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.

/pdf/linked-data-the-story-so-far-2a9zvmaysa.pdf

Linked Data - the story so far

Twitter, a popular microblogging service, has received much attention recently. An important characteristic of Twitter is its real-time nature. For example, when an earthquake occurs, people make many Twitter posts (tweets) related to the earthquake, which enables detection of earthquake occurrence promptly, simply by observing the tweets. As described in this paper, we investigate the real-time interaction of events such as earthquakes in Twitter and propose an algorithm to monitor tweets and to detect a target event. To detect a target event, we devise a classifier of tweets based on features such as the keywords in a tweet, the number of words, and their context. Subsequently, we produce a probabilistic spatiotemporal model for the target event that can find the center and the trajectory of the event location. We consider each Twitter user as a sensor and apply Kalman filtering and particle filtering, which are widely used for location estimation in ubiquitous/pervasive computing. The particle filter works better than other comparable methods for estimating the centers of earthquakes and the trajectories of typhoons. As an application, we construct an earthquake reporting system in Japan. Because of the numerous earthquakes and the large number of Twitter users throughout the country, we can detect an earthquake with high probability (96% of earthquakes of Japan Meteorological Agency (JMA) seismic intensity scale 3 or more are detected) merely by monitoring tweets. Our system detects earthquakes promptly and sends e-mails to registered users. Notification is delivered much faster than the announcements that are broadcast by the JMA.

/pdf/earthquake-shakes-twitter-users-real-time-event-detection-by-1tue7cvj9p.pdf

Earthquake shakes Twitter users: real-time event detection by social sensors

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

/pdf/jumping-nlp-curves-a-review-of-natural-language-processing-3os35aikfr.pdf

Jumping NLP Curves: A Review of Natural Language Processing Research

Natural language processing (NLP) is a theory-motivated range of computational techniques for the automatic analysis and representation of human language. NLP research has evolved from the era of punch cards and batch processing (in which the analysis of a sentence could take up to 7 minutes) to the era of Google and the likes of it (in which millions of webpages can be processed in less than a second). This review paper draws on recent developments in NLP research to look at the past, present, and future of NLP technology in a new light. Borrowing the paradigm of `jumping curves? from the field of business management and marketing prediction, this survey article reinterprets the evolution of NLP research as the intersection of three overlapping curves-namely Syntactics, Semantics, and Pragmatics Curves- which will eventually lead NLP research to evolve into natural language understanding.

Jumping NLP Curves: A Review of Natural Language Processing Research [Review Article]

This paper deals with applying semantic Web technologies to the social Web can lead to a social semantic Web, creating a network of interlinked and semantically rich knowledge. One of the most visible trends on the Web is the emergence of social Web sites, which help people create and gather knowledge by simplifying user contributions via blogs, tagging and folksonomies, wikis, podcasts, and online social networks. The social Web has enabled community-based knowledge acquisition.

/pdf/interlinking-the-social-web-with-semantics-2if662cz07.pdf

Interlinking the Social Web with Semantics

A wealth of information has recently become available as browsable RDF data on the Web, but the selection of client applications to interact with this Linked Data remains limited. We show how to browse Linked Data with Fenfire, a Free and Open Source Software RDF browser and editor that employs a graph view and focuses on an engaging and interactive browsing experience. This sets Fenfire apart from previous table- and outline-based Linked Data browsers.

/pdf/browsing-linked-data-with-fenfire-x57w09l61e.pdf

Browsing Linked Data with Fenfire

Social network and data portability has recently gained a lot of interest as one of the issues for social media sites on the Web. In this paper, we will show how Semantic Web technologies and especially the FOAF and SIOC vocabularies can be used to model user information and user-generated content in a machine-readable way. Thus, we will see how data and network information can be reused among various services and applications, at almost zero-cost for developers of such tools.

/pdf/social-networks-and-data-portability-using-semantic-web-55xd9gqi6k.pdf

Social Networks and Data Portability using Semantic Web technologies

Among the activities that people participate in on the Social Web are argumentative discussions and decision making. This paper analyzes a series of use-cases (from the perspective of social media sites) that share the presence of such argumentative discussions and where the structure of online discussions can be represented in SIOC. Our goal is to externalize implicit argumentation structures hidden in the usergenerated content. For capturing it and making it explicit, we propose a SIOC Argumentation ontology module as a formal representation.

/pdf/expressing-argumentative-discussions-in-social-media-sites-2k0tbambpn.pdf

Expressing Argumentative Discussions in Social Media Sites.

This paper describes work performed during the last few years in the context of the SIOC project in order to model social data on the Web using Semantic Web technologies. We will give an overview of the SIOC model, describe various applications and use cases that take advantage of it (from domains ranging from mobile phones to life sciences), as well as mention future works regarding the project.

/pdf/sioc-content-exchange-and-semantic-interoperability-between-1erzi9tflq.pdf

SIOC: Content Exchange and Semantic Interoperability Between Social Networks

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