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LIMES is a link discovery framework for the Web of Data. It implements time-efficient approaches for large-scale link discovery based on the characteristics of metric spaces. It is easily configurable via a web interface. It can also be downloaded as standalone tool for carrying out link discovery locally.

"Semantic Science is a new community portal to support the development of Semantic Web technologies (guides/presentations, RDF/OWL ontologies, knowledge systems) to facilitate the management, integration and discovery of scientific knowledge."

"iServe is what we refer to as service warehouse which unifies service publication, analysis, and discovery through the use of lightweight semantics as well as advanced discovery and analytic capabilities. iServe provides the typical features of service registries and additional functionality that exploits service descriptions, service annotations and further data gathered and derived from the analysis of these descriptions, data crawled from the Web, periodic monitoring and user activities."

In order to support data set owners to publish their datasets as Linked Data on the Web, as well as to support data consumers to access and integrate Linked Data from the Web, the LATC project has compiled a library of open source toolkits that cover all stages of the Linked Data publication (modeling, linking, serving) and consumption process (discovery, consolidation, application). By gathering high-quality open source tools in the form of a consistent library, we hope to lower the barriers to publishing Linked Data as well as to interacting with the Web of Data.

The goal of the SWS Challenge is to develop a common understanding of various technologies intended to facilitate the automation of mediation, choreography and discovery for Web Services using semantic annotations. The intent of this challenge is to explore the trade-offs among existing approaches. Additionally we would like to figure out which parts of problem space may not yet be covered.

the team of developers will transition the semantic platform (DataStaR) developed at Cornell University from a single library software prototype to a well-documented, open-source platform ready for adoption and extension at other institutions wishing to provide research data sharing and discovery services.

Hello Janos, Thanks for sending me information and content about Web 3.0. It's interesting topic and I am looking into it.

Best in class semantic search discovery tool DISQOVER is a semantic search platform that integrates disparate life sciences data. The data is made navigable through a novel indexing engine. Complex queries can be run intuitively and are delivered at speed, enabling you to find smarter data faster with DISQOVER.

a new life sciences company bringing vascular informatics to oncology research, drug discovery and translational development.

mashpoint is a framework that allows data rich apps to be connected and browsed in a new way. It allows selections of data from one app to be inputed in other apps, improving discovery of information on a more granular level.

VoID (from "Vocabulary of Interlinked Datasets") is an RDF based schema to describe linked datasets. With VoID the discovery and usage of linked datasets can be performed both effectively and efficiently. A dataset is a collection of data, published and maintained by a single provider, available as RDF, and accessible, for example, through dereferenceable HTTP URIs or a SPARQL endpoint.

The network of scientists will facilitate scholarly discovery. Institutions will participate in the network by installing VIVO, or by providing semantic web-compliant data to the network.

Following the workshop in Video on the Web, the goal of the Video in the Web activity is to make video a "first class citizen" of the Web. Video on the Web (and this includes audio, as the two are typically used together) has seen explosive growth, improving the richness of the user experience but leading to challenges in content discovery, searching, indexing and accessibility. Enabling users (from individuals to large organizations) to put video in the Web requires that we build a solid architectural foundation that enables people to create, navigate, search, link and distribute video, effectively making video part of the Web instead of an extension that doesn't take full advantage of the Web architecture.

Splice is a new contextual discovery technology that automatically augments your Twitter and Facebook feeds with rich related information, so you don't have to search for it.

Knowledge Organization Systems/Services (KOS) model the underlying semantic structure of a domain. Embodied as Web-based services, they can facilitate resource discovery and retrieval. They act as semantic road maps and make possible a common orientation by indexers and future users (whether human or machine).

Semantic Radar is a semantic metadata detector for Mozilla Firefox. Available at Mozilla Add-ons site. It is a browser extension which inspects web pages for links to Semantic Web metadata and informs about presence of it by showing an icon in browser's status bar. Currently it supports RDF autodiscovery (SIOC, FOAF, DOAP and any type) and RDFa metadata detection. New: Semantic Radar can now ping the Semantic Web Ping Service when metadata are detected. This allows for a community based discovery of the Semantic Web data.

"While Sig.ma is by no mean the first data aggregator for the Semantic Web, its contribution is to show that the sum is really bigger than the single parts and exciting possibilities lie in a holistic approach for automatic semistructured data discovery and consolidation.

LOUD3R is a real-time content discovery, curation and publishing platform that delivers the best news, blogs, photos, videos and social media about any topic. We combine semantic search and aggregation technology with human knowledge to provide publishers and marketers the hottest, freshest, most relevant content on the web.

Rapid-I provides software, solutions, and services in the fields of predictive analytics, data mining, and text mining. The company concentrates on automatic intelligent analyses on a large-scale base, i.e. for large amounts of structured data like database systems and unstructured data like texts. The open-source data mining specialist Rapid-I enables other companies to use leading-edge technologies for data mining and business intelligence. The discovery and leverage of unused business intelligence from existing data enables better informed decisions and allows for process optimization.