• LarkcProject
• WP2
• integration
• reasoning
• lyon

Identifying Reasoning and Selection (workshop in Lyon)

Scenarios

Simple reasoning with factForge

SPARQL query: find airports near London (example from http://factforge.net/sparql)

PREFIX geo-pos: <http://www.w3.org/2003/01/geo/wgs84_pos#>
PREFIX omgeo: <http://www.ontotext.com/owlim/geo#>
PREFIX dbpedia: <http://dbpedia.org/resource/>
PREFIX dbp-ont: <http://dbpedia.org/ontology/>
PREFIX ff: <http://factforge.net/>
PREFIX om: <http://www.ontotext.com/owlim/>

SELECT distinct ?airport ?label ?RR
WHERE {
        dbpedia:London geo-pos:lat ?latBase ;
                       geo-pos:long ?longBase .
        ?airport omgeo:nearby(?latBase ?longBase "50mi");
                 a dbp-ont:Airport ;
                 ff:preferredLabel ?label ;
                 om:hasRDFRank ?RR .
} ORDER BY DESC(?RR)

Repository: http://factforge.net/sparql

With (OWLIM) reasoning: 50 results Without: 0

• Which selection methods to use?
• Which reasoner to use?
• How to decide when the results are satisfying or not?

Urban Computing

Query 2: Show the restaurants which locate in Amsterdam Center and open on Monday morning.

Expressing the query above in SPARQL seems to be impossible, because the information come from different data sources with different data format. Some of them are not RDF-based (i.e., not semantic data). The location of restaurant may be found from Google map, whereas the open time of the restaurants may be found from the webpage of Amsterdam city guide, which is of text-format.

The SPARQL query may look like: (however, it is not correct). We need a domain-specific component for pre-processing of that kind of queries:

SELECT ?restaurant ?address
WHERE  {
        ?restaurant hasAddress ?address
        ?address in 'AmsterdamCenter'
        ?restaurant hasOpenTime ?openTime
        ?openTime hasDay 'Monday'
        ?opentime hasStartTime ?starttime
        ?starttime atPeriod 'Morning'.
}

7b (Angus)

it isn't as simple as just a sparql query. We hope to have experimental apparatus that technical WPs can use ready for the meeting

Rule-based reasoning ?

Have a usecase? Add it here

Reasoning with noisy data ?

Have a usecase? Add it here

Heuristics in the interleaving reasoning and selection workflow

1. Submit SPARQL query
2. Smart selection with heuristics (figure out which selector to use)
   • Do selection (return a set of statements)
3. Smart reasoning with heuristics (figure out which reasoner to use)
   • Do reasoning (return set of variable bindings)
4. Smart evaluation with heuristics (decide whether the output of reasoning is good enough)
   • if YES, go to 5
   • if NO, repeat 2 or 3 or both
5. return result

6. (optional) Ask the user to evaluate the relevance of results, and feed that into 4 (?QueryQuarry from MPG?)