LDOW 2015 - Use cases for Linked Data Visualization Model

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Use Cases for Linked Data Visualization Model Jakub Klímek Jiří Helmich Martin Nečaský http://xrg.cz | contact@ xrg.cz XML and Web Engineering Research Group Faculty of Mathematics and Physics Charles University, Prague Czech Republic klimek@ fit.cvut.cz Faculty of Information Technology Czech Technical University in Prague

Transcript of LDOW 2015 - Use cases for Linked Data Visualization Model

Use Cases

for Linked Data Visualization Model

Jakub Klímek

Jiří Helmich

Martin Nečaskýhttp://xrg.cz | [email protected] and Web Engineering Research GroupFaculty of Mathematics and PhysicsCharles University, PragueCzech Republic

[email protected] of Information TechnologyCzech Technical University in Prague

Use Cases for LDVM 2

Nowadays, a vast amount of Linked Data is available on the Internet. That’s great and that’s exactly what we wanted.

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But what happens when some LOD expert wants to get something in return from the community and use the data present in LOD cloud?

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He might be a bit confused, since there are many different datasets and he has no idea what exactly they contain. Is he able to link his data with the LOD cloud? What visualizations are available? E.g. datahub.io does not help very much.

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Typically, he starts running some queries like “first 100 triples” or “first 100 concepts” againsta SPARQL endpoint. That is not very convenient.

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An ideal way would be to offer him a list of visualizations that are available based on selected dataset(s). We’ve been working on a tool for automated visualization discovery for a while.

DEMO

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https://www.youtube.com/watch?v=NqBGhyfNeJo

Linked Data Visualization Model (LDVM)

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We assemble LDVM-compliant pipelines with 4 types of components (data sources, analyzers, transformers and visualizers).

LDVM compatibility check

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ASK {?s s:geo ?g .?g a s:GeoCoordinates ;

s:latitude ?lat ;s:longitude ?lng .

}

[] ruianlink:obec <ex1>;s:geo [

s:longitude "14.417780" ;s:latitude "50.084552" .

] .

Output data sample

Input descriptor

Use Cases for LDVM

Each component has an input descriptor and an output data sample. If input descriptor of a component matches to an output data sample of another, those are said to be compatible.

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LDVM discovery

In each iteration of the visualization discovery, we take fragments from the last iteration and try to combine them with all available components based on compatibility checking.

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LDVM discovery

The iterative process terminates when no component was chained into any of the current fragments. Pipeline is complete when it ends with a visualizer.

LDVM vocabulary

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http://lov.okfn.org/dataset/lov/vocabs/ldvm

https://github.com/payola/ldvm

We’ve published a vocabulary for describing LDVM components and pipelines. Everyone can describe e.g. his visualizer and clearly state it’s interface by writing down its descriptors.

DEMO

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https://www.youtube.com/watch?v=IY3WPIq_gaM

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?s s:geo ?g .?g a s:GeoCoordinates ;

s:latitude ?lat ;s:longitude ?lng .

?s s:geo ?g ;?p ?o .

?o a skos:Concept .

?o s:description ?d .

Descriptors are, in fact, bound to component features. Those are mandatory (like coordinates for putting a marker on a map) or optional (like descriptions for infoboxes).

LDVMi

http://ldvm.opendata.cz

https://github.com/payola/LDVMi

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LDVMi

Read the full paper at http://events.linkeddata.org/ldow2015/papers/ldow2015_paper_08.pdf

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Thank you for your attentionJakub Klímek

Jiří Helmich

Martin Nečaskýhttp://xrg.cz | [email protected] and Web Engineering Research GroupFaculty of Mathematics and PhysicsCharles University, PragueCzech Republic

[email protected] of Information TechnologyCzech Technical University in Prague