SlideShare una empresa de Scribd logo
1 de 25
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

Más contenido relacionado

La actualidad más candente

Explorations in bioinformatics
Explorations in bioinformaticsExplorations in bioinformatics
Explorations in bioinformaticsDouglas Joubert
 
Pistoia Alliance-Elsevier Datathon
Pistoia Alliance-Elsevier DatathonPistoia Alliance-Elsevier Datathon
Pistoia Alliance-Elsevier DatathonPistoia Alliance
 
Data for AI models, the past, the present, the future
Data for AI models, the past, the present, the futureData for AI models, the past, the present, the future
Data for AI models, the past, the present, the futurePistoia Alliance
 
provenance of microarray experiments
provenance of microarray experimentsprovenance of microarray experiments
provenance of microarray experimentsHelena Deus
 
Data sharing - Data management - The SysMO-SEEK Story
Data sharing - Data management - The SysMO-SEEK StoryData sharing - Data management - The SysMO-SEEK Story
Data sharing - Data management - The SysMO-SEEK StoryResearch Information Network
 
Semantic approaches for biomedical knowledge discovery - Discovery Science 20...
Semantic approaches for biomedical knowledge discovery - Discovery Science 20...Semantic approaches for biomedical knowledge discovery - Discovery Science 20...
Semantic approaches for biomedical knowledge discovery - Discovery Science 20...Michel Dumontier
 
The Research Object Initiative: Frameworks and Use Cases
The Research Object Initiative:Frameworks and Use CasesThe Research Object Initiative:Frameworks and Use Cases
The Research Object Initiative: Frameworks and Use CasesCarole Goble
 
Sowmya Raghavan Strand Life
Sowmya Raghavan Strand LifeSowmya Raghavan Strand Life
Sowmya Raghavan Strand LifeEmTech
 
Euretos presentation ACS
Euretos presentation ACSEuretos presentation ACS
Euretos presentation ACSalbertmons
 
Claudia medina: Linking Health Records for Population Health Research in Brazil.
Claudia medina: Linking Health Records for Population Health Research in Brazil.Claudia medina: Linking Health Records for Population Health Research in Brazil.
Claudia medina: Linking Health Records for Population Health Research in Brazil.Flávio Codeço Coelho
 
Ai in drug design webinar 26 feb 2019
Ai in drug design webinar 26 feb 2019Ai in drug design webinar 26 feb 2019
Ai in drug design webinar 26 feb 2019Pistoia Alliance
 
Model Organism Linked Data
Model Organism Linked DataModel Organism Linked Data
Model Organism Linked DataMichel Dumontier
 
Connecting data across our clinical data warehouses: UC-Research eXchange (UC...
Connecting data across our clinical data warehouses: UC-Research eXchange (UC...Connecting data across our clinical data warehouses: UC-Research eXchange (UC...
Connecting data across our clinical data warehouses: UC-Research eXchange (UC...CTSI at UCSF
 
2020.04.07 automated molecular design and the bradshaw platform webinar
2020.04.07 automated molecular design and the bradshaw platform webinar2020.04.07 automated molecular design and the bradshaw platform webinar
2020.04.07 automated molecular design and the bradshaw platform webinarPistoia Alliance
 
SEEKing our way to better presentation of data and models from scientific inv...
SEEKing our way to better presentation of data and models from scientific inv...SEEKing our way to better presentation of data and models from scientific inv...
SEEKing our way to better presentation of data and models from scientific inv...Natalie Stanford
 

La actualidad más candente (20)

Explorations in bioinformatics
Explorations in bioinformaticsExplorations in bioinformatics
Explorations in bioinformatics
 
EVQLV Deck
EVQLV Deck EVQLV Deck
EVQLV Deck
 
Pistoia Alliance-Elsevier Datathon
Pistoia Alliance-Elsevier DatathonPistoia Alliance-Elsevier Datathon
Pistoia Alliance-Elsevier Datathon
 
Data for AI models, the past, the present, the future
Data for AI models, the past, the present, the futureData for AI models, the past, the present, the future
Data for AI models, the past, the present, the future
 
McIntosh "Improving the quality of preprints with automated checks"
McIntosh "Improving the quality of preprints with automated checks"McIntosh "Improving the quality of preprints with automated checks"
McIntosh "Improving the quality of preprints with automated checks"
 
provenance of microarray experiments
provenance of microarray experimentsprovenance of microarray experiments
provenance of microarray experiments
 
Data sharing - Data management - The SysMO-SEEK Story
Data sharing - Data management - The SysMO-SEEK StoryData sharing - Data management - The SysMO-SEEK Story
Data sharing - Data management - The SysMO-SEEK Story
 
Semantic approaches for biomedical knowledge discovery - Discovery Science 20...
Semantic approaches for biomedical knowledge discovery - Discovery Science 20...Semantic approaches for biomedical knowledge discovery - Discovery Science 20...
Semantic approaches for biomedical knowledge discovery - Discovery Science 20...
 
The Research Object Initiative: Frameworks and Use Cases
The Research Object Initiative:Frameworks and Use CasesThe Research Object Initiative:Frameworks and Use Cases
The Research Object Initiative: Frameworks and Use Cases
 
Sowmya Raghavan Strand Life
Sowmya Raghavan Strand LifeSowmya Raghavan Strand Life
Sowmya Raghavan Strand Life
 
Euretos presentation ACS
Euretos presentation ACSEuretos presentation ACS
Euretos presentation ACS
 
Why should Journals ask fo RRIDs?
Why should Journals ask fo RRIDs?Why should Journals ask fo RRIDs?
Why should Journals ask fo RRIDs?
 
Claudia medina: Linking Health Records for Population Health Research in Brazil.
Claudia medina: Linking Health Records for Population Health Research in Brazil.Claudia medina: Linking Health Records for Population Health Research in Brazil.
Claudia medina: Linking Health Records for Population Health Research in Brazil.
 
Online Resources to Support Open Drug Discovery Systems
Online Resources to Support Open Drug Discovery SystemsOnline Resources to Support Open Drug Discovery Systems
Online Resources to Support Open Drug Discovery Systems
 
Ai in drug design webinar 26 feb 2019
Ai in drug design webinar 26 feb 2019Ai in drug design webinar 26 feb 2019
Ai in drug design webinar 26 feb 2019
 
Model Organism Linked Data
Model Organism Linked DataModel Organism Linked Data
Model Organism Linked Data
 
Pepe "Enriching Preprints with Provenance, Reproducibility, and Trustworthiness"
Pepe "Enriching Preprints with Provenance, Reproducibility, and Trustworthiness"Pepe "Enriching Preprints with Provenance, Reproducibility, and Trustworthiness"
Pepe "Enriching Preprints with Provenance, Reproducibility, and Trustworthiness"
 
Connecting data across our clinical data warehouses: UC-Research eXchange (UC...
Connecting data across our clinical data warehouses: UC-Research eXchange (UC...Connecting data across our clinical data warehouses: UC-Research eXchange (UC...
Connecting data across our clinical data warehouses: UC-Research eXchange (UC...
 
2020.04.07 automated molecular design and the bradshaw platform webinar
2020.04.07 automated molecular design and the bradshaw platform webinar2020.04.07 automated molecular design and the bradshaw platform webinar
2020.04.07 automated molecular design and the bradshaw platform webinar
 
SEEKing our way to better presentation of data and models from scientific inv...
SEEKing our way to better presentation of data and models from scientific inv...SEEKing our way to better presentation of data and models from scientific inv...
SEEKing our way to better presentation of data and models from scientific inv...
 

Similar a eScience Institute presentation on eagle-i

NCBO haendel talk 2013
NCBO haendel talk 2013NCBO haendel talk 2013
NCBO haendel talk 2013mhaendel
 
Research resources: curating the new eagle-i discovery system
Research resources: curating the new eagle-i discovery systemResearch resources: curating the new eagle-i discovery system
Research resources: curating the new eagle-i discovery systemNicole Vasilevsky
 
ISMB/ECCB 2013 Keynote Goble Results may vary: what is reproducible? why do o...
ISMB/ECCB 2013 Keynote Goble Results may vary: what is reproducible? why do o...ISMB/ECCB 2013 Keynote Goble Results may vary: what is reproducible? why do o...
ISMB/ECCB 2013 Keynote Goble Results may vary: what is reproducible? why do o...Carole Goble
 
Creating Sustainable Communities in Open Data Resources: The eagle-i and VIVO...
Creating Sustainable Communities in Open Data Resources: The eagle-i and VIVO...Creating Sustainable Communities in Open Data Resources: The eagle-i and VIVO...
Creating Sustainable Communities in Open Data Resources: The eagle-i and VIVO...Robert H. McDonald
 
Standardizing scholarly output with the VIVO ontology
Standardizing scholarly output with the VIVO ontologyStandardizing scholarly output with the VIVO ontology
Standardizing scholarly output with the VIVO ontologymhaendel
 
RDA Scholarly Infrastructure 2015
RDA Scholarly Infrastructure 2015RDA Scholarly Infrastructure 2015
RDA Scholarly Infrastructure 2015William Gunn
 
Force11: Enabling transparency and efficiency in the research landscape
Force11: Enabling transparency and efficiency in the research landscapeForce11: Enabling transparency and efficiency in the research landscape
Force11: Enabling transparency and efficiency in the research landscapemhaendel
 
Presentation to the J. Craig Venter Institute, Dec. 2014
Presentation to the J. Craig Venter Institute, Dec. 2014Presentation to the J. Craig Venter Institute, Dec. 2014
Presentation to the J. Craig Venter Institute, Dec. 2014Mark Wilkinson
 
Bioinformatics databases: Current Trends and Future Perspectives
Bioinformatics databases: Current Trends and Future PerspectivesBioinformatics databases: Current Trends and Future Perspectives
Bioinformatics databases: Current Trends and Future PerspectivesUniversity of Malaya
 
Connecting people, places and things
Connecting people, places and things Connecting people, places and things
Connecting people, places and things Ringgold Inc
 
Amia 2013: How can bio-ontologies support clinical and translational science?
Amia 2013: How can bio-ontologies support clinical and translational science? Amia 2013: How can bio-ontologies support clinical and translational science?
Amia 2013: How can bio-ontologies support clinical and translational science? Carlo Torniai
 
Open PHACTS for BDE SC1.1
Open PHACTS for BDE SC1.1Open PHACTS for BDE SC1.1
Open PHACTS for BDE SC1.1BigData_Europe
 
Using Taxonomies to Create People Directories and Author Networks
Using Taxonomies to Create People Directories and Author Networks Using Taxonomies to Create People Directories and Author Networks
Using Taxonomies to Create People Directories and Author Networks Access Innovations, Inc.
 
VIVO: enabling the discovery of research and scholarship
VIVO: enabling the discovery of research and scholarshipVIVO: enabling the discovery of research and scholarship
VIVO: enabling the discovery of research and scholarshipPaul Albert
 
Why should researchers care about data curation?
Why should researchers care about data curation?Why should researchers care about data curation?
Why should researchers care about data curation?Varsha Khodiyar
 
Leveraging the power of the web - Open Repositories 2015
Leveraging the power of the web - Open Repositories 2015Leveraging the power of the web - Open Repositories 2015
Leveraging the power of the web - Open Repositories 2015Kaitlin Thaney
 
Reproducibility (and the R*) of Science: motivations, challenges and trends
Reproducibility (and the R*) of Science: motivations, challenges and trendsReproducibility (and the R*) of Science: motivations, challenges and trends
Reproducibility (and the R*) of Science: motivations, challenges and trendsCarole Goble
 

Similar a eScience Institute presentation on eagle-i (20)

NCBO haendel talk 2013
NCBO haendel talk 2013NCBO haendel talk 2013
NCBO haendel talk 2013
 
Research resources: curating the new eagle-i discovery system
Research resources: curating the new eagle-i discovery systemResearch resources: curating the new eagle-i discovery system
Research resources: curating the new eagle-i discovery system
 
Martone grethe
Martone gretheMartone grethe
Martone grethe
 
ISMB/ECCB 2013 Keynote Goble Results may vary: what is reproducible? why do o...
ISMB/ECCB 2013 Keynote Goble Results may vary: what is reproducible? why do o...ISMB/ECCB 2013 Keynote Goble Results may vary: what is reproducible? why do o...
ISMB/ECCB 2013 Keynote Goble Results may vary: what is reproducible? why do o...
 
Creating Sustainable Communities in Open Data Resources: The eagle-i and VIVO...
Creating Sustainable Communities in Open Data Resources: The eagle-i and VIVO...Creating Sustainable Communities in Open Data Resources: The eagle-i and VIVO...
Creating Sustainable Communities in Open Data Resources: The eagle-i and VIVO...
 
Standardizing scholarly output with the VIVO ontology
Standardizing scholarly output with the VIVO ontologyStandardizing scholarly output with the VIVO ontology
Standardizing scholarly output with the VIVO ontology
 
RDA Scholarly Infrastructure 2015
RDA Scholarly Infrastructure 2015RDA Scholarly Infrastructure 2015
RDA Scholarly Infrastructure 2015
 
Force11: Enabling transparency and efficiency in the research landscape
Force11: Enabling transparency and efficiency in the research landscapeForce11: Enabling transparency and efficiency in the research landscape
Force11: Enabling transparency and efficiency in the research landscape
 
NISO Virtual Conference Scientific Data Management: Caring for Your Instituti...
NISO Virtual Conference Scientific Data Management: Caring for Your Instituti...NISO Virtual Conference Scientific Data Management: Caring for Your Instituti...
NISO Virtual Conference Scientific Data Management: Caring for Your Instituti...
 
FAIRer Research
FAIRer ResearchFAIRer Research
FAIRer Research
 
Presentation to the J. Craig Venter Institute, Dec. 2014
Presentation to the J. Craig Venter Institute, Dec. 2014Presentation to the J. Craig Venter Institute, Dec. 2014
Presentation to the J. Craig Venter Institute, Dec. 2014
 
Bioinformatics databases: Current Trends and Future Perspectives
Bioinformatics databases: Current Trends and Future PerspectivesBioinformatics databases: Current Trends and Future Perspectives
Bioinformatics databases: Current Trends and Future Perspectives
 
Connecting people, places and things
Connecting people, places and things Connecting people, places and things
Connecting people, places and things
 
Amia 2013: How can bio-ontologies support clinical and translational science?
Amia 2013: How can bio-ontologies support clinical and translational science? Amia 2013: How can bio-ontologies support clinical and translational science?
Amia 2013: How can bio-ontologies support clinical and translational science?
 
Open PHACTS for BDE SC1.1
Open PHACTS for BDE SC1.1Open PHACTS for BDE SC1.1
Open PHACTS for BDE SC1.1
 
Using Taxonomies to Create People Directories and Author Networks
Using Taxonomies to Create People Directories and Author Networks Using Taxonomies to Create People Directories and Author Networks
Using Taxonomies to Create People Directories and Author Networks
 
VIVO: enabling the discovery of research and scholarship
VIVO: enabling the discovery of research and scholarshipVIVO: enabling the discovery of research and scholarship
VIVO: enabling the discovery of research and scholarship
 
Why should researchers care about data curation?
Why should researchers care about data curation?Why should researchers care about data curation?
Why should researchers care about data curation?
 
Leveraging the power of the web - Open Repositories 2015
Leveraging the power of the web - Open Repositories 2015Leveraging the power of the web - Open Repositories 2015
Leveraging the power of the web - Open Repositories 2015
 
Reproducibility (and the R*) of Science: motivations, challenges and trends
Reproducibility (and the R*) of Science: motivations, challenges and trendsReproducibility (and the R*) of Science: motivations, challenges and trends
Reproducibility (and the R*) of Science: motivations, challenges and trends
 

Más de mhaendel

Patient-led deep phenotyping using a lay-friendly version of the Human Phenot...
Patient-led deep phenotyping using a lay-friendly version of the Human Phenot...Patient-led deep phenotyping using a lay-friendly version of the Human Phenot...
Patient-led deep phenotyping using a lay-friendly version of the Human Phenot...mhaendel
 
Semantics for rare disease phenotyping, diagnostics, and discovery
Semantics for rare disease phenotyping, diagnostics, and discoverySemantics for rare disease phenotyping, diagnostics, and discovery
Semantics for rare disease phenotyping, diagnostics, and discoverymhaendel
 
The Software and Data Licensing Solution: Not Your Dad’s UBMTA
The Software and Data Licensing Solution: Not Your Dad’s UBMTA The Software and Data Licensing Solution: Not Your Dad’s UBMTA
The Software and Data Licensing Solution: Not Your Dad’s UBMTA mhaendel
 
Equivalence is in the (ID) of the beholder
Equivalence is in the (ID) of the beholderEquivalence is in the (ID) of the beholder
Equivalence is in the (ID) of the beholdermhaendel
 
Building (and traveling) the data-brick road: A report from the front lines ...
Building (and traveling) the data-brick road:  A report from the front lines ...Building (and traveling) the data-brick road:  A report from the front lines ...
Building (and traveling) the data-brick road: A report from the front lines ...mhaendel
 
GA4GH Monarch Driver Project Introduction
GA4GH Monarch Driver Project IntroductionGA4GH Monarch Driver Project Introduction
GA4GH Monarch Driver Project Introductionmhaendel
 
GA4GH Phenotype Ontologies Task team update
GA4GH Phenotype Ontologies Task team updateGA4GH Phenotype Ontologies Task team update
GA4GH Phenotype Ontologies Task team updatemhaendel
 
Reusable data for biomedicine: A data licensing odyssey
Reusable data for biomedicine:  A data licensing odysseyReusable data for biomedicine:  A data licensing odyssey
Reusable data for biomedicine: A data licensing odysseymhaendel
 
Data Translator: an Open Science Data Platform for Mechanistic Disease Discovery
Data Translator: an Open Science Data Platform for Mechanistic Disease DiscoveryData Translator: an Open Science Data Platform for Mechanistic Disease Discovery
Data Translator: an Open Science Data Platform for Mechanistic Disease Discoverymhaendel
 
Global phenotypic data sharing standards to maximize diagnostic discovery
Global phenotypic data sharing standards to maximize diagnostic discoveryGlobal phenotypic data sharing standards to maximize diagnostic discovery
Global phenotypic data sharing standards to maximize diagnostic discoverymhaendel
 
How open is open? An evaluation rubric for public knowledgebases
How open is open?  An evaluation rubric for public knowledgebasesHow open is open?  An evaluation rubric for public knowledgebases
How open is open? An evaluation rubric for public knowledgebasesmhaendel
 
Deep phenotyping to aid identification of coding & non-coding rare disease v...
Deep phenotyping to aid identification  of coding & non-coding rare disease v...Deep phenotyping to aid identification  of coding & non-coding rare disease v...
Deep phenotyping to aid identification of coding & non-coding rare disease v...mhaendel
 
Science in the open, what does it take?
Science in the open, what does it take?Science in the open, what does it take?
Science in the open, what does it take?mhaendel
 
Global Phenotypic Data Sharing Standards to Maximize Diagnostics and Mechanis...
Global Phenotypic Data Sharing Standards to Maximize Diagnostics and Mechanis...Global Phenotypic Data Sharing Standards to Maximize Diagnostics and Mechanis...
Global Phenotypic Data Sharing Standards to Maximize Diagnostics and Mechanis...mhaendel
 
Phenopackets as applied to variant interpretation
Phenopackets as applied to variant interpretation Phenopackets as applied to variant interpretation
Phenopackets as applied to variant interpretation mhaendel
 
Credit where credit is due: acknowledging all types of contributions
Credit where credit is due: acknowledging all types of contributionsCredit where credit is due: acknowledging all types of contributions
Credit where credit is due: acknowledging all types of contributionsmhaendel
 
Deep phenotyping for everyone
Deep phenotyping for everyoneDeep phenotyping for everyone
Deep phenotyping for everyonemhaendel
 
Why the world needs phenopacketeers, and how to be one
Why the world needs phenopacketeers, and how to be oneWhy the world needs phenopacketeers, and how to be one
Why the world needs phenopacketeers, and how to be onemhaendel
 
On the frontier of genotype-2-phenotype data integration
On the frontier of genotype-2-phenotype data integrationOn the frontier of genotype-2-phenotype data integration
On the frontier of genotype-2-phenotype data integrationmhaendel
 
The Monarch Initiative: A semantic phenomics approach to disease discovery
The Monarch Initiative: A semantic phenomics approach to disease discoveryThe Monarch Initiative: A semantic phenomics approach to disease discovery
The Monarch Initiative: A semantic phenomics approach to disease discoverymhaendel
 

Más de mhaendel (20)

Patient-led deep phenotyping using a lay-friendly version of the Human Phenot...
Patient-led deep phenotyping using a lay-friendly version of the Human Phenot...Patient-led deep phenotyping using a lay-friendly version of the Human Phenot...
Patient-led deep phenotyping using a lay-friendly version of the Human Phenot...
 
Semantics for rare disease phenotyping, diagnostics, and discovery
Semantics for rare disease phenotyping, diagnostics, and discoverySemantics for rare disease phenotyping, diagnostics, and discovery
Semantics for rare disease phenotyping, diagnostics, and discovery
 
The Software and Data Licensing Solution: Not Your Dad’s UBMTA
The Software and Data Licensing Solution: Not Your Dad’s UBMTA The Software and Data Licensing Solution: Not Your Dad’s UBMTA
The Software and Data Licensing Solution: Not Your Dad’s UBMTA
 
Equivalence is in the (ID) of the beholder
Equivalence is in the (ID) of the beholderEquivalence is in the (ID) of the beholder
Equivalence is in the (ID) of the beholder
 
Building (and traveling) the data-brick road: A report from the front lines ...
Building (and traveling) the data-brick road:  A report from the front lines ...Building (and traveling) the data-brick road:  A report from the front lines ...
Building (and traveling) the data-brick road: A report from the front lines ...
 
GA4GH Monarch Driver Project Introduction
GA4GH Monarch Driver Project IntroductionGA4GH Monarch Driver Project Introduction
GA4GH Monarch Driver Project Introduction
 
GA4GH Phenotype Ontologies Task team update
GA4GH Phenotype Ontologies Task team updateGA4GH Phenotype Ontologies Task team update
GA4GH Phenotype Ontologies Task team update
 
Reusable data for biomedicine: A data licensing odyssey
Reusable data for biomedicine:  A data licensing odysseyReusable data for biomedicine:  A data licensing odyssey
Reusable data for biomedicine: A data licensing odyssey
 
Data Translator: an Open Science Data Platform for Mechanistic Disease Discovery
Data Translator: an Open Science Data Platform for Mechanistic Disease DiscoveryData Translator: an Open Science Data Platform for Mechanistic Disease Discovery
Data Translator: an Open Science Data Platform for Mechanistic Disease Discovery
 
Global phenotypic data sharing standards to maximize diagnostic discovery
Global phenotypic data sharing standards to maximize diagnostic discoveryGlobal phenotypic data sharing standards to maximize diagnostic discovery
Global phenotypic data sharing standards to maximize diagnostic discovery
 
How open is open? An evaluation rubric for public knowledgebases
How open is open?  An evaluation rubric for public knowledgebasesHow open is open?  An evaluation rubric for public knowledgebases
How open is open? An evaluation rubric for public knowledgebases
 
Deep phenotyping to aid identification of coding & non-coding rare disease v...
Deep phenotyping to aid identification  of coding & non-coding rare disease v...Deep phenotyping to aid identification  of coding & non-coding rare disease v...
Deep phenotyping to aid identification of coding & non-coding rare disease v...
 
Science in the open, what does it take?
Science in the open, what does it take?Science in the open, what does it take?
Science in the open, what does it take?
 
Global Phenotypic Data Sharing Standards to Maximize Diagnostics and Mechanis...
Global Phenotypic Data Sharing Standards to Maximize Diagnostics and Mechanis...Global Phenotypic Data Sharing Standards to Maximize Diagnostics and Mechanis...
Global Phenotypic Data Sharing Standards to Maximize Diagnostics and Mechanis...
 
Phenopackets as applied to variant interpretation
Phenopackets as applied to variant interpretation Phenopackets as applied to variant interpretation
Phenopackets as applied to variant interpretation
 
Credit where credit is due: acknowledging all types of contributions
Credit where credit is due: acknowledging all types of contributionsCredit where credit is due: acknowledging all types of contributions
Credit where credit is due: acknowledging all types of contributions
 
Deep phenotyping for everyone
Deep phenotyping for everyoneDeep phenotyping for everyone
Deep phenotyping for everyone
 
Why the world needs phenopacketeers, and how to be one
Why the world needs phenopacketeers, and how to be oneWhy the world needs phenopacketeers, and how to be one
Why the world needs phenopacketeers, and how to be one
 
On the frontier of genotype-2-phenotype data integration
On the frontier of genotype-2-phenotype data integrationOn the frontier of genotype-2-phenotype data integration
On the frontier of genotype-2-phenotype data integration
 
The Monarch Initiative: A semantic phenomics approach to disease discovery
The Monarch Initiative: A semantic phenomics approach to disease discoveryThe Monarch Initiative: A semantic phenomics approach to disease discovery
The Monarch Initiative: A semantic phenomics approach to disease discovery
 

Último

Z Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot GraphZ Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot GraphThiyagu K
 
A Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy ReformA Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy ReformChameera Dedduwage
 
Student login on Anyboli platform.helpin
Student login on Anyboli platform.helpinStudent login on Anyboli platform.helpin
Student login on Anyboli platform.helpinRaunakKeshri1
 
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...christianmathematics
 
Russian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in Delhi
Russian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in DelhiRussian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in Delhi
Russian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in Delhikauryashika82
 
1029 - Danh muc Sach Giao Khoa 10 . pdf
1029 -  Danh muc Sach Giao Khoa 10 . pdf1029 -  Danh muc Sach Giao Khoa 10 . pdf
1029 - Danh muc Sach Giao Khoa 10 . pdfQucHHunhnh
 
Class 11th Physics NEET formula sheet pdf
Class 11th Physics NEET formula sheet pdfClass 11th Physics NEET formula sheet pdf
Class 11th Physics NEET formula sheet pdfAyushMahapatra5
 
Arihant handbook biology for class 11 .pdf
Arihant handbook biology for class 11 .pdfArihant handbook biology for class 11 .pdf
Arihant handbook biology for class 11 .pdfchloefrazer622
 
IGNOU MSCCFT and PGDCFT Exam Question Pattern: MCFT003 Counselling and Family...
IGNOU MSCCFT and PGDCFT Exam Question Pattern: MCFT003 Counselling and Family...IGNOU MSCCFT and PGDCFT Exam Question Pattern: MCFT003 Counselling and Family...
IGNOU MSCCFT and PGDCFT Exam Question Pattern: MCFT003 Counselling and Family...PsychoTech Services
 
Introduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The BasicsIntroduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The BasicsTechSoup
 
social pharmacy d-pharm 1st year by Pragati K. Mahajan
social pharmacy d-pharm 1st year by Pragati K. Mahajansocial pharmacy d-pharm 1st year by Pragati K. Mahajan
social pharmacy d-pharm 1st year by Pragati K. Mahajanpragatimahajan3
 
Nutritional Needs Presentation - HLTH 104
Nutritional Needs Presentation - HLTH 104Nutritional Needs Presentation - HLTH 104
Nutritional Needs Presentation - HLTH 104misteraugie
 
Holdier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfHoldier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfagholdier
 
Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17Celine George
 
Measures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeMeasures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeThiyagu K
 
Measures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SDMeasures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SDThiyagu K
 
Sanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdfSanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdfsanyamsingh5019
 
Web & Social Media Analytics Previous Year Question Paper.pdf
Web & Social Media Analytics Previous Year Question Paper.pdfWeb & Social Media Analytics Previous Year Question Paper.pdf
Web & Social Media Analytics Previous Year Question Paper.pdfJayanti Pande
 

Último (20)

Z Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot GraphZ Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot Graph
 
INDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptx
INDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptxINDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptx
INDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptx
 
A Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy ReformA Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy Reform
 
Student login on Anyboli platform.helpin
Student login on Anyboli platform.helpinStudent login on Anyboli platform.helpin
Student login on Anyboli platform.helpin
 
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
 
Russian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in Delhi
Russian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in DelhiRussian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in Delhi
Russian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in Delhi
 
1029 - Danh muc Sach Giao Khoa 10 . pdf
1029 -  Danh muc Sach Giao Khoa 10 . pdf1029 -  Danh muc Sach Giao Khoa 10 . pdf
1029 - Danh muc Sach Giao Khoa 10 . pdf
 
Class 11th Physics NEET formula sheet pdf
Class 11th Physics NEET formula sheet pdfClass 11th Physics NEET formula sheet pdf
Class 11th Physics NEET formula sheet pdf
 
Arihant handbook biology for class 11 .pdf
Arihant handbook biology for class 11 .pdfArihant handbook biology for class 11 .pdf
Arihant handbook biology for class 11 .pdf
 
IGNOU MSCCFT and PGDCFT Exam Question Pattern: MCFT003 Counselling and Family...
IGNOU MSCCFT and PGDCFT Exam Question Pattern: MCFT003 Counselling and Family...IGNOU MSCCFT and PGDCFT Exam Question Pattern: MCFT003 Counselling and Family...
IGNOU MSCCFT and PGDCFT Exam Question Pattern: MCFT003 Counselling and Family...
 
Introduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The BasicsIntroduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The Basics
 
Advance Mobile Application Development class 07
Advance Mobile Application Development class 07Advance Mobile Application Development class 07
Advance Mobile Application Development class 07
 
social pharmacy d-pharm 1st year by Pragati K. Mahajan
social pharmacy d-pharm 1st year by Pragati K. Mahajansocial pharmacy d-pharm 1st year by Pragati K. Mahajan
social pharmacy d-pharm 1st year by Pragati K. Mahajan
 
Nutritional Needs Presentation - HLTH 104
Nutritional Needs Presentation - HLTH 104Nutritional Needs Presentation - HLTH 104
Nutritional Needs Presentation - HLTH 104
 
Holdier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfHoldier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdf
 
Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17
 
Measures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeMeasures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and Mode
 
Measures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SDMeasures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SD
 
Sanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdfSanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdf
 
Web & Social Media Analytics Previous Year Question Paper.pdf
Web & Social Media Analytics Previous Year Question Paper.pdfWeb & Social Media Analytics Previous Year Question Paper.pdf
Web & Social Media Analytics Previous Year Question Paper.pdf
 

eScience Institute presentation on eagle-i

  • 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

Notas del editor

  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