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

DBpedia is a community effort to extract structured information from Wikipedia and to make this information available on the Web. DBpedia allows you to ask sophisticated queries against datasets derived from Wikipedia and to link other datasets on the Web to Wikipedia data. We describe the extraction of the DBpedia datasets, and how the resulting information is published on the Web for human-andmachine-consumption. We describe some emerging applications from the DBpedia community and show how website authors can facilitate DBpedia content within their sites. Finally, we present the current status of interlinking DBpedia with other open datasets on the Web and outline how DBpedia could serve as a nucleus for an emerging Web of open data.

/pdf/dbpedia-a-nucleus-for-a-web-of-open-data-64wla3p0zr.pdf

DBpedia: a nucleus for a web of open data

The theory of affordances

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.

/pdf/context-aware-computing-for-the-internet-of-things-a-survey-3nibvvc921.pdf

Context Aware Computing for The Internet of Things: A Survey

https://people.inf.elte.hu/kiss/11kor/cikkek/20%20DBpedia.pdf

DBpedia - A crystallization point for the Web of Data

The Web is increasingly understood as a global information space consisting not just of linked documents, but also of Linked Data. The Linked Data principles provide a basis for realizing this Web of Data, or Semantic Web. Since early 2007 numerous data sets have been published on the Web according to these principles, in domains as broad as music, books, geographical information, films, people, events, reviews and photos. In combination these data sets consist of over 2 billion RDF triples, interlinked by more than 3 million triples that cross data sets. As this Web of Linked Data continues to grow, and an increasing number of applications are developed that exploit these data sets, there is a growing need for data publishers, researchers, developers and Web practitioners to understand Linked Data principles and practice. Run by some of the leading members of the Linked Data community, this tutorial will address those needs, and provide participants with a solid foundation from which to begin publishing Linked Data on the Web, as well as to implement applications that consume Linked Data from the Web.

/pdf/how-to-publish-linked-data-on-the-web-proposal-for-a-half-amiot2b9sd.pdf

How to Publish Linked Data on the Web - Proposal for a Half-day Tutorial at ISWC2008

VoID is an RDF Schema vocabulary for expressing metadata about RDF datasets. It is intended as a bridge between the publishers and users of RDF data, with applications ranging from data discovery to cataloging and archiving of datasets. This document is a detailed guide to the VoID vocabulary. It describes how VoID can be used to express general metadata based on Dublin Core, access metadata, structural metadata, and links between datasets. It also provides deployment advice and discusses the discovery of VoID descriptions.

Describing linked datasets with the VoID vocabulary

In this paper we discuss the design and implementation of voiD, the \Vocabulary Of Interlinked Datasets", a vocabulary that allows to formally describe linked RDF datasets. We report on use cases for voiD, the current state of the specication and its potential applications in the context of linked datasets.

/pdf/describing-linked-datasets-on-the-design-and-usage-of-void-oiti1a1jhx.pdf

Describing Linked Datasets On the Design and Usage of voiD, the "Vocabulary Of Interlinked Datasets"

Semantic Web technologies have been around for a while. However, such technologies have had little impact on the development of real-world Web applications to date. With linked data, this situation has changed dramatically in the past few months. This article shows how linked data sets can be exploited to build rich Web applications with little effort.

Exploiting Linked Data to Build Web Applications

In this paper we discuss the design and implementation of voiD, the “Vocabulary Of Interlinked Datasets”, a vocabulary that allows to formally describe linked RDF datasets. We report on use cases for voiD, the current state of the specification and its potential applications in the context of linked datasets.

/pdf/describing-linked-datasets-2y6rrcg7y5.pdf

Michael Hausenblas

Papers

How to Publish Linked Data on the Web - Proposal for a Half-day Tutorial at ISWC2008

Describing linked datasets with the VoID vocabulary

Describing Linked Datasets On the Design and Usage of voiD, the "Vocabulary Of Interlinked Datasets"

Exploiting Linked Data to Build Web Applications

Describing Linked Datasets.