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

This paper addresses several key issues in the ArnetMiner system, which aims at extracting and mining academic social networks. Specifically, the system focuses on: 1) Extracting researcher profiles automatically from the Web; 2) Integrating the publication data into the network from existing digital libraries; 3) Modeling the entire academic network; and 4) Providing search services for the academic network. So far, 448,470 researcher profiles have been extracted using a unified tagging approach. We integrate publications from online Web databases and propose a probabilistic framework to deal with the name ambiguity problem. Furthermore, we propose a unified modeling approach to simultaneously model topical aspects of papers, authors, and publication venues. Search services such as expertise search and people association search have been provided based on the modeling results. In this paper, we describe the architecture and main features of the system. We also present the empirical evaluation of the proposed methods.

ArnetMiner: extraction and mining of academic social networks

The article included many scenarios in which intelligent agents and bots undertook tasks on behalf of their human or corporate owners. Of course, shopbots and auction bots abound on the Web, but these are essentially handcrafted for particular tasks: they have little ability to interact with heterogeneous data and information types. Because we haven't yet delivered large-scale, agent-based mediation, some commentators argue that the semantic Web has failed to deliver. We argue that agents can only flourish when standards are well established and that the Web standards for expressing shared meaning have progressed steadily over the past five years

/pdf/the-semantic-web-revisited-21caz3h92j.pdf

The Semantic Web Revisited

ContextThe quality of consumer health information on the World Wide Web is
an important issue for medicine, but to date no systematic and comprehensive
synthesis of the methods and evidence has been performed.ObjectivesTo establish a methodological framework on how quality on the Web is
evaluated in practice, to determine the heterogeneity of the results and conclusions,
and to compare the methodological rigor of these studies, to determine to
what extent the conclusions depend on the methodology used, and to suggest
future directions for research.Data SourcesWe searched MEDLINE and PREMEDLINE (1966 through September 2001), Science
Citation Index (1997 through September 2001), Social Sciences Citation Index
(1997 through September 2001), Arts and Humanities Citation Index (1997 through
September 2001), LISA (1969 through July 2001), CINAHL (1982 through July
2001), PsychINFO (1988 through September 2001), EMBASE (1988 through June
2001), and SIGLE (1980 through June 2001). We also conducted hand searches,
general Internet searches, and a personal bibliographic database search.Study SelectionWe included published and unpublished empirical studies in any language
in which investigators searched the Web systematically for specific health
information, evaluated the quality of Web sites or pages, and reported quantitative
results. We screened 7830 citations and retrieved 170 potentially eligible
full articles. A total of 79 distinct studies met the inclusion criteria,
evaluating 5941 health Web sites and 1329 Web pages, and reporting 408 evaluation
results for 86 different quality criteria.Data ExtractionTwo reviewers independently extracted study characteristics, medical
domains, search strategies used, methods and criteria of quality assessment,
results (percentage of sites or pages rated as inadequate pertaining to a
quality criterion), and quality and rigor of study methods and reporting.Data SynthesisMost frequently used quality criteria used include accuracy, completeness,
readability, design, disclosures, and references provided. Fifty-five studies
(70%) concluded that quality is a problem on the Web, 17 (22%) remained neutral,
and 7 studies (9%) came to a positive conclusion. Positive studies scored
significantly lower in search (P = .02) and evaluation
(P = .04) methods.ConclusionsDue to differences in study methods and rigor, quality criteria, study
population, and topic chosen, study results and conclusions on health-related
Web sites vary widely. Operational definitions of quality criteria are needed.

/pdf/empirical-studies-assessing-the-quality-of-health-2zwfbp74fk.pdf

Empirical Studies Assessing the Quality of Health Information for Consumers on the World Wide Web: A Systematic Review

http://www.cs.man.ac.uk/~horrocks/Publications/download/2003/HoPH03a.pdf

From SHIQ and RDF to OWL: the making of a Web Ontology Language

Rdf vocabulary description language 1.0 : Rdf schema

This specification describes the FOAF language, defined as a dictionary of named properties and classes using W3C's RDF technology. Status of This Document FOAF has been evolving gradually since its creation in mid-2000. There is now a stable core of classes and properties that will not be changed, beyond modest adjustments to their documentation to track implementation feedback and emerging best practices. New terms may be added at any time (as with a natural-language dictionary), and consequently this specification is an evolving work. The FOAF RDF namespace, by contrast, is fixed and it's identifier is not expected to change. Furthermore, efforts are underway to ensure the long-term preservation of the FOAF namespace, its xmlns.com domain name and associated documentation. This document is created by combining the RDFS/OWL machine-readable FOAF ontology with a set of per-term documents. Future versions may incorporate multilingual translations of the term definitions. The RDF version of the specification is also embedded in the HTML of this document, or available directly from the namespace URI by content negotiation. The FOAF specification is produced as part of the FOAF project, to provide authoritative documentation of the contents, status and purpose of the RDF/XML vocabulary and document formats known informally as 'FOAF'. The authors welcome comments on this document, preferably via the public FOAF developers list foaf-dev@lists.foaf-project.org; public archives are available. A historical backlog of known technical issues is acknowledged, and available for discussion in the FOAF wiki. Proposals for resolving these issues are welcomed, either on foaf-dev or via the wiki. Further work is also needed on the explanatory text in this specification and on the FOAF website; progress towards this will be measured in the version number of future revisions to the FOAF specification. This revision of the specification includes a first draft description of the new foaf:openid property. The prose description of this property is likely to evolve, but the basic mechanism seems robust. To accompany this support for OpenID in the FOAF specification, the FOAF wiki has also been updated to support usage of OpenID by members of the developer community. This revision of the spec also involves a change in FOAF Vocabulary Specification http://xmlns.com/foaf/spec/ 1 of 38 5/4/2009 2:00 PM

FOAF Vocabulary Specification

Separation between content and presentation has always been one of the important design aspects of the Web. Historically, however, even though most Web sites were driven off structured databases, they published their content purely in HTML. Services such as Web search, price comparison, reservation engines, etc. that operated on this content had access only to HTML. Applications requiring access to the structured data underlying these Web pages had to build custom extractors to convert plain HTML into structured data. These efforts were often laborious and the scrapers were fragile and error-prone, breaking every time a site changed its layout.

Schema.org: evolution of structured data on the web

This paper introduces SKOS Core, an RDF vocabulary for expressing the basic structure and content of concept schemes (thesauri, classification schemes, subject heading lists, taxonomies, terminologies, glossaries and other types of controlled vocabulary). SKOS Core is published and maintained by the W3C Semantic Web Best Practices and Deployment Working Group. The main purpose of this paper is to provide an initial basis for establishing clear recommendations for the use of SKOS Core and DCMI Metadata Terms in combination. Also discussed are management policies for SKOS Core and other RDF vocabularies, and the relationship between a 'SKOS concept scheme' and an 'RDFS/OWL ontology'.

/pdf/skos-core-simple-knowledge-organisation-for-the-web-7wa4enwq6d.pdf

SKOS core: simple knowledge organisation for the web

There are thousands of data repositories on the Web, providing access to millions of datasets. National and regional governments, scientific publishers and consortia, commercial data providers, and others publish data for fields ranging from social science to life science to high-energy physics to climate science and more. Access to this data is critical to facilitating reproducibility of research results, enabling scientists to build on others' work, and providing data journalists easier access to information and its provenance. In this paper, we discuss Google Dataset Search, a dataset-discovery tool that provides search capabilities over potentially all datasets published on the Web. The approach relies on an open ecosystem, where dataset owners and providers publish semantically enhanced metadata on their own sites. We then aggregate, normalize, and reconcile this metadata, providing a search engine that lets users find datasets in the “long tail” of the Web. In this paper, we discuss both social and technical challenges in building this type of tool, and the lessons that we learned from this experience.

Dan Brickley

Papers

Rdf vocabulary description language 1.0 : Rdf schema

FOAF Vocabulary Specification

Schema.org: evolution of structured data on the web

SKOS core: simple knowledge organisation for the web

Google Dataset Search: Building a search engine for datasets in an open Web ecosystem