Making Data Usable as Well as Useful
Cherri M. Pancake
NACSE (Oregon State University)
pancake@nacse.org
Northwest Alliance for Computational Science & Engineering − Oregon State University
Data Usability Is a “Human Problem”
Ø Data and documents are accumulated by a “cast of
hundreds”
Ø Destined to serve a “cast of
thousands” with distinct
§ Disciplinary backgrounds
§ Levels of expertise
§ Understanding of technology
Complex Data
Massive Data
Extreme
Extreme
Diversity
Scales process
delivery
delivery
process
How
How can
can the
the data
data
make
make data/information
data/information
intelligible
intelligible and
and usable?
usable?
Northwest Alliance for Computational Science & Engineering
Traditional Delivery: Link-Based
Ø Sensor data accessible by
format, year, site code
Ø Links indicate “meaning”,
provide access
Northwest Alliance for Computational Science & Engineering
Task-oriented Delivery
Exposes data meaning in ways that reflect key user tasks
Ø Well-chosen defaults
§ Help unfamiliar users
§ “Most likely values” based on
user studies
Ø Guided process
§ Users can follow different
paths based on different
needs
SDSU Biological Field Stations DB
Northwest Alliance for Computational Science & Engineering
Making Task-Oriented Delivery Work
Ø Results formatted onthe-fly
Ø Downloadable to
spreadsheets
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Usability Engineering 101
Ø Make the system reflect the tasks the user wants to
accomplish
Ø Make system respond to the needs of its different user
audiences
Northwest Alliance for Computational Science & Engineering
Audience-Oriented Delivery tailors access to support
different audiences
Ø Multi-key approach
maximizes flexibility for
individual users
§ Requires scientific
expertise
Ø Simple additions can
transforms interface for
use by novices
Lichens of North America DB
Northwest Alliance for Computational Science & Engineering
Usability Engineering 101
Ø Make the system reflect the tasks the user wants to
accomplish
Ø Make system respond to the needs of its different user
audiences
Ø Make the system adapt to the user – not the other way
around
Northwest Alliance for Computational Science & Engineering
Adding Intelligence to Delivery Systems
Ø To be most useful, data delivery systems must
locate/retrieve data that are personally relevant
§ Pertinent to individual user’s needs
§ Accessible at appropriate level of detail
§ Assist user’s step-by-step exploration
Ø Machine intelligence can assist these processes
§ Automatically leverage specialist/consultant expertise
§ Allow current users to benefit from past user experiences
Northwest Alliance for Computational Science & Engineering
Intelligent Delivery harnesses artificial intelligence to
adjust to user’s needs
Ø “Seed” system with expert
ratings/recommendations
Ø Use recommendations to
suggest user’s next steps
Tsunami Digital Library
Northwest Alliance for Computational Science & Engineering
Making Intelligent Delivery Work
Ø Engage users in rating “usefulness” of results
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Making Intelligent Delivery Work (2)
Ø Remember what each user did in the past, to make
future searches easier
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Summary
Ø Recording & preserving data only provides the “raw
material” (data that’s useful)
Ø Future usefulness depends on audiences who
§ Weren’t involved in data acquisition
§ May not know the data exists
§ Don’t know how to find it effectively
Ø Usability is required to attract those audiences
Our
Our challenge
challenge is
is to
to build
build systems
systems that
that help
help
Diverse
Diverse audiences
audiences ...
...
Access
Access data
data in
in “natural”
“natural” ways
ways ...
...
To
To accomplish
accomplish their
their tasks
tasks more
more productively
productively
Northwest Alliance for Computational Science & Engineering