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Facilitating the information exchange and interoperability between stakeholders during the life-cycle of an asset can be one of the fundamental necessities for developing an enhanced information exchange framework. Such a framework can also improve the successful accomplishment of building projects. This paper aims to use Semantic Web technologies for facilitating information exchange within existing building projects.

In real-world building projects, the construction industry’s information supply chain may initiate from near scratch when new building projects are started resulting in diverse data structures represented in unstructured data sources, like Excel spreadsheets and documents. Large-scale data generated throughout a building's life-cycle requires exchanging and processing during an asset's Operation and Maintenance (O&M) phase. Building information modelling (BIM) processes and related technologies can address some of the challenges and limitations of information exchange and interoperability within new building projects. However, the use of BIM in existing and retrofit assets has been hampered by the challenges surrounding the limitations of existing technologies.

The aim of this paper is twofold. Firstly, it briefly outlines the framework previously developed for generating semantically enriched 3D retrofit models. Secondly, a framework is proposed focussing on facilitating the information exchange and interoperability for existing buildings. Semantic Web technologies and standards, such as Web Ontology Language and existing AEC domain ontologies are used to enhance and improve the proposed framework.

The proposed framework is evaluated by implementing an example application and the Resource Description Framework data produced by the previously developed framework. The proposed approach makes a valuable contribution to the asset/facilities management (AM/FM) domain. It should be of interest to various FM practices for existing assets, such as the building information/knowledge management for design, construction and O&M stages of an asset’s life-cycle.

This paper aims to propose a brand new ontology development methodology, called Yet Another Methodology for Ontology (YAMO) and demonstrate, step by step, the building of a formally defined large-scale faceted ontology for food.

YAMO is motivated by facet analysis and an analytico-synthetic classification approach. The approach ensures quality of the system precisely; it makes the system flexible, hospitable, extensible, sturdy, dense and complete. YAMO consists of two-way approaches: top-down and bottom-up. Based on YAMO, domain food, formally defined as large-scale ontology, is designed. To design the ontology and to define the scope and boundary of the domain, a group of people were interviewed to get a practical overview, which provided more insight to the theoretical understanding of the domain.

The result obtained from evaluating the ontology is a very impressive one. Based on the study, it was found that 94 per cent of the user’s queries were successfully met. This shows the efficiency and effectiveness of the YAMO methodology. An evaluator opined that the ontology is very deep and exhaustive.

The authors envision that the current work will have great implications on ontology developers and practitioners. YAMO will allow ontologists to construct a very deep, high-quality and large-scale ontology.

This paper illustrates a brand new ontology development methodology and demonstrates how the methodology can be applied to build a large-scale high-quality domain ontology.

This study proposes a framework for Earthwork Ontology (EW-Onto) to support and enhance data exchange in the project and the efficient decision-making in the planning and execution phases.

The development of EW-Onto started from defining the concepts and building taxonomies for earthwork operations and equipment following the METHONTOLOGY approach. In addition, several rules have been extracted from safety codes and implemented as SWRL rules. The ontology has been implemented using Protégé. The consistency of EW-Onto has been checked and it has been evaluated using a survey.

The assessment of EW-Onto by experts indicates an adequate level of consensus with the framework, as an initial step for explicit knowledge exchanges within the earthwork domain.

The use of an ontology within the earthwork domain can help: (1) link and identify the relationships between concepts, define earthwork semantics, and classify knowledge in a hierarchical way accepted by experts and end-users; (2) facilitate the management of earthwork operations and simplify information exchange and interoperability between currently fragmented systems; and (3) increase the stakeholders' knowledge of earthwork operations through the provision of the information, which is structured in the context of robust knowledge.

This paper proposes a framework for Earthwork Ontology (EW-Onto) to support and enhance data exchange in the project and the efficient decision-making in the planning and execution phases. EW-Onto represents the semantic values of the entities and the relationships, which are identified and formalized based on the basic definitions available in the literature and outlined by experts.

This study aims to develop a synthetic knowledge repository consisted of interrelated Web Ontology Language.

The ontology composes the main framework to categorize data of product life cycle with eco-design mode (PLC-EDM) and automatically infer specialists’ knowledge for data confirmation, eventually assisting the utilizations and generation of strategies toward decision-making

(i) utilization of a novel model with ontology mode for information reuse cross the different eco-design applications; (ii) generation of a sound platform toward life cycle evaluation; and (iii) implementation of the PLC-EDM model along the product generation process.

It cannot substitute an evaluation tool of life cycle. Certainly, this model does not predict the “target and range” and/or the depiction of the “utility module” that are basic activities in life cycle assessments as characterized through the international organization for standardization regulations.

As portion of this framework, a prototype Web application is presented which is applied to produce, reuse and verify knowledge of product life cycle.

By counting upon the ontology, the information conducted by the utilization is certainly semantically represented to promote the data sharing among various participants and tools. Besides, the data can be verified against possible faults by inferring over the ontology. Hence, a feasible way to a popular topic in the domain of eco-design applications extension in the industry.

The goals are: to lean on rigid modeling principles; and to promote the interoperability and diffusion of the ontology toward particular utilization demands.

Early Modern emblem books are primary sources for scholars studying the European Renaissance. Linked Open Data (LOD) is an approach for organizing and modeling information in a data-centric manner compatible with the emerging Semantic Web. The purpose of this paper is to examine ways in which LOD methods can be applied to facilitate emblem resource discovery, better reveal the structure and connectedness of digitized emblem resources, and enhance scholar interactions with digitized emblem resources.

This research encompasses an analysis of the existing XML-based Spine (emblem-specific) metadata schema; the design of a new, domain-specific, Resource Description Framework compatible ontology; the mapping and transformation of metadata from Spine to both the new ontology and (separately) to the pre-existing Schema.org ontology; and the (experimental) modification of the Emblematica Online portal as a proof of concept to illustrate enhancements supported by LOD.

LOD is viable as an approach for facilitating discovery and enhancing the value to scholars of digitized emblem books; however, metadata must first be enriched with additional uniform resource identifiers and the workflow upgrades required to normalize and transform existing emblem metadata are substantial and still to be fully worked out.

The research described demonstrates the feasibility of transforming existing, special collections metadata to LOD. Although considerable work and further study will be required, preliminary findings suggest potential benefits of LOD for both users and libraries.

This research is unique in the context of emblem studies and adds to the emerging body of work examining the application of LOD best practices to library special collections.

The need to flexibly react to changing demands and to cost-efficiently manage customized production even for lot size of one requires a dynamic and holistic integration of service-based processes within and across enterprises of the value chain. In this context, this paper aims at presenting ODERU, the authors’ novel pragmatic approach for automatically implementing service-based manufacturing processes at design and runtime within a cloud-based elastic manufacturing platform.

ODERU relies on a set of semantic annotations of business process models encoded into an extension of the business process model and notation (BPMN) 2.0 standard. Leveraging the paradigms of semantic SOA and XaaS, ODERU integrates pattern-based semantic composition of process service plans with QoS-based optimization based on multi-objective constraint optimization problem solving.

The successful validation of ODERU in two industrial use cases for maintenance process optimization and automotive production in the European project CREMA revealed its usefulness for service-based process optimization in general and for significant cost reductions in maintenance in particular.

ODERU provides a pragmatic and flexible solution to optimal service composition with the following three main advantages: full integration of semantic service selection and composition with QoS-based optimization; executability of the generated optimal process service plans by an execution environment as they include service assignments, data flow (variable bindings) and optimal variable assignments; and support of fast replanning in a single model and plan.

Matter is an important topic of science as a discipline since its inception. Nevertheless, along with the evolution of semantic web, matter has got equal importance among the ontology developers. The current work describes an ontology of matter that the authors developed in the lab. The purpose of this paper is to come up with an exhaustive list of concepts and relations to cover matter domain under one umbrella, after identifying the gaps in the present ontologies.

Ontology was developed following faceted analytico-synthetic approach of knowledge organization. The authors followed hybrid developmental approach which includes top-down as well as bottom-up development strategy, for creating classes and subclasses. The authors modelled matter domain comprehensively considering different aspects of matter. The theories behind the modelling approach helps to maintain the consistency of further extensions.

Final ontology has around 280 concepts and as many as 60 properties which include both object property and datatype property.

There exists very vague definition of concepts in different subject areas, as matter is a domain of study in physics, chemistry, material science, metallurgy, etc. Same material has been adopted differently depending upon purpose of its study/use in that field. For example aspirin is simply a chemical compound in chemistry, whereas in medicine it is also an agent.

Present work claims to influence the ontology engineers to develop more extension to this core ontology of matter (COMAT). Also this will find its use in information retrieval, semantic annotations and in several other semantic knowledge-based systems.

COMAT is the most recent work of the domain. Originality lies in the way matter domain has been looked up, from a very wide perspective, as well as in the approach of modelling the domain.

IEEE Ontologies for Robotics and Automation Working Group were divided into subgroups that were in charge of studying industrial robotics, service robotics and autonomous robotics. This paper aims to present the work in-progress developed by the autonomous robotics (AuR) subgroup. This group aims to extend the core ontology for robotics and automation to represent more specific concepts and axioms that are commonly used in autonomous robots.

For autonomous robots, various concepts for aerial robots, underwater robots and ground robots are described. Components of an autonomous system are defined, such as robotic platforms, actuators, sensors, control, state estimation, path planning, perception and decision-making.

AuR has identified the core concepts and domains needed to create an ontology for autonomous robots.

AuR targets to create a standard ontology to represent the knowledge and reasoning needed to create autonomous systems that comprise robots that can operate in the air, ground and underwater environments. The concepts in the developed ontology will endow a robot with autonomy, that is, endow robots with the ability to perform desired tasks in unstructured environments without continuous explicit human guidance.

Creating a standard for knowledge representation and reasoning in autonomous robotics will have a significant impact on all R&A domains, such as on the knowledge transmission among agents, including autonomous robots and humans. This tends to facilitate the communication among them and also provide reasoning capabilities involving the knowledge of all elements using the ontology. This will result in improved autonomy of autonomous systems. The autonomy will have considerable impact on how robots interact with humans. As a result, the use of robots will further benefit our society. Many tedious tasks that currently can only be performed by humans will be performed by robots, which will further improve the quality of life. To the best of the authors’knowledge, AuR is the first group that adopts a systematic approach to develop ontologies consisting of specific concepts and axioms that are commonly used in autonomous robots.