Current industry standards for describing web services focus on interoperability across different development platforms but fail to provide a consistent foundation to be able to acquire some automation, like to make intelligent searches or service compositions. Effective web services discovery should be defined as the process of matching user requests with some available web services and must focus on semantics, depending directly on the ability to make semantic specifications about web services at a machine-readable level. This paper proposes an implementation of OWL-S to support semantic discovery for Brazilian Air-Traffic Management Web Services.
The use of semantic web technologies and of ontologies is raising growing interest in industry. Industry is facing during these last decades, with the rapid development and use of a set of applications for specific needs, new issues due to a lack of interoperability, which conducts to growing costs. When digitization of industry is accelerating, ontologies and digital data standards based on models pave the way to solve these issues by improving interoperability between applications and between actors of the value chain. Recent European H2020 projects and clusters, Joint Industrial Projects in industry and advanced standards of Standardization Development Organizations converge towards new ways of modeling, structuring, and managing digital technical data across applications using ontologies thanks to advanced conceptual, methodological, and semantic technologies. In this paper, we will provide preliminary results for structuring transverse information knowledge and data in a proper manner using industry standards and semantic framework.
This work discusses how to connect business decision support systems, implemented in terms of the BPMN and DMN standards, with materials modelling workflows. The suggested approach facilitates interoperability of materials modelling software tools covering the main phenomena involved in advanced corrosion protection and active protective coatings’ behaviour. The proposed system integrates materials modelling methodologies with decision support in business processes using a knowledge-based architecture. Thus, this contribution showcases the missing link between business processes, materials science, and computational engineering workflows for industrially relevant use cases; here, specifically, corrosion and protective-coating modelling. At the implementation level, we report on novel features of the process modelling suite ProMo for ontology and process-topology based materials modelling workflow construction and documentation. ProMo is extended to address challenges specific to the H2020 project VIPCOAT which works toward establishing an open innovation platform for active protective coatings and accelerated corrosion tests, including assessments of their in-service durability. Connections between quantitatively reliable materials modelling tools, their integration into simulation workflows, and ontology-based knowledge representation are considered, addressing the use case from VIPCOAT.
In this paper, we report on the current state of the development of the Open Translation Environment (OTE), which is based on the Elementary Multiperspective Material Ontology (EMMO) – a top-level ontology for applied science, to support Translators in the Materials domain. We describe the conceptual architecture of the OTE, as well as some of its main components.
Space System Engineering is an iterative process in which various domain-specific viewpoints are integrated to present the final mission. This multi-disciplinary character of digital space systems creates interoperability issues. To deal with these issues, European Space Agency (ESA) initiated the OSMoSE project ( O verall S emantic Mo delling for S ystem E ngineering) to promote the digital continuity and interoperability among the involved stakeholders. OSMoSE provides a top-level space system ontology (OSS) and domain-specific ontologies. This paper aims at proposing a framework to create domain-specific ontologies for space systems. The concept of Perspective is proposed to define the system from the viewpoint of different engineering domains. This approach help us to identify all important information for each discipline as well as identifying interfaces between sub-systems. The proposed approach is presented by means of an example from a simulated earth observation mission (EagleEye) and the ontology is made using NORMA ORM (Object-Role Modelling) tool.
Developing systems that facilitate natural interaction between humans and industrial systems by using current state-of-the art technologies, such as Deep Learning techniques, requires large amounts of training data, usually scarce in industrial scenarios, and the resulting systems are difficult to adapt to other settings. This paper illustrates an ontology-driven adaptation of KIDE4I, a generic semantic-based task-oriented dialogue system, to set up with a limited amount of effort KIDE4Assistant, a dialogue system for assistance in maintenance procedures through natural interactions. This adaptation approach bridges the gaps related to data availability and system reuse by exploiting expert knowledge together with existing ontologies and resources to obtain a fully-functional task-oriented dialogue system. Furthermore, the evaluation of KIDE4Assistant, performed through a user experimentation, shows the promising results of this approach.
Depending on the complexity of the assembly design and required production constraints, factories employ various types of joining operations as part of product fabrication. Manufacturers, who are in the business of assembling, gain their competence based on what types of processes and resources they use as well as how they are used in these joining operations. For data interoperability and exchange among the partners of distributed manufacturing, these joining operations need to be described formally to build a common set of vocabulary. Current ontologies in the related topics lack the details of the process characterization in their analysis and do not adopt foundational concepts to build such definitions. This paper presents an ontology-driven characterization of the joining operations to formalize a set of definitions on ontologically grounding concepts towards the construction of a taxonomy of the joining operations.
Functional modelling is a well-studied topic in engineering and applies more broadly to areas like biology, management and organization studies. While it is an essential part of building and describing engineering systems, to apply functional modelling consistently in practice remains difficult. This obstacle is especially painful since digitalisation is becoming an increasingly important aspect of modern engineering enterprises. To study the causes of such a difficulty, we analyze two typical problems that are encountered when modelling engineering systems and that are intertwined with functional aspects: identity of system components across time, and granularity management of the system models. The problems are introduced and used to compare a few ontological and engineering approaches that can deal with them. We illustrate our findings with a brief example.
Asset management is comprised of data-intensive activities such as condition and performance monitoring, scheduling of repairs and preventive maintenance, capital project monitoring, and life-cycle costing. Like so many areas of industry, asset management is hindered by an evolution of legacy systems that has resulted in a complex web of disparate data systems making it difficult to track and report on assets. We aim to address this challenge for Toronto Water with the implementation of an ontology-supported data hub. Toronto Water is a major organization responsible for the treatment and supply of safe drinking water, the collection and treatment of wastewater, and stormwater management for the City of Toronto – serving a population of over 6 million people. In this paper, we focus on the identification of requirements for an ontology of asset management. This will be a key deliverable of the project that will serve to guide the survey of existing ontologies, as well as the development of the data hub itself. It is our hope that these requirements will serve to inform both the ontology and industry communities. The requirements not only identify the required scope for the ontology, but also illustrate the way in which ontologies can be used to support various asset management activities.
The Industrial Ontologies Foundry (IOF) was formed to create a suite of interoperable ontologies. Ontologies that would serve as a foundation for data and information interoperability in all areas of manufacturing. To ensure that each ontology is developed in a structured and mutually coherent manner, the IOF has committed to the tiered architecture of ontology building based on the Basic Formal Ontology (BFO) as top level. One of the critical elements of a successful tiered architecture build is the domain mid-level ontologies. However, thus far there has been no mid-level manufacturing ontology that is based on BFO. The IOF has recently released the IOF Core version 1 beta to fill this gap. This paper documents the development process and gives an overview of the current content of the IOF Core. Finally, the paper describes how the IOF Core can be used as the basis for a more domain-specific Supply Chain Ontology.
This document shows the current research progress and methodology applied to build a domain ontology for describing facilities in offshore petroleum production plants, based on an extensive requirement collection developed in industry and formalized through a set of competency questions. The final goal is to create a uniform and formally defined reference vocabulary to help engineers and information technology people label and relate measures and facilities in the production plant monitoring and simulation. The ontology uses BFO as a top-level ontology and employs GeoCore and an ongoing version of the core ontology produced by the Industry Ontology Foundry (IOF) as middle-level ontologies. This research is part of the Petwin project that studies the best practices for developing a digital twin for monitoring and simulating petroleum production in the industry.
Recent academic and industrial initiatives show an increasing interest in the use of foundational ontologies to support the development of domain-specific ontologies. Foundational ontologies guarantee formal and conceptual robustness, and at the same time support the integration of multiple domain-ontologies aligned to the same foundational ontology. This paper reports some ongoing work in this area focusing on the application of the dolce ontology in the manufacturing domain. Taking advantage of the newly formal representation of dolce in OWL and building on previous modeling works, the paper shows how different modeling strategies can be used depending on the engineering requirements at hand, and discusses advantages and disadvantages of these strategies. We exemplify the discussion by means of an industrial case study.
The field of materials characterisation encompasses a wide range of methods and related research communities. This has led to a proliferation of terminologies and data management approaches, hindering collaboration and interoperability. In this work, a domain ontology designed to model the common aspects across the different characterisation methodologies is presented. This ontology, called the CHAMEO ontology, is based on a recent CEN Workshop Agreement (CWA 17815) which introduced a standardised terminology and the Characterisation Data (CHADA) documentation scheme. The goal of CHAMEO is to provide a framework for harmonising the underlying method-specific ontologies, which can be developed by reusing and specialising the generic constructs of the CHAMEO ontology. This work is part of a broader initiative under the umbrella of the European Materials Modelling Council (EMMC), for the development of interconnected materials modelling ontologies based on a common root that is the Elementary Multiperspective Material Ontology (EMMO). The CHAMEO ontology was developed within the NanoMECommons European project that has the goal of harmonising characterisation protocols. The CHAMEO ontology has also been aligned with a number of recently developed, EMMO-based domain ontologies for the classification of materials, models, manufacturing processes and software products related to Materials Modelling. Availability. The axiomatization of the ontology is stored in a GitHub repository available at: https://github.com/emmo-repo/domain-characterisation-methodology, and is published at the following URL: http://emmo.info/emmo/domain/chameo/chameo.
Models for Manufacturing (MfM) is a novel approach proposed by the authors to apply Ontology-Based Engineering (OBE) concepts to Manufacturing. The methodology is based in a 3-Layers Model (3LM) framework and supported by any modelling tools easy-to-use. The Ontology layer comprises the ontological definition holding the knowledge of the domain. This work presents the introduction of metamodels or surrogate models for supporting MfM methodology with the objective to maintain independence with commercial software tools. This paper introduces the proposed metamodels and relationships, shows the link within the MfM Ontology layer and discusses the further activities.
Business process modelling (BPM) notations describe processes using a graphical representation of process-relevant entities and their interplay. Despite the wide literature on the comparison between different modelling languages, the BPM community still lacks an ontological characterisation of process constructs. Purpose of this paper is to start filling this gap by providing a first ontological analysis of the main business process entities. The analysis and the resulting characterisation aim at illustrating the different perspectives that BPM languages implicitly take on business processes, as well as guiding the modellers in making an appropriate choice when selecting among different notations.
Choreography diagrams have been introduced in the Business Process Model and Notation language 2.0 (BPMN 2.0), one among the most used languages for modelling and analyzing business processes in industry, in order to provide a view on the interaction between participants. Besides the intuitive definition of choreographies as interfaces among participants, the BPMN 2.0 specifications also define choreographies as business contracts among the parties. However, the adoption and the diffusion of the business contract nature of choreography diagrams seem to be hindered by the underspecification of the notation, which does not allow to model and formalize constraints and relationships among choreography entities, which would need to be specified in a business contract. In this paper we provide a preliminary investigation of some of the open issues characterizing BPMN 2.0 choreography diagrams when looking at the business contract nature of the notation, by focusing on those related to messages and participants.
This paper intends to share the development experience of the application ontology of the SaaS version of the decision statistical mapping and geomarketing software Cartes and Données (C and D). The ontology describing the C and D application domain was conceived for automation of semantic annotation of CD7Online’s users data to help users better understand their data and make better selection and representation choices. We followed the application ontology development methodology of Noy and McGuinness, which we expanded with the mapping to an upper ontology and an additional ontology evaluation step according to user specific needs.
Product Lifecycle Management (PLM) deals with information modelling across the entire lifespan of industrial products. The use of computer-based technologies for PLM purposes requires product knowledge to be specified in formal languages, so that the semantics of the modelling elements is explicitly defined in relation to experts' conceptualisations. Ontologies used in PLM contexts are often developed to satisfy specific application requirements, and the meaning of the employed concepts is left unspecified. In this paper, we present a preliminary ontology focused on the notion of product from the engineering design and manufacturing perspectives. Our aim is to contribute at the development of a comprehensive ontological specification of product knowledge for product lifecycle modelling applications.
The Enterprise Modeling (EM) community has recognized formal ontologies as a promising instrument to address some of the challenges in the EM field. The studies have shown that the main benefits of applying formal ontologies in the realm of EM are the machine-reasoning, flexibility of the logic-based schema and ability to integrate easily a number of data sources. However, in order to realize the potential benefits, among others, formal ontologies fulfilling specific requirements need to be available. In this paper, we discuss a set of generic requirements towards formal ontologies in the realm of EM and check their fulfillment with the aim to identify directions of future work.
Management of block storage virtualization systems in large environments can become very complex. For standard management tasks, such as the creation and maintenance of disk arrays, and problem isolation, specialized storage management tools are used. Such tools must query the storage virtualization system for topologies and performance statistics, correlating this information with external sources and defined policies, and providing an interface for the storage administrators. By using ontologies as information models in a storage management tool, correlation of elements, aggregation and querying becomes a lot more flexible and configurable. In this paper we present an ontology-based architecture that serves as backend for a storage management tool. We describe the approach and performance optimizations and give an evaluation of the prototypical implementation.
