A Semantic Approach for Digital

Long-Term Preservation of Electronic

Health Documents Stephan Kiefer, Fraunhofer Institute Biomedical Engineering

Fraunhofer Institute for Biomedical Engineering n  One of the 60 r+d institutes of Fraunhofer Society n  360 projects annually, 120 with industry, in the fields:

u Biotechnology and Biobanking Technology u Cryo-Biotechnology u Stem Cell Research u Neuromonitoring, Neuroprosthetics u Miniaturized Systems u Ultrasound Systems u eHealth, Telemedicine, e-Infrastructures

n  Fraunhofer Biomaterial Archives

Motivation and Background •  Transition from paper based to full

electronic health record.

•  Data need to be kept for decades. •  Life long electronic health records need

to be accessible and usable for up to 100 years and more.

•  Media, formats, standards, applications and operating systems will become obsolete.

•  Data volumes produced in the healthcare sector are immense.

=> Digital preservation requires planning.

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© Fraunhofer IBMT (Foto: Bernd Müller).

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Economical Solutions for Long Term Digital Preservation

3 4 INNOVATIONS USE CASES Healthcare Clinical Studies Financial Services 1. EVALUATE Cost, Value and Risk

2. AUTOMATE Preservation Lifecycle

3. PROTECT Content-aware data protection

4. SCALE using ICT innovations

http://www.ensure-fp7.eu

Typical Preservation Workflow

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ENSURE OAIS* based System Architecture

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*OAIS - Reference Model for an Open Archival Information System, ISO 14721:2003 AIP, SIP, DIP: OAIS Information Packages of the archive

OAIS and the role of ontologies in ltdp •  OAIS Archival Information Package:

–  Content Information: Data Object together with its Representation Information

–  Preservation Description Information: Reference, Fixity, Provenance and Context Information (i.e. PREMIS)

–  Packaging Information (i.e. XFDU)

•  Our approach: Modelling metadata through ontologies •  Focus on information discovery and retrieval •  Other potential usage: security/privacy, provenance

management, preservation planning •  A strong need to address ontology ageing.

Hope: Can be leveraged to trigger actions on the archive to ensure consistency and usability

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ltpao:ArchivalInformationPackage

xsd:string

ltpao:aipCopyId

ltpao:hasParent

ltdpao:isChildOf

xsd:string

ltpao:aipLogicalId

xsd:string

ltpao:aipVersionId

ltpao:AIPRole

ltpao:hasRole

ltdpao:isRoleOf

xsd:string

ltpao:aipName

nie:InformationElement

ltpao:PreservationInformationPackage

ltpao:ArchivalInformationPackage

ltpao:SubmissionInformationPackage

ltpao:DisseminationInformationPackage

ltpao:PreservationDescriptionInformation

ltpao:Reference

ltpao:Provenance ltpao:Context ltpao:Fixity

ltpao:AccessRights

nfo:Folder

nfo:DataContainer

ltpao:hasContentDataObject

isContentDataObjectOf

ltpao:descriptedBy

ltdpao:descripes

xsd:string

ltpao:aipCopyId

ltpao:hasParent

ltdpao:isChildOf

xsd:string

ltpao:aipLogicalId

xsd:string

ltpao:aipVersionId

ltpao:AIPRole

ltpao:hasRole

ltdpao:isRoleOf

ltpao:AIPStandardRole

ltpao:AIPStorletRole

ltpao:AIPTransformation

Role

xsd:stringltpao:externalId

xsd:dateTime

ltpao:dateLastFixityValidation

ltpao:PackageManifest

ltpao:XFDUManifest

ltpao:PREMISManifest

nfo:Document

ltpao:hasManifest

ltdpao:isManifestOf

ltpao:XIPManifest

nie:DataSource

xsd:string

ltpao:aipName

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Concept for an initial Long-Term Preservation

Archive Ontology (LTPAO)

OAIS archive specific knowledge: •  Metadata format •  Preservation Description

Information •  AIP related metadata

ENSURE Preservation Ontologies

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Preservation Ontology Framework Ingest

Preservation Ontology Framework Ontologies

Registry(Ontologies, Views,

RDFTemplates)

RDF Storage

Preservation Runtime

Information Selector

Semantic Indexer

- MIME-type identication- Full-text and metadata

extraction- RDF and PREMIS

encoding

Access

Semantic Search &

Query Interface

Query(SPARQL)

Data Retriever

Query Results (SPARQL Results XML)

Metadata store

requestIngest

Packager

Preservation Asset Digital Lifecycle Management

(PDALM)

Content-Aware Data

Protection

Preservation-Aware Storage

Services

Full-text Index

Ingest request Access request

openSearchGUI

prepareIndex (files location)

package(files location)

triggerReindex/

Transformation

storeRDF (RDF/XML)

startAccess (AIP IDs)

prepareDIP (files location)

getOntologies(Views)

synchronise

getRDFTemplatesOntologies Manager

(Maintenance, Versioning)

commitIndex (files location, AIP Id)

ontology update request

dpFilter(AIP Map)

Semantic Search & Query Interface

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Semantic Search & Query Interface

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ENSURE Preservation Ontologies

• Digital objects represented as instances of ontologies

• NEPOMUK Information Element ontologies used as upper-level ontologies

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Concept for a DICOM Data Model Ontology

DICOM Data Model specific knowledge:

•  Represents logical structure of DICOM elements and real world relations

•  Concentration on attributes that are relevant for later searches

nie:InformationElement

ddmo:DICOM_IOD

nfo:DataContainer

xsd:string

nfo:Media

ddmo:DICOM_IE

ddmo:Patient_IE ddmo:Study_IE ddmo:Serie_IE

ddmo:Visit_IE ddmo:Equipment_IE

ddmo:Image_IE

nfo:Visual

nfo:Image

ddmo:includeIE

ddmo:belongsToIOD

ddmo:isSubjectOf

ddmo:makesVisit

ddmo:includeStudy

ddmo:containsSerie

ddmo:containsImage

ddmo:DICOM_Module

ddmo:createsStudy

ddmo:Patient_Module

ddmo:includeModule

ddmo:belongsToIE

ddmo:attributePatientID

ddmo:DICOM_DIR

ddmo:belongsToFilesetddmo:decriptesFileset

xsd:stringddmo:attributePatientName

ddmo:includePatientModule

ddmo:belongsToPatientIE

ddmo:Visit_Module

ddmo:includeVisitModule

ddmo:belongsToVisitIE

ddmo:attributeVisitDate xsd:dateTime

ENSURE Preservation Ontologies

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DICOM Data Model Ontology (2)

•  Integration of established terminologies/taxonomies or domain ontologies

•  Example ICD10 codes (International Code of Diseases) as subclasses of Attribute ‘Admitting_Diagnosis’

ddmo:Admitting_Diagnosis

icd:InfectiousAndParasiticDiseases

icd:Neoplasms

icd:MalignantNeoplasms

Icd:InSituNeoplasms

icd:BenignNeoplasms

icd:NeoplasmsOfUncertain OrUnknownBehaviour

ENSURE Preservation Ontologies

•  Long-term accessibility and usability of eHealth data is an issue in healthcare organisations.

•  Ontologies and semantic web technologies can help to manage preservation metadata more effectively.

•  They enable searching and accessing digital objects with evolving search profiles (ongoing research).

•  They have also the potential to model preservation knowledge including evolving privacy policies as a whole.

•  The influence of updating ontologies on the consistency of the archive must be carefully analysed.

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Conclusions

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Questions? Contact: Stephan Kiefer Fraunhofer Institute for Biomedical Engineering Dep. Telematics & Intelligent Health Systems St. Ingbert, Germany stephan.kiefer@ibmt.fraunhofer.de Eliot Salant (co-ordinator) IBM Haifa Research Labs salant@il.ibm.com

http://www.ensure-fp7.eu The research leading to these results has received funding from the European Community's FP7 Research Framework Programme under grant agreement n° 270000.