how semantic technology helps researchers

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Darrell W. Gunter Collexis an Elsevier Company June 24, 2010 "How semantic technology enhances the productivity of scientific researchers."

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This presentation provides three cases studies as to how the Collexis technology helps a researcher to be more effective in their researcher.

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Page 1: How Semantic Technology Helps Researchers

Darrell W. Gunter

Collexis an Elsevier Company

June 24, 2010

"How semantic technology enhances the productivity of scientific researchers."

Page 2: How Semantic Technology Helps Researchers

Our Agenda For TodayThe Challenges of Scientific Research

The Collexis Technology

Case Studies

Professional Networks

Institutional Networks Johns Hopkins & Asklepios

Managing the Peer Review Process

Summation

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The Facts

1,2,3

The Author is under great pressure!

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Collexis Technology

KnowledgeBaseText Fingerprint

Collexis Fingerprint Engine

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Collexis Knowledge Engine 7.0

Tokenizer Normalizer Abbreviation

expansion

DehyphenationLanguage detection

Coordination expansion

Part-of-Speech tagging

Entity recognition based on regular expressions

Noun phrase detection

Concept findingPart-of-speech based disambiguation of

thesaurus concepts

Exclude known idioms

Fingerprint aggregation

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Collexis Knowledge Engine 7.0Modular NLP workbench – processing and analyzing of text

documents

Retrieval and aggregation engine – serving the application

layer

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Collexis – selected references

American Institute of Physics Stanford University

Asklepios Kliniken Johnson & Johnson

Johns Hopkins University University of California, San

Franciscio

Dana Farber Cancer Institute

Harvard University

National Institutes of Health

Mayo Clinic

California Institute for

Quantitative Biosciences (QB3),

The Wellcome TrustAlbert Einstein College of

Medicine

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Explore instead of Searching!

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Creating expert profiles from documents using semantic technologies

Document fingerprints aggregated to expert profiles!

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BiomedExperts – more than 300,000+ registered users

Prepopulated network – based on PubMed

1.8 million precalculated experts

More than 24 million co-author relations between them

Representing over 3,500 institutions

From 190 countries

Growing each day between 500 and 1000 users

BME data used in other applications

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Co-author based

networks

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Geographical

mapping of the

co-author network

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Johns Hopkins: The Issue! Connecting Experts

Fall retreat: Main issue how do they take advantage of the

university’s expertise and build collaboration

First solution – Repurpose a parking lot to be a coffee shop

for the JH community to grab a cup of Joe and find new

collaborators.

Outcome – Great coffee, great conversation but

collaboration did not take off.

The Collexis Solution – Expert Institutional Dashboard!

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Same Application for the NIH

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AsklepiosFacts and Figures

• Asklepios - Europe‘s largest health care provider

– 500.000 patients for inpatient care per year, 95 hospitals, 21.000 beds– 34.500 employees– Asklepios owns medical nursing and allied health schools– Home care programs and residential care programs

• Asklepios International – Pacific Health System – California– Greece, Athens Medical Center– University hospital in Shanghai: Joint Venture with Siemens and Tongji University

Page 23: How Semantic Technology Helps Researchers

Optimize Workflows (e.g. Avoid interruptions

caused by knowledge search, retrieval, and application)

Distribute Expert Knowledge

(across multiple locations, time zones, medical

conditions)

Guide Workflows(e.g. Care Plans, Expert-Task Context Allocation)

Help Asklepios to know “what Asklepios knows”

Stimulate new Knowledge Acquisition Usage

Models

Why Knowledge Management?

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• Patient, male, age of 62, needs a knee joint prosthesis due to Rheumatoid Arthritis

• Where is the best place to get it?

• Criteria which will be taken into account:– Geographical aspects– Recommendation of his GP– Publicly available information - mostly via Internet

• Strongest competitors: university hospitals (within the region)

Use Case 1 – Expert profiles

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Asklepios Research Profiles

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Expert Profile of Prof. Grifka

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Make Internal Expertise available!

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Provide a single point of search for all relevant content from

publishers!

Link internal expertise / experience and external

knowledge sources!

Provide a single point of search for all relevant content from

publishers!

Link internal expertise / experience and external

knowledge sources!

Page 29: How Semantic Technology Helps Researchers

• Patient with lung cancer and reduced renal function

• Decision in chemotherapeutic drug is pending

• Preferred choice: Cisplatin as chemotherapeutic agent

• Open questions: can Cisplatin be used which has nephrotoxicity as a side effect?

Use Case 4 - External Resources and Internal Experience Use Case 4 - External Resources and Internal Experience

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Search - Cisplatin shows the relevant publications from Springer, Elsevier, Thieme, OVID and other publishers

Asklepios Intelligent Digital Library

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Opening an journal article…

…shows immediately similar publications colleagues

… and the names and expert profiles

Link External Knowledge and

Internal Expertise

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Key Issues in STM IndustryPublishers / Editors

Finding the right reviewer

Expanding their pool of reviewers

Institutions

Determining what grants they should go after

Determining who within their organization is best to apply

Grant Funding Organizations

Analyzing the vast amount of grant applications submitted.

Determining who within the organization is best qualified to review the grant application

(known and unknown)

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The Challenge for STM PublishersReceive thousands of manuscripts annually

Timely process to conduct the Peer Review Process

Timely process to determine who should review it.

Important for reviewer to free of conflicts of interest

Ethics of review process are paramount

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Key Benefits Reviewer FinderFingerprint of manuscript - Clarity

Determine the best reviewer

Free of conflicts

More efficient and effective process

Ultimately increases profitability

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The effectiveness of Semantic Technology

Aggregates the researcher's publications into a Fingerprint of weighted

relevant concepts

Expert Profiles (individual, institution, dept, country,etc.)

Shows co-author relationships (who publishes with whom)

Conduct search by key concepts

Match content from a variety of sources based on a key concept,

researcher, country, etc.

Determine expert for peer review, grant application, project, etc.

Page 40: How Semantic Technology Helps Researchers

www.collexis.com

Thank you for your attention!

Darrell W. Gunter

[email protected], cell +1-973-454-3475