Group items tagged

Last week, I participated in a WWW2007 panel called "Multimedia Metadata Standards in a Semantic Web 3.0", where I took the opportunity to declare the Semantic Web dead. As you can imagine, such a declaration in front of a crowd of semantic web researchers provoked many responses. While I believe panels should be provocative and entertaining, I also have specific reasons for why I went as far as calling the Semantic Web "dead". Let me explain what I mean.

"The semantic web proposes to inject machine meaningful data into the existing human language oriented web. As part of this effort, on the semantic web, URIs are used to identify entities. But there is currently no standard way to specify what it is that any given URI is to identify, or to whom, or when. Recent work in linguistics offers ideas for a solution to this lack. It focuses on the pragmatics of actual language use among ensembles of people. Also, the World Wide Web provides a set of technologies, in the form of socially constructed web sites, that could be employed to provide a solution. In this paper, I suggest how such socially constructed web sites could be used to address the problem of establishing common ground among a community of machines of the referent of a URI used on the semantic web. The result is a proposal to automate social meaning by creating societies of machines that share knowledge representations identified by URIs."

What tagging does point to convincingly is the social aspect of naming. In a given natural language, many sorts of identifiers, such as common words, are socially centralized. Other sorts of identifiers, such as proper names, are socially decentralized, varying from local context to local context. Black has noticed a correspondence between this socially grounded identification process and the use of socially constructed Web sites.

I hope that "Smarter" is going to be a key tag for the Web 3.0, and yet I think "More Open, More Ubiquitous, with even More Information (Overload) and a little Smarter" is what it's really going to be. We'll have to wait till "Web 4.0" for a web that really is stepwise more intelligent, one that could really be called semantic and hold the hidden promises of a "Semantic Web". And the reason I believe this is that the community is focused on linking more stuff together in new ways and breaking down data siloes, much more than it is focused on creating new, smarter filters for all the data that's going to be made accessible that way.

KHarvester (Informal Knowledge Harvester) is a SOA layer which collects RDF data from web pages. It provides REST based Web Services for managing data available on Social Semantic Information Sources (SSIS): semantic blogs, semantic wikis, and JeromeDL (the Social Semantic Digital Library). These Web Services allow saving harvested data in the informal knowledge repository, and providing them in a form of informal Learning Objects (LOs) that are described accroding to LOM (Learning Object Metadata) standard. Also, IKHarvester is an extension to Didaskon system. Didaskon (διδάσκω - gr. teach) delivers a framework for composing an on-demand curriculum from existing Learning Objects provided by e-Learning services (formal learning). Moreover, the system derives from SSIS which provide informal knowledge. Then, the selection and work-flow scheduling of Learning Objects is based on the semantically annotated specification of the user's current skills/knowledge (pre-conditions), anticipated resulting skills/knowledge (goal) and technical details of the clients platform.

MOAT (Meaning Of A Tag) provides a Semantic Web framework to publish semantically-annotated content from free-tagging. While tags are widely used in Web 2.0 services, their lack of machine-understandable meaning can be a problem for information retrieval, especially when people use tags that can have different meanings depending on the context. MOAT aims to solve this by providing a way for users to define meaning(s) of their tag(s) using URIs of Semantic Web resources (such as URIs from dbpedia, geonames … or any knowledge base), and then annotate content with those URIs rather than free-text tags, leveraging content into Semantic Web, by linking data together. Moreover, tag meanings can be shared between people, providing an architecture of participation to define and exchange potential meanings of tags within a community of users. To achieve this goal, MOAT relies on an architecture that can be deployed for any organisation or community and that involves a lightweight ontology, a MOAT server, and some third-party clients .

The semantic mapping of the English language is the key to making Natural Language Processing (NLP) effective. Cognition's unique Semantic Map, which it built over the past 24 years, is the most comprehensive and complete map of the English language available today. It can be used in support of the Semantic Web for semantic search, search tools, business analytics, machine translation, document search, context search, and much more.

welcome to gnowsis, the Semantic Desktop environment published by the Knowledge Management Lab of the DFKI. Gnowsis is a reference implementation of parts of the Nepomuk Semantic Desktop framework. The Nepomuk project provides a standardized, conceptual framework for Semantic Desktops.Gnowsis can be used in research projects or by interested individuals to benefit from Semantic Web technologies.

Semantic Exchange is a collaborative industry news, research, and education initiative about all things web 3.0 and semantic web, and sponsored by industry leading semantic technology providers.

The SMW+ User Forum is an online community for users and developers of Semantic MediaWiki+ in a commercial or production environment with the purpose to improve and extend Semantic Media Wiki+. SMW+ Forum fuses the social networking aspect of Web 2.0 with semantic technologies.

KIM is a software platform for: * Semantic annotation of text At more length: automatic ontology population and open-domain dynamic semantic annotation of unstructured and semi-structured content for Semantic Web and KM applications * Indexing and retrieval (semantically-enabled and IE-enhanced search technology) * Query and exploration of formal knowledge * Co-occurrence tracking and ranking of entities * Entity popularity timelines analysis

In our latest podcast I talk to Mark Greaves, Director of Knowledge Systems Research at Vulcan. We talk about Mark's background, Vulcan's interest in the Semantic Web, and explore the opportunities to build a business on top of semantic technologies.

There's a long-time debate between those who advocate for semantic markup, and those who believe that machine learning will eventually get us to the holy grail of a Semantic Web, one in which computer programs actually understand the meaning of what they see and read.

Want to create your own semantic search engine, but just don't have the PhDs? Semantic search engine Hakia is opening up APIs to let anyone build their own semantic search application on top of its technology. Hakia looks at the meaning of Web pages and matches search queries using its own quality index of trusted, relevant sites.

The Sematic Web Client Library represents the complete Semantic Web as a single RDF graph. The library enables applications to query this global graph using SPARQL- and find(SPO) queries. To answer queries, the library dynamically retrieves information from the Semantic Web by dereferencing HTTP URIs and by following rdfs:seeAlso links. The library is written in Java and is based on the Jena framework.

Faviki is a social bookmarking tool that allows users to annotate the contents of web pages by Wikipedia concepts. Using Wikipedia as a source of a universal controlled vocabulary, it provides so-called 'semantic tags' which are standardized and computer-interpretable. In this way, Faviki is able to solve some common problems related to classic 'folksonomy' tags, in particular: polysemy, synonymy, different lexical forms, and lack of a commonly agreed meaning of terms. In a wider perspective, Faviki aims to speed up the transition from Web 2.0 to the Semantic Web.

In this article, we'll analyze the trends and technologies that power the Semantic Web. We'll identify patterns that are beginning to emerge, classify the different trends, and peak into what the future holds.

s Richard MacManus recently predicted, in 2008 we'll witness the rise of semantic web services. From the native support for Microformats in Firefox 3, to the New York Times' utilization of rich headers metadata, to this week's release of the Social Graph API by Google, semantics are starting to slip onto the web. The impact is being felt because large companies are really starting to focus on structured information. In the same vein, last week Reuters - an international business and financial news giant - launched an API called Open Calais. The API does a semantic markup on unstructured HTML documents - recognizing people, places, companies, and events. This technology is the next generation of the Clear Forest offering, which Reuters acquired last year. We have profiled Clear Forest on ReadWriteWeb and in this post we will look at what Reuters opened up and why.

The NeuroCommons project seeks to make all scientific research materials - research articles, annotations, data, physical materials - as available and as useable as they can be. We do this by both fostering practices that render information in a form that promotes uniform access by computational agents - sometimes called "interoperability". We want knowledge sources to combine meaningfully, enabling semantically precise queries that span multiple information sources. Our work covers general data and knowledge sources used in computational biology as well as sources specific to neuroscience and neuromedicine. The practices that we develop and promote are designed to play well on the Semantic Web. We view our technical work not as creating a new service or content library, although we do both, but rather as helping to promote the growth of semantically linked scientific information.

Proceedings of the Workshop on Semantic Search (SemSearch 2008) at the 5th European Semantic Web Conference (ESWC 2008) Tenerife, Spain, June 2nd, 2008.

IkeWiki is a new kind of Wiki (a Semantic Wiki ) developed by SalzburgResearch that allows users to annotate pages and links between pages with semantic annotations. Such annotations are useful because they give machines a certain amount of "understanding" of the content that goes beyond merely displaying the page. This information can then e.g. be used for context-specific presentation of pages, advanced querying, consistency verification or drawing conclusions. Currently, IkeWiki can make use of some of the knowledge represented in RDFS and OWL schemas to display enhanced navigation tools. Furthermore, we implemented a sample "biology ontology" that automatically displays a taxonomy box for biological objects. Although IkeWiki looks and behaves like Wikipedia/MediaWiki in many aspects, it is a complete rewrite, and the system design significantly differs from other Wikis. IkeWiki makes full use of Semantic Web technologies like RDF(S) and OWL using the Jena RDF store, and is implemented as an AJAX-based Rich Internet Application, based on the Dojo Toolkit