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The eagle-i Network:
enabling research resource
discovery
Melissa Haendel
Oregon Health & Science University Library
03.15.13
LIBRARY
Outline
 History of eagle-i Network
 Basic features & functionality
 Relationship to research lifecycle & community
 Future collaborations
Dreams of a bench scientist
Better access to resources and expertise
More reproducible science
Credit where credit is due
Visible and interoperable data
Efficient science.
All of these dreams are aided by
semantic technologies:
 Uniform resource
Identifiers
 Ontologies (enabling
common reference,
differencing)
 Linked Data
 … and applications
that use them
 Helping researchers find invisible resources
Reagents, instruments, services, model and non-model organisms,
protocols, biospecimens, human studies, software and research
opportunities

 Adding meaningful semantic relationships between
resources
 Making this data available using ontology-driven approach
to research resource annotation and discovery
 Reducing time-consuming and expensive duplication of
resources
eagle-i Network
eagle-i Network
The problem
A
B
?
x
Failed experiment
Polyclonal anti-TGFβ RI
Santa Cruz Biotechnology
A
Identifying resources
eagle-i: making research resourcesmore visible
B
Successful
experiment!
The problem
Information is context dependent
Ontologies provide links, or “context” for
information
Nice automobile
is_a
Operating system
is_a
Fast mammal
is_a
named_after
named_after
SWEET: an ontology-driven data collectiontool
www.eagle-i.net
How are resources shared in eagle-i?
eagle-i data with a new
user-friendly user interface
Enables quality search of
OHSU cores in Google
Enables an OHSU cross-core
search for instruments and
services
Developed by UCSF:
http://ctsiatucsf.github.com/plumage/
OHSU Core Search = leveraging eagle-i
www.ohsu.edu/research/coresearch/
ISF
net w o r k
ISF can be used by other applications
 eagle-i is an ontology-driven application . . . for collecting
and searching research resources.
 VIVO is an ontology-driven application . . . for collecting
and
displaying information about people.
 CTSAconnect will produce a single Integrated Semantic
Framework, a modular collection of ontologies
eagle-i
Resources
VIVO
Peopleeagle-i
VIVO
Semantic
Clinical
activities
Merging VIVO and eagle-i semanticinfrastructure
eagle-i
Identify potential
collaborators, relevant
resources, and expertise
across scientific disciplines
Assemble teams of scientists
to address specific research
questions
Evaluate scientific outcomes
Oregon Health & Science
University
Cornell University
University of Florida
Stony Brook University
University at Buffalo
Harvard University
CTSAconnect | Reveal Connections. Realize Potential.
Antibody Registry and eagle-i
use a shared ontology
Publishing unique identifiers can
aid scientific reproducibility
Antibodies are not very uniquely identifiable in 57 publications
Percent
0%
20%
40%
60%
80%
100%
Commercial antibody
identifiable
Non-commercial antibody
identifiable
n=207
n=8
Working with publishers to increase
reporting guidelines
PreservePublishResearch
CTSAconnect
Reveal Connections.
Realize Potential.
net w o r k
Scholarly scientific research cycle
We can all work together to make research
resourcesmore visibleand researchmore efficient.
Successful
experiment!
net w o r k
Resources
Ontology Development Group
http://bit.ly/ohsuontdevgroup
CTSAconnect project
ctsaconnect.org
CTSAconnect ontology
http://code.google.com/p/connect-isf/
VIVO integrated search
vivosearch.org
eagle-i federated search
http://www.eagle-i.net
eagle-i ontology
http://code.google.com/p/eagle-i/
eagle-i software code
https://open.med.harvard.edu/display/eaglei/Software
OHSU Cores Search
www.ohsu.edu/research/coresearch
OHSU Library Ontology Development Group
Melissa Haendel – Co-Lead, Neuroscientist/Ontologist
Carlo Torniai – Co-Lead, Computer Scientist/Ontologist
Nicole Vasilevsky – Project Manager, Cell Biologist/Ontologist
Scott Hoffmann – Engineer/Ontologist
Erik Segerdell – Biologist/Ontologist
Matthew Brush – Molecular biologist/Ontologist
Shahim Essaid – MD/Bioinformatist/Ontologist
CTSAconnect
eagle-i
OHSU
Melissa Haendel
Carlo Torniai
Nicole Vasilevsky
Chris Kelleher
Shahim Essaid
Cornell University
Dean Krafft
Jon Corson-Rikert
Brian Lowe
University of Florida
Mike Conlon
Chris Barnes
Nicholas Rejack
OHSU
Melissa Haendel
Carlo Torniai
Nicole Vasilevsky
Scott Hoffmann
Matthew Brush
Jackie Wirz
Stony Brook University
Moises Eisenberg
Erich Bremer
Janos Hajagos
Harvard University
Daniela Bourges
Sophia Cheng
University at Buffalo
Barry Smith
Dagobert Soergel
Zaloni
Will Corbett
Ranjit Das
Ben Sharma
Harvard University
Lee Nadler
Doug MacFadden
Marc Ciriello
Richard Pearse
Daniela Bourges
Tenille Johnson
Vanderbilt University
Gordon Bernard
Lisa Robins
Penn
Garret Fitzgerald
Faith Coldren
Acknowledgements

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The eagle-i Network: enabling research resource discovery

  • 1. The eagle-i Network: enabling research resource discovery Melissa Haendel Oregon Health & Science University Library 03.15.13 LIBRARY
  • 2. Outline  History of eagle-i Network  Basic features & functionality  Relationship to research lifecycle & community  Future collaborations
  • 3. Dreams of a bench scientist Better access to resources and expertise More reproducible science Credit where credit is due Visible and interoperable data Efficient science.
  • 4. All of these dreams are aided by semantic technologies:  Uniform resource Identifiers  Ontologies (enabling common reference, differencing)  Linked Data  … and applications that use them
  • 5.  Helping researchers find invisible resources Reagents, instruments, services, model and non-model organisms, protocols, biospecimens, human studies, software and research opportunities   Adding meaningful semantic relationships between resources  Making this data available using ontology-driven approach to research resource annotation and discovery  Reducing time-consuming and expensive duplication of resources eagle-i Network
  • 8. ? x Failed experiment Polyclonal anti-TGFβ RI Santa Cruz Biotechnology A Identifying resources
  • 9. eagle-i: making research resourcesmore visible B Successful experiment!
  • 10. The problem Information is context dependent
  • 11. Ontologies provide links, or “context” for information Nice automobile is_a Operating system is_a Fast mammal is_a named_after named_after
  • 12. SWEET: an ontology-driven data collectiontool
  • 13. www.eagle-i.net How are resources shared in eagle-i?
  • 14. eagle-i data with a new user-friendly user interface Enables quality search of OHSU cores in Google Enables an OHSU cross-core search for instruments and services Developed by UCSF: http://ctsiatucsf.github.com/plumage/ OHSU Core Search = leveraging eagle-i
  • 16. ISF net w o r k ISF can be used by other applications
  • 17.  eagle-i is an ontology-driven application . . . for collecting and searching research resources.  VIVO is an ontology-driven application . . . for collecting and displaying information about people.  CTSAconnect will produce a single Integrated Semantic Framework, a modular collection of ontologies eagle-i Resources VIVO Peopleeagle-i VIVO Semantic Clinical activities Merging VIVO and eagle-i semanticinfrastructure eagle-i
  • 18. Identify potential collaborators, relevant resources, and expertise across scientific disciplines Assemble teams of scientists to address specific research questions Evaluate scientific outcomes Oregon Health & Science University Cornell University University of Florida Stony Brook University University at Buffalo Harvard University CTSAconnect | Reveal Connections. Realize Potential.
  • 19. Antibody Registry and eagle-i use a shared ontology
  • 20. Publishing unique identifiers can aid scientific reproducibility Antibodies are not very uniquely identifiable in 57 publications Percent 0% 20% 40% 60% 80% 100% Commercial antibody identifiable Non-commercial antibody identifiable n=207 n=8 Working with publishers to increase reporting guidelines
  • 22. We can all work together to make research resourcesmore visibleand researchmore efficient. Successful experiment! net w o r k
  • 23. Resources Ontology Development Group http://bit.ly/ohsuontdevgroup CTSAconnect project ctsaconnect.org CTSAconnect ontology http://code.google.com/p/connect-isf/ VIVO integrated search vivosearch.org eagle-i federated search http://www.eagle-i.net eagle-i ontology http://code.google.com/p/eagle-i/ eagle-i software code https://open.med.harvard.edu/display/eaglei/Software OHSU Cores Search www.ohsu.edu/research/coresearch
  • 24. OHSU Library Ontology Development Group Melissa Haendel – Co-Lead, Neuroscientist/Ontologist Carlo Torniai – Co-Lead, Computer Scientist/Ontologist Nicole Vasilevsky – Project Manager, Cell Biologist/Ontologist Scott Hoffmann – Engineer/Ontologist Erik Segerdell – Biologist/Ontologist Matthew Brush – Molecular biologist/Ontologist Shahim Essaid – MD/Bioinformatist/Ontologist
  • 25. CTSAconnect eagle-i OHSU Melissa Haendel Carlo Torniai Nicole Vasilevsky Chris Kelleher Shahim Essaid Cornell University Dean Krafft Jon Corson-Rikert Brian Lowe University of Florida Mike Conlon Chris Barnes Nicholas Rejack OHSU Melissa Haendel Carlo Torniai Nicole Vasilevsky Scott Hoffmann Matthew Brush Jackie Wirz Stony Brook University Moises Eisenberg Erich Bremer Janos Hajagos Harvard University Daniela Bourges Sophia Cheng University at Buffalo Barry Smith Dagobert Soergel Zaloni Will Corbett Ranjit Das Ben Sharma Harvard University Lee Nadler Doug MacFadden Marc Ciriello Richard Pearse Daniela Bourges Tenille Johnson Vanderbilt University Gordon Bernard Lisa Robins Penn Garret Fitzgerald Faith Coldren Acknowledgements

Hinweis der Redaktion

  1. This is just a draft- copied from RedCap slides
  2. Text -> more complex on images Look for word “jaguar”- no meaning in the word- can be animal, car, operating system.Information is syntaxic not semantic, unable to know what we are referring to exactly
  3. If we want to keep this slide, need to update the screenshot SWEET is an ontology-driven data collection tool
  4. How are resources shared in eagle-i?
  5. Include publication in landscape pictureFor commercial antibodies- identifiable/non-commercial identifiableNumber of antibodies and number of papersBring back to eagle-i
  6. Move to end