OpenScienceLink General Intro
July 2013
CIP-ICT PSP-2012-6
ICT PSP Main Theme: Open
Data and Open Access to
Scientific Information
OpenScienceLink
OpenScienceLink General Intro, July 2013
Outline
• Presentation of Partners
• Short Introduction to the Project: Motivation,
Concept, Objectives, Approach, Tangible Outcomes,
Summary of Evaluation Comments
OpenScienceLink
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OpenScienceLink Consortium
Participant organisation
name
Short
Name
1
Technische Universität Dresden
TUD
2
National Technical University of
Athens
NTUA
Part.
4
5
Lithuanian University of Health
Sciences
National and Kapodistrian
University of Athens
Country
Expertise
Bioinformatics,
Semantic Search,
Germany
Medical Experts,
Data and Text
Mining
Social Networks,
Greece Semantic Reasoning,
SOA
LUHS
Lithuania
Medical Research
NKUA
Greece
Pharmacology
Research
6
Katholieke Universiteit Leuven
KU Leuven
Belgium
IPR/Legal
7
Consiglio Nazionale Delle
Ricerche
CNR
Italy
Clinical Research
8
Procon Ltd.
Procon
Bulgaria
Publisher
Germany
Semantic Search,
Text Mining, Data
Providers
9
Transinsight GmbH
OpenScienceLink
TI
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OpenScienceLink
Short Introduction to the Project
OpenScienceLink
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OpenScienceLink in Brief
Open Semantically-enabled, Social-aware Access to Scientific Data
Duration: 36 months
ICT PSP Main Theme identifier:
THEME 2 - DIGITAL CONTENT, OPEN DATA AND CREATIVITY
Objective 2.2: Open Data and open access to scientific information
b) Open access to scientific information
Budget:
Commission contribution: 2,099,977 euros
Total budget: 4,199,955 euros
Partners: 8
OpenScienceLink
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OpenScienceLink Landscape
Scientific Research Peer Review: biased; incomplete; slow
•
•
•
•
often limited reviewers’ expertise in the specific field
time consuming access to scientific information (dispersed, unlinked and likely hidden)
review outcome: often poorly justified and subjective
limited pool of reviewers
Research evaluation metrics and systems vs actual quality, novelty and impact of
the published work
• 15% of the journals’ scientific papers account for 50% of the citations
• the dynamics of the field and of the citations as well as the source of the latter not taken into
consideration
Limited publishing and sharing of scientific data
• Lack of motivation and means
• No linking with related research conducted
Detection of trends in biomedical and clinical research
• currently based on specific time snapshots of the research being conducted
• excessive amount of dispersed scientific information published daily (at a
variety of data sources) which is difficult to access, comprehend, evaluate and
link
OpenScienceLink
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The Biomedical Landscape in particular
Average Drug Development timeline: >10 years from basic research
to market
High failure rate :
Research
in
Biomedical
and
Clinical
Domain
5 in 5000 compounds that enter preclinical testing make it to
human testing
1 out of the 5 ones tested in people is approved
Cost per drug candidate is more than € 900 million, with the greatest
cost being failure.
New active ingredients reaching the patients yearly significantly
decreasing: ~ 60/year (late 1980s), 52 (1991), 31 (2001), 20-25
(currently)
Drug Repositioning
OpenScienceLink
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OpenScienceLink Overall Objectives
• To introduce and pilot a holistic approach to the
publication, sharing, linking, review and evaluation of
research results, based on the open access to scientific
information.
• To empower a novel eco-system for open access to
scientific information, which will provide a range of
added-value services for all stakeholders.
OpenScienceLink
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OpenScienceLink Pilot Services
#1 - Data journals development based on semantically-enabled
research dynamics detection
#2 - Novel open, semantically-assisted peer review process
#3 - Research Trends Detection and Analysis
#4: Dynamic researchers’ collaboration based on non-declared,
semantically-inferred relationships
#5: Scientific field-aware, Productivity- and Impact-oriented
Enhanced Research Evaluation Services
OpenScienceLink
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Research Dynamics-aware
Open Access Data Journals
Development
Data Mining for Biomedical
and Clinical Research Trends
Detection and Analysis
NovelPlatform
open, semanticallyOpenScienceLink
assisted peer review process
UniProt,
Data Mining for Proactive Formulation of Scientific
Collaborations
GO,
MeSH,
Scientific field-aware, Productivity- and Impactoriented Enhanced Research Evaluation System
OpenScienceLink Added-value Services
CDM,
DMAP,
Concept
Correlation
Ranking
PONTE Eligibility Criteria,
PONTE Global EHR,
PONTE Drug,
Term Cooccurrence
Index Building
PONTE Disease,
PONTE Target
SocIoS Data Model
Semantic
Filtering
Models/Ontologies
Ontology-based
Data mining
Knowledgebased Concept
Correlation
Social Media
Information
Aggregation
Content
Ranking
Crowd-sourcing
Mechanism
Community
Lifecycle
Monitoring
Influencer
Tracking
Results
Ranking
Text
Annotation
OpenScienceLink
Topic-based Community
Identification
Policy
Evaluation
Social Media Services
Open Access Data Infrastructure
PROMISCUOUS DATABASE
IUCLID DS
Registry of Open Access Repositories
Event
Detection
Recommendation
Semantic Data Mining and Reasoning
Services
Linked Data
(DrugBank,
Diseasome,
LinkedCT,
SIDER,…)
Sentiment
Analysis
Social Media Data Feeds
Social Media
Data
Social
Media
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GoPubMed Platform
A semantic search engine for the life sciences
Data mining, semantic
filtering and ranking
mechanisms
Document annotation with
ontology concepts
Instant ontology-based
viewing of the retrieved
results
OpenScienceLink
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PONTE Platform
• Provision of a set of tools, mechanisms, models
and services which facilitate the researchers’ work
towards formulating their test of hypothesis,
designing clinical trial protocols and selecting
subjects for potential recruitment to clinical trials:
 Intelligent semantic inference mechanisms
 Knowledge-based correlation services
 Models of clinical trial protocol, drug, disease,
target, patient health data, eligibility criteria,
…
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SocIoS Platform
• Social media aggregation
through a powerful object
model
• Social analytics services
• Cross-platform
application development
and deployment
• Open source components
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+Spaces Platform (positive spaces)
• Citizen engagement
through applications that
leverage on social media
platforms like Twitter and
Facebook but also 3D
virtual worlds
• Typical and innovative
engagement mechanisms
(polls, debates, Role
playing simulation)
• Cross-platform application
deployment
• Open source components
OpenScienceLink
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OpenScienceLink Impact (1/3)
Stakeholder
Expected Impact
Researchers
•Wider access to scientific information, and research data sets
•Boosting of academic excellence and allowing for equal opportunities
•Empower collaborative and/or cross disciplinary research;
•Faster and more reliable review of research work
•Acceleration in advancement of research
•Build research on others’ work with an increased degree of confidence
•Influence researchers into moving into new promising research areas
•Research data sharing will allow for reduction of the research effort replication
•Efficient access to related research work and data
•Less time-consuming process
Reviewers
•Stronger confidence for the review outcome
Gov. Funding •Efficient and effective allocation of governmental and private funds to research
Agencies / •Prioritisation of research efforts towards topics with high success potential
Research
•Speeding up of research agenda
Funding
Authorities
OpenScienceLink
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OpenScienceLink Impact (2/3)
Stakeholder
Expected Impact
•Building and maintenance of a reviewers’ pool with high relevance to the
journal’s field;
•Increased quality and reliability of the review outcome; limiting bias,
incompleteness and delays; increased level of confidence for the quality of the
research work
Publishers •Higher quality journals’ content through an improved review process
•Development of data journals with high expected impact; data sharing as
publication
•Improved publisher’s reputation within the research community
•Faster, more reliable decisions on developing/altering/ending journals based on
the identified research dynamics
•Faster access to novel R&D research
•Development of novel products and services that generate growth and job
positions, thereby addressing key societal challenges;
Citizens and
•Especially concerning the expected boosting of the biomedical and clinical
the Society
research domain:
(as a whole)
Reduced healthcare costs of tomorrow and more affordable medication;
Healthier citizens
Improving Quality of Life
OpenScienceLink
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OpenScienceLink Impact (3/3)
Stakeholder
Expected Impact
•More accurate and of higher success potential identification of research areas
for funding and resource allocation
•Improved, scientifically-sound prioritisation of research efforts
Enterprises •Efficient reaching to high-quality researchers within a specific research field
relying on
(which is of the company’s interest) for collaboration and thus establishment of
R&D for
stronger bonds between industry and researchers
their
•Access to and use of more reliable metrics representing the research value (in
products
terms of quality, efficiency, relevance and viability) of published research work,
and services researchers and institutions
(e.g.,
•Earlier and more reliable decisions resulting in reduced costs and reduction of
pharma
opportunity costs
companies) •Improved resource management through early identification of failure and
repositioning of resources to other research areas of great interest and with
high impact
•Reduced reluctance of companies to invest in research
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Service-oriented
Architecture (SOA)
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Technical Interoperability
• XML based protocols (SOAP or REST)
• Related Web Services
–
–
–
–
–
–
SOAP 1.2
Web Services Addressing
Web Services Notification
WSDL-S
Web Services Metadata Exchange
Web Services Resource Framework
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Data Interoperability
• Open Archives Initiative Protocol for Metadata
Harvesting (OAI-PMH)
• OAI-PMH will be employed by data providers
wishing to make their data available to the
harvesters of the OpenScienceLink platform
• This protocol will be also used in order to publish
metadata and enable search over its
repositories
OpenScienceLink
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Semantic Interoperability
• W3C RDF/OWL ontologies
• Linked Data approach
• UMLS mappings between domain ontologies
(GO, MeSH, UniProt)
• Shared models
OpenScienceLink
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Thank you very much!
► Want to get involved?
Visit us at:
http://projects.biotec.tu-dresden.de/opensciencelink/
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