Presentation given at UQ Winterschool 2014. The advent of the Internet is bringing about fundamental changes in the ways that research is performed and communicated. These have been particularly driven by the growing importance of data, as well as the tools available to work with this data. This presentation will examine this shift, drawing on examples from the life‐sciences, and try to make some predictions about the next five years.

1. The life-sciences as a
pathfinder in data-
intensive research
practice
Dr Andrew Treloar, Director of
Technology
11 July 2014 CC-BY-SA, @atreloar 1

2. Structure presentation
 Research Lifecycles
 Functions of Scholarly Communication
 Pointers to the future
 Characterising the future
 Pathfinder problems
 Conclusions
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3. So many lifecycles…
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4. Minimal Research Lifecycle
Think
DoShare
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5. Sharing: Scholarly Communication
System and its Functions
 Registration
 Certification
 Awareness
 Archiving
(Rosendaal and Geurts, 1997)
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6. System of Journals
 Registration
 submission of manuscript
 Certification
 peer-review (pre-publication)
 commentary (post-publication)
 Awareness
 discovery services
 Archiving
 libraries (print)
 publishers (electronic)
 special purpose organisations (e.g. Portico)
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7. Pointers to the future
“the future is already here – it’s
just not very evenly distributed”
William Gibson, NPR interview
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8. Registration: BioRxiv
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9. Registration: Github
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10. Registration: WikiPathways
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11. Registration: NeuroLex
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12. Registration: Nanopublications
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13. Registration: some observations
 Decoupling registration from certification
 Timestamping, versioning
 Registration of various types of objects
 Machines as creators and contributors
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14. Certification: PubMed Commons
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15. Certification: PubPeer
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16. Certification: Publons
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17. Certification: some observations
 Peer-review decoupled from publication process
 Certification of various types of objects
 Machines validating form
 Social endorsement
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18. Awareness: myExperiment
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19. Awareness: eLabNotebook RSS
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20. Awareness: Twitter
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21. Awareness: some observations
 Awareness for various types of objects
 Real time awareness
 Awareness support targeted at machines
 Awareness through social media
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22. Archiving: PDB
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23. Archiving: GenBank
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24. Characterising the future
Fixed Varying
Discrete Continuous
Hidden VisibleResearch Process
Nature of object
Process of making public
Speed of communicationDelayed Instant
Atomic CompoundAtomicity of object
Communicated object
Publication
+data proxies
Publication +
linked data +
linked models
Formal InformalNature of process11 July 2014 CC-BY-SA, @hvdsomp and @atreloar 24

25. Fundamental changes
 The research process (objects, social
dimension) is becoming more exposed
 Articles, books are no longer the only
relevant objects for research
communication
 Objects are no longer static
 Machines are joining humans as (co-
)creators and consumers of research
objects
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26. Pathfinder problems
 Integrity of the scholarly record
 The three obsolescences
 hardware
 file format
 software
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27. System of Journals: Archiving
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28. Web of Objects: Archiving?
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29. Not just citation relationships
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30. The problem of obsolescence
 Lifescience research environment can be viewed
as undergoing a process of accelerated evolution
 Other disciplines will hit these problems in time
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31. Cambrian explosion
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32. Hardware obsolescence: Roche 454
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33. Software obsolescence: too much choice, not
enough support
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34. Abandonware
 “Last summer, a member of the biology department of the
University of Udine in Italy approached Nicola Vitacolonna
with an intriguing project. The ANREP program, which
annotates structural motifs in gene or protein sequences,
was out of date having been written more than a decade
ago. Although still used by molecular biologists, its slow
computing ability meant a straightforward multiple search
could take all night on a desktop PC. The Udine biologist
wanted Vitacolonna, a postdoctoral fellow in
computational biology, to write a program that could do
the job more quickly.”
 Sam Jaffe, Scientists Abandon their Software, The Scientist, Feb 16, 2004
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35. File format obsolescence: Illumina
 Probability of error in basecalling encoded using ascii
code to reduce file size
 Meaning of the ascii code changed along the life cycle
and for data generated at different time points the
quality might be encoded differently
 “If you get an error like "Invalid quality score value",
your fastq file probably has Sanger (offset 33) instead
of Illumina (ASCII offset 64) quality scores. You'll need
to add the option "-Q33" to your FASTX Toolkit
arguments”. Obviously…
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36. Everett Rogers, Diffusion of Innovation, 1962
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37. Conclusions
 Need to move to a smaller number of standard file
formats
 Need to move to a more sustainable model of
software development and maintenance
 Need to encourage platform manufacturers to
innovate around the hardware, not the software
 NOTE: other disciplines are looking to lifesciences
to work out how to solve some of these problems
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38. On best practices in the development of
bioinformatics software, Front. Genet., 02 Jul 14
 Source code available to reviewers
 Software indexed, citable, available
 Source code documented
 Source code managed
 Test libraries, sample data and dataset repositories
available
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39. Questions?
 andrew.treloar@ands.org.au
 @atreloar
 https://www.slideshare.net/atreloar/the-
lifesciences-as-a-pathfinder-in-dataintensive-
research-practice
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