The term “Linked Data” refers to a set of best practices for publishing and connecting structured data on the Web. These best practices have been adopted by an increasing number of data providers over the last three years, leading to the creation of a global data space containing billions of assertions— the Web of Data. In this article, the authors present the concept and technical principles of Linked Data, and situate these within the broader context of related technological developments. They describe progress to date in publishing Linked Data on the Web, review applications that have been developed to exploit the Web of Data, and map out a research agenda for the Linked Data community as it moves forward.

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Linked Data - the story so far

The World Wide Web has enabled the creation of a global information space comprising linked documents. As the Web becomes ever more enmeshed with our daily lives, there is a growing desire for direct access to raw data not currently available on the Web or bound up in hypertext documents. Linked Data provides a publishing paradigm in which not only documents, but also data, can be a first class citizen of the Web, thereby enabling the extension of the Web with a global data space based on open standards - the Web of Data. In this Synthesis lecture we provide readers with a detailed technical introduction to Linked Data. We begin by outlining the basic principles of Linked Data, including coverage of relevant aspects of Web architecture. The remainder of the text is based around two main themes - the publication and consumption of Linked Data. Drawing on a practical Linked Data scenario, we provide guidance and best practices on: architectural approaches to publishing Linked Data; choosing URIs and vocabularies to identify and describe resources; deciding what data to return in a description of a resource on the Web; methods and frameworks for automated linking of data sets; and testing and debugging approaches for Linked Data deployments. We give an overview of existing Linked Data applications and then examine the architectures that are used to consume Linked Data from the Web, alongside existing tools and frameworks that enable these. Readers can expect to gain a rich technical understanding of Linked Data fundamentals, as the basis for application development, research or further study.

Linked Data: Evolving the Web into a Global Data Space

The Resource Description Framework (RDF) is the standard knowledge representation language for the Semantic Web, an evolution of the World Wide Web that aims to provide a well-founded infrastructure for publishing, sharing and querying structured data. This article provides an introduction to RDF and its related vocabulary definition language RDF Schema, and explains its relationship with the OWL Web Ontology Language. Finally, it provides an overview of the historical development of RDF and related languages for Web metadata.

Resource Description Framework (RDF)

Semantic Web models and technologies provide information in machine-readable languages that enable computers to access the Web more intelligently and perform tasks automatically without the direction of users. These technologies are relatively recent and advancing rapidly, creating a set of unique challenges for those developing applications. 

Semantic Web for the Working Ontologist is the essential, comprehensive resource on semantic modeling, for practitioners in health care, artificial intelligence, finance, engineering, military intelligence, enterprise architecture, and more. Focused on developing useful and reusable models, this market-leading book explains how to build semantic content (ontologies) and how to build applications that access that content.

New in this edition: 


Coverage of the latest Semantic Web tools for organizing, querying, and processing information - see details in TOC below

Detailed information on the latest ontologies used in key web applications including ecommerce, social networking, data mining, using government data, and more




Updated with the latest developments and advances in Semantic Web technologies for organizing, querying, and processing information, including SPARQL, RDF and RDFS, OWL 2.0, and SKOS 
Detailed information on the ontologies used in today's key web applications, including ecommerce, social networking, data mining, using government data, and more 
Even more illustrative examples and case studies that demonstrate what semantic technologies are and how they work together to solve real-world problems

Table of Contents

1?What Is The Semantic Web?
2?Semantic Modeling
3?RDF - The Basis of the Semantic Web
4?SPARQL - The Query Language for RDF
5?Semantic Web Application Architecture
6?RDF And Inferencing
7?RDF Schema Language
8?RDFS-Plus
9?SKOS - the Simple Knowledge Organization System
10?Ontologies in the Wild: Linked Open Data and the Open Graph Project
11?Basic OWL
12?Counting and Sets In OWL 
13?MORE Ontologies in the Wild: QUDT, GoodRelations, and OBO Foundry
14?Good and Bad Modeling Practices 
15?OWL 2.0 Levels and Logic
16?Conclusions
17?Frequently Asked Questions

Semantic Web for the Working Ontologist: Effective Modeling in RDFS and OWL

Information extraction (IE) aims to retrieve certain types of information from natural language text by processing them automatically. For example, an IE system might retrieve information about geopolitical indicators of countries from a set of web pages while ignoring other types of information. Ontology-based information extraction (OBIE) has recently emerged as a subfield of information extraction. Here, ontologies - which provide formal and explicit specifications of conceptualizations - play a crucial role in the IE process. Because of the use of ontologies, this field is related to knowledge representation and has the potential to assist the development of the Semantic Web. In this paper, we provide an introduction to ontology-based information extraction and review the details of different OBIE systems developed so far. We attempt to identify a common architecture among these systems and classify them based on different factors, which leads to a better understanding on their operation. We also discuss the implementation details of these systems including the tools used by them and the metrics used to measure their performance. In addition, we attempt to identify the possible future directions for this field.

/pdf/ontology-based-information-extraction-an-introduction-and-a-3hrx5s063u.pdf

Ontology-based information extraction: An introduction and a survey of current approaches

The Resource Description Framework RDF allows you to describe web documents and resources from the real world - people, organisations, things - in a computer-processable way Publishing such descriptions on the web creates the semantic web URIs are very important as the link between RDF and the web This article presents guidelines for their effective use We discuss two strategies, called 303 URIs and hash URIs We give pointers to several web sites that use these solutions, and briefly discuss why several other proposals have problems

/pdf/cool-uris-for-the-semantic-web-4nq8vqqdey.pdf

Cool URIs for the semantic web

In this paper we will give an overview of the Semantic Desktop paradigm, beginning with the history of the term, a definition, current work and its relevance to knowledge management of the future. Existing applications and research results are listed and their role as building blocks of the future Semantic Desktop described. Based on the analysis of existing systems we propose two software architecture paradigms, one for the Semantic Desktop at large and another for applications running on a Semantic Desktop. A view on the context aspect of the Semantic Desktop and the Knowledge Management aspect is given. Based on the current events and projects, we give an outlook on the next steps.

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Overview and outlook on the semantic desktop

This paper introduces the NEPOMUK project which aims to create a standard and reference implementation for the Social Semantic Desktop. We outline the requirements and functionalities that were identified for a useful Semantic Desktop system and present an architecture that fulfills these requirements which was acquired by incremental refinement of the architecture of existing Semantic Desktop prototypes. The NEPOMUK project is primarily motivated by three real-life industrial use-cases, we briefly outline these and the processes used to extract required functionalities from the people working in these areas today, and we present a selection of typical tasks where the Semantic Desktop could be of benefit.

The NEPOMUK Project - On the way to the Social Semantic Desktop

To integrate office appliances, there are different standards, consisting of data formats and communication protocols The WWW and Semantic Web standards are already designed for worldwide integration and can be transferred to office integration We present our vision of the Semantic Desktop – a Semantic Web enhanced desktop environment Central is the idea of taking know-how from the Semantic Web to tackle personal information management The architecture is based on a Semantic Web Server running as Desktop service Existing desktop applications (email client, browser, office applications) are integrated The semantic glue between them is expressed with ontologies This architecture will enable us to create tools for information management faster and cheaper Based on the local Semantic Desktop Servers, teams of knowledge workers can set up peer-to-peer connections Distributed Organisational Memories can be based on Semantic Desktops The gnowsis framework is an open source project led by the DFKI that realizes parts of this vision Gnowsis was used to test our ideas and allow others to experiment

http://www.dfki.uni-kl.de/~sauermann/papers/Sauermann2005a.pdf

The Gnowsis Semantic Desktop for Information Integration.

In this paper we present lessons learned from building a Semantic Desktop system, the gnowsis beta. On desktop computers, semantic software has to provide stable services and has to reflect the personal view of the user. Our approach to ontologies, the Personal Information Model PIMO allows to create tagging services like del.icio.us on the desktop. A semantic wiki allows further annotations. Continuous evaluations of the system helped to improve it. These results were created in the EPOS research project and are available in the open source projects Aperture, kaukoluwiki, and gnowsis and will be continued in the Nepomuk project. By using these components, other developers can create new desktop applications the web 2.0 way.

/pdf/semantic-desktop-2-0-the-gnowsis-experience-1n1m6269t2.pdf

Leo Sauermann

Papers

Cool URIs for the semantic web

Overview and outlook on the semantic desktop

The NEPOMUK Project - On the way to the Social Semantic Desktop

The Gnowsis Semantic Desktop for Information Integration.

Semantic desktop 2.0: the Gnowsis experience