This plugin is developped inside Inria, by the Wimmics research team, with the support of the Dream team.
This plugin is made available through the CeCILL-B licence.
The main page for the following videos can found at SemanticWebImport Plugin Videos.
The SemanticWebImport plugin is intended to allow the import of semantic data into Gephi. The imported data are obtained by processing a SPARQL request on the semantic data. The data can be accessed following three manners:
We begin by showing how to make run the preset examples which come with the plugin. Then we detail the three drivers allowing to import semantic data.
In all the following cases, it is required there is a currently opened project, otherwise the graph can not be built.
General Description of the GUIThe plugin consist of fourth tabs:
First tab of the plugin
This tab allows to select among the available SPARQL drivers how the semantic data can be accessed. Currently, the choice can be made between (i) access to local data through the Corese engine; (ii) access to a remote REST SPARQL endpoint; (iii) access to a remote SOAP SPARQL enpoint.
Second tab of the plugin
The SPARQL editor to enter a SPARQL request that extract the data used to build the graph. It is mandatory to be a construct request.
Third tab of the plugin
This tab contains the log, i.e. the outputs of the plugin.
Configurations managementFourth tab of the plugin
This tab allows to manage the configurations. I.e. it contains: (i) the selector for preset examples and the load button to activate them.
Note that to launch the query, the Run button is set at the bottom of the window.
To use the plugin, follow these steps:
To obtain the BBC example, foolow the following steps:
The Corese driver allows to process locally a SPARQL request on RDF files. The RDF files can be provided as:
CoreseDriver Panel
The CoreseDriver is made of three parts:
The REST SPARQL driver allows to make process a SPARQL request on a remote SPARQL endpoint with REST interface.
Rest Driver Panel
The Rest panel is made of the following parts:
The SOAP SPARQL driver has a single parameter, the URL of the endpoint.
Soap Driver Panel
Gephi: extensions in the SPARQL queryWhen building a query, some special keywords can be used to customize the results in gephi. http://gephi.org/ is used as the namespace for this extension. It is counselled to add the line "namespace gephi: http://gephi.org/" at the beginning of the query.
As previously stated, the import of data can be pre or post processed with a script plugin.
import org.openide.util.Lookup as Lookup import org.gephi.ranking.api.RankingController import org.gephi.ranking.api.Ranking as Ranking import org.gephi.ranking.api.Transformer as Transformer import java.awt.Color as Color rankingController = Lookup.getDefault().lookup(org.gephi.ranking.api.RankingController) # Set the color in function of the degree. degreeRanking = rankingController.getModel().getRanking(Ranking.NODE_ELEMENT, Ranking.DEGREE_RANKING); colorTransformer = rankingController.getModel().getTransformer(Ranking.NODE_ELEMENT, Transformer.RENDERABLE_COLOR) colorTransformer.setColors([Color.BLUE, Color.YELLOW]) rankingController.transform(degreeRanking, colorTransformer) # Set the size in function of the degree of the nodes. sizeTransformer = rankingController.getModel().getTransformer(Ranking.NODE_ELEMENT, Transformer.RENDERABLE_SIZE) sizeTransformer.setMinSize(3) sizeTransformer.setMaxSize(40) rankingController.transform(degreeRanking, sizeTransformer) ### Layout of the graph # Construction of a layout object import org.gephi.layout.plugin.forceAtlas2.ForceAtlas2Builder as ForceAtlas2Builder import org.gephi.layout.plugin.forceAtlas2.ForceAtlas2 as ForceAtlas2 fa2builder = ForceAtlas2Builder() fa2 = ForceAtlas2(fa2builder) # Setting the layout object import org.gephi.graph.api.GraphController as GraphController graphModel = Lookup.getDefault().lookup(GraphController).getModel() fa2.setGraphModel(graphModel) fa2.setAdjustSizes(True) # To prevent overlap print "executing layout" # Run the layout. fa2.initAlgo() for i in range(5000): fa2.goAlgo()
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