,
,
,
, , vol.145
,
, 156 9.4.1 Jeux de données, requêtes et configuration, vol.156
,
, Ces données stockées demeurent indispensables dans plusieurs domaines d'application tels que l'e-santé, la biologie, l'étude de la biodiversité, etc., où le croisement de données statiques et dynamique est requis. Pour la gestion combinée de données RDF statiques et dynamiques, plusieurs systèmes RSP tels que C-SPARQL, CQELS et CQELS Cloud prennent en charge le croisement (jointure) entre données RDF statiques et dynamiques. Ces systèmes réalisent la jointure 9.4 Évaluations Cette section évalue le système proposé à partir de la section 9, Les données RDF stockées sont très importantes dans le contexte des flux de données RDF. Ces données concernent les ontologies de domaine associées à un domaine d'application des flux de données, des données RDF résumées et/ou historiées des données RDF à fréquence de rafraîchissement très lent (hebdomadaire, mensuel, semestriel, trimestriel
, Nous utilisons trois ensembles de données du monde réel utilisés dans les benchmarks SRBench, vol.4
, Ces jeux de données contiennent (i ) des données RDF en continu collectées depuis les stations météorologiques des US (LinkedSensorData 5 ), (i i ) des données RDF stockées décrivant l'emplacement des stations (GeoNames 6 ) et (i i i ) les localisations de GeoNames décrites dans un autre jeu de données RDF stocké
, La Figure 9.7 présente un aperçu des flux de données utilisés et des jeux de données stockées. En tant que flux de fichiers RDF, nous utilisons un ensemble de données Linked-5
, 165 10.1.2 2 ème contribution : résumé orienté graphe de flux de données RDF 166 10.1.3 3 ème contribution : interrogation de flux de données RDF compressées au format RDSZ
, 168 10.2.1 Exploration et élagage de graphes RDF
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, Requête Q4 Query q4 AS SELECT ?sensor ?, value FROM STREAM <ht t p : //ex.sh >
, WHERE { ?eventID ssn :hasValue observation ; ssn :isProducedBy ?sensor
, SensorOutput. ?observation qudt :numValue ?value ; qudt :unit
, A.5 Requête Q5 QUERY q5 AS SELECT ?aSub ?anObj (count( distinct ?subject) as ?count)
,
, WHERE { ?subject weather :type ?object . ?aSub sens-obs :aProp ?anObj
, sens-obs :anotherProp ?anotherObj
, { select ?name (count( distinct ?object) as ?count2)
,
, /r eposi t or y.or g /bi bl i o.r d f > WHERE { ?object weather :name ?name
, aProp ?aName .} GROUP BY ?name }} GROUP by ?aSub ?anObj }
,
,
, FROM REPOSITORY <LSM> WHERE { ?sens om-owl :processLocation ?sensLocation ; om-owl :generatedObs ?obs . ?sensLocation wgs84_pos :alt "%Altitude%"??xsd :float ; wgs84_pos :lat "%Latitude%"??xsd :float ; wgs84_pos :long "%Longitude%"??xsd :float. ?obs om-owl :observedPrty weather :_AirTemp ; om-owl :result [om-owl :floatValue ?temp].} GROUP BY ?sens B.2 Requête Q10 SELECT DISTINCT ?lat ?, SELECT (MIN( ?temperature) AS ?minTemperature) (MAX( ?temperature) AS ?maxTemperature) FROM STREAM <LObD>
, ?sensor om-owl :processLocation ?sensorLocation . ?sensorLocation wgs84_pos :alt ?alt
, Requête Q11 SELECT DISTINCT ?sensor FROM STREAM <LObD> [RANGE 60s TUMBLING] FROM REPOSITORY <LSM> WHERE { ?sensor om-owl :generatedObservation ?observation
, om-owl :hasLocatedNearRel [om-owl :hasLocation ?nearbyLocation
, ?observation a ?observationType
, om-owl :observedProperty ?observationProperty
, om-owl :result
, SELECT AVG( ?value2) AS ?avgValue WHERE { ?sensor2 om-owl :generatedObservation ?observation2
, FILTER ( sameTerm( ?nearbyLocation, ?nearbyLocation2)) ?observation2 a ?observationType
, om-owl :observedProperty ?observationProperty
, FILTER ( ABS( ?value -?avgValue) / ?avgValue> "0.10"??xsd :float)
, FROM REPOSITORY <LSM> FROM REPOSITORY <GeoNames> WHERE { ?sensor om-owl :generatedObservation ?temperatureObservation ; om-owl :generatedObservation ?humidityObservation, Requête Q12 SELECT ?name (AVG( ?temperature) AS ?avgTemperature) (AVG( ?humidity) AS ?avgHumidity) FROM STREAM <LObD>
, om-owl :hasLocatedNearRel [om-owl :hasLocation ?nearbyLocation
, ?temperatureObservation om-owl :observedProperty weather :_AirTemperature ; om-owl :result
, ?humidityObservation om-owl :observedProperty weather :_RelativeHumidity ; om-owl :result
, i"))} } UNION { SELECT ?name WHERE ?nearbyLocation gn :parentFeature+ ?parentFeature. ?parentFeature gn :featureClass ?parentClass ; gn :name | gn :officialName ?name, { SELECT ?name WHERE { ?nearbyLocation gn :featureClass ?featureClass ; gn :name | gn :officialName ?name ; gn :population ?population. FILTER ( ?population > 15000 && REGEX( ?featureClass, "P
, FROM REPOSITORY <LSM> FROM REPOSITORY <GeoNames> WHERE { ?airport gn :featureClass ?airportClass ; wgs84_pos :lat ?lat ; wgs84_pos :long ?long ; gn :name|gn :officialName ?airportName ; gn :parentFeature+ ?city, city gn :featureClass ?cityClass. rdf :type/rdfs :subClassOf* yago :Hurricane111467018 ; dbpprop :damages ?damage. ?nearbyLocation gn :parentFeature* ?area. ?area gn :name|gn :officialName ?areaName.}