Demo: Linking Wildland Fire and Government Budget

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Infobox (featured demo) edit with form
  • name: Demo: Linking Wildland Fire and Government Budget

live demo here


Facts about this Demonstration

Live Demo(s)
Video Demo(s) Data source(s)
Other Data source(s)
Technology Used
Related SPARQL
Related Demo(s)

Interesting Observations

  • billions of dollars are spent on fighting wildland fire.
  • the big drop of wild fire in 1985 is strange, can we find explanations.
  • While the number of fires are more stable in the past 20 year, the amount of burned land has been growing in the past five years. Meanwhile, the budget is also growing (almost non-linearly in recent years). It would useful to explain which department, Department of the Interior or Department of Agriculture, is taking the primary role in fighing wildland fire and should receive more budget allocation.
more information

Technology Highlights

Find relevant data in Budget Dataset

We use SPARQL to list relevant Budget Accounts

PREFIX rdf: <> 
SELECT ?p  sum(xsd:integer (?o)) ?agency
 # match the specific BGP first, then filter based on account_name. only join with the completely unbound triple pattern after the filter so that the intermediate result size isn't large.
  ?s 	<> ?account_name.
  ?s  <> ?bureau.
  ?s <> ?agency . 
  filter (regex(?account_name,"Wildland Fire"))
 ?s ?p ?o.
group by ?p ?agency

Collect Annotations from Users

We use semantic wiki to help users collaboratively contribute news on Dataset_WildfireNews. The news is then published on-the-fly via Wildfire News RSS

Here, the RSS data is not loaded into the triple store, so it will be related every time we reload the live demo. Following is the sample sparql query (with FROM clause):

SELECT ?date ?title ?link
?s <> ?title .
?s <> ?link .
?s <> ?description .
?s <> ?date.

Connect to Dbpedia/Wikipedia

We can query dbpedia for wildland fires in the US using the category yago-class:WildfiresInTheUnitedStates. Note that dbpedia provide sparql endpoint at

SELECT distinct ?subject ?label ?comment ?page ?image ?arces
      ?s a <>.
      ?s <> ?label.
      filter (lang(?label)="en")
     ?s <> ?subject.
 ?s <> ?comment.  
 ?s <> ?page. 

  optional{ ?s <> ?image. }
  optional{ ?s <> ?arces. }

 filter (lang(?comment)="en")
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