Linked Data – The Next 5 Years: From Hype to Action

Linked Data and the Semantic Web have been around for quite a while and have been hyped again and again. In the meantime, a large number of enterprises and even whole industries have adopted semantic web technologies for several purposes (for example, visit Allotrope Foundation). “Gartner’s Hype Cycle 2015 for Advanced Analytics and Data Science” has put Linked Data into the trough of disillusionment, which is another clear indicator to be ready for takeoff.

The pace of semantic web technology adoption may vary from industry to industry, but in average it has increased even more than expected. Just in 2012, Gartner has predicted that the Semantic Web won’t reach the plateau of productivity within the next 10 years, only three years later it seems like it will be there in 5 to 10 years.

Linked Data Hype or not, it has entered the adoption phase. In the next 5 years we finally can see to which degree enterprises will use semantic web technologies for data analytics, data integration, and knowledge discovery.

What are the main obstacles that are frequently mentioned by potential users? Which best practices for implementing linked data on a larger scale have already been developed? What are the ‘low-hanging fruits’, and how could a concrete action plan look like? Will the often predicted interlinking of an open semantic web and corporate semantic webs take place? Which other technology (of the above mentioned hype cycles) might play a crucial role as an enabler for enterprise linked data? Which other (mega-)trends will influence the pace of linked data adoption, and which related organisational challenges should be expected?

Please visit Andreas Blumauer’s talk ‘Linked Data – The Next 5 Years: From Hype to Action’ at SEMANTiCS 2016 in Leipzig to get some valuable impulses for your Linked Data project!

 

Why semantic knowledge graphs matter

Most information professionals already know: separation of content and presentation helps to manage and deliver complex information. This can only be done by using enriched structured content. Some call this intelligent content.

But why exactly is metadata per document (some call it “tagging”) not enough?

Here is a very brief slide-deck, which explains the difference between the traditional approach and the graph-based approach to develop not only a metadata layer seperated from the content layer, but also a knowledge layer on top of it.

Why semantic knowledge graphs matter

SKOS as a Key Element in Enterprise Linked Data Strategies

The challenges in implementing linked data technologies in enterprises are not limited to technical issues only. Projects like these deal also with organisational hurdles to be crossed, for instance the development of employee skills in the area of knowledge modelling and the implementation of a linked data strategy which foresees a cost-effective and sustainable infrastructure of high-quality and linked knowledge graphs. SKOS is able to play a key role in enterprise linked data strategies due to its relative simplicity in parallel with its ability to be mapped and extended by other controlled vocabularies, ontologies, entity extraction services and linked open data.

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10 Business Solutions based on Linked Data and Semantic Technologies

2013: Linked data technologies have matured, linked data community has grown, interest both from private industry and from the government is considerable.

A key questions that I get asked again and again is: which business solutions can be built based on linked data? Here is ‘our’ list of 10 solutions:

Linked Data: Standing on the shoulders of giants

When Mariano Consens explained at this year´s Triplify Challenge @ I-Semantics in Graz how he built together with Oktie Hassanzadeh the winning project “Linked Movie Database“, one important thing became clear to me: Linked Data isn´t just a playground anymore, no: it´s a very efficient way to build useful applications standing on the shoulders of giants. Congratulations to the winners!

Mariano Consens