Poster presentation at the International Society for Biocuration Conference in Washington, DC in 2012.

1. Research
resources:
cura,ng
the
new
eagle-­‐i
discovery
system
Nicole
Vasilevsky1,
Tenille
Johnson2,
Karen
Corday2,
Carlo
Torniai1,
Ma:hew
Brush1,
Sco:
Hoffmann1,
Erik
Segerdell1,
Melanie
L.
Wilson1,
Christopher
J.
Shaffer1,
David
Robinson1,
and
Melissa
A.
Haendel1**
1
Oregon
Health
&
Science
University,
Library,
Portland,
Oregon
2
Harvard
Medical
School,
Center
for
Biomedical
InformaTcs,
Cambridge,
Massachuse:s
The
Ideal
Scholarly
Research
Cycle
o Researchers
produce
data
and
resources
that
lead
to
publicaTons.
Resources
and
data
1
Public
repositories
• eagle-­‐i
• MODs
• NIF
• Entrez
Gene...
Researcher
2
Professional
networking:
• VIVO
• Harvard
Profiles
• LinkedIn…
o Published
data
informs
researchers
of
new
experimental
designs.
Publica,ons
Public
repositories
• PubMed
• Google
Scholar
• Mendeley…
3
o InformaTon
about
researchers,
resources,
data,
and
published
papers
is
stored
in
various
public
repositories.
How
can
we
make
this
cycle
more
efficient?
Provide
scien,sts
with
the
tools
they
need
to
record
their
resources
during
the
course
of
research
During
the
course
of
collecTng
informaTon
about
research
resources,
which
many
laboratories
were
willing
to
share,
we
discovered
that
while
larger
core
faciliTes
rouTnely
have
resource
and
workflow
organizaTon
strategies,
primary
research
labs
very
rarely
do.
This
creates
barriers
to
reproducing
experiments
as
well
as
to
publishing
and
sharing
resources.
Giving
labs
organizaTonal
tools
can
help
address
these
issues.
The
eagle-­‐i
workflow
Seman,c
Web
Entry
and
Edi,ng
Tool
Data
Cura,on
at
eagle-­‐i
Data
collecTon
CuraTon
guidelines
Decision
trees
BiocuraTon
User
interface
design
SWEET
Search
applicaTon
Components
of
the
eagle-­‐i
annotaTon
tool,
known
by
the
acronym
SWEET,
are
generated
directly
from
the
eagle-­‐i
ontology.
The
SWEET
contains
both
annotaTon
fields
that
are
auto-­‐populated
using
the
ontology
(purple
box)
and
free
text
(orange
box).
Entrez
Gene
ID
links
out
to
the
NCBI
database
(red
box).
Fields
in
the
SWEET
can
also
link
records
to
other
records
in
the
repository,
such
as
related
publicaTons
or
documentaTon
(blue
box).
Users
can
request
new
terms
be
added
to
the
ontology
using
the
Term
Request
field.
SPARQL
query
tool
for
QA
Ontology
development
Google
code
Ontology
Browser
Development
of
data
curaTon
pracTces
at
eagle-­‐i
depended
on
the
Resource
NavigaTon
team
for
data
collecTon,
the
CuraTon
team
for
ontology
development
and
data
QA,
and
the
SoWware
team
for
user
interface
design
in
an
iteraTve
process.
Tools
and
documentaTon
were
developed
to
assist
users
and
team
members
with
each
of
these
processes.
Ontological
modeling
of
research
resources
Decision
trees
assist
with
data
entry
and
annota,on
of
resources
Denotes
quesTons
eliciTng
informaTon
for
annotaTon.
AnnotaTon
tool
InsTtuTonal
repositories
Denotes
required
annotaTons.
Denotes
redirecTon
to
a
different
decision
tree.
Denotes
drop
down
or
annotaTon
field
examples.
Denotes
higher
value/priority
annotaTons.
Denotes
medium
value/
priority
annotaTons.
Denotes
lower
value/priority
annotaTons.
erms
new
t
Biocurator
t
eques
R
Ontology
Request
resources
Researcher
Search
applicaTon
Lessons
Learned
eagle-­‐i
parTcipaTng
lab
The
goal
of
eagle-­‐i
is
to
make
scienTfic
research
resources
more
visible
via
a
federated
network
of
insTtuTonal
repositories.
Using
an
ontology-­‐driven
approach
for
biomedical
resource
annotaTon
and
discovery,
the
Network
currently
includes
resources
from
23
insTtuTons.
www.eagle-­‐i.net
Open
source
so;ware
available
at:
h=ps://open.med.harvard.edu/display/eaglei/So;ware
eagle-­‐i
Ontology
GoogleCode:
h=p://code.google.com/p/eagle-­‐i/
Major
eagle-­‐i
resource
types
are
shown
as
dark
boxes.
Persons
and
laboratories
play
a
central
role
in
eagle-­‐i.
Classes
and
properTes
are
reused
from
pre-­‐exisTng
ontologies
or
created
de
novo.
Examples
of
some
of
the
relaTons
between
the
classes
are
indicated.
New
ini,a,ves
with
eagle-­‐i
NCATS
has
funded
two
new
projects
that
leverage
eagle-­‐i
to
further
translaTonal
science.
The
first
project
aims
to
expand
the
breadth,
quality,
and
discoverability
of
data
about
people
and
resources
by
harmonizing
the
ontologies
of
VIVO,
eagle-­‐i,
and
ShareCenter
(www.ctsaconnect.org).
The
second
project
aims
to
expand
the
eagle-­‐i
plakorm
to
new
CTSA
insTtuTons,
and
to
publish
resources
as
Linked
Open
Data.
• Balance
the
data
you
need
with
the
data
you
can
get
• Documenta,on
and
quality
assurance
are
itera,ve
• Tools
and
technology
choices
depend
on
the
above
Acknowledgements
**We,
the
authors,
represent
the
members
and
leaders
of
the
eagle-­‐i
CuraTon
team,
and
describe
some
of
the
efforts
and
products
of
all
teams
involved
in
the
development
of
the
eagle-­‐i
discovery
system.
We
would
like
to
thank
the
Resource
NavigaTon
team,
led
by
Richard
Pearse;
SoWware
Build
team,
led
by
Daniela
Bourges;
and
Project
Management
team,
led
by
Julie
McMurry.
We
would
also
like
to
thank
Jackie
Wirz.
We
gratefully
acknowlege
NIH
award
#U24RR029825.