OpenScienceLink OpenScienceLink General Intro, July 2013 July 2013 OpenScienceLink General Intro...

OpenScienceLink OpenScienceLink General Intro, July 2013

July 2013

OpenScienceLink General Intro

CIP-ICT PSP-2012-6ICT PSP Main Theme: Open Data and Open Access to Scientific Information


Outline

• Presentation of Partners

• Short Introduction to the Project: Motivation, Concept, Objectives, Approach, Tangible Outcomes, Summary of Evaluation Comments

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OpenScienceLink ConsortiumPart. Participant organisation

nameShort Name

Country Expertise

1 Technische Universität Dresden TUD German

y

Bioinformatics, Semantic Search, Medical Experts,

Data and Text Mining

2 National Technical University of Athens NTUA Greece

Social Networks, Semantic

Reasoning, SOA

4 Lithuanian University of Health Sciences LUHS Lithuani

a Medical Research

5 National and Kapodistrian University of Athens 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

9 Transinsight GmbH TI Germany

Semantic Search, Text Mining, Data

Providers

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OpenScienceLinkShort Introduction to the Project

4


OpenScienceLink in Brief

Open Semantically-enabled, Social-aware Access to Scientific DataDuration: 36 monthsICT 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 informationBudget:

Commission contribution: 2,099,977 eurosTotal budget: 4,199,955 euros

Partners: 8

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OpenScienceLink LandscapeScientific 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

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The Biomedical Landscape in particular

Research in

Biomedical and

Clinical Domain

Average Drug Development timeline: >10 years from basic research to market

High failure rate :

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

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OpenScienceLink Overall Objectives

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• 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 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

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OpenScienceLink Platform

Social Media ServicesSemantic Data Mining and Reasoning

Services

OpenScienceLink Added-value Services

Ontology-based Data mining

Crowd-sourcing Mechanism

Influencer Tracking

Topic-based Community Identification

Social Media Information Aggregation

Event Detection

Community Lifecycle

Monitoring

Data Mining for Biomedical and Clinical Research Trends

Detection and Analysis

Social Media Data

Social Media

Social Media Data Feeds

Sentiment Analysis

Text Annotation

Semantic Filtering

Term Co-occurrence

Index Building

Results Ranking

Novel open, semantically-assisted peer review process

Research Dynamics-aware Open Access Data Journals

DevelopmentUniProt,

GO,

MeSH,

CDM,

DMAP,

PONTE Eligibility Criteria,

PONTE Global EHR,

PONTE Drug,

PONTE Disease,

PONTE Target

SocIoS Data Model

Models/Ontologies Recommendation

Content Ranking

Linked Data (DrugBank, Diseasome,LinkedCT, SIDER,…)IUCLID DS

PROMISCUOUS DATABASE

Registry of Open Access Repositories

Open Access Data Infrastructure

Scientific field-aware, Productivity- and Impact-oriented Enhanced Research Evaluation System

Data Mining for Proactive Formulation of Scientific Collaborations

Knowledge-based Concept

Correlation

Concept Correlation

Ranking

Policy Evaluation

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OpenScienceLink OpenScienceLink General Intro, July 2013 11

GoPubMed Platform

A semantic search engine for the life sciences

Data mining, semantic filtering and ranking mechanisms

Instant ontology-based viewing of the retrieved results

Document annotation with ontology concepts


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, …


SocIoS Platform

• Social media aggregation through a powerful object model

• Social analytics services• Cross-platform

application development and deployment

• Open source components


+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 Impact (1/3)

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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

Reviewers•Efficient access to related research work and data•Less time-consuming process•Stronger confidence for the review outcome

Gov. Funding Agencies / Research Funding

Authorities

•Efficient and effective allocation of governmental and private funds to research•Prioritisation of research efforts towards topics with high success potential•Speeding up of research agenda



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Publishers

•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

•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

Citizens and the Society (as a whole)

•Faster access to novel R&D research•Development of novel products and services that generate growth and job positions, thereby addressing key societal challenges;

•Especially concerning the expected boosting of the biomedical and clinical research domain:

Reduced healthcare costs of tomorrow and more affordable medication;Healthier citizensImproving Quality of Life



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Enterprises relying on R&D for

their products

and services (e.g.,

pharma companies)

•More accurate and of higher success potential identification of research areas for funding and resource allocation

• Improved, scientifically-sound prioritisation of research efforts•Efficient reaching to high-quality researchers within a specific research field (which is of the company’s interest) for collaboration and thus establishment of stronger bonds between industry and researchers

•Access to and use of more reliable metrics representing the research value (in terms of quality, efficiency, relevance and viability) of published research work, researchers and institutions

•Earlier and more reliable decisions resulting in reduced costs and reduction of opportunity costs

• 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


Service-oriented Architecture (SOA)


• 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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Technical 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

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Data Interoperability


• W3C RDF/OWL ontologies• Linked Data approach• UMLS mappings between domain ontologies

(GO, MeSH, UniProt)• Shared models

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Semantic Interoperability


Thank you very much!

►Want to get involved?

Visit us at:http://projects.biotec.tu-dresden.de/opensciencelink/

http://projects.biotec.tu-dresden.de/opensciencelink/



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