Description:
US government is spending billions of dollars on fighting with Wildland Fire, and this demos show their correlations.
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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: <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
SELECT ?p sum(xsd:integer (?o)) ?agency
WHERE
{GRAPH <http://data-gov.tw.rpi.edu/vocab/Dataset_401>
{
# 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 <http://data-gov.tw.rpi.edu/vocab/p/401/account_name> ?account_name.
?s <http://data-gov.tw.rpi.edu/vocab/p/401/bureau_name> ?bureau.
?s <http://data-gov.tw.rpi.edu/vocab/p/401/agency_name> ?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
FROM <http://data-gov.tw.rpi.edu/wiki/Special:Ask/-5B-5BCategory:Wildfire-20News-20Item-5D-5D/-3FDcterms:created%3Ddate/sort%3DDcterms:created/order%3DDESC/format%3Drss/title%3DWildfire-20News/description%3DEvents-20important-20to-20Wildland-20Fire-20fighting-20and-20budgeting/limit%3D10>
WHERE {
?s <http://purl.org/rss/1.0/title> ?title .
?s <http://purl.org/rss/1.0/link> ?link .
?s <http://purl.org/rss/1.0/description> ?description .
?s <http://purl.org/dc/elements/1.1/date> ?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
http://dbpedia.org/sparql.
SELECT distinct ?subject ?label ?comment ?page ?image ?arces
WHERE {
{
{
{
?s a <http://dbpedia.org/class/yago/WildfiresInTheUnitedStates>.
?s <http://www.w3.org/2000/01/rdf-schema#label> ?label.
filter (lang(?label)="en")
}
?s <http://www.w3.org/2004/02/skos/core#subject> ?subject.
filter(regex(?subject,"[1-2][0-9][0-9][0-9]_in_the_United_States"))
}
?s <http://www.w3.org/2000/01/rdf-schema#comment> ?comment.
?s <http://xmlns.com/foaf/0.1/page> ?page.
optional{ ?s <http://xmlns.com/foaf/0.1/depiction> ?image. }
optional{ ?s <http://dbpedia.org/property/acres> ?arces. }
filter (lang(?comment)="en")
}
}