Linked Data

ld

Linked Data is a loosely defined term, but tbl's http://www.w3.org/DesignIssues/LinkedData.html is the common source for its foundation of Four Design Principles.

Benefits of Linked Data

Semantic interoperability is crucial in building cost efficient it systems that integrate numerous data sources. Since 2009 the Linked Data paradigm has emerged as a light weight approach to improve data portability ferderated IT systems. By building on Semantic Web standards the Linked Data approach offers significant benefits compared to conventional data integration approaches. These are according to Auer: Auer, Sören (2011). Creating Knowledge Out of Interlinked Data. In: Proceedings of WIMS’11, May 25-27, 2011, p. 1-8

On top of these technological principles Linked Data promises to improve the reusability and richness (in terms of depth and broadness) of content thus adding significant value to the content value chain.

lod Community

w3c Data Activity - Building the Web of Data

More and more Web applications provide a means of accessing data. From simple visualizations to sophisticated interactive tools, there is a growing reliance on the availability of data which can be “big” or “small”, of diverse origin, and in different formats; it is usually published without prior coordination with other publishers — let alone with precise modeling or common vocabularies. The Data Activity recognizes and works to overcome this diversity to facilitate potentially Web-scale data integration and processing. It does this by providing standard data exchange formats, models, tools, and guidance.

The overall vision of the Data Activity is that people and organizations should be able to share data as far as possible using their existing tools and working practices but in a way that enables others to derive and add value, and to utilize it in ways that suit them. Achieving that requires a focus not just on the interoperability of data but of communities.

lod References and Resources

Tools

Linked Data api

Linked Data offers a set of best practices for publishing, sharing and linking data and information on the web. It is based on use of http uris and semantic web standards such as rdf.

For some web developers the need to understand the RDF data model and associated serializations and query language (SPARQL) has proved a barrier to adoption of linked data. This project seeks to develop apis, data formats and supporting tools to overcome this barrier. Including, but not limited to, accessing linked data via a developer-friendly JSON format. More information:

Examples/In the Wild

Linked Data: New Ontologies Website - bbc

Ontologies provides access to the bbc's ontologies it uses to support audience facing applications.

Basic Concepts: Connecting Content with Linked Data

Ontologies are used to describe the world around us, content the bbcM/abbr> creates, and the management, storage, and sharing of these data with the Linked Data Platform.

bbc.co.uk/ontologies is a human friendly view of the data models in the Linked Data Platform and is meant to give a comprehensive understanding of which ontologies the bbc uses, why and how. This is provided for members of the public and anyone who wants to get a better understanding of the bbc's Linked Data.

Community

References and Resources

Sofia Angeletou's Slides from the 'What Linked Data Does, What Linked Data Needs' discussion panel. vote 2014 tagging.jpg vote 2014 news-tagging-v2-2 (3).jpg My main role in BBC News Online, therefore, is to work with our teams to uncover which types of tags, which relationships, and then which instances (Birmingham City Council is an instance of a Council) we might need. Once I've done so, I construct what's known as an Ontology - a specification of the types and relationships that we're going to use - essentially like a dictionary, or a cook book, of allowed concepts. They don't all have to be used, and we can use as many or as few Ontologies as we need, but the types and relationships do need to be specified somewhere. vote 2014 politics ontology.jpg

Linked Data in the Content Value Chain

or Why Dynamic Semantic Publishing makes sense …

According to Cisco communication within electronic networks has become increasingly content-centric. i.e. Cisco reports for the time period from 2011 to 2016 an increase of 90% of video content, 76% of gaming content, 36% VoIP, 36% file sharing being transmitted electronically. Hence it is legitimate to ask what role Linked Data takes in the content production process. Herein we can distinguish five sequential steps:

  1. 1) content acquisition
  2. 2) content editing
  3. 3) content bundling
  4. 4) content distribution
  5. 5) content consumption

As illustrated in the figure below Linked Data can contribute to each step by supporting the associated intrinsic production function.

Linked Data in the Content Value Chain

ldbc (Linked Data Benchmark Council)

ldbc aims to establish industry cooperation between vendors of RDF and Graph database technologies in developing, endorsing, and publishing reliable and insightful benchmark results.

ldbc

Here you may find the results for different benchmarks, i.e. the Social Network Benchmark (SNB) and the Semantic Publishing Benchmark (SPB), their definitions and best practices, the repositories where to find the data generators and the query implementations, an access to the intranet for the LDBC industry partners and a list of the LDBC member vendors.

ldp (Linked Data Platform)

lod (Linking Open Data)

lod2 Creating Knowledge out of Interlinked Data

lod2 Technology Stack

Research Projects Focusing on Linked Data

Linking Open Drug Data (lodd

A highlight of this project is using state-of-the-art semantic link discovery techniques for interlinking the published datasets. More on the interlinking methodology can be found on the Interlinking page.

One of the main goals of this project is investigating use cases that demonstrate how researchers in life science, as well as physicians and patients can take advantage of the connected data sets. Read more about some of the use cases.

lod References and Resources

MichaelHausenblas -- I joined the LOD community project in June 2007 after Chris Bizer has told me about this great idea. In the meantime quite some things emerged and I think I have left some traces ;) In the beginning I was interested in building a linked dataset, which actually yielded riese, the RDFised and interlinked version of the Eurostat's statistical data. As a by-product we developed a pradigm allowing for manual interlinking, called UCI (User-Contributed Interlinking). Then my focus shifted and I wanted to build applications on top of linked data which triggered the creation of voiD, the 'Vocabulary of Interlinked Datasets'. Now, as I'm a multimedia guy at heart, I also started to apply linked data principles to multimedia content. Finally, I gave a LOD tutorial at ISWC08 with Tom, Chris, Richard and Olaf (see also my quick intro into linked data). I've participated in (and co-organised) several LOD Gatherings so far and plan to do so in the future.