Towards FAIR Data Sharing in the German Medical Informatics Initiative
Ganslandt T1, Sax U2, Semler SC3
1 Heinrich-Lanz-Center for Digital Health (HLZ), Mannheim University Medicine, Ruprecht-Karls-University Heidelberg2 Department of Medical Informatics, University Medicine Göttingen3 Technology & Method Platform for Networked Medical Research (TMF) e.V. Berlin
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Grant 01ZZ1801E
The German Medical Informatics Initiative
MEDINFO 2019 Lyon - Workshop FAIR Data Sharing | Ganslandt T | Towards FAIR Data Sharing in the German MII | 26.08.2019 Page 2
Foster re-use ofroutine clinical data
Demonstrate utilitythrough clinical use cases
StrengthenMedical Informatics
as a discipline
150 M€ fundingby BMBF
Long-term perspective
The 4 MII Consortia
MEDINFO 2019 Lyon - Workshop FAIR Data Sharing | Ganslandt T | Towards FAIR Data Sharing in the German MII | 26.08.2019 Page 3
Image source: http://www.medizininformatik-initiative.de/en/node/5
The Collaborative MII Governance Structure & Working Groups
MEDINFO 2019 Lyon - Workshop FAIR Data Sharing | Ganslandt T | Towards FAIR Data Sharing in the German MII | 26.08.2019 Page 4
Image source: https://www.medizininformatik-initiative.de/en/about-initiative/organisational-structure-and-actors
Where can we realize FAIR along the research process?
MEDINFO 2019 Lyon - Workshop FAIR Data Sharing | Ganslandt T | Towards FAIR Data Sharing in the German MII | 26.08.2019 Page 5
Consent WG
Broad consent, Consent implementation
Data Sharing WG
SharedPolicies
HarmonizedProcesses
Central projectregistry
Interoperability WG
MII Coredataset
Metadataannotation
Research process
Interoperability WG Modular MII Core Dataset
MEDINFO 2019 Lyon - Workshop FAIR Data Sharing | Ganslandt T | Towards FAIR Data Sharing in the German MII | 26.08.2019 Page 6
Oncology Pathology findings
Imaging findings
PDMS/Biosignals
Biomaterial
Genetic tests Structure data
Billing codes
Cost data
Exte
nsi
on
mo
du
les
Diagnoses
Procedures
Lab findings
Medication
PersonDemographics Case data
Bas
ic m
od
ule
s
Definition of scope & priorities mandatory vs. optional modules based on data availability & relevance
to the consortial use cases
Abstraction of consortial data structures essential for cross-consortial data usage shared definition of data structures & terminologies based on HL7 FHIR profiles governance process, including HL7 balloting
FAIR
I1: broadly applicable knowledge representation I2: vocabularies that follow FAIR principles R1.3: meets domain-relevant community standards
Interoperability WG Metadata Annotation
MEDINFO 2019 Lyon - Workshop FAIR Data Sharing | Ganslandt T | Towards FAIR Data Sharing in the German MII | 26.08.2019 Page 7
Description of data availability “in general” regarding types & volume of data
(inventory & map of MII data, also curated sets) specifically regarding data protection restrictions
Description of data provenance “in general” regarding data sources, intention
of data capture and transformations specifically for core dataset modules (e.g. laboratory
equipment & test kits used to create a finding)
Description of data quality “in general” regarding overall quality metrics specifically regarding fitness for individual use
FAIR
F2: described with rich metadata R1: richly described with relevant attributes R1.2: associated with detailed provenance
Data Sharing WG Policies, Processes & Central Registry
MEDINFO 2019 Lyon - Workshop FAIR Data Sharing | Ganslandt T | Towards FAIR Data Sharing in the German MII | 26.08.2019 Page 8
Shared data usage policy including mandatory terms of service,
data transfer agreements & governance structures mandate to archive & share result data
Harmonized data sharing processes currently being modelled in BPMN to be supported by consortial software
implementations
Central project registry organizes cross-consortial access to data provides register of both consortial as well as
cross-consortial data projects
FAIR
F4: registered or indexed in a searchable resource A2: metadata stay accessible R1.1: clear and accessible usage license
Consent WG Capture & Application of Patient Consent
MEDINFO 2019 Lyon - Workshop FAIR Data Sharing | Ganslandt T | Towards FAIR Data Sharing in the German MII | 26.08.2019 Page 9
Establishment of broad consent document modular, including use of biospecimens,
insurance data and re-contacting the patients coordinated with state & federal data protection
offices as well as association of ethics committees
Implementation of consent structured electronic representation electronic capture of consent
FAIR R1: richly described with relevant attributes
R1.1: clear and accessible usage license
MII (upcoming) FAIR Achievements & Challenges
MEDINFO 2019 Lyon - Workshop FAIR Data Sharing | Ganslandt T | Towards FAIR Data Sharing in the German MII | 26.08.2019 Page 10
F2: described with rich metadata F4: registered or indexed in a searchable resource
A2: metadata stay accessible
I1: broadly applicable knowledge representation I2: vocabularies that follow FAIR principles
R1: richly described with relevant attributes R1.1: clear and accessible usage license R1.2: associated with detailed provenance R1.3: meets domain-relevant community standards
FAIR
No
t ye
tFA
IR F1: globally unique & persistent identifier F3: metadata includes identifier of referenced data
A1: retrievable by identifier over open protocol
I3: includes references to other (meta)data
local responsibilityfor archiving
limited detailsin central registry
availability/licensing ofterminologies (e.g. SNOMED CT)?
mapping to othercommon data models?
structured representation /compatibility to CC licenses?
Evaluation of Personal Health TrainIntegration of identifiers
into research process
Outlook: German National Research Data Infrastructure (NFDI)
MEDINFO 2019 Lyon - Workshop FAIR Data Sharing | Ganslandt T | Towards FAIR Data Sharing in the German MII | 26.08.2019 Page 11
NFDI 4 Medicine
FAIR Implementation for secondary use
as well as basic research
sustainability
current status:LOI received,
grant proposal TBD by October 2019