linked environment data and how we are implementing seis søren roug
TRANSCRIPT
Linked Environment Dataand
how we are implementingSEIS
Søren Roug
The current situation
• Find dataset
The current situation
• Find dataset• Download it
The current situation
• Find dataset• Download it• Import it
The current situation
• Find dataset• Download it• Import it• Clean it
The current situation
• Find dataset• Download it• Import it• Clean it• Create chart
Vision statement
Too much manual work
We want to eliminate all steps but the last!
...And we’re going to use Linked Data technology to do it
Solution to the data format problem
• In addition to the HTML for human eyes we’re asking for a new format called RDF that machines can understand
• It is a modernisation of CSV, Excel and all the other data dump formats
• This is all we ask a producer to provide... and some metadata
• No Web Services – just files
No more searching on foreign sites
• The remote nodes provide lists of their datasets
• Called manifests or semantic sitemaps• Also in RDF format• Controlled vocabulary URLs in metadata
Use any identifier, we create equivalence links between them
How to create equivalence links
• We set up correspondance tables between the URLs.
• This is called an ontologyhttp://eurostat.europa.eu/countries#UK
= http://eea.europa.eu/countries.rdf#GB
• Some RDF databases handle ontologies transparently. When you use one, you get the data for the other too
Remember this?
Now we can make the join
Downloading made easy!
Click on the title to see if it is in the database
Downloading made easy
Seconds later...
Status
• EEA has deployed two triple stores called Content Registry and Semantic Data Service that import all lists and all data• Content Registry is for Reportnet deliveries• Semantic Data Service is for published
datasets
• We have created RDF of several data sets: Reportnet, GEMET, EUNIS, ITIS, NUTS, NACE etc.
• We can also load Eurostat SDMX data via the LATC project
SDS and CR’s Role
ITIS Reportnet PRTR
Harvesting
ContentRegistry
EUNIS Other...
SPARQL JSON RDF Querying
RDFRDF RDF XML
OtherVisualisationEUNIS ReportnetQA system
Queries
Comparing data: Where do EUNIS and ITIS not agree on naming?
PREFIX e: <http://eunis.eea.europa.eu/rdf/species-schema.rdf#>PREFIX itis: <http://eunis.eea.europa.eu/rdf/schema.rdf#>PREFIX dwc: <http://rs.tdwg.org/dwc/terms/> SELECT ?eunisname ?eunisauthor ?itisname ?itisauthor ?usage WHERE { ?eunisurl e:validName 1; e:sameSynonym ?itisurl; e:binomialName ?eunisname; dwc:scientificNameAuthorship ?eunisauthor. ?itisurl itis:nameUsage "invalid",?usage; itis:completename ?itisname; itis:hasAuthor ?auurl. ?auurl itis:shortAuthor ?itisauthor}
Results
eunisname eunisauthor itisname itisauthor usage
Chondrocladia alaskensis
Lambe,1900 Chondrocladia alaskensis
Lambe 1895 invalid
Myxilla parasitica (Lambe,1900) Myxilla parasitica Lambe 1893 invalid
Hymedesmia primitiva
Lundbeck,1910 Hymedesmia primitiva
Lundbeck 1910 invalid
Asbestopluma lycopodium
(Levinsen,1886) Asbestopluma lycopodium
Levinsen 1886 invalid
Esperiopsis rigida
Lambe,1900 Esperiopsis rigida Lambe 1893 invalid
Cordylophora lacustris
Allman, 1844 Cordylophora lacustris
Allman 1844 invalid
Example of SPARQL queryFuture prospects for the European otter
(From Reportnet)
PREFIX art17: <http://rdfdata.eionet.europa.eu/art17/ontology/>PREFIX eea: <http://rdfdata.eionet.europa.eu/eea/ontology/> SELECT ?country ?region ?future WHERE {[] art17:forSpecies <http://eunis.eea.europa.eu/species/1435>; art17:hasRegionalReport ?report.?report art17:conclusion_future ?future; art17:forCountry ?curl; art17:region ?bgregion.?bgregion eea:name ?region.?curl eea:name ?country} ORDER BY ?country ?region
Result: Future of the European otter
country region future
Austria Alpine Inadequate (U1)
Austria Continental Inadequate (U1)
Belgium Atlantic Bad (U2)
Belgium Continental Bad but improving (U2+)
Czech Republic Continental Favourable (FV)
Czech Republic Pannonian Favourable (FV)
Estonia Boreal Favourable (FV)
Queries on EUNIS
Visualisations
Water use per NUTS level 2 in 2007Top 20
Combination of twoEurostat SDMX datasets
Linked Data in map views
GHG per capita 1990-2009
