What everybody knows but nobody says can hurt interdisciplinary research

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What everybody knows but nobody says can hurt
interdisciplinary research

• John V. Carlis
• University of Minnesota

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What we have here is a lack of communication
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Messages

• What everybody knows, nobody says
• Missed (not mis-) communication
  painful surprises
• Plan for success exponential growth in
  data beyond human scale
• Yeah! good work to do invent together

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Inter-Disciplinary Research

• IT-ist CS/Eng. /Math/Stat
• Tool Builder content neutral
• Biologist soils/neuro/microbio/dent/biochem/ecol/
  vet
• Content Seeker/Maker tool user
• Surprises Do

Inter-Alien Research
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Can an IT-ist become a Biologist or vice versa?

• Well, lifes too short
• specialization of labor
• bioinformatics grad minor
• CBCB in our future?

Ante-Disciplinary?
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Business Surprise

• User NO!
• IT but I built what you told me to build
• User I gave you a typical example, but of
  course there are exceptions
• IT you didnt tell me
• User you didnt ask, and, besides,
  everybody knows that

worse in science but why?
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Science for IT is harder

• Business human decides complexity
• Science -- reality gtgt models
• Exponential growth in data
• Competing models
• Lots of vocabulary
• Specific vs Abstract
• Vocabulary sloshes

? Surprises
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Surprise (1/5) Context

• Ph is not Ph
• need to remember instrument used
• Annotation
• Beyond genome is harder
• What plus When Where microarray mass
  spec
• ? harder to share/re-use data

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Surprise (2/5) Casual Vocabulary

• chimp
• chimp baby
• chimp offspring
• chimp offspring close personal
  friend

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Surprise (3/5) Success Brings Pain

• Prosites curated protein patterns
• descriptions 2 mb of free (con)text
• human browses ? toooo little
• success ? tooooooo many
• Genbank
• Obsolete fields
• misc
• Parsing free text is hard error prone

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Surprise (4/5) Vocabulary missing/overloaded/off

• Text readable only by those who already know
• Nouns pretty good
• Verbs -- Janeways Immunology
  mediate,
• Pathway
• BAD diagrams

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e.g., metadata
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Surprise (5/5) Idiosyncratic brain viewing

• Different machines,conditions warping
  parameters
• Fuss til it looks right
• a days work! requires scarce expertise
• Doesnt scale to comparisons among images

? processing plan is data too
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Can IT-ist ignore performance?

• IT-ist expects specifications
• Short run efficiency for given specs
• get it working
• but cycles/space cheap/available
• Change?
• Plan for unplanned changes

not trained/rewarded ? attitude lack vision
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• Togetherness
• Communication
• Anchored/Enabled/Rewarded

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Vocabulary Mantrawhat do we mean by one of this
type?

• Data Model
• What to remember, not how
• Fine distinctions singular/plural
• disease vs affliction
• host vs pathogen
• Multi, not single function,
• so not partition cluster

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Hit Limits ? DBMS Extensions

• manual brain image manipulations? new
  content-neutral operators
• this is a special case of what more general
  task
• constant ? vector
• multi-hull

not the query parachute in then explore
territory
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Interdisciplinary Impedance Mismatch

• Mundane vs interesting
• Messy problem (seeking insights) vs optimal
  solution (irrelevant but hopeful)
• Good clusters/fast algorithm/DB
• not directly a Bio goal
• Some professional danger but big potential reward

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Good Work

• Expect to struggle to communicate
• invent vocabulary
• define verbs
• Seek visionary colleagues
• ?

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