The Role of Schema.Org in a Semantic Model of Library Resources
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Applications
Applications CSE 595 – Semantic Web Instructor: Dr. Paul Fodor Stony Brook University http://www3.cs.stonybrook.edu/~pfodor/courses/cse595.html GoodRelations BBC Artists BBC World Cup Website Lecture Outline Government Data New York Times Sig.ma and Sindice Swoogle OpenCalais Schema.org data.world Elsevier Audi Data Integration Swiss Life EnerSearch E-Learning Web Services Multimedia Collection Indexing at Scotland Yard Online Procurement at Daimler Device Interoperability at Nokia 2 Publication Management @ Semantic Web Primer GoodRelations E-commerce, and in particular Business-to-Consumer (B2C) e- commerce, has been one of the main drivers behind the rapid adoption of the World Wide Web in everyday live It is now commonplace to see URLs listed on storefronts and goods vehicles Taking the UK as an example, the B2C market has grown from £87 million in April 2000 to £68.4 billion by the end of 2009, a thousand-fold increase over a single decade USA 2017 B2C market was $660 billion, but the growth is decreasing 3 statista.com @ Semantic Web Primer GoodRelations E-commerce marketplace is suffering from all the deficits of the traditional web: E-commerce websites are typically generated from structured information systems, listing price, availability, type of product, delivery options, etc., but by the time this information reaches the company’s web pages, it has been turned into HTML and all machine-interpretable structure has disappeared, with the result that machines can no longer distinguish a price from a product-code -
Product Schema, SEO, Structured Data | Caliber Media Group & Schema.Org Products | Product Schema | SEO
ProductCamp: Product Schema, SEO, Structured Data | Caliber Media Group & Schema.org Products | Product Schema | SEO Caliber Media Group presented at Product Camp Southern California 2014, and Caliber also volunteered its services towards this conference’s success. Caliber Media Group ProductCamp: Product Schema, SEO, Structured Data | Caliber Media Group & Schema.org Products | Schema | Examples Resources | Tools | Readings 2 ProductCamp SoCal 2014 & Schema: Google, after Schema ProductCamp SoCal 2014 & Schema: Google via Disconnect & Yahoo, after Schema , ProductCamp SoCal 2014 & Schema: How did Caliber help ProductCamp beat all of the other events? ProductCamp SoCal 2014 & Schema: So what was inside the pages? ProductCamp SoCal 2014 & Schema: So what was inside the pages? ProductCamp SoCal 2014 & Schema: So what was inside the pages? Search => Schema, with JSON-LD Search & Schema: When & Who? Very short version… Martin Hepp http://www.heppnetz.de/projects/goodrelations/ ProductCamp SoCal 2014 & Schema: When & Who? Short version…here they come… ProductCamp SoCal 2014 & Schema: GoodRelations added… Search & Schema: Why, and… What does Schema do for me? http://www.schema.org ProductCamp SoCal 2014 & Schema: Product since this is ProductCamp http://schema.org/Product ProductCamp SoCal 2014 & Schema: An actual Product, since this is ProductCamp… ProductCamp SoCal 2014 & Schema: Recall, Products as Structured Data Structure -- Hierarchy -- Structured Data Search & Schema: Show me Schema examples… Schema: Product ontology | microdata | Knowledge Graph ProductCamp SoCal 2014 & Schema: Product ProductCamp SoCal 2014 & Schema: Google ProductCamp SoCal 2014 & Schema: Product Schema locally ProductCamp SoCal 2014 & Schema: Product locally ProductCamp SoCal 2014 & Schema: Local Schema gone wild… Search & Product Schema | Knowledge Graph from Google Knowledge Vault – where? Search & Product Schema | Knowledge Graph – where? Google Tables. -
Poolparty Semantic Suite Functional Overview
PoolParty Semantic Suite Functional Overview Andreas Blumauer CEO & Managing Partner Semantic Web Company / PoolParty Semantic Suite 2 Semantic Web Company (SWC) ▸ Founded in 2004, based in Vienna ▸ Privately held 3 ▸ 50 FTE ▸ Software Engineers & Consultants for Introducing NLP, Semantics and Machine learning Semantic Semantic Web AI ▸ Developer & Vendor of Company PoolParty Semantic Suite ▸ Participating in projects with €2.5 million funding for R&D ▸ ~30% revenue growth/year ▸ SWC named to KMWorld’s ‘100 Companies That Matter in Knowledge Management’ in 2016, 2017 and 2018 ▸ www.semantic-web.com 2017 2016 PoolParty Semantic Suite ▸ Most complete Semantic Middleware on the Global Market ▸ Semantic AI: Fusion of Knowledge 4 Graphs, NLP, and Machine Learning ▸ W3C standards compliant Fact sheet: PoolParty ▸ First release in 2009 ▸ Current version 7.0 ▸ On-premises or cloud-based ▸ Over 200 installations world-wide ▸ Named as Sample Vendor in Gartner’s Hype Cycle for AI 2018 ▸ KMWorld listed PoolParty as Trend-Setting Product 2015, 2016, 2017, and 2018 ▸ www.poolparty.biz We work with Global Fortune Companies, and with some of the largest GOs and NGOs from over 20 countries. SWC head- US UK quarters West US Selected Customer References East 5 ● Credit Suisse ● Boehringer Ingelheim Selected ● Roche ● adidas Customer ● The Pokémon Company ● Fluor AUS/ References ● Harvard Business School NZL ● Wolters Kluwer and Partners ● Philips ● Nestlé ● Electronic Arts Selected Partners ● Springer Nature ● Pearson - Always Learning ● Enterprise Knowledge ● Healthdirect Australia ● Mekon Intelligent Content Solutions ● World Bank Group ● Soitron ● Canadian Broadcasting Corporation ● Accenture ● Oxford University Press ● EPAM Systems ● International Atomic Energy Agency ● BAON Enterprises ● Siemens ● Findwise ● Singapore Academy of Law ● Tellura Semantics ● Inter-American Development Bank ● HPC ● Council of the E.U. -
Semantic Technologies for Systems Engineering (ST4SE)
Semantic Technologies for Systems Engineering (ST4SE) Update at INCOSE IW, 27 Jan 2019, Torrance, CA, USA Hans Peter de Koning European Space Agency, ESA/ESTEC, Noordwijk, The Netherlands Based on earlier presentations and contributions by other ST4SE Core Team Members Objectives of the ST4SE Foundation To promote and champion the open-source development and utilization of ontologies and semantic technologies to support system engineering practice, education, and research 1. Provide a semantically rich language to communicate among systems engineers and other stakeholders 2. Define patterns that can be used to check for consistency and completeness 3. Support querying of information from model 4. Focus on adding value by balancing the expected benefits from being formal and the cost of being formal ST4SE Update | INCOSE IW | 2019-01-27, Torrance, CA, USA 2 MBSE Challenge – 3 Kinds of Communication . Person ↔ Person . Machine ↔ Machine . Person ↔ Machine Person . All bi-directional (of course) . All need to work flawlessly Machine ST4SE Update | INCOSE IW | 2019-01-27, Torrance, CA, USA 3 Outline . Background on Semantic Technologies • Knowledge representation, reasoning, querying . Semantic Technologies for System Engineering • Motivation • Scope and focus • Relationship between ST4SE and SysML 2.0 . ST4SE Approach • Open-source foundation • Bootstrapping: (best) practices for defining, demonstrating and documenting patterns ST4SE Update | INCOSE IW | 2019-01-27, Torrance, CA, USA 4 Increasing levels of semantic precision (and understanding -
The Application of Semantic Web Technologies to Content Analysis in Sociology
THEAPPLICATIONOFSEMANTICWEBTECHNOLOGIESTO CONTENTANALYSISINSOCIOLOGY MASTER THESIS tabea tietz Matrikelnummer: 749153 Faculty of Economics and Social Science University of Potsdam Erstgutachter: Alexander Knoth, M.A. Zweitgutachter: Prof. Dr. rer. nat. Harald Sack Potsdam, August 2018 Tabea Tietz: The Application of Semantic Web Technologies to Content Analysis in Soci- ology, , © August 2018 ABSTRACT In sociology, texts are understood as social phenomena and provide means to an- alyze social reality. Throughout the years, a broad range of techniques evolved to perform such analysis, qualitative and quantitative approaches as well as com- pletely manual analyses and computer-assisted methods. The development of the World Wide Web and social media as well as technical developments like optical character recognition and automated speech recognition contributed to the enor- mous increase of text available for analysis. This also led sociologists to rely more on computer-assisted approaches for their text analysis and included statistical Natural Language Processing (NLP) techniques. A variety of techniques, tools and use cases developed, which lack an overall uniform way of standardizing these approaches. Furthermore, this problem is coupled with a lack of standards for reporting studies with regards to text analysis in sociology. Semantic Web and Linked Data provide a variety of standards to represent information and knowl- edge. Numerous applications make use of these standards, including possibilities to publish data and to perform Named Entity Linking, a specific branch of NLP. This thesis attempts to discuss the question to which extend the standards and tools provided by the Semantic Web and Linked Data community may support computer-assisted text analysis in sociology. First, these said tools and standards will be briefly introduced and then applied to the use case of constitutional texts of the Netherlands from 1884 to 2016. -
Semantic Science: Ontologies, Data and Probabilistic Theories
Semantic Science: Ontologies, Data and Probabilistic Theories David Poole1, Clinton Smyth2, and Rita Sharma2 1 Department of Computer Science, University of British Columbia http://www.cs.ubc.ca/spider/poole/ 2 Georeference Online Ltd., http://www.georeferenceonline.com/ Abstract. This chapter overviews work on semantic science. The idea is that, using rich ontologies, both observational data and theories that make (probabilistic) predictions on data are published for the purposes of improving or comparing the theories, and for making predictions in new cases. This paper concentrates on issues and progress in having machine accessible scientific theories that can be used in this way. This paper presents the grand vision, issues that have arisen in building such systems for the geological domain (minerals exploration and geohazards), and sketches the formal foundations that underlie this vision. The aim is to get to the stage where: any new scientific theory can be tested on all available data; any new data can be used to evaluate all existing theories that make predictions on that data; and when someone has a new case they can use the best theories that make predictions on that case. 1 Introduction The aim of the semantic web (Berners-Lee and Fischetti, 1999; Berners-Lee et al., 2001) is that the world's information is available in a machine-understandable form. This chapter overviews what we call semantic science, the application of semantic technology and reasoning under uncertainty to the practice of science. Semantic science requires machine-understandable information of three sorts: on- tologies to define vocabulary, data about observations of the world, and theories that make predictions on such data. -
Usage of Ontologies and Software Agents for Knowledge-Based Design of Mechatronic Systems
INTERNATIONAL CONFERENCE ON ENGINEERING DESIGN, ICED’07 28 - 31 AUGUST 2007, CITE DES SCIENCES ET DE L'INDUSTRIE, PARIS, FRANCE USAGE OF ONTOLOGIES AND SOFTWARE AGENTS FOR KNOWLEDGE-BASED DESIGN OF MECHATRONIC SYSTEMS Ewald G. Welp1, Patrick Labenda1 and Christian Bludau2 1Ruhr-University Bochum, Germany 2Behr-Hella Thermocontrol GmbH, Lippstadt, Germany ABSTRACT Already in [1, 2 and 3] the newly developed Semantic Web Service Platform SEMEC (SEMantic and MEChatronics) has been introduced and explained. It forms an interconnection between semantic web, semantic web services and software agents, offering tools and methods for a knowledge-based design of mechatronic systems. Their development is complex and connected to a high information and knowledge need on the part of the engineers involved in it. Most of the tools nowadays available cannot meet this need to an adequate degree and in the demanded quality. The developed platform focuses on the design of mechatronic products supported by Semantic web services under use of the Semantic web as a dynamic and natural language knowledge base. The platform itself can also be deployed for the development of homogenous, i.e. mechanical and electronical systems. Of special scientific interest is the connection to the internet and semantic web, respectively, and its utilization within a development process. The platform can be used to support interdisciplinary design teams at an early phase in the development process by offering context- sensitive knowledge and by this to concretize as well as improve mechatronic concepts [1]. Essential components of this platform are a design environment, a domain ontology mechatronics as well as a software agent. -
Designing an Ontology for Managing the Diets of Hypertensive Individuals
Designing an Ontology for Managing the Diets of Hypertensive Individuals A thesis submitted to the College of Communication and Information of Kent State University in partial fulfillment of the requirements for the Master of Library and Information Science and Master of Science dual degree program By Julaine Clunis January, 2016 Thesis Written By Julaine Clunis BSc., Northern Caribbean University, 2005 M.L.I.S., Kent State University, 2016 M.S., Kent State University, 2016 Approved By ___________________________________________ Marcia Lei Zeng, Advisor ___________________________________________ Jeffrey W. Fruit, Director, School of Library and Information Science ___________________________________________ Amy Reynolds, Dean, College of Communication and Information Table of Contents List of Figures ................................................................................................................................ v List of Tables ............................................................................................................................... vii List of Acronyms and Abbreviations ....................................................................................... viii Glossary of Terms ......................................................................................................................... x Terms Relating to Health and Medicine ............................................................................................. xii Acknowledgements ................................................................................................................... -
Building Semantic Enterprise Architecture Solutions with Topbraid Suite™
Towards Executable Enterprise Models: Building Semantic Enterprise Architecture Solutions with TopBraid Suite™ Towards Executable Enterprise Models: Building Semantic Enterprise Architecture Solutions with TopBraid Suite™ What is Enterprise Architecture and Why is it Important to Business? Enterprise Architecture (EA) captures “what is happening” in the enterprise: how the enterprise’s activities, processes, capabilities, systems and components, information resources and technologies relate to the enterprise’s missions, goals and measurement system. To do this, EA expresses the interrelated structure of an enterprise’s processes, capabilities systems, information resources and technology dependencies. The objective of EA is to be able to understand the relationships between these elements; analyze and continuously adjust them for alignment with the business strategy, improved effectiveness and quality of service. When a Business Executive asks "what is an enterprise architecture and why is it useful?" a typical answer is “a model of how the enterprise works.” Useful, because it explains how business activities and processes use capabilities; how capabilities map to competencies and IT systems; how systems depend on technologies; and, how value is generated with measurable results that realize business goals. Increasingly, the demands of modern enterprises to both optimize their day to day operations and develop strategic capabilities and resources in their organizations, processes and infrastructures are driving the need for higher levels of Enterprise Architecture (EA) solutions. EA has emerged from a pure IT discipline to an embedded business tool that can focus on business-centered capability management. To support the business needs of complex, distributed enterprises, Enterprise Architecture practice and enabling technology/tools are evolving from Reference-only (text, models) to Interoperable (standards based) to Executable (federated, model-based, semantic-enabled). -
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]. -
Oracle Database Semantic Technologies Overview
<Insert Picture Here> Oracle Database Semantic Technologies Overview 1 Oracle Semantic Technologies Agenda • Semantic technologies for the enterprise • Why use Oracle Database as a semantic data store • Customer examples • Features Overview 2 Semantic Technologies for the Enterprise • Designed to represent knowledge in a distributed world • A method to decompose knowledge into small pieces, with rules about the semantics of those pieces • RDF data is self-describing; it “means” something • Allows you to model and integrate DBMS schemas • Allows you to integrate data from different sources without custom programming • Supports decentralized data management • Infer implicit relationships across data This presentation on Oracle Spatial 11g semantic technologies assumes some knowledge of basic principles of semantics. Semantic technologies provide a metadata repository to access other data •Semantics abstracts unstructured content by extracting meaning from entities in underlying data and structuring it so it can be queried in a meaningful way •RDF (Resource Description Framework) is the standard for encoding this metadata into a flexible triples data model (subject- object –predicate) •RDF can also be used to model and integrate relational data •So RDF can be used to describe relationships across a variety of data sources w/o custom programming •RDF allows you to manage metadata models centrally w/o bringing all of the data into one place •RDF Schema & OWL takes an RDF store to the next level with the ability to create inferences or new -
Introduction of Semantic Technology for SAS® Programmers Kevin Lee, Clindata Insight, Moraga, CA
PharmaSUG 2016 – Paper IB02 Introduction of Semantic Technology for SAS® programmers Kevin Lee, Clindata Insight, Moraga, CA ABSTRACT There is a new technology to express and search the data that can provide more meaning and relationship – semantic technology. The semantic technology can easily add, change and implement the meaning and relationship to the current data. Companies such as Facebook and Google are currently using the semantic technology. For example, Facebook Graph Search use semantic technology to enhance more meaningful search for users. The paper will introduce the basic concepts of semantic technology and its graph data model, Resource Description Framework (RDF). RDF can link data elements in a self-describing way with elements and property: subject, predicate and object. The paper will introduce the application and examples of RDF elements. The paper will also introduce three different representation of RDF: RDF/XML representation, turtle representation and N-triple representation. The paper will also introduce “CDISC standards RDF representation, Reference and Review Guide” published by CDISC and PhUSE CSS. The paper will discuss RDF representation, reference and review guide and show how CDISC standards are represented and displayed in RDF format. The paper will also introduce Simple Protocol RDF Query Language (SPARQL) that can retrieve and manipulate data in RDF format. The paper will show how programmers can use SPARQL to re-represent RDF format of CDISC standards metadata into structured tabular format. Finally, paper will discuss the benefits and futures of semantic technology. The paper will also discuss what semantic technology means to SAS programmers and how programmers take an advantage of this new technology.