Semantic Web

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WordLift 2.0 (Pitch at JBoye11 in Aarhus)
Knowledge Media Institute | The Open University

Knowledge Media Institute | The Open University

The Knowledge Media Institute (KMi) was set up in 1995 in recognition of the need for the Open University to be at the forefront of research and development in a convergence of areas that impacted on the OU's very nature: Cognitive and Learning Sciences, Artificial Intelligence and Semantic Technologies, and Multimedia. We chose to call this convergence Knowledge Media. Knowledge Media is about the processes of generating, understanding and sharing knowledge using several different media, as well as understanding how the use of different media shape these processes. KMi operates with reference to a number of basic tenets, which define the context in which we formulate and pursue our research objectives: Strategic Threads Our research is aligned with a number of broad strategic threads, currently Future Internet, Knowledge Management, Multimedia & Information Systems, Narrative Hypermedia, New Media Systems, Semantic Web & Knowledge Services and Social Software.
pdx music map pdx music map Example applications (see also): For unknown bands, an idea was to relate them to you in terms of bands you already know/like (in addition to manually clicking on maybe a “Like” button a la Facebook, it could be assumed that you know of bands that’ve played shows you attended, for instance), using the “six degrees of separation” mechanism like Music Routes. A caveat with all this is that new bands formed by “nobodies” would be at a disadvantage for discovery on this system - less links on the graph - and would still need to be discovered the old-fashioned way. Proposed structure
Install XSPARQL | Bridging the RDF and XML worlds Install XSPARQL | Bridging the RDF and XML worlds XSPARQL is a prototype implementation of the XSPARQL language. This rewriter translates an XSPARQL query into an XQuery as described in the XSPARQL Language Specification. Downloading XSPARQL You can download XSPARQLer in two different ways: as precompiled package or as source via the sourceforge subversion repository. Package
LeifW/MusicPath - GitHub
A new generation in ontology development tools is needed. This documentation provides an explication of the landscape under which this new generation of tools is occurring.[1] Ontologies supply the structure for relating information to other information in the semantic Web or the linked data realm. Normative Landscape of Ontology Tools - TechWiki Normative Landscape of Ontology Tools - TechWiki
features - owltools - Summary of features of OWLTools - Wrapper for OWL API features - owltools - Summary of features of OWLTools - Wrapper for OWL API This page describes some of the varied features of OWLTools. Some of these may eventually be split off into separate projects. For a complete and current list of sub-projects, see the API docs Convenience Methods on top of the OWL API OWLTools leverages the full features of the OWL API and OWL Reasoner API, but provides convenience methods for common tasks. OBO-Style Wrapper
owlpopulous - Semantic Spreadsheets for Populating OWL/RDF vocabularies Populous is an generic tool for building ontologies from simple spreadsheet like templates. The Populous approach is useful when a repeating ontology design pattern emerges that need to be populated en-mass. The use of a simple interface, similar to that of a spreadsheet, means that the templates can be populated by users with little or no knowledge of ontology development. Once these templates are populated, Populous supports transforming the data into an OWL ontology using a expressive pattern language. Spreadsheets are currently transformed into OWL/RDF using the Ontology Pre-Processing Language v2 (OPPL). owlpopulous - Semantic Spreadsheets for Populating OWL/RDF vocabularies
Semantic Web Tools Semantic Web Tools Locational information — points of interest/POIs, paths/routes/polylines, or polygons/regions — is common to many physical things in our real world. Because of its pervasiveness, it is important to have flexible and powerful display widgets that can respond to geo-locational data. We have been working for some time to extend our family of semantic components [1] within the open semantic framework (OSF) [2] to encompass just such capabilities.
DEMO | Generate HTML DEMO | Generate HTML [ Set your naming convention for your elements. Click the help icon to know more] You can choose/set the naming convention for your elements. Examples: For Ruby on Rails auto binding, the convention is table_name[column_name] ASP.NET MVC auto binding, the convention is table_name.column_name Custom Naming Convention: Sometimes you will need your own custom naming convention, in that case you can enter your own expressions with the tokens {table_name} and {column_name} Example for a custom expression is baf_{table_name}_{column_name}_value .
RIOT - Jena Wiki
Jena vs Sesame: is there a serious, complete, up-to-date, unbiased, well informed, side by side, comparison between the two? Jena vs Sesame: is there a serious, complete, up-to-date, unbiased, well informed, side by side, comparison between the two? Here's my take. I don't use either Jena or Sesame as a persistent triple store and don't expect to ever do so. There are so many other products out there (4store, Virtuoso, BigOWLIM, StarDog) and I see myself using Jena/Sesame as an API to access them. On the other hand, I do have a need for something that handles a small number of triples (say 1000 typically and 1M in an extreme case) in RAM. I don't want to deal with setup and teardown time for a "big" triple store. I do care about feature support, and I think Jena wins that hands down.
Semantic Web? It's Not Rocket Science. Except at NASA. - W3C Blog Semantic Web? It's Not Rocket Science. Except at NASA. - W3C Blog I met Jeanne Holm last week during the W3C Advisory Committee meeting. Jeanne is the Chief Knowledge Architect at the Jet Propulsion Laboratory (JPL), California Institute of Technology, and leads the Knowledge Management Team at NASA. When we started talking about NASA’s use of Semantic Web technology I asked whether the application satisfies three criteria: The application aggregates data from three independently developed sources.The data is used in ways not originally intended (“serendipitous reuse”).The cost of aggregation is low, requiring only a small amount of connective tissue.
Michael Grove, VP of Engineering, Twitter: @mikegrovesoftClark & Parsia, LLC 7 June 2011 About Clark & Parsia Develop Semantic Technology infrastructure-level products and related solutions Customer-funded since 2005 Active in W3C standardization work: OWL, SPARQL, OWL 2, WSDL, etc. Offices in Washington, DC and Boston Customers in government and industry, including banking, aerospace, health care, oil & gas, etc. In this talk I describe how we've combined the best of two worlds— Stardog for scalable query answering and instance reasoning, and Pellet 3 for expressive schema reasoning —into a single, coherent, scalable system for Enterprise Semantics. Stardog and Pellet 3: Semantics for the Enterprise
NLP

General Overview LIMES implements novel time-efficient approaches for link discovery in metric spaces. Our approaches different approximation techniques to compute estimates of the similarity between instances. These estimates are then used to filter out a large amount of those instance pairs that do not suffice the mapping conditions. By these means, LIMES can reduce the number of comparisons needed during the mapping process by several orders of magnitude. Projects / LIMES
rdfa-core-java - RDFa Core 1.1 implementation in Java rdfa-core-java is a Java implementation of the RDFa Core 1.1 draft. Project is following specification strictly and passes all current unit tests. rdfa-core-java includes XHTML+RDFa 1.1 host language support and supports both SAX and DOM parsing. Project is part of a closed world assumption based message validation service created under Finnish government funded Tikesos-project. Unlike other parsers, rdfa-core-java stores information about the locations of RDFa attributes in XML (Line and Column numbers in SAX, Nodes in DOM). This information is used by the validation service to provide user-friendly messages (such as cardinality failures, undefined data types, invalid data types, unexpected properties, etc.) about the document structure.
The mission of the Library Linked Data incubator group is to help increase global interoperability of library data on the Web, by bringing together people involved in Semantic Web activities—focusing on Linked Data—in the library community and beyond, building on existing initiatives, and identifying collaboration tracks for the future. The group has explored how existing building blocks of librarianship, such as metadata models, metadata schemas, standards and protocols for building interoperability and library systems and networked environments, encourage libraries to bring their content, and generally re-orient their approaches to data interoperability towards the Web, also reaching to other communities. It has also envisioned these communities as a potential major provider of authoritative datasets (persons, topics...) for the Linked Data Web. C Library Linked Data Incubator Group
antidot/db2triples - GitHub
D2RQ - Treating Non-RDF Databases as Virtual RDF Graphs - Chris Bizer
Antidot’s Open Source db2triples Implements R2RML and Direct Mapping
shellac/JenaJung - GitHub
tinkerpop/gremlin - GitHub
5 Simple Provenance Statements | Semantic Web Activity News
Launch Press Release
The Challenge of Building the Semantic Web
LODWheel
LDIF – Linked Data Integration Framework
The Naive CIO — MakingITclear®
PR-OWL Home
DATAVERSITY
All about Open Linked Data and Semantic Web
Semantic Web
Home - GitHub
Linked Java
fluid Operations | flexibility comes first!
Semantic Web Lab
sadi - Semantic Automated Discovery and Integration (SADI)
A Graph-Based Movie Recommender Engine from the Spring Roo Perspective
A Graph-Based Movie Recommender Engine « Marko A. Rodriguez
Semantic Save – Prototype | Trueg's Blog
Why Semantic Web Technologies: Are We Asking the Wrong Question? - TechnicaLee Speaking
Saving Months, Not Milliseconds: Do More Faster with the Semantic Web - TechnicaLee Speaking
Graph Store

Callimachus
Volkswagen’s RDF Data Management Workflow at Frederick Giasson