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Understanding E-Science: A
   Symposium for Medical
         Librarians

                   13 February 2012
The Texas Medical Center Library & The National Network
     of Libraries of Medicine South Central Region
         Neil Rambo, NYU School of Medicine
OUTLINE

- Definitions
- Terminology
- Examples
- Characteristics of
biomedicine & health care
- Opportunities for libraries
- Library strengths
- Challenges & opportunities
Theory
                                                                                                  Experiment
                                                                                                 Observation




Image from http://data3.blog.de/media/618/2452618_3cd174b3ff_m.jpg for limited educational use only.
Theory
                     Experiment
                    Observation




Image from http://www.drfphoto.com/images/db/static_electricity1.jpg
for limited educational use only.


 Copyright DAVID R FRAZIER Photolibrary, Inc. All Rights Reserved.
 dave@drfphoto.com
Theory
                                                                                                 Experiment
                                                                                                Observation


Image from http://openlearn.open.ac.uk/file.php/3317/T307_1_051i.jpg
for limited educational use only.




                                               Image obtained from http://content.cdlib.org/xtf/data/13030/gw/ft3q2nb2gw/figures/ft3q2nb2gw_00001.jpg
                                               for limited educational use only.
Theory
   Experiment
  Observation
Computational
      Science




Image from http://www.hubis.com/blog/images/SDSC_1.jpg
for limited educational use only.
Theory
   Experiment
  Observation
Computational
      Science
     eScience
NSF Ocean Observatories
         Initiative




Copyright © 2008 The Computing Research Association   http://www.cra.org/ccc/images/Essential_Elements_v3.jpg
It’s all about the data
• Dependent on access to data
• Key capabilities
  – Sensor networks
  – Databases
  – Machine learning
  – Data mining
  – Visualization
• Capabilities are expected to be
  ubiquitous
eScience is…

• A new research methodology
  – Fueled by networked capabilities and vast
    amounts of data
  – Data-driven and computationally intensive
• Team science, inter- & multi-
  disciplinary
• Multi-institutional & global
• Not a singular model
E-science fundamentally alters the ways in
                       which scientists carry out their work, the tools
                       they use, the types of problems they address,
                       and the nature of the documentation and
                       publication that results from their research.
                       E-science requires new strategies for research
                       support and significant development of
                       infrastructure.



Association of Research Libraries: Report
of the Joint Task Force on Library Support
for E-Science, Dec. 2007
escience?

      e-science?

e-Science?

             eScience?

E-Science?
Bioinformatics…
    Health informatics…
           -Omics…
        Research IT…
Enterprise data warehouse…
    EMR  HIE  RHIO 
L.O. Hertzberger, e-Science and the VL-e
Approach, Trans. on Comput. Syst. Biol. IV,
LNBI 3939, pp. 58-67, 2006.
L.O. Hertzberger, e-Science and the VL-e Approach, Trans. on Comput
Human Genome Turns 10

"When I was in training, genetics was
a small insignificant subspecialty of
pediatrics, and now pediatrics is a
small insignificant subspecialty of
genetics.” – Robert Marion


F. Collins, R. Marion, J.P. Evans, April 1, 2010, Nature
escience +

biomedicine & health care =

           ???
Human health
•   Universal interest
•   High stakes
•   Privacy & confidentiality
•   $$$
•   Federal & state regulations
•   Local competition
•   Culture of medicine
•   NIH & National Library of Medicine
Opportunities for libraries

• Managing research assets
  – Data curation
• Supporting new forms of
  communication & publication
• Supporting virtual organizations
• Contributing to policy development
Areas for library engagement

• Data curation
  – Preservation + access  re-use
  – Archival practice: selection, access, how
    long to preserve, IP rights management
• New forms of publication
• Virtual organizations
• Policy development
Areas for library engagement

• Data curation
• New forms of publication
  – eJournal links to underlying data
  – Reader manipulation of data
  – Journal + database = hybrid publication
• Virtual organizations
• Policy development
Areas for library engagement

• Data curation
• New forms of publication
• Virtual organizations
  – Content, data, tools to enable collaboration
  – Challenge of multi-institutional service model
  – Extension of digital library environments
• Policy development
Areas for library engagement

•   Data curation
•   New forms of publication
•   Virtual organizations
•   Policy development
    – Funding agency data policies
    – NIH public access law
    – Open access  Open data
    – ScienceCommons licensing models
Library strengths

• Open access: deep understanding &
  experience
• Integration and interoperability tools
• Archival practices and policies
• Preservation and metadata
Library strengths

• Open access: deep understanding &
  experience
  – Policies, practices, roles
  – Institutional & domain repositories
• Integration and interoperability tools
• Archival practices and policies
• Preservation and metadata
Library strengths

• Open access: deep understanding &
  experience
• Integration and interoperability tools
  – Link resolvers, federated search,
    metadata standards
• Archival practices and policies
• Preservation and metadata
Library strengths

• Open access: deep understanding &
  experience
• Integration and interoperability tools
• Archival practices and policies
  – Both business & technical strategies
  – Research, resource, reference collections
• Preservation and metadata
Library strengths

• Open access: deep understanding &
  experience
• Integration and interoperability tools
• Archival practices and policies
• Preservation and metadata
  – Understanding information life cycle
  – Importance of assuring access & usability
Challenges/Opportunities

• Research +/- Clinical environments
• iSchools aren’t responding sufficiently
• Need to draw from other disciplines &
  professional training
• Need to forge new, expanded partnerships
  – Joint research projects with faculty
    researchers
  – Pilot informatics tools & services
Questions? … Thank you!




                                                                  Neil Rambo
                                                                  neil.rambo@med.nyu.edu
Copyright © 2008 Sandhills Publishing Company U.S.A. All rights reserved.

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Neil Rambo "Understanding E-Science: A Symposium for Medical Librarians"

  • 1. Understanding E-Science: A Symposium for Medical Librarians 13 February 2012 The Texas Medical Center Library & The National Network of Libraries of Medicine South Central Region Neil Rambo, NYU School of Medicine
  • 2. OUTLINE - Definitions - Terminology - Examples - Characteristics of biomedicine & health care - Opportunities for libraries - Library strengths - Challenges & opportunities
  • 3. Theory Experiment Observation Image from http://data3.blog.de/media/618/2452618_3cd174b3ff_m.jpg for limited educational use only.
  • 4. Theory Experiment Observation Image from http://www.drfphoto.com/images/db/static_electricity1.jpg for limited educational use only. Copyright DAVID R FRAZIER Photolibrary, Inc. All Rights Reserved. dave@drfphoto.com
  • 5. Theory Experiment Observation Image from http://openlearn.open.ac.uk/file.php/3317/T307_1_051i.jpg for limited educational use only. Image obtained from http://content.cdlib.org/xtf/data/13030/gw/ft3q2nb2gw/figures/ft3q2nb2gw_00001.jpg for limited educational use only.
  • 6. Theory Experiment Observation Computational Science Image from http://www.hubis.com/blog/images/SDSC_1.jpg for limited educational use only.
  • 7. Theory Experiment Observation Computational Science eScience
  • 8. NSF Ocean Observatories Initiative Copyright © 2008 The Computing Research Association http://www.cra.org/ccc/images/Essential_Elements_v3.jpg
  • 9. It’s all about the data • Dependent on access to data • Key capabilities – Sensor networks – Databases – Machine learning – Data mining – Visualization • Capabilities are expected to be ubiquitous
  • 10. eScience is… • A new research methodology – Fueled by networked capabilities and vast amounts of data – Data-driven and computationally intensive • Team science, inter- & multi- disciplinary • Multi-institutional & global • Not a singular model
  • 11. E-science fundamentally alters the ways in which scientists carry out their work, the tools they use, the types of problems they address, and the nature of the documentation and publication that results from their research. E-science requires new strategies for research support and significant development of infrastructure. Association of Research Libraries: Report of the Joint Task Force on Library Support for E-Science, Dec. 2007
  • 12. escience? e-science? e-Science? eScience? E-Science?
  • 13. Bioinformatics… Health informatics… -Omics… Research IT… Enterprise data warehouse… EMR  HIE  RHIO 
  • 14. L.O. Hertzberger, e-Science and the VL-e Approach, Trans. on Comput. Syst. Biol. IV, LNBI 3939, pp. 58-67, 2006.
  • 15. L.O. Hertzberger, e-Science and the VL-e Approach, Trans. on Comput
  • 16.
  • 17. Human Genome Turns 10 "When I was in training, genetics was a small insignificant subspecialty of pediatrics, and now pediatrics is a small insignificant subspecialty of genetics.” – Robert Marion F. Collins, R. Marion, J.P. Evans, April 1, 2010, Nature
  • 18. escience + biomedicine & health care = ???
  • 19. Human health • Universal interest • High stakes • Privacy & confidentiality • $$$ • Federal & state regulations • Local competition • Culture of medicine • NIH & National Library of Medicine
  • 20.
  • 21.
  • 22. Opportunities for libraries • Managing research assets – Data curation • Supporting new forms of communication & publication • Supporting virtual organizations • Contributing to policy development
  • 23. Areas for library engagement • Data curation – Preservation + access  re-use – Archival practice: selection, access, how long to preserve, IP rights management • New forms of publication • Virtual organizations • Policy development
  • 24. Areas for library engagement • Data curation • New forms of publication – eJournal links to underlying data – Reader manipulation of data – Journal + database = hybrid publication • Virtual organizations • Policy development
  • 25. Areas for library engagement • Data curation • New forms of publication • Virtual organizations – Content, data, tools to enable collaboration – Challenge of multi-institutional service model – Extension of digital library environments • Policy development
  • 26. Areas for library engagement • Data curation • New forms of publication • Virtual organizations • Policy development – Funding agency data policies – NIH public access law – Open access  Open data – ScienceCommons licensing models
  • 27. Library strengths • Open access: deep understanding & experience • Integration and interoperability tools • Archival practices and policies • Preservation and metadata
  • 28. Library strengths • Open access: deep understanding & experience – Policies, practices, roles – Institutional & domain repositories • Integration and interoperability tools • Archival practices and policies • Preservation and metadata
  • 29. Library strengths • Open access: deep understanding & experience • Integration and interoperability tools – Link resolvers, federated search, metadata standards • Archival practices and policies • Preservation and metadata
  • 30. Library strengths • Open access: deep understanding & experience • Integration and interoperability tools • Archival practices and policies – Both business & technical strategies – Research, resource, reference collections • Preservation and metadata
  • 31. Library strengths • Open access: deep understanding & experience • Integration and interoperability tools • Archival practices and policies • Preservation and metadata – Understanding information life cycle – Importance of assuring access & usability
  • 32. Challenges/Opportunities • Research +/- Clinical environments • iSchools aren’t responding sufficiently • Need to draw from other disciplines & professional training • Need to forge new, expanded partnerships – Joint research projects with faculty researchers – Pilot informatics tools & services
  • 33. Questions? … Thank you! Neil Rambo neil.rambo@med.nyu.edu Copyright © 2008 Sandhills Publishing Company U.S.A. All rights reserved.