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A D V A N C E D
M A T E R I A L S
&
P R O C E S S E S |
A P R I L
2 0 1 6
2 5
T
echnological advances are con-
tinually made through innovative
processing, characterization, and
modeling techniques. Yet, efforts to
develop and deploy new materials are
hampered due to constraints in discov-
ering and accessing materials data and
a lack of interoperability among ad-
vanced analytic tools and techniques.
What could scientists accomplish with-
out these constraints? This is the goal
of the federal government’s Materials
Genome Initiative (MGI) launched in
2011—to develop an infrastructure that
eliminates these constraints, accelerat-
ing advanced materials discovery and
deployment. This article explores how
semantic technologies address three of
the four key challenges outlined in the
MGI Strategic Plan
[1]
, namely:
1. Lead a culture shift in materials re-
search by establishing mechanisms
that facilitate the flow of knowledge
across the materials-development
continuum through deeper commu-
nity collaboration.
2. Integrate experimental, computa-
tional, and theoretical knowledge
by developing advanced simulation
tools that are validated through
experimental data with networks to
share useful modeling and analysis
code and access to quantitative syn-
thesis and characterization tools.
DISTRIBUTED, CONNECTED
EVERYTHING: IT’S ALREADY
HAPPENING
The Materials Genome Initiative aims to enable discovery, manufacture,
and deployment of advanced materials twice as fast as using
traditional development methodologies, at a fraction of the cost.
Sam Chance, iNovex Information Systems, Hanover, Md.
Clare Paul, Air Force Research Laboratory, Dayton, Ohio
3. Make digital data accessible through
broad, open access to validated
data and tools generated by the
materials community across the
materials development continuum.
This allows both reuse of individual
data sets and application of data
analytics techniques to examine
the aggregation of large volumes of
data frommany disparate sources.
A CULTURE SHIFT
Web 1.0 gained traction in ways
that its creators did not expect. The
initial attempt to link documents via
a global network was motivated in
large part by the scientific community.
Web 1.0 creators built a framework for
global connectivity. As this framework
grew through incremental gains in
global adoption, commercial interests
became involved, and it created a sym-
biotic relationship
driving sustainable
growth well beyond initial expectations.
The adoption curve for transfor-
mative technologies extends well be-
yond typical technology curves, and
barriers to adoption are many. Extend-
ing this concept beyond the enterprise
and across an entire community of
enterprises increases the challenges
Fig. 1 —
Adoption curve for transformative technologies follows a path similar to Tuckman’s
group development model of form-storm-norm-perform.