linked data for improved vaccine information systems

https://w3id.org/vacseen SWAT4LS, 8th December 2015, Cambridge

Getting VacSeen-ated: Linked Data for ImprovedVaccine Information Systems

Monika Solankihttps://w3id.org/people/msolanki

@nimonika

University of Oxford

Joint work withPartha S Bhattacharjee, Rahul Bhattacharyya, Isaac Ehrenberg,

Sanjay SarmaAuto ID Labs, MIT

https://w3id.org/vacseen

https://w3id.org/people/msolanki


MotivationThe expansion of vaccine programs globally...

[email protected], @nimonika Linked Data for Improved Vaccine Information Systems



Motivation...has accentuated challenges for governments...

Most developing countries are not equipped to efficiently store,track, and transport increased vaccine volumes




Motivation...and manufacturers

Lack of visibility and control over supply chainLimited ability for demand forecastingExposure to counterfeiting and diversion of productsLimited ability to cope with regulatory developments




MotivationSeveral approaches are under development to address the vaccineaccess challenge




Motivation

ObservationsDespite improved information flow, issues aboutinteroperability and at-scale last mile tracking continue topersist.Several studies have reported the effectiveness of usingbarcodes in tracking vaccine consumption.




MotivationOur research focuses on the Information Technology dimension




ContributionsDemonstrate the utility of VacSeen in authenticatingbarcode scans and generating attendant rich contextualinformation.Geolocate and classify the scans based on whether or notthey were recorded by authorized personnel usingauthenticated devices.Exploit multiple data sources: mobile applications, barcodedatabases, healthcare provider databases and LOD cloud.Two (mobile/Android) applications: generate biomedicalfactsheets about the vaccines, identifying nearest airport toa selected scan location.




VacSeen: Process flowMobile-based barcode scans on the field are retrospectively validatedusing a data lake formed from logistical and health informationsystems




VacSeen: Knowledge representation

EEM*: The EPCIS Event ModelVaccine transaction events as abstractions for traceability.Focuses on a tight conformance with the EPCIS 1.1*standard and Simplicity.EEM has been mapped* to PROV-O*.

*http://purl.org/eem#*http://www.w3.org/ns/prov#

*http://www.gs1.org/epcis*http://fispace.aston.ac.uk/ontologies/eem_prov.html

M. Solanki et al. EPCIS event-based traceability in pharmaceutical supplychains via automated generation of linked pedigrees. ISWC 2014



http://purl.org/eem#

http://www.w3.org/ns/prov#

http://www.gs1.org/epcis

http://fispace.aston.ac.uk/ontologies/eem_prov.html


VacSeen: Knowledge representationEEM modules

Temporaltime of occurrencetime of recordtimezone offset

BusinessActionDispositionBusiness stepTransaction

ProductEPCEPCClassAggregation IdentifiersInput/Output Quantity List

SpatialReadPoint LocationBusiness LocationSourceDestination

EPCIS EventObject EventAggregationEventTransactionEventTransformationEventQuantityEvent** Deprecated in EPCIS 1.1

Structure of EEM

Sensors

EPC Readers

GoodRelations,CollectionsDUL

Semantic Sensor Network Ontology

wgs84, vCard

DUL

CBVVocabPROV-O

EPCISExceptionHierarchy of EPCISException




VacSeen: Knowledge representationVacSeen1*

The VacSeen1 ontology uses and extends EEM to model barcodescan, product, and personnel data

Extended with existing, well known ontologies to fullyaddress the needs of the project.Light-weight ontology with just enough formalization toenable detailed querying.Minimal rules to avoid issues pertaining to inferencing.

*http://www.violinet.org/vaccineontology/



http://www.violinet.org/vaccineontology/


VacSeen: Knowledge representation

Important stepsGeneration of persistent URIsUsing ontology classes in RDB-RDF translation

Next stepsMaking URIs dereferenceableUsing classes from Vaccine Ontology and Vaccine AdverseEvent Ontology for new applications




VacSeen: RDB→RDF using D2RQ

While R2RML is the standard for RDB→RDF translation,D2RQ is used because of its similarity with RDF, extensivesupport, and compatibility with the former.Logically closer to RDF than RDB compared to R2RMLresulting in relatively less complex queries.Supports standards such as R2RML.Extensively used and well documented.




VacSeen: RDB→RDF using D2RQ

Important stepsCustomization of mapping file using ontology terms.Enforcement of integrity constraints on data by specifyingintegrity constraints in the mapping file.




VacSeen: Data storage

Triplestore: GraphDB-Lite over Sesame

Graphical Interface for implementation by less technicalusers.Freely available.DL and rule-based reasoning support.Multiple options for storage, access, and querying.

Datasets loaded and used: vaccine data, healthcare systemdata, and barcode scan data.




VacSeen: Typical SPARQL queriesLatitude, Longitude, operatorID, deviceID of scan events where theGTIN scanned exists in the sc_data database, the operator ID existsin the scan_operator table, and the device ID exists in thescan_device table

Query using EEM & VacSeen1SELECT DISTINCT ?EPCISEvent ?GTIN ?operatorID ?deviceID ?latitude ?longitudeWHERE{

?EPCISEvent a eem:EPCISEvent.?EPCISEvent vacseen1:ScanID ?scanID.?EPCISEvent eem:EPCNumber ?GTIN.?s vacseen1:sc_data_GTIN ?GTIN.?EPCISEvent vacseen1:scan_event_operatorID ?operatorID.?scanOperator vacseen1:scan_operator_OperatorID ?operatorID.?EPCISEvent vacseen1:scan_event_deviceID ?deviceID.?scanDevice vacseen1:scan_device_DeviceID ?deviceID.?EPCISEvent vacseen1:LatitudeOfBarcodeScanEvent ?latitude.FILTER(?latitude > ’0.0’).?EPCISEvent vacseen1:LongitudeOfBarcodeScanEvent ?longitude.

}




VacSeen: Typical SPARQL queries

Data about Rotavirus vaccine from DBpediaINSERT{?s ?p ?o}WHERE{SERVICE <http://dbpedia.org/sparql>{{

:Rotavirus_vaccine ?p ?o.BIND(:Rotavirus_vaccine AS ?s)

}UNION{?s ?p :Rotavirus_vaccine.BIND(:Rotavirus_vaccine AS ?o)

}}

}




VacSeen: Data storageWhile it is easy to get started with Sesame and do routine operations,issues can arise when using plug-ins

ChallengesIssues with “jsonp callbacks” because of incompatibility of GraphDB-Lite with recent releases of Sesame.

Absence of access to SPARQL lifting because of aforementioned incompatibility

Absent GraphDB customer-support for non-paying users

ResolutionSesame mailing lists

Replacement of jar files as a temporary measure

Permanent solution through replacement of jsonp callback with CORS headers for cross-domain access




VacSeen: Exploiting the LOD cloud

Two applications:

Creating biomedical factsheets about vaccines using Dbpedia.

Identifying nearest airports to every scan location for logisticalplanning.




VacSeen: Scan Authentication

Provides additional context for each barcode scan to get adeeper understanding about vaccine handling operations.




VacSeen: Next steps

Future work will focus on developing more advanced LinkedData-based applications that leverage large scale and secure data



linked data for improved vaccine information systems

Healthcare