A Conceptual Framework for Constructing Distributed Object Libraries Using Gellish
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Iot4cps Deliverable
IoT4CPS – Trustworthy IoT for CPS FFG - ICT of the Future Project No. 863129 Deliverable D5.1 Lifecycle Data Models for Smart Automotive and Smart Manufacturing Deliverable number: D5.1 Dissemination level: Public Delivery data: 13. June 2018 Editor: Violeta Damjanovic-Behrendt Author(s): Violeta Damjanovic-Behrendt (SRFG) Michaela Mühlberger (SRFG) Cristina de Luca (IFAT) Thomos Christos (IFAT) Reviewers: Heinz Weiskirchner (NOKIA) Edin Arnautovic (TTTech) The IoT4CPS project is partially funded by the “ICT of the Future” Program of the FFG and the BMVIT. The IoT4CPS Consortium: IoT4CPS – 863129 Lifecycle Data Models for Smart Automotive and Smart Manufacturing AIT – Austrian Institute of Technology GmbH AVL – AVL List GmbH DUK – Donau-Universität Krems IFAT – Infineon Technologies Austria AG JKU – JK Universität Linz / Institute for Pervasive Computing JR – Joanneum Research Forschungsgesellschaft mbH NOKIA – Nokia Solutions and Networks Österreich GmbH NXP – NXP Semiconductors Austria GmbH SBA – SBA Research GmbH SRFG – Salzburg Research Forschungsgesellschaft SCCH – Software Competence Center Hagenberg GmbH SAGÖ – Siemens AG Österreich TTTech – TTTech Computertechnik AG IAIK – TU Graz / Institute for Applied Information Processing and Communications ITI – TU Graz / Institute for Technical Informatics TUW – TU Wien / Institute of Computer Engineering XNET – X-Net Services GmbH Document Control Title: Lifecycle Data Models for Smart Automotive and Smart Manufacturing Type: Public Editor(s): Violeta Damjanovic-Behrendt Author(s): Violeta -
Openo&M Oil & Gas Industry Use Cases with Scenarios and Enabling
OpenO&M Oil & Gas Industry Use Cases with Scenarios and Enabling Technology Ken Bever MIMOSA CTO [email protected] +1 (513) 276-4105 1 Use Cases 1 Handover Information from EPC to O/O 2 Engineering Upgrades to O&M 3 Field Changes to Plant/Facility Engineering 4 Up-to-Date Product Data Library (from On-line RDL) 5 O&M Asset Configuration Updates 6 Preventive Maintenance Triggering 7 (Semi-) Automatic Triggering of Condition Based Maintenance (CBM) 8 Early Warning Notifications 9 Incident Management/Accountability 10 Information Provisioning of O&M Systems 2 Systems Requiring Interoperability AHMS Asset Health Management System MES Manufacturing Execution System CIR Common Interoperability Registry MMS Maintenance Management System CMS Condition Monitoring System OPM Operational Performance Modelling & Optimization System DCS Distributed Control System ORM Operational Risk Management System DMS Document Management System PDM Product Data Management System EAM Enterprise Asset Management System PLC Programmable Logic Controller ENG Engineering Schematic Topology and PORT Enterprise KPI/Event Portal Instrumentation Tag Configuration Management System ERM Enterprise Risk Management System PSMS Process Safety Management System ERP Enterprise Resource Planning System QMS Quality Management System HMI Human-Machine Interface (Operator Console) REG O&M Product, Structure, Asset Registry with System Standardised Data Dictionary and Taxonomy ISBM Information Service Bus Model SCADA Supervisory Control and Data Acquisition LIMS Lab Information Management -
Data Warehouse: an Integrated Decision Support Database Whose Content Is Derived from the Various Operational Databases
1 www.onlineeducation.bharatsevaksamaj.net www.bssskillmission.in DATABASE MANAGEMENT Topic Objective: At the end of this topic student will be able to: Understand the Contrasting basic concepts Understand the Database Server and Database Specified Understand the USER Clause Definition/Overview: Data: Stored representations of objects and events that have meaning and importance in the users environment. Information: Data that have been processed in such a way that they can increase the knowledge of the person who uses it. Metadata: Data that describes the properties or characteristics of end-user data and the context of that data. Database application: An application program (or set of related programs) that is used to perform a series of database activities (create, read, update, and delete) on behalf of database users. WWW.BSSVE.IN Data warehouse: An integrated decision support database whose content is derived from the various operational databases. Constraint: A rule that cannot be violated by database users. Database: An organized collection of logically related data. Entity: A person, place, object, event, or concept in the user environment about which the organization wishes to maintain data. Database management system: A software system that is used to create, maintain, and provide controlled access to user databases. www.bsscommunitycollege.in www.bssnewgeneration.in www.bsslifeskillscollege.in 2 www.onlineeducation.bharatsevaksamaj.net www.bssskillmission.in Data dependence; data independence: With data dependence, data descriptions are included with the application programs that use the data, while with data independence the data descriptions are separated from the application programs. Data warehouse; data mining: A data warehouse is an integrated decision support database, while data mining (described in the topic introduction) is the process of extracting useful information from databases. -
Multi-Domain Semantic Information and Physical Behavior Modeling of Power Systems and Gas Turbines Expanding the Common Information Model
SPECIAL SECTION ON CYBER-PHYSICAL SYSTEMS Received October 20, 2018, accepted November 7, 2018, date of publication November 20, 2018, date of current version December 19, 2018. Digital Object Identifier 10.1109/ACCESS.2018.2882311 Multi-Domain Semantic Information and Physical Behavior Modeling of Power Systems and Gas Turbines Expanding the Common Information Model FRANCISCO J. GÓMEZ 1, (Member, IEEE), MIGUEL AGUILERA CHAVES2, LUIGI VANFRETTI 3, (Member, IEEE), AND SVEIN HARALD OLSEN4 1Royal Institute of Technology, SE-100 44 Stockholm, Sweden 2Instituto Costarricense de Electricidad, San José 10032-1000, Costa Rica 3Renssealer Polytechnic Institute, Troy, NY 12180-3590, USA 4Statnett SF, 0423 Oslo, Norway Corresponding authors: Francisco J. Gómez ([email protected]) and Luigi Vanfretti ([email protected]) The work of F. J. Gómez was supported by the ITEA3 Project 14018, Open Cyber-Physical System Model-Driven Certified Development (openCPS). The work of L. Vanfretti was supported in part by the Engineering Research Center Program of the National Science Foundation and the Department of Energy under Award EEC-1041877 and in part by the CURENT Industry Partnership Program. ABSTRACT Due to the rapid increase of intermittent energy resources (IERs), there is a need to have dispatchable production available to ensure secure operation and increase opportunity for energy system flexibility. Gas turbine-based power plants offer flexible operation that is being improved with new technology advancements. Those plants provide, in general, quick start together with significant ramping capability, which can be exploited to balance IERs. Consequently, to understand the potential source of flexibility, better models for gas turbines are required for power system studies and analysis. -
Bi-Directional Transformation Between Normalized Systems Elements and Domain Ontologies in OWL
Bi-directional Transformation between Normalized Systems Elements and Domain Ontologies in OWL Marek Suchanek´ 1 a, Herwig Mannaert2, Peter Uhnak´ 3 b and Robert Pergl1 c 1Faculty of Information Technology, Czech Technical University in Prague, Thakurova´ 9, Prague, Czech Republic 2Normalized Systems Institute, University of Antwerp, Prinsstraat 13, Antwerp, Belgium 3NSX bvba, Wetenschapspark Universiteit Antwerpen, Galileilaan 15, 2845 Niel, Belgium Keywords: Ontology, Normalized Systems, Transformation, Model-driven Development, Ontology Engineering, Software Modelling. Abstract: Knowledge representation in OWL ontologies gained a lot of popularity with the development of Big Data, Artificial Intelligence, Semantic Web, and Linked Open Data. OWL ontologies are very versatile, and there are many tools for analysis, design, documentation, and mapping. They can capture concepts and categories, their properties and relations. Normalized Systems (NS) provide a way of code generation from a model of so-called NS Elements resulting in an information system with proven evolvability. The model used in NS contains domain-specific knowledge that can be represented in an OWL ontology. This work clarifies the potential advantages of having OWL representation of the NS model, discusses the design of a bi-directional transformation between NS models and domain ontologies in OWL, and describes its implementation. It shows how the resulting ontology enables further work on the analytical level and leverages the system design. Moreover, due to the fact that NS metamodel is metacircular, the transformation can generate ontology of NS metamodel itself. It is expected that the results of this work will help with the design of larger real-world applications as well as the metamodel and that the transformation tool will be further extended with additional features which we proposed. -
A Survey and Classification of Controlled Natural Languages
A Survey and Classification of Controlled Natural Languages ∗ Tobias Kuhn ETH Zurich and University of Zurich What is here called controlled natural language (CNL) has traditionally been given many different names. Especially during the last four decades, a wide variety of such languages have been designed. They are applied to improve communication among humans, to improve translation, or to provide natural and intuitive representations for formal notations. Despite the apparent differences, it seems sensible to put all these languages under the same umbrella. To bring order to the variety of languages, a general classification scheme is presented here. A comprehensive survey of existing English-based CNLs is given, listing and describing 100 languages from 1930 until today. Classification of these languages reveals that they form a single scattered cloud filling the conceptual space between natural languages such as English on the one end and formal languages such as propositional logic on the other. The goal of this article is to provide a common terminology and a common model for CNL, to contribute to the understanding of their general nature, to provide a starting point for researchers interested in the area, and to help developers to make design decisions. 1. Introduction Controlled, processable, simplified, technical, structured,andbasic are just a few examples of attributes given to constructed languages of the type to be discussed here. We will call them controlled natural languages (CNL) or simply controlled languages.Basic English, Caterpillar Fundamental English, SBVR Structured English, and Attempto Controlled English are some examples; many more will be presented herein. This article investigates the nature of such languages, provides a general classification scheme, and explores existing approaches. -
Data Models for Home Services
__________________________________________PROCEEDING OF THE 13TH CONFERENCE OF FRUCT ASSOCIATION Data Models for Home Services Vadym Kramar, Markku Korhonen, Yury Sergeev Oulu University of Applied Sciences, School of Engineering Raahe, Finland {vadym.kramar, markku.korhonen, yury.sergeev}@oamk.fi Abstract An ultimate penetration of communication technologies allowing web access has enriched a conception of smart homes with new paradigms of home services. Modern home services range far beyond such notions as Home Automation or Use of Internet. The services expose their ubiquitous nature by being integrated into smart environments, and provisioned through a variety of end-user devices. Computational intelligence require a use of knowledge technologies, and within a given domain, such requirement as a compliance with modern web architecture is essential. This is where Semantic Web technologies excel. A given work presents an overview of important terms, vocabularies, and data models that may be utilised in data and knowledge engineering with respect to home services. Index Terms: Context, Data engineering, Data models, Knowledge engineering, Semantic Web, Smart homes, Ubiquitous computing. I. INTRODUCTION In recent years, a use of Semantic Web technologies to build a giant information space has shown certain benefits. Rapid development of Web 3.0 and a use of its principle in web applications is the best evidence of such benefits. A traditional database design in still and will be widely used in web applications. One of the most important reason for that is a vast number of databases developed over years and used in a variety of applications varying from simple web services to enterprise portals. In accordance to Forrester Research though a growing number of document, or knowledge bases, such as NoSQL is not a hype anymore [1]. -
Universidad Carlos III De Madrid Escuela Politécnica Superior
Universidad Carlos III de Madrid Escuela Politécnica Superior Ingeniería en Informática Proyecto Fin de Carrera DISEÑO DE UN MUNDO VIRTUAL PARA LA ENSEÑANZA DE ARQUITECTURA SOFTWARE Autor: Verónica Casado Manzanero Tutor: Anabel Fraga Vázquez Diciembre, 2009 DISEÑO DE UN MUNDO VIRTUAL PARA LA ENSEÑANZA DE ARQUITECTURA SOFTWARE Agradecimientos En primer lugar querría dar las gracias a mis padres, por su apoyo, comprensión, generosidad, por darme todo lo que necesito y más, y sobre todo, por enseñarme a ser como soy y servirme de ejemplo para convertirme en mejor persona cada día. También me gustaría recordar a mi hermana por ayudarme siempre en lo he necesitado con esa gran dosis de paciencia que sé que ha de tener. A mis amigas Carol y Raquel, por permanecer siempre a mi lado a pesar de estar semanas sin vernos. A mi novio Marcos, por pasarme esa paciencia y tranquilidad suya que tanto aprecio, por apoyarme en todo momento, por creer en mí y por permanecer a mi lado durante estos seis largos años. Por último, agradecerle a mi tutora Anabel toda la ayuda prestada, tanto en las asignaturas como en este proyecto. Gracias a su inestimable ayuda y entusiasmo he podido completar con éxito el trabajo aquí propuesto. Ha sido un verdadero placer trabajar con ella. Verónica Casado Manzanero 3/254 Universidad Carlos III de Madrid DISEÑO DE UN MUNDO VIRTUAL PARA LA ENSEÑANZA DE ARQUITECTURA SOFTWARE Verónica Casado Manzanero 4/254 Universidad Carlos III de Madrid DISEÑO DE UN MUNDO VIRTUAL PARA LA ENSEÑANZA DE ARQUITECTURA SOFTWARE Contenido 1. Introducción y motivación ......................................................................................... -
A Method for Reusing and Re-Engineering Non-Ontological Resources for Building Ontologies
Departamento de Inteligencia Artificial Facultad de Informatica´ PhD Thesis A Method for Reusing and Re-engineering Non-ontological Resources for Building Ontologies Author : Msc. Boris Marcelo Villazon´ Terrazas Advisor : Prof. Dr. Asuncion´ Gomez´ Perez´ 2011 ii Tribunal nombrado por el Sr. Rector Magfco. de la Universidad Politecnica´ de Madrid, el d´ıa...............de.............................de 20.... Presidente : Vocal : Vocal : Vocal : Secretario : Suplente : Suplente : Realizado el acto de defensa y lectura de la Tesis el d´ıa..........de......................de 20...... en la E.T.S.I. /Facultad...................................................... Calificacion´ .................................................................................. EL PRESIDENTE LOS VOCALES EL SECRETARIO iii iv Abstract Current well-known methodologies for building ontologies do not consider the reuse and possible subsequent re-engineering of existing knowledge resources. The ontologization of non-ontological resources has led to the design of several specific methods, techniques and tools. These are mainly specific to a particular resource type, or to a particular resource implementation. Thus, everytime ontol- ogy engineers are confronted with the task of re-engineering a new resource into an ontology, they develop ad-hoc solutions for transforming such resource into a single ontology. Within the context of the NeOn project, we propose a novel methodology for building ontology networks: the NeOn Methodology, a methodology based on sce- narios. One -
ISO 15926, and the Data Handover Standard CFIHOS Based on It
Enabling step-change For managers: About the interoperability standard for process plants ISO 15926, and the data handover standard CFIHOS based on it. ISO 15926 & CFIHOS Onno Paap – https://www.linkedin.com/in/onnopaap/ March 2020 Purpose Interoperability using standards: For data integration ─ISO 15926 For data handover from Engineering contractor to Owner/Operator ─CFIHOS (Capital Facilities Information Handover Spec) Purpose: Decrease risk by higher data quality and save cost. 2 ISO 15926 – what is it? International standard, ISO TC184-SC4 WG3 (industrial data related to discrete products); Neutral layer used for data integration; Federation of databases – Semantic Web technology; Interoperability standard; Interoperability meaning: “the ability of different types of computers, networks, operating systems, and applications to work together effectively, without prior communication, in order to exchange information in a useful and meaningful manner”. 3 What is in ISO 15926? Reference data library (RDL) = A central online database http://data.posccaesar.org/rdl And also a work-in-progress database http://data.15926.org/rdl Data integration and interoperability methodology Open source software http://15926.tools 4 Why did we need ISO 15926? Shell said: We need a data model that can withstand the changes of the times. A process plant can be running for a period up to 50 years while software typically is changing every 2 years. BP said: A system of systems must interoperate through major projects and operations Reference data is critical, but does not deliver interoperability alone Standard connectors are required to deliver interoperability Commercially available ‘interoperability’ solutions depend on fragile, expensive and proprietary integration 5 What is the scope of ISO 15926? ISO 15926 is targeted for data on process plants. -
Data Exchange Solutions Using ISO 15926 Adaptive Information Model Manoj Dharwadkar, Phd., Director of Technology Management Bentley Systems Inc
Data Exchange Solutions using ISO 15926 Adaptive Information Model Manoj Dharwadkar, PhD., Director of Technology Management Bentley Systems Inc. Semantic Days 2008, Stavanger, Norway Outline • Bentley Overview • Data interoperability strategy based on ISO 15926 • Bentley’s implementation of ISO 15926 • The role of Bentley Class Editor and Adaptive Information Model Bentley’s Mission Help improve the world’s infrastructure Serving Distributed Enterprises Conceptual Mechanical Construction Financing Procurement Design Design Project Site Structural Fabrication Management Design Design The business of infrastructure entails distributed enterprises A Strong Global Company • 24 years of growth and stability • 2,500+ employees, 80 offices, 40 countries Distinctions 1. A comprehensive software portfolio that is multi-discipline and integrated, just like your projects 2. Collaboration servers that allow distributed enterprises to successfully deliver infrastructure projects 3. A commitment to interoperability to maximize the return on your investments in data Portfolio of Products POSC Caesar IDS and FIATECH ADI are accelerating ISO 15926 • Collaboration between both projects – IDS (Intelligent Data Sets) • Reference data expansion and Methodologies • Online reference data hosting, browsing, and editing • Simple implementation approaches •Training – ADI (Accelerating Deployment of ISO 15926) • Focus on implementation and tools • Reference Data System (RDS) software and utilities •Training • Bentley is very active in both projects Slide: 8 Data -
Modeling and Conformance Testing for the Engineering Information Integration Standard ISO 15926
NISTIR 7917 Modeling and Conformance Testing for the Engineering Information Integration Standard ISO 15926 Peter Denno Mark Palmer http://dx.doi.org/10.6028/NIST.IR.7917 NISTIR 7917 Modeling and Conformance Testing for the Engineering Information Integration Standard ISO 15926 Peter Denno Mark Palmer Systems Integration Division Engineering Laboratory http://dx.doi.org/10.6028/NIST.IR.7917 February, 2013 U.S. Department of Commerce Rebecca Blank, Acting Secretary National Institute of Standards and Technology Patrick D. Gallagher, Under Secretary of Commerce for Standards and Technology and Director ABSTRACT The process and power industries and their suppliers have invested in multiple initiatives to develop and deploy a new information exchange and integration standard, ISO 15926, Industrial automation systems and integration — Integration of life-cycle data for process plants including oil and gas production facilities. Although the potential benefits of this standard have been demonstrated in pilot projects, broad, cost-effective deployment may require improved methods, tools, and testing. This publication identifies requirements for successful implementation of ISO 15926-based information exchange. Currently there exists a draft methodology for information modeling with ISO-15926, documented in a patchwork of ISO-approved and draft-status documents, and supplemented by documents produced by industry projects [1], [2]. However, there are variations and no consensus as to the criteria for achieving interoperability. There are reasons to believe that successful implementation of ISO 15926 - based exchanges will require substantial refinement of the methodology. Further, there are many more requirements for successful implementation – matters of technical sufficiency and organizational responsibility – that have received insufficient attention.