Thailand, which aims to add to work carried out relating to such operations in this part of the world such as by Bhatnagar et al. (1999). This research uses a combination of a qualitative case study along with a quantitative approach (Fuzzy Cognitive Mapping) to model and analyse the constructs which underpin the dynamics involved within a 3PL scenario. As such, both the combined approaches are based upon the development and testing of a hypothesis via empirical primary and computational data. Hence, using extant literature, and combined qualitative and quantitative research approaches, the paper identifies significant and pertinent critical success factors for reverse 3PL performance (centred around the indogenous/exogenous relationship between information systems, resource commitment and organizational structure). The paper also explores the deep inter-relationships involved within 3PL operations using the Fuzzy Cognitive Mapping technique, contributing to the existing literature on reverse 3PL and performant supply chains, and identifying critical success factors and underlying determinants of reverse 3PL of use to those industry and investigating the area from an academic perspective

Temporal meta-model framework for Enterprise Information Systems (EIS) development

This thesis has developed a Temporal Meta-Model Framework for semi-automated Enterprise System Development, which can help drastically reduce the time and cost to develop, deploy and maintain Enterprise Information Systems throughout their lifecycle. It proposes that the analysis and requirements gathering can also perform the bulk of the design phase, stored and available in a suitable model which would then be capable of automated execution with the availability of a set of specific runtime components

Platform emergence in double unknown: Common challenge strategy

International audienceThe proposed paper deals with platform emergence in double unknown situations when technology and markets are highly uncertain. The interest in technological platform development to enable creation of products and processes that support present and future development of multiple options is widely recognized by practitioners and academics The existing literature considers already existing platforms and the development is based on exploiting this common platform core to build future markets and technological derivatives. However, when we are in double unknown situations, markets and technologies are highly uncertain and neither options, nor platform core are known. Thus, how can one ensure platform emergence in double unknown?The history of innovation promotes mostly singular challenge strategy to guide innovative development. But in certain sectors, like semiconductors, telecommunications, pharmaceuticals, the success of common challenge strategy applicable to several markets is more important than singular project success. Thus, which strategy to choose for innovative technological platform emergence? Why common challenge strategy appears to be so challenging and risky? The objective of the paper is to define what are the precise market and technological conditions that in certain situations lead to 1) develop common building block (common core) that facilitate all the others projects but don't provide access directly to the market 2) launch singular project exploration to emerge future platform core consequently. We attempt to address our research questions by formally describing each strategy and fabricating simple economical model to compare them. For simulation the data was created by taking into account specifics of real management situations and parameters were chosen based on the literature review. Then we illustrate the insights of the model through a case study of innovative technology development in semiconductor industry. The in-depth empirical case study was conducted in STMicroelectronics, one of the leaders in the semiconductor industry. The data for case study was gathered from advanced technology platform with several interdependent modules developed by company and introduced to the several markets after all. This paper contributes to existing work on platform emergence by introducing the strategy of platform core construction in double unknown based on future common challenge investigation

The Interoperability of Things: Interoperable solutions as an enabler for IoT and Web 3.0

This paper presents an overview of the interoperability concepts along with the challenges for the IoT domain and the upcoming Web 3.0. We identify four levels of interoperability and the relevant solutions for accomplishing vertical and horizontal compatibility between the various layers of a modern IoT ecosystem, referred to as: technological, syntactic, semantic, and organizational interoperability. The goal is to achieve cross-domain interaction and facilitate the proper usage and management of the provided IoT services and applications. An interoperability framework is also proposed where the involved system components can cooperate and offer the seamless operation from the device to the backend framework. This by-design end-to-end interoperation enables the interplay of several complex service composition settings and the management of the system via patterns. The overall proposal is adopted by the EU funded project SEMIoTICS as an enabler towards the IoT and Web 3.0, even when products from different vendors are utilized

Achieving supply chain integration using RFID technology: The case of emerging intelligent B-to-B e-commerce processes in a living laboratory

Purpose: Despite the high operational and strategic potentials of RFID technology, very little studies have been conducted about its role as enabler of supply chain integration to achieve high-level operational efficiency. Therefore, this study is an initial effort towards bridging the existing knowledge gap in the literature. Design/methodology: This exploratory research was conducted in one retail supply chain. A multi-method approach combining a longitudinal real-life case study and a methodology integrating several steps, including a “Living Laboratory” strategy was used and involved all members of a product line to analyze in terms of their contributing activities and their interface with other supply chain members, the aim being to explore the impact of RFID technology on inter- and intra-organizational processes and information systems. Findings: Our results provide support to the role of RFID as enabler of better integration of timeliness and accuracy data flows into information systems, business process optimization through automation, better system-to-system communication and better inter- and-intra-organizational business process integration. Furthermore, they also validate the unique characteristics of RFID technology such as enabler of realtime multiple tags items data collection and exchange within the supply chain and the read-and-write capability that may help, for example, to reuse some RFID tags within the supply chain and therefore reduce the cost related to the purchase of the said RFID tags. Finally, the study also reveals the importance of business process renovation and complementary investments during the adoption of RFID technology in order to achieve high level of business value from the technology