LinkedPipes Visualization

Visualization of Linked Data

LinkedPipes Visualization stands for our idea that we, data consumers, should be able to work with Linked (Open) Data (5* open data) in a more convenient way than with 3* open data such as an Excel file. So far, this is not the case.

Payola, Linked Data Visualization Model Implementation (LDVMi), LinkedPipes Visualization Assistant and finally, LinkedPipes Applications are all evolutions of this idea.

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play_for_workGitHub
schoolPapers
play_for_workGitHub

What's new

  • whatshot2016-06-02: LinkedPipes Visualization @ ESWC 2016 Demo Track

    LinkedPipes Visualization was presented at ESWC 2016 Demo Track!

  • fast_forward2016-03-03: One click visualizations

    We have streamlined the visualization discovery process for the case when you have your RDF file with only one meaningful possible visualization. This means that you get this visualization on one click. Try it out with a SKOS concept scheme or an RDF data cube! If you don’t have your own data, try e.g. the EU programmes and switch to Tree visualization.

  • lightbulb_outline2016-03-01: Merging of data sources

    When you fill two or more URLs in the “URL containing RDF” field, you create a merged data source. This is especially helpful for merging RDF data cube observations and the DSD, as these two need to be in one data source.

  • whatshot2016-02-29: IRI dereferencing in Data Cube visualizer

    When you want to visualize a data cube and only provide the DSD and observations, we will dereference the IRIs of your dimension values to see if we can get labels for them. This means that you don’t have to provide the used code lists as long as their items are dereferenceable. Try it out! Use these two URLs in the “URL containing RDF” field: Observations, DSD. If you examine the files, you will see that the labels for days, age categories and sexes are not there. Nevertheless, you will see them in the visualization, because we get them by dereferencing their IRIs.

  • fast_forward2016-02-28: Feeling lucky

    You can click on “Feeling lucky” button and see what visualization of your data we will choose. For example, if you want to visualize a data cube and you also provide SKOS concept schemes used on dimensions, when you simply click on “Visualize”, you will have to choose from the Data cube visualizer and the Concept scheme visualizer. In this particular case, you probably want the data cube visualizer and that is what you get when you are feeling lucky.

lightbulb_outlineMore Tips & Tricks

Features

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Standards compliant

We focus on support of the web standards. By using well-known open source libraries first, we make sure that offer a state-of-the-art support of web standards such as RDF 1.1 and SPARQL 1.1. This means that in LinkedPipes Visualization, you can use data both from RDF dumps and SPARQL endpoints.

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Linked Data vocabularies based

LinkedPipes Visualization currently supports the Simple Knowledge Organization System (SKOS), the RDF Data Cube Vocabulary (DCV) and for map visualizations, Schema.org's GeoCoordinates. If you want to visualize Linked Data, the only way to do it is to obey web standards

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Automation oriented

You point LinkedPipes Visualization to the data and it tells you what it sees in it. This way, you get to a visualization in just a few clicks. So far, this works with data cubes, hierarchies and code lists and points on a map. Check out our research to see how we do that.