OpenAIRE-RDM@healthdata

Health Research Data Management
for Open Science
MD-Paedigree final conference, May 22-23 2017, Rome
@openaire_eu
Natalia Manola
OpenAIRE Managing Director
Athena Research & Innovation Centre

Outline
• Who we are
• Open Science (and health data)
• Europe’s OA policies
• Research data management practices

Question
How to guarantee the ongoing availability of
research data?
From local availability to distributed access.

Clinical data in predictive medicine
Researchers following 30,000 Type 2 diabetic patients
for a decade were able to use an analytics model to
predict the risk of developing dementia while suffering
from the endocrine disease
The Lancet Diabetes & Endocrinology journal
Clinical data IS research data

• Institutional, national and international
perspectives on OA policies & e-
Infrastructures
Open Access experts
• Building efficient e-Infra technologies
• State of the art technologies (big data,
linked data)
Information & Computer
Science experts
• Legal &policy recommendations
Legal experts
• Best practices for data
• Linking to data infrastructures
Data communities
Who we are
A European key e-Infrastructure to
support Open Access and Open
Science
In 24x7 operation since Dec 2010
Nodes in 34 countries
www.openaire.eu

Human
Network
Digital
Network
… foster the social and technical links
that enable Open Science in Europe and beyond
National Open Access
Desks (NOADs)
34 OA expert nodes in all Europe
• (OA) Policy aligning
• Technical assistance
• Training
Tools and services to
implement OA
At university/organization or
national

Human
Network
Digital
Network
… foster the social and technical links
that enable Open Science in Europe and beyond
National Open Access
Desks (NOADs)
34 OA expert nodes in all Europe
• (OA) Policy aligning
• Technical assistance
• Training
Tools and services to
implement OA
At university/organization or
nationalInteroperability at all levels -
technical, human, legal, policy, organizational

Integrated Scientific Information System
20 mi unique publications
800 validated data providers
500Κ publications linked to projects
from 12 funders
60 K datasets linked to
publications or funders
3.5 K links to software
All linked together - Linked Open Data

Open Science - beyond open data
CC-BY Andreas Neuhold
https://commons.wikimedia.org/wiki/File:Open_Science_-_Prinzipien.png
• Access to research facilities
• Access to processing
capabilities
• Communication at all levels
of research life cycle

Open Science - beyond open data
CC-BY Andreas Neuhold
https://commons.wikimedia.org/wiki/File:Open_Science_-_Prinzipien.png
• Access to research facilities
• Access to processing
capabilities
• Communication at all levels
of research life cycle
Change in how we
operate
interact with citizens
are evaluated
are valued
are taking decisions on policies

Why open data
•…
•Transparency
•Reproducibility
•Accountability
•...
TRUST

Why open data
•…
•Transparency
•Reproducibility
•Accountability
•...
Open data and data sharing are similar -
not identical
TRUST
“Most Published Research Findings Are False”- JPA Ioannidis, 2005

Data and decision flow in health
Traditional view
Doct
or
Admini
strator
Rese
arche
r

Data and decision flow in health
Current view
Innovator
Doct
or
Admini
strator
Rese
arche
r
Patient
Policy
Maker
Educator

Hospitals are research data
producing organizations
… and must guarantee availability of health
data beyond their participation in projects or
studies

Open Science requires good research data
management practices
Medical Data Challenges
1. Technical
2. Ethical
3. Legal
Same as other domains –
health is more sensitive

Data Flow for precision medicine
Data Mining
Disease signatures
Patient grouping & similarity
Personalized Model
Guided Medicine
For a particular
patient
Unknown / missing data
Predict value of missing
variable
Variable dependencies & causality
Simulation Models
Create Statistical
Simulation
Models
Individualized diagnosis,
prognosis & treatment plan
Model & VerificationKnowledge Discovery Reasoning & decision support
Domain knowledge &
assumptions
Clinical workflows
TOP-DOWNRaw data from biomarker based
personalized acquisition
Data
Preprocessing
Curation & Profiling
Transformed &
Validated Data
BOTTOM-UP
Data- & model-based medicine
Data produced in many stages

Data Flow for P. Medicine
Data Mining
Disease signatures
Patient grouping & similarity
Personalized Model
Guided Medicine
For a particular
patient
Unknown / missing data
Predict value of missing
variable
Variable dependencies & causality
Simulation Models
Create Statistical
Simulation
Models
Individualized diagnosis,
prognosis & treatment plan
Model & VerificationKnowledge Discovery Reasoning & decision support
Domain knowledge &
assumptions
Clinical workflows
TOP-DOWNRaw data from biomarker based
personalized acquisition
Data
Preprocessing
Curation & Profiling
Transformed &
Validated Data
BOTTOM-UP
Data- & model-based medicine
Data produced in many stages
Data in many cycles: produced and processed at different
stages
Data must have be properly stewarded at all stages
Data may be shared at any stage
• At least: open data linked to publication

CHALLENGES

Data ethics principles
• Privacy-preserving analysis of clinical data for research
• Transparency and explanation of results of opaque algorithms
• Honesty and lack of bias in result presentation
• …

Research reproducibility
• Data provenance
• Data cleaning and curation
• Data profiling and validation
• Data transformation for cleaning and curation
• Workflow support for repeating experiments and reproducing
results

Sharing data: legal mechanisms
• European legal context
• General Data Protection Regulation (GDPR)
• Give citizens control of their personal data - effective from 25
May 2018
• New mechanisms of trust and value-based relationships
between people, hospitals, research centres, businesses
• Smart contracts – blockchain
• Informed consent

H2020 Policies
OA Policies in Europe
… and beyond

H2020 Open Access policies
• Publications
• Openly accessible and minable.
Eligible costs for APCs.
• Research data
• Openly accessible research data
can typically be accessed, mined,
exploited, reproduced and
disseminated free of charge for the
user.

Publications ARE data!
2.5 mi EN publications published every year
Text and data mining the future way to extract knowledge

metadata
standards
persistent identifiers
permissive / simple licences
certified repositories
quality
vocabularies

Three top reasons to opt out
Anonymization ?

Data management for organisations -
a few rules of thumb

What should be preserved and shared?
• The data needed to validate results in scientific publications
(minimally!).
• The associated metadata: the dataset’s creator, title, year of
publication, repository, identifier etc.
• Follow a metadata standards and be FAIR.
• Documentation: code books, lab journals, informed consent
forms – domain-dependent, and important for understanding the
data and combining them with other data sources.
• Software, hardware, tools, syntax queries, machine
configurations – domain-dependent, and important for using the
data. (Alternative: information about the software etc.)

What should be preserved and shared?
• The data needed to validate results in scientific publications
(minimally!).
• The associated metadata: the dataset’s creator, title, year of
publication, repository, identifier etc.
• Follow a metadata standards and be FAIR.
• Documentation: code books, lab journals, informed consent
forms – domain-dependent, and important for understanding the
data and combining them with other data sources.
• Software, hardware, tools, syntax queries, machine
configurations – domain-dependent, and important for using the
data. (Alternative: information about the software etc.)
Basically, everything that is needed to
replicate a study should be available.

How much does it cost? Who pays?
• What are the costs for making data FAIR in your project?
• Resources needed for long term access
• “Well budgeted data stewardship plans should be made mandatory and
expect that on average about 5% of research expenditure should be spent
on properly managing and stewarding data”
• Who pays? How?
UKDS model http://www.data-archive.ac.uk/create-manage/planning-for-sharing/costing
HLEG report http://ec.europa.eu/research/openscience/pdf/realising_the_european_open_science_cloud_2016.pdf#view=fit&pagemode=none

How much does it cost? Who pays?
• What are the costs for making data FAIR in your project?
• Resources needed for long term access
• “Well budgeted data stewardship plans should be made mandatory and
expect that on average about 5% of research expenditure should be spent
on properly managing and stewarding data”
• Who pays? How?
UKDS model http://www.data-archive.ac.uk/create-manage/planning-for-sharing/costing
HLEG report http://ec.europa.eu/research/openscience/pdf/realising_the_european_open_science_cloud_2016.pdf#view=fit&pagemode=none
Hospitals:
Commit to investment for continuous data curation
Consider a resident data steward or data scientist

For how long?
RDNL Selection criteria: http://www.researchdata.nl/en/services/data-management/selecting-research-data/
DCC How-to guide: http://www.dcc.ac.uk/resources/how-guides/appraise-select-data
• When regenerating data is cheaper than archiving, don’t archive.
Select what data you’ll need and want to retain.
• 10 years is often stated in data policies and academic codes, but
data can be valuable for ages, in climatology, sociology, health
sciences, astronomy, linguistics, …

For how long?
RDNL Selection criteria: http://www.researchdata.nl/en/services/data-management/selecting-research-data/
DCC How-to guide: http://www.dcc.ac.uk/resources/how-guides/appraise-select-data
• When regenerating data is cheaper than archiving, don’t archive.
Select what data you’ll need and want to retain.
• 10 years is often stated in data policies and academic codes, but
data can be valuable for ages, in climatology, sociology, health
sciences, astronomy, linguistics, …
Health: look beyond minimal retention periods

Institution
RDM policy
Facilities
€$£
Research
funders
Publishers
Data Availability
policy
Commercial
partners
Find who is responsible for what
https://www.openaire.eu/briefpaper-rdm-infonoads
Organization/hospital structure for data management

How can OpenAIRE help?
Participating in the
European Open Science Cloud initiative

Support material
Briefing papers, factsheets,
webinars, workshops, FAQs
Information on
• Open Research Data Pilot
• Creating a data management
plan
• Selecting a data repository
• Personal data
Helpdesk - in 34 countries
Training

OpenAIRE services
• Integrated research catalogue (pubs, data, ..)
• Zenodo (@CERN) – repository for all types of publications, data
and software
• Amnesia - an anonymization tool for all
• Data providers – Interoperability Guidelines, validation,…
• Project coordinators – reporting
• Funders and institutions – monitoring
• Research communities – gathering, monitoring all research
MONITORING DASHBOARDS

OpenAIRE services
• Integrated research catalogue (pubs, data, ..)
• Zenodo (@CERN) – repository for all types of publications, data
and software
• Amnesia - an anonymization tool for all
• Data providers – Interoperability Guidelines, validation,…
• Project coordinators – reporting
• Funders and institutions – monitoring
• Research communities – gathering, monitoring all research
MONITORING DASHBOARDS
Be part of the research ecosystem.
Get connected!

www.openaire.eu
@openaire_eu
facebook.com/groups/openaire
linkedin.com/groups/OpenAIRE-3893548
Thank you!
natalia@di.uoa.gr
Questions?

OpenAIRE-RDM@healthdata

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