DOCSLIB.ORG

FI-WARE Product Vision Front Page Ref

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text

Load more

FI-WARE Product Vision front page Ref. Ares(2011)1227415 - 17/11/20111 FI-WARE Product Vision front page Large-scale Integrated Project (IP) D2.2: FI-WARE High-level Description. Project acronym: FI-WARE Project full title: Future Internet Core Platform Contract No.: 285248 Strategic Objective: FI.ICT-2011.1.7 Technology foundation: Future Internet Core Platform Project Document Number: ICT-2011-FI-285248-WP2-D2.2b Project Document Date: 15 Nov. 2011 Deliverable Type and Security: Public Author: FI-WARE Consortium Contributors: FI-WARE Consortium. Abstract: This deliverable provides a high-level description of FI-WARE which can help to understand its functional scope and approach towards materialization until a first release of the FI-WARE Architecture is officially released. Keyword list: FI-WARE, PPP, Future Internet Core Platform/Technology Foundation, Cloud, Service Delivery, Future Networks, Internet of Things, Internet of Services, Open APIs Contents Articles FI-WARE Product Vision front page 1 FI-WARE Product Vision 2 Overall FI-WARE Vision 3 FI-WARE Cloud Hosting 13 FI-WARE Data/Context Management 43 FI-WARE Internet of Things (IoT) Services Enablement 94 FI-WARE Applications/Services Ecosystem and Delivery Framework 117 FI-WARE Security 161 FI-WARE Interface to Networks and Devices (I2ND) 186 Materializing Cloud Hosting in FI-WARE 217 Crowbar 224 XCAT 225 OpenStack Nova 226 System Pools 227 ISAAC 228 RESERVOIR 229 Trusted Compute Pools 230 Open Cloud Computing Interface (OCCI) 231 OpenStack Glance 232 OpenStack Quantum 233 Open vSwitch 234 Claudia 235 PaaS Management Platform 237 OpenStack Swift 239 Nada Management Framework 240 OpenStack Keystone 241 Materializing Data/Context Management in FI-WARE 242 Context Awareness Platform (CAP) 248 AMIT 249 Hadoop 251 MongoDB 251 SAMSON Platform 252 Codoan 253 White Diamond 254 Meta-data Processor 255 Location server 256 Location Provider 257 QueryBroker 258 Semantic Annotator (SAnr) 259 NeOn Toolkit 260 Sesame 262 OWLIM 263 Materializing Internet of Things (IoT) Services Enablement in FI-WARE 264 Cumulocity 274 FossTrak 277 M2MPlanet/Pangoo 278 IDAS 279 ISIS 281 IoT-A 282 Atos SOL 283 Sensei 284 Linked Data Platform and Gateway 286 Materializing Applications/Services Ecosystem and Delivery Framework in FI-WARE 288 USDL 3.0 Specifications M5 295 Apache Chemistry Client and Server 296 JENA SDB/TDB RDF Store 297 USDL Service Marketplace OS 298 PREMIUM-Services Pricing Strategies Simulator 300 Ericsson eStore 301 Revenue Sharing System 302 EricssonCommonCompositionCore 303 WebConnectivityEnabler 305 Wirecloud Mashup Platform 307 Mashup Factory 310 LighSemantic-enabled Design Time Semi-automatic Service Composition 311 WSO2-Mediation-Layer-Extension 312 Light-Semantics-enable Process and Data Mediation Composer 313 SLA Model 314 Materializing Security in FI-WARE 315 IoT Internet protocols fuzzing framework 320 FI-Ware Vulnerability assessment 321 Ontology handler 321 Vulnerabilities OVAL scanner 322 NVD 323 Attack trace engine 324 Service-Level-SIEM 325 CVSS 326 Visualization Framework 328 Fragmento 329 Compliance Governance Dashboard 331 CRLT Compliance Request Language Tools 333 USDL Language 334 S&D Run-Time Framework 336 Stork 338 Identity Management 341 White Label IdP 342 Access Control 345 Privacy Enabler 347 Idemix - Privacy-Preserving Credential Library 348 Idemix - Credential-based Authentication Engine 350 Accountable privacy policies 352 PrimeLife Policy Engine: PPL 353 Database Anonymization Optional Asset 356 Secure Storage Service (SSS) Optional Asset (Thales) 359 Morphus Optional Asset (INRIA) 362 Materializing the Interface to Networks and Devices (I2ND) in FI-WARE 363 WEB Runtime Engine 367 Meego 368 Web API 369 Reinforcement Learning 371 Network Organizer 372 ZigBee GAL 373 NOX based OpenFlow controller 374 Network Element Virtualizer 374 DRAGON 375 OpenEPC Platform 376 Device Connection Platform 378 API mediation 381 Fast Telecom Service helper 382 Voicemail enabler 383 Intelligent Network Identity Management 384 Network-centric Resource Management 385 Seamless Network Connectivity 386 References Article Sources and Contributors 388 Image Sources, Licenses and Contributors 391 FI-WARE Product Vision 2 FI-WARE Product Vision Introduction The FI-WARE Product Vision provides a high-level description of the FI-WARE Platform. FI-WARE aims to provide a framework for development of smart applications in the Future Internet. FI-WARE is being developed as part of the Future Internet Public Private Partnership (FI-PPP) program launched by the European Commission in collaboration with the ICT Industry. However, it has a global ambition. More information about the FI-PPP program can be found at: • http:/ / www. fi-ppp. eu • http:/ / ec. europa. eu/ information_society/ activities/ foi/ lead/ fippp/ index_en. htm More information about FI-WARE can be found at: • http:/ / www. fi-ware. eu FI-WARE Chapters You should start reading the Overall FI-WARE Vision. It will give you an overview of some basic concepts and principles that are general to FI-WARE (Generic Enablers, FI-WARE Instances, etc). The Reference Architecture of the FI-WARE platform is structured along a number of technical chapters, namely: • Cloud Hosting • Data/Context Management • Internet of Things (IoT) Services Enablement • Applications/Services Ecosystem and Delivery Framework • Security • Interface to Networks and Devices (I2ND) You can get a description of each of these chapters by clicking on the chapter name in the list above. Each chapter description is structured so that a general overview of the chapter is provided first, where main Generic Enablers in the chapter are identified and briefly described. Afterwards, a more detailed description of each of these Generic Enablers is provided. A precise list of terms and definition is provided for each chapter that can work as basic vocabulary that will help to establish the basis for fruitful discussions around FI-WARE. A list of references is also provided that could be helpful to complement what has been described. Finally, a description of points still under discussion is included. It will transparently present some topics that are currently being targeted as part of ongoing discussions within the project. The FI-WARE project will draw upon the wealth of results already achieved through earlier Research projects, not only within the EU FP but also at national- or corporate-funded levels, aiming to leverage them further through a systematic integration with a complete system perspective. A description of what are the products (assets) that will be considered as baseline for the development of a first reference implementation of each Generic Enablers in FI-WARE can be found in Materializing the FI-WARE Vision. They will evolve and will be integrated together following an Agile development process you can monitor following the definition and evolution of backlog entries associated to the chapter and/or each of the Generic Enablers. A description of projects whose results may be be considered for further integration is provided in those cases where implementation of the Generic Enabler is not planned for the current FI-WARE major release. Overall FI-WARE Vision 3 Overall FI-WARE Vision Background and Motivations Changing ICT Landscapes and Trends Over the last couple of years, a number of technology trends are recognized as significant new directions in the ICT landscape, which will usher in the era of the Future Internet in Europe. A first major trend is the on-going industrialization of IT in the form of cloud computing and open service delivery platforms. The on-demand, pay-per-use nature of these provisioning models is expected to fundamentally change how IT infrastructures are provisioned, essentially enabling them to be delivered as a service. Secondly, new wireless networking technologies such as LTE (4G) and the deployment of Fibre to The Home (FTTH) will offer increased network capacity and bandwidth to customers, thereby paving the way for new (real-time) applications in mobile data networks as well as for stationary scenarios. Furthermore, the virtualization of classical carrier networks is also on-going and starting to find new areas of application. Thirdly, the Internet of Things is safely taking hold, with the vision of ubiquitously connecting intelligent devices and sensors and offering new possibilities for contextual and environmental information sensing, processing and analysis, thereby opening the door to new automation and control applications and services in various sectors. Lastly, the maturing Internet of Services is accelerating the creation of complex value networks of service providers, consumers, and intermediaries bringing businesses and end customers innovative applications better tailored to their needs. These networks increasingly span various different players that historically have worked largely separated from each other thereby leading to more agile and dynamic business relationships and environments never seen before. The Market Stakeholder Perspectives Brought together, the above trends are the core drivers towards the emergence of a new era in the evolution of the Internet, which we may refer to as Future Internet. It will carry the potential for realizing new business opportunities for established and emerging application and service providers in areas such as telecommunications, healthcare, media and e-government. This Future Internet will address some key demands and expectations from the various market stakeholders
Recommended publications
  • FI-WARE User and Programmers Guide WP6 Front Page 1 FI-WARE User and Programmers Guide WP6 Front Page

    FI-WARE User and Programmers Guide WP6 Front Page 1 FI-WARE User and Programmers Guide WP6 Front Page

    FI-WARE User and Programmers Guide WP6 front page 1 FI-WARE User and Programmers Guide WP6 front page Large-scale Integrated Project (IP) D.6.4.a: User and Programmers Guide Project acronym: FI-WARE Project full title: Future Internet Core Platform Contract No.: 285248 Strategic Objective: FI.ICT-2011.1.7 Technology foundation: Future Internet Core Platform Project Document Number: ICT-2011-FI-285248-WP6-D6.4a Project Document Date: 30 June 2012 Deliverable Type and Security: Public Author: FI-WARE Consortium Contributors: FI-WARE Consortium Abstract: This deliverable contains the User and Programmers Guide for the Generic Enablers of Data/Context Management chapter, being included in the First FI-WARE release. Keyword list: FI-WARE, Generic Enabler, Bigdata, Context, Events, Semantic Web, Multimedia. Contents BigData Analysis - User and Programmer Guide 2 CEP - User and Programmer Guide 89 Location Platform - User and Programmer Guide 90 Multimedia Analysis - User and Programmer Guide 95 Query Broker - User and Programmer Guide 105 Semantic Annotation - Users and Programmers Guide 110 Semantic Application Support - Users and Programmers Guide 113 BigData Analysis - User and Programmer Guide 2 BigData Analysis - User and Programmer Guide Introduction This guide covers the user and development aspects of the SAMSON platform, version 0.6.1. The SAMSON platform has been designed for the processing of large amounts of data, in continuous mode (streaming), distributing tasks in a medium-size cluster of computers, following the MapReduce paradigm Jeffrey Dean and Sanjay Ghemawat. “MapReduce: Simplified data processing on large clusters” [1]. The platform provides the necessary framework to allow a developer to focus on solving analytical problems without needing to know how distribute jobs and data, and their synchronization.
  • INFOCOMP / Datasys 2017 International Expert Panel: Challenges on Web Semantic Mapping and Information Processing

    INFOCOMP / Datasys 2017 International Expert Panel: Challenges on Web Semantic Mapping and Information Processing

    INFOCOMP / DataSys 2017 International Expert Panel: Challenges on Web Semantic Mapping and Information Processing INFOCOMP / DataSys 2017 International Expert Panel: Challenges on Web Semantic Mapping and Information Processing June 28, 2017, Venice, Italy The Seventh International Conference on Advanced Communications and Computation (INFOCOMP 2017) The Seventh International Conference on Advances in Information Mining and Management (IMMM 2017) The Twelfth International Conference on Internet and Web Applications and Services (ICIW 2017) INFOCOMP/IMMM/ICIW (DataSys) June 25{29, 2017 - Venice, Italy INFOCOMP, June 25 { 29, 2017 - Venice, Italy INFOCOMP / DataSys 2017 International Expert Panel: Challenges on Web Semantic Mapping and Information Processing INFOCOMP / DataSys 2017 International Expert Panel: Challenges on Web Semantic Mapping and Information Processing INFOCOMP Expert Panel: Web Semantic Mapping & Information Proc. INFOCOMP Expert Panel: Web Semantic Mapping & Information Proc. Panelists Claus-Peter R¨uckemann (Moderator), Westf¨alischeWilhelms-Universit¨atM¨unster(WWU) / Leibniz Universit¨atHannover / North-German Supercomputing Alliance (HLRN), Germany Marc Jansen, University of Applied Sciences Ruhr West, Deutschland Fahad Muhammad, CSTB, Sophia Antipolis, France Kiyoshi Nagata, Daito Bunka University, Japan Claus-Peter R¨uckemann, WWU M¨unster/ Leibniz Universit¨atHannover / HLRN, Germany INFOCOMP 2017: http://www.iaria.org/conferences2017/INFOCOMP17.html Program: http://www.iaria.org/conferences2017/ProgramINFOCOMP17.html
  • Thinking Outside the Tbox

    Thinking Outside the Tbox

    Thinking Outside the TBox Multiparty Service Matchmaking as Information Retrieval David J. Lambert School of Informatics University of Edinburgh I V N E R U S E I T H Y T O H F G E R D I N B U Doctor of Philosophy Centre for Intelligent Systems and their Applications School of Informatics University of Edinburgh 2009 Abstract Service oriented computing is crucial to a large and growing number of computational undertakings. Central to its approach are the open and network-accessible services provided by many different organisations, and which in turn enable the easy creation of composite workflows. This leads to an environment containing many thousands of services, in which a programmer or automated composition system must discover and select services appropriate for the task at hand. This discovery and selection process is known as matchmaking. Prior work in the field has conceived the problem as one of sufficiently describing individual services using formal, symbolic knowledge representation languages. We review the prior work, and present arguments for why it is optimistic to assume that this approach will be adequate by itself. With these issues in mind, we examine how, by reformulating the task and giving the matchmaker a record of prior service performance, we can alleviate some of the problems. Using two formalisms—the incidence calculus and the lightweight coordination calculus—along with algorithms inspired by information retrieval techniques, we evolve a series of simple matchmaking agents that learn from experience how to select those services which performed well in the past, while making minimal demands on the service users.
  • The Resource Description Framework and Its Schema Fabien Gandon, Reto Krummenacher, Sung-Kook Han, Ioan Toma

    The Resource Description Framework and Its Schema Fabien Gandon, Reto Krummenacher, Sung-Kook Han, Ioan Toma

    The Resource Description Framework and its Schema Fabien Gandon, Reto Krummenacher, Sung-Kook Han, Ioan Toma To cite this version: Fabien Gandon, Reto Krummenacher, Sung-Kook Han, Ioan Toma. The Resource Description Frame- work and its Schema. Handbook of Semantic Web Technologies, 2011, 978-3-540-92912-3. hal- 01171045 HAL Id: hal-01171045 https://hal.inria.fr/hal-01171045 Submitted on 2 Jul 2015 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. The Resource Description Framework and its Schema Fabien L. Gandon, INRIA Sophia Antipolis Reto Krummenacher, STI Innsbruck Sung-Kook Han, STI Innsbruck Ioan Toma, STI Innsbruck 1. Abstract RDF is a framework to publish statements on the web about anything. It allows anyone to describe resources, in particular Web resources, such as the author, creation date, subject, and copyright of an image. Any information portal or data-based web site can be interested in using the graph model of RDF to open its silos of data about persons, documents, events, products, services, places etc. RDF reuses the web approach to identify resources (URI) and to allow one to explicitly represent any relationship between two resources.
  • Report of the Committee on Data Management

    Report of the Committee on Data Management

    REPORT OF THE COMMITTEE ON DATA MANAGEMENT GOVERNMENT OF INDIA NATIONAL STATISTICAL COMMISSION MINISTRY OF STATISTICS AND PROGRAMME IMPLEMENTATION NEW DELHI CONTENTS Page Number Constitution, Terms of Reference and Members‘ List (i) Acknowledgements (vii) List of Abbreviations (ix) Introduction, Executive Summary, and Main observations (xviii) Chapter - 1 Indian Statistical system, Challenges in Official Statistics & data management and remedial measures 1. The importance of official statistics 1 2. Current scenario of National Statistical System in India 3 3. Need to know and right to share 4 4. Issues of decentralized system 5 5. Vertical and horizontal issues 7 6. Priority 9 7. Inter operability 9 8. Need for assessability and communicability 10 9. Need for scanning of published data before conversion into defined data format 11 10. Non-official data providers 12 11. Consistency in definition and standards 13 12. Draw upon insights into problems 13 13. Technological and technical issues 15 14. Training intervention/ capacity building 17 15. Technology versus Applications 19 16. Legal framework for providing data 19 17. Setting up of Data Management Division 20 Chapter - 2 Conceptual framework on Data management 1. Data Management 22 2. Data governance 25 3. Data Architecture, Analysis and Design 26 4. Database Management 29 5. Data Security Management 30 6. Data Quality Management 32 7. Reference and Master Data Management 34 8. Data Warehousing and Business Intelligence Management 36 9. Document, Record and Content Management 39 10. Meta Data Management 40 11. Contact Data Management 42 12. Data Movement 44 13. Statistical Data Metadata Exchange (SDMX) 44 14. Secured Data Centers 46 Chapter -3 Recommendations: 1.
  • Guidelines for Publishing Structured Metadata on the Web

    Guidelines for Publishing Structured Metadata on the Web

    Final Report Research Data Alliance Research Metadata Schemas Working Group Guidelines for publishing structured metadata on the web 15 June 2021, V3.0 Mingfang Wu, Nick Juty, RDA Research Metadata Schemas WG, Julia Collins, Ruth Duerr, Chantel Ridsdale, Adam Shepherd, Chantelle Verhey, Leyla Jael Castro Creative Commons Attribution Only 4.0 license (CC-BY) RDA Research Metadata Schemas Working Group Table of Contents Executive Summary ................................................................................................................... 1 Terminology ............................................................................................................................... 2 1. Introduction ......................................................................................................................... 4 2. Process to publish structured metadata .............................................................................. 6 3. Data model ......................................................................................................................... 7 4. Recommendations .............................................................................................................. 9 Recommendation 1: Clarify the purpose(s) of your markup (or why you want to markup your data) ......................................................................................................................................10 Recommendation 2: Identify what resources are to be marked up with structured data .........11 Recommendation
  • Metadata in the Context of the European Library Project

    Metadata in the Context of the European Library Project

    DC-2002: METADATA FOR E-COMMUNITIES: SUPPORTING DIVERSITY AND CONVERGENCE 2002 Proceedings of the International Conference on Dublin Core and Metadata for e-Communities, 2002 October 13-17, 2002 - Florence, Italy Organized by: Associazione Italiana Biblioteche (AIB) Biblioteca Nazionale Centrale di Firenze (BNCF) Dublin Core Metadata Initiative (DCMI) European University Institute (IUE) Istituto e Museo di Storia della Scienza (IMSS) Regione Toscana Università degli Studi di Firenze DC-2002 : metadata for e-communities : supporting diversity and con- vergence 2002 : proceedings of the International Conference on Dublin Core and Metadata for E-communities, 2002, October 13-17, 2002, Florence, Italy / organized by Associazione italiana biblioteche (AIB) … [at al.]. – Firenze : Firenze University Press, 2002. http://epress.unifi.it/ ISBN 88-8453-043-1 025.344 (ed. 20) Dublin Core – Congresses Cataloging of computer network resources - Congresses Print on demand is available © 2002 Firenze University Press Firenze University Press Borgo Albizi, 28 50122 Firenze, Italy http://epress.unifi.it/ Printed in Italy Proc. Int. Conf. on Dublin Core and Metadata for e-Communities 2002 © Firenze University Press DC-2002: Metadata for e-Communities: Supporting Diversity and Convergence DC-2002 marks the tenth in the ongoing series of International Dublin Core Workshops, and the second that includes a full program of tutorials and peer-reviewed conference papers. Interest in Dublin Core metadata has grown from a small collection of pioneering projects to adoption by governments and international organ- izations worldwide. The scope of interest and investment in metadata is broader still, however, and finding coherence in this rapidly growing area is challenging. The theme of DC-2002 — supporting diversity and convergence — acknowledges these changes.
  • D2.2 Specification Shopping

    D2.2 Specification Shopping

    Contract No. H2020 – 636078 INFORMATION TECHNOLOGIES FOR SHIFT TO RAIL D1.6 – Proof-of-Concept Packaged Resolvers Core Features Due date of deliverable: 31/08/2016 Actual submission date: 13/12/2016 Leader Deliverable: Mariotta Guido (LEONARDO) Reviewed: Y Document status Revision Date Description 1 12/12/2016 Reviewed by TRENITALIA 2 13/12/2016 Final version after TMC approval Project funded from the European Union’s Horizon 2020 research and innovation program Dissemination Level PU Public X CO Confidential, restricted under conditions set out in Model Grant Agreement CI Classified, information as referred to in Commission Decision 2001/844/EC Start date of project: 01/05/2015 Duration: 30 months ITR-WP1-D-FIN-026-02 Page 1 of 68 13/12/2016 Contract No. H2020 – 636078 INTRODUCTION Chapters 1 through 8 of this document describe the purpose, design drivers, use cases, provided capabilities, logical function sequences, components and interfaces of the IT2Rail Interoperability Framework. Chapter 9 documents the implementation of the core release (CREL) features of the design, namely: 1. The IT2Rail rdf-framework foundation framework for processing data expressed in the Resource Descriptor Framework (RDF) language, semantically annotated with terms described in the domain’s ontology, the latter written in the Ontology Web Language (OWL). The framework provides additionally connectivity to distributed triple stores, including the IT2Rail triple store that implements the Ontology Repository, containing the OWL ontology, and the Semantic Web Service Registry containing service descriptors also represented as RDF statements. 2. The Semantic Graph Manager component of the design, based on the IT2Rail rdf framework, which provides semantic data discovery, query an aggregation over linked, distributed triple stores.
  • Metadata Management Services for Spatial Data Infrastructure - a Case Study of a User-Centric Implementation Strategy for an Academic Institution

    Metadata Management Services for Spatial Data Infrastructure - a Case Study of a User-Centric Implementation Strategy for an Academic Institution

    MASTERARBEIT Titel der Masterarbeit Metadata Management Services for Spatial Data Infrastructure - A Case Study of a User-centric Implementation Strategy for an Academic Institution Verfasser Mag. Peter Lanz angestrebter akademischer Grad Master of Science (MSc) Wien, 2011 Studienkennzahl lt. Studienblatt: A 066 856 Studienrichtung lt. Studienblatt : Master Kartographie und Geoinformation Betreuerin: Prof. Dr. Tobia Lakes 2 Metadata Management Services for Spatial Data Infrastructure Metadata Management Services for Spatial Data Infrastructure 3 CONTENTS CONTENTS...................................................................................................................................... 3 LIST OF FIGURES ............................................................................................................................. 6 LIST OF TABLES ............................................................................................................................... 7 GLOSSARY ...................................................................................................................................... 8 ZUSAMMENFASSUNG....................................................................................................................10 ABSTRACT .....................................................................................................................................12 ACKNOWLEDGEMENT ...................................................................................................................14 1. INTRODUCTION
  • (Semantic) Web

    (Semantic) Web

    KBS Development on the (Semantic) Web David Corsar and Derek Sleeman Department of Computing Science, University of Aberdeen Aberdeen, UK {dcorsar, d.sleeman}@abdn.ac.uk Abstract out reference to any other particular component; repositories were developed for each type of component and were re- The benefits of reuse have long been recognized in the sponsible for the storage and provision of different examples knowledge engineering community where the dream of creating knowledge based systems (KBSs) on-the-fly of each of these components. In theory, to develop a new from libraries of reusable components is still to be fully KBS, the knowledge engineer or an automated agent sim- realised. In this paper we present a two stage methodol- ply selects the appropriate components for their task (from ogy for creating KBSs: first reusing domain knowledge repositories) and configures them to work together. Con- by mapping it, where appropriate, to the requirements figuration was often simply viewed as a mapping process: of a generic problem solver; and secondly using this for example, for a PSM to work with a particular domain mapped knowledge and the requirements of the prob- ontology, mappings would be defined between the two: the lem solver to “drive” the acquisition of the additional mappings would allow the PSM to access and use the do- knowledge it needs. For example, suppose we have main knowledge provided by the domain ontology during available a KBS which is composed of a propose-and- the PSM’s execution. Despite considerable research focused revise problem solver linked with an appropriate knowl- edge base/ontology from the elevator domain.
  • Semantic Web Services SS 2018

    Semantic Web Services SS 2018

    4/23/2018 Semantic Web Services SS 2018 Semantic Web Anna Fensel 23.04.2018 © Copyright 2010‐2018 Dieter Fensel, Ioan Toma, and Anna Fensel 1 Where are we? # Title 1 Introduction 2 Web Science + Cathy O’Neil’s talk: “Weapons of Math Destruction” 3 Service Science 4 Web services 5 Web2.0 services + ONLIM APIs (separate slideset) 6 Semantic Web 7 Semantic Web Service Stack (WSMO, WSML, WSMX) 8 OWL-S and the others 9 Semantic Services as a Part of the Future Internet and Big Data Technology 10 Lightweight Annotations 11 Linked Services 12 Applications 13 Mobile Services 2 1 4/23/2018 Agenda 1. Motivation 1. Development of the Web 1. Internet 2. Web 1.0 3. Web2.0 2. Limitations of the current Web 2. Technical solution 1. Introduction to Semantic Web 2. Architecture and languages 3. Semantic Web - Data 4. Extensions 1. Linked (Open) Data 2. Schema.org 3. LOV 5. Summary 6. References 3 MOTIVATION 4 2 4/23/2018 DEVELOPMENT OF THE WEB 5 Development of the Web 1. Internet 2. Web 1.0 3. Web 2.0 6 3 4/23/2018 INTERNET 7 Internet • “The Internet is a global system of interconnected computer networks that use the standard Internet Protocol Suite (TCP/IP) to serve billions of users worldwide. It is a network of networks that consists of millions of private and public, academic, business, and government networks of local to global scope that are linked by a broad array of electronic and optical networking technologies.” http://en.wikipedia.org/wiki/Internet 8 4 4/23/2018 A brief summary of Internet evolution Age of eCommerce Mosaic Begins WWW Internet Created 1995 Created 1993 Named 1989 and Goes TCP/IP TCP/IP Created 1984 ARPANET 1972 1969 Hypertext Invented Packet 1965 Switching First Vast Invented Computer 1964 Network Silicon Envisioned A Chip 1962 Mathematical 1958 Theory of Memex Communication Conceived 1948 1945 1945 1995 Source: http://slidewiki.org/slide/24721 9 WEB 1.0 10 5 4/23/2018 Web 1.0 • “The World Wide Web ("WWW" or simply the "Web") is a system of interlinked, hypertext documents that runs over the Internet.
  • Semantic Web Service Selection Based on Service Provider's

    Semantic Web Service Selection Based on Service Provider's

    D A D’Mello et al: SEMANTIC WEB SERVICE SELECTION BASED ON BUSINESS OFFERINGS Semantic Web Service Selection Based on Service Provider’s Business Offerings Demian Antony D’Mello V.S. Ananthanarayana Department of Computer Science and Engineering Department of Information Technology St. Joseph Engineering College, Mangalore National Institute of Technology Karnataka Karnataka, INDIA – 575 028 SrinivasNagar, INDIA – 575 025 e-mail: [email protected] e-mail: [email protected] Abstract—Semantic Web service discovery finds a match between the service requirement and service advertisements based on the semantic descriptions. The matchmaking mechanism might find semantically similar Web services having same matching score. In this paper, the authors propose the semantic Web service selection mechanism which distinguishes semantically similar Web services based on the Quality of Service (QoS) and Business Offerings (BO). To realize the semantic Web service discovery and selection (ranking), we propose the semantic broker based Web service architecture which recommends the best match for the requester based on the requested functionality, quality and business offerings. The authors design the semantic broker which facilitates the provider to advertise the service by creating OWL-S service profile consisting information related to functionality, quality and business offerings. After the service advertisement, the broker computes and records matchmaking information to improve the performance (service query time) of discovery and selection process. The broker also reads requirements from the requester and finds the best (profitable) Web service by matching and ranking the advertised services based on the functionality, capability, quality and business offering. Keywords-Semantic broker, Service selection, Quality of Service, Business offering, Ontology I.