This web page is the home of the LOD cloud diagram. This image shows datasets that have been published in Linked Data format, by contributors to the Linking Open Data community project and other individuals and organisations. It is based on metadata collected and curated by contributors to the Data Hub . Clicking the image will take you to an interactive SVG version, where each dataset is a hyperlink to its entry in Datahub.
The diagram is maintained by Andrejs Abele and John McCrae (Insight Centre for Data Analytics at NUI Galway). For any questions and comments, please email email@example.com and John.McCrae@insight-centre.org. The original version was developed by Richard Cyganiak and Anja Jentzsch.
Last updated: 2017-02-20
Yes. This work is available under a CC-BY-SA license. This means you can include it in any other work under the condition that you give proper attribution. If you create derivative works (such as modified or extended versions of the diagram), then you must also license them as CC-BY-SA.
Please give attribution along the following lines:
"Linking Open Data cloud diagram 2017, by Andrejs Abele, John P. McCrae, Paul Buitelaar, Anja Jentzsch and Richard Cyganiak. http://lod-cloud.net/"
First, make sure that you publish data according to the Linked Data principles. We interpret this as:
If you have any problem please contact John McCrae
See the question above—please make sure that it meets the criteria, is in the Data Hub, and that we know about it. Other possible reasons why we exclude some datasets are:
Datasets of these kinds are important and valuable. They are, however, outside of the scope that we (somewhat arbitrarily) choose to display in this particular diagram.
Probably not. Unfortunately, most publishers do not publish their data with an explicit license. This leaves re-users in the dark about the specific rights that are granted or reserved by the publisher.
Given this state of affairs, we take a liberal view of what we consider “open”. If the data is openly accessible from a network point of view – that is, it's not behind an authorization check or paywall – then we will probably add it to the Cloud.
Before using any data, you should always check the publisher's website for the terms and conditions. If you don't find anything, then the safest course of action is to assume that the publisher reserves all rights…
(Note that the Data Hub takes a stricter view on openness and considers a dataset “open” only if it has an explicit license that meets the Open Definition.)
This diagram shows a particular perspective on the Web of Data. There are many other possible, perfectly valid, and valuable perspectives as well, that focus on other data formats, on other publishing methods, and on highlighting other aspects besides size, topic and interlinks. We chose to show this particular view, and encourage everyone to explore and visualise other views as well. See the Related Resources section for similar visualisations.
We occasionally update the diagram. Ask us if you need a more precise answer.
The image shows datasets that are published in Linked Data format and are interlinked with other dataset in the cloud.
The size of the circles corresponds to the number edges connected to each dataset. The numbers are calculated based on connected datasets in the diagram.
|Circle size||Edge count|
The line indicate the existence of at least one link between two datasets. A link, for our purposes, is an RDF triple where subject and object URIs are in the namespaces of different datasets.
In the interactive version, color of the line indicates the direction of the link, e.g., if a link from A to B is green then it means that dataset A contains RDF triples that use identifiers from B, and if it is read, it means that dataset B contains RDF triples that use identifiers from A .
Some versions of the cloud have separate pages with statistics about these datasets. There is no plan to continue this for any future versions of the diagram.
Other projects provide deeper information on the datasets in the LOD Cloud diagram:
Here are some similar or related efforts that visualise the Web of Data on a high level.