Overview of scientific discourse annotatoin

A
brief
introduc.on
to

current
eﬀorts
in
scien.ﬁc
discourse
annota.on

Anita
de
Waard
Disrup/ve
Technology
Director,
Elsevier
Labs
-‐
also
on
behalf
of
HCLS/UU/D2S...
hEp://elsatglabs.com/labs/anita

Thursday, October 20, 2011

One
way
of
subdividing
the
ﬁeld
of
Scien/ﬁc
Discourse
Annota/on:

2


One
way
of
subdividing
the
ﬁeld
of
Scien/ﬁc
Discourse
Annota/on:
Five
levels
of
markup:

2


One
way
of
subdividing
the
ﬁeld
of
Scien/ﬁc
Discourse
Annota/on:
Five
levels
of
markup:

1.Sec/on:
“Discussion”,
~
several
paragraphs
(+HCLS)

2


One
way
of
subdividing
the
ﬁeld
of
Scien/ﬁc
Discourse
Annota/on:
Five
levels
of
markup:

1.Sec/on:
“Discussion”,
~
several
paragraphs
(+HCLS)
2.Module:
“Research
Ques/on”,
~
paragraph

2


One
way
of
subdividing
the
ﬁeld
of
Scien/ﬁc
Discourse
Annota/on:
Five
levels
of
markup:

1.Sec/on:
“Discussion”,
~
several
paragraphs
(+HCLS)
2.Module:
“Research
Ques/on”,
~
paragraph
3.Statement:
“Hypothesis”,
~
sentence/clause
(+UU)

2


One
way
of
subdividing
the
ﬁeld
of
Scien/ﬁc
Discourse
Annota/on:
Five
levels
of
markup:

1.Sec/on:
“Discussion”,
~
several
paragraphs
(+HCLS)
2.Module:
“Research
Ques/on”,
~
paragraph
3.Statement:
“Hypothesis”,
~
sentence/clause
(+UU)
4.Rela/on:
“Supports”,
~
hyperlink
(En/ty:
“Gene
Name”,
~
NP)

2


One
way
of
subdividing
the
ﬁeld
of
Scien/ﬁc
Discourse
Annota/on:
Five
levels
of
markup:

1.Sec/on:
“Discussion”,
~
several
paragraphs
(+HCLS)
2.Module:
“Research
Ques/on”,
~
paragraph
3.Statement:
“Hypothesis”,
~
sentence/clause
(+UU)
4.Rela/on:
“Supports”,
~
hyperlink
(En/ty:
“Gene
Name”,
~
NP)
5.Special
case
of
3&4:
Claim/Evidence
network
(+D2S)

2


One
way
of
subdividing
the
ﬁeld
of
Scien/ﬁc
Discourse
Annota/on:
Five
levels
of
markup:

1.Sec/on:
“Discussion”,
~
several
paragraphs
(+HCLS)
2.Module:
“Research
Ques/on”,
~
paragraph
3.Statement:
“Hypothesis”,
~
sentence/clause
(+UU)
4.Rela/on:
“Supports”,
~
hyperlink
(En/ty:
“Gene
Name”,
~
NP)
5.Special
case
of
3&4:
Claim/Evidence
network
(+D2S)
For
each
level:

2


One
way
of
subdividing
the
ﬁeld
of
Scien/ﬁc
Discourse
Annota/on:
Five
levels
of
markup:

1.Sec/on:
“Discussion”,
~
several
paragraphs
(+HCLS)
2.Module:
“Research
Ques/on”,
~
paragraph
3.Statement:
“Hypothesis”,
~
sentence/clause
(+UU)
4.Rela/on:
“Supports”,
~
hyperlink
(En/ty:
“Gene
Name”,
~
NP)
5.Special
case
of
3&4:
Claim/Evidence
network
(+D2S)
For
each
level:

a) Why?
Use
cases

2


One
way
of
subdividing
the
ﬁeld
of
Scien/ﬁc
Discourse
Annota/on:
Five
levels
of
markup:

1.Sec/on:
“Discussion”,
~
several
paragraphs
(+HCLS)
2.Module:
“Research
Ques/on”,
~
paragraph
3.Statement:
“Hypothesis”,
~
sentence/clause
(+UU)
4.Rela/on:
“Supports”,
~
hyperlink
(En/ty:
“Gene
Name”,
~
NP)
5.Special
case
of
3&4:
Claim/Evidence
network
(+D2S)
For
each
level:

a) Why?
Use
cases

b) What,
by
whom?
Concepts,
ontology,
authors?
2


One
way
of
subdividing
the
ﬁeld
of
Scien/ﬁc
Discourse
Annota/on:
Five
levels
of
markup:

1.Sec/on:
“Discussion”,
~
several
paragraphs
(+HCLS)
2.Module:
“Research
Ques/on”,
~
paragraph
3.Statement:
“Hypothesis”,
~
sentence/clause
(+UU)
4.Rela/on:
“Supports”,
~
hyperlink
(En/ty:
“Gene
Name”,
~
NP)
5.Special
case
of
3&4:
Claim/Evidence
network
(+D2S)
For
each
level:

a) Why?
Use
cases

b) What,
by
whom?
Concepts,
ontology,
authors?
c) How?
Manual,
automated?
2


1.
Sec/on-‐level
markup

3


1.
Sec/on-‐level
markup

INTRODUCTION

3


1.
Sec/on-‐level
markup
a.Why
mark
up
sec/ons?
-‐ Search:
e.g.
search
for
en//es

in
Methods
-‐ Visualisa/on:
e.g.
structured

browse
at
sec/on
level

INTRODUCTION

3


1.
Sec/on-‐level
markup
a.Why
mark
up
sec/ons?
-‐ Search:
e.g.
search
for
en//es

in
Methods
-‐ Visualisa/on:
e.g.
structured

browse
at
sec/on
level
b.What,
by
whom?
-‐ Background/Contribu/on/
Discussion
model
for
CS INTRODUCTION

-‐ HCLS:
Ontology
of
Rhetorical

Blocks
(ORB)=
IMRaD
in
OWL

3


1.
Sec/on-‐level
markup
a.Why
mark
up
sec/ons?
-‐ Search:
e.g.
search
for
en//es
Annotation

in
Methods
-‐ Visualisa/on:
e.g.
structured

browse
at
sec/on
level
b.What,
by
whom?
Discussion
model
for
CS INTRODUCTION

-‐ HCLS:
Ontology
of
Rhetorical

Blocks
(ORB)=
IMRaD
in
OWL

3


1.
Sec/on-‐level
markup
a.Why
mark
up
sec/ons?
-‐ Search:
e.g.
search
for
en//es
Annotation

in
Methods
-‐ Visualisa/on:
e.g.
structured

browse
at
sec/on
level
b.What,
by
whom?
Discussion
model
for
CS INTRODUCTION

-‐ HCLS:
Ontology
of
Rhetorical

Blocks
(ORB)=
IMRaD
in
OWL
c. Automate?

-‐ Yes
-‐[Hovy/Ramakrishnan] 3


HCLS
SciDis:
develop
standards
for
this
markup

4


2.a.
Module-‐level
markup:
why?
-‐ BeEer
search:
e.g.
query
inside
‘Research
ques/on’
-‐ Ini/al
idea:
content
reuse,
e.g.
-‐ Write
Methods
sec/ons
once,
import/link
many
-‐ Diﬀerent
way
of
crea/ng
a
collec/on
of
scholarly

content:
not
standalone
narra/ve,
but
connected

set
of
modules

5


2.b.
Module-‐level
markup:
What,
by
whom?

6


2.b.
Module-‐level
markup:
What,
by
whom?

-‐ Kircz,
’98:
“a
much
more
radical

approach
would
be
to
[break]
apart
the

linear
text
into
independent
modules,

each
with
its
own
unique
cogni/ve

character.”

6


2.b.
Module-‐level
markup:
What,
by
whom?

-‐ Kircz,
’98:
“a
much
more
radical

approach
would
be
to
[break]
apart
the

linear
text
into
independent
modules,

each
with
its
own
unique
cogni/ve

character.”
-‐ Harmsze,
‘00:
modular
model
for

physics
papers

6


2.b.
Module-‐level
markup:
What,
by
whom?

-‐ Kircz,
’98:
“a
much
more
radical

approach
would
be
to
[break]
apart
the

linear
text
into
independent
modules,

each
with
its
own
unique
cogni/ve

character.”
-‐ Harmsze,
‘00:
modular
model
for

physics
papers
-‐ LiquidPub,
2010:
Structured
Knowledge

Objects

6


2.b.
Module-‐level
markup:
What,
by
whom?

-‐ Kircz,
’98:
“a
much
more
radical

approach
would
be
to
[break]
apart
the

linear
text
into
independent
modules,

each
with
its
own
unique
cogni/ve

character.”
-‐ Harmsze,
‘00:
modular
model
for

physics
papers
-‐ LiquidPub,
2010:
Structured
Knowledge

Objects

-‐ HCLS:
Medium-‐grained
structure:

core
narra/ve
components 6


Story
grammar
model
for
science
The Story of Goldilocks and Story Grammar Paper The AXH Domain of Ataxin-1 Mediates
the Three Bears Neurodegeneration through Its Interaction with Gﬁ-1/
Senseless Proteins
Once upon a time Time Setting Background The mechanisms mediating SCA1 pathogenesis are still not fully
understood, but some general principles have emerged.
a little girl named Goldilocks Characters Objects of study the Drosophila Atx-1 homolog (dAtx-1) which lacks a polyQ tract,

She went for a walk in the forest. Location Experimental studied and compared in vivo effects and interactions to those of
Pretty soon, she came upon a setup the human protein
house.
She knocked and, when no one Goal Theme Research Gain insight into how Atx-1's function contributes to SCA1
answered, goal pathogenesis. How these interactions might contribute to the
disease process and how they might cause toxicity in only a
she walked right in. subset of neurons in SCA1 is not fully understood.
Atx-1 may play a role in the regulation of gene expression
Attempt Hypothesis

At the table in the kitchen, there Name Episode 1 Name dAtX-1 and hAtx-1 Induce Similar Phenotypes When
were three bowls of porridge. Overexpressed in Files
Goldilocks was hungry. Subgoal Subgoal test the function of the AXH domain
She tasted the porridge from the Attempt Method overexpressed dAtx-1 in flies using the GAL4/UAS system
first bowl. (Brand and Perrimon, 1993) and compared its effects to those of
This porridge is too hot! she Outcome Results hAtx-1.
Overexpression of dAtx-1 by Rhodopsin1(Rh1)-GAL4, which
exclaimed. drives expression in the differentiated R1-R6 photoreceptor cells
(Mollereau et al., 2000 and O'Tousa et al., 1985), results in
neurodegeneration in the eye, as does overexpression of hAtx-1
[82Q]. Although at 2 days after eclosion, overexpression of either
So, she tasted the porridge from Activity Data (data not shown),
Atx-1 does not show obvious morphological changes in the
the second bowl.
photoreceptor cells
This porridge is too cold, she said Outcome Results both genotypes show many large holes and loss of cell integrity
at 28 days
So, she tasted the last bowl of Activity Data (Figures 1B-1D).
porridge.
Ahhh, this porridge is just right, Outcome Results Overexpression of dAtx-1 using the GMR-GAL4 driver also
she said happily and induces eye abnormalities. The external structures of the eyes
7 that overexpress dAtx-1 show disorganized ommatidia and loss
she ate it all up. Data (Figure 1F),
of interommatidial bristles


2.c.
Module-‐level
markup:
how?

8


2.c.
Module-‐level
markup:
how?
-‐ Automated
recogni/on:
very
diﬃcult:

8


2.c.
Module-‐level
markup:
how?
-‐ Automated
recogni/on:
very
diﬃcult:
-‐ How
do
you
know
where
the
boundaries
are?

8


2.c.
Module-‐level
markup:
how?
-‐ Automated
recogni/on:
very
diﬃcult:
-‐ How
do
you
know
where
the
boundaries
are?

-‐ Even
diﬃcult
for
author
to
iden/fy!

8


2.c.
Module-‐level
markup:
how?
-‐ Automated
recogni/on:
very
diﬃcult:
-‐ How
do
you
know
where
the
boundaries
are?

-‐ Even
diﬃcult
for
author
to
iden/fy!

-‐ Author
creates:
templates.

8


2.c.
Module-‐level
markup:
how?
-‐ Automated
recogni/on:
very
diﬃcult:
-‐ How
do
you
know
where
the
boundaries
are?

-‐ Even
diﬃcult
for
author
to
iden/fy!

-‐ Author
creates:
templates.
-‐ XPharm,
2001:
modular
text
book
in
pharmacology:

8


2.c.
Module-‐level
markup:
how?
-‐ Automated
recogni/on:
very
diﬃcult:
-‐ How
do
you
know
where
the
boundaries
are?

-‐ Even
diﬃcult
for
author
to
iden/fy!

-‐ Author
creates:
templates.
-‐ XPharm,
2001:
modular
text
book
in
pharmacology:
-‐ Only
works
if
you

pay
authors!

8


2.c.
Module-‐level
markup:
how?
-‐ Automated
recogni/on:
very
difficult:
-‐ How
do
you
know
where
the
boundaries
are?

-‐ Even
difficult
for
author
to
iden/fy!

-‐ Author
creates:
templates.
-‐ XPharm,
2001:
modular
text
book
in
pharmacology:
-‐ Only
works
if
you

pay
authors!
-‐ Mo/f
detec/on
work
might
offer
help?

8


3.
Statement-‐level
markup

9


3.
Statement-‐level
markup
a.Why?
-‐ Automated
summarisa/on?
-‐ Towards
claim-‐evidence
networks

9


3.
Statement-‐level
markup
a.Why?
-‐ Automated
summarisa/on?
-‐ Towards
claim-‐evidence
networks
b.How,
by
whom?

-‐ Comparison
of
three
groups:

1.Liakata
et
al.:
CoreSC
2.Ananiadou
et
al.:
Metaknowledge
annota/on
3.De
Waard/Pander
Maat:
Discourse
Segment
Types
-‐ Annotated
three
texts:
compare
schemes,
levels,

annota/on
overlap
9


3.1
Liakata
et
al.:
Core-‐Scien/ﬁc
Concepts

(CoreSC)
Annota/on
Scheme

s


3.1
Liakata
et
al.:
Core-‐Scien/fic
Concepts

(CoreSC)
Annota/on
Scheme
Three-‐layer,
ontology-‐mo/vated
annota/on
scheme
for
sentence

annota/on,
which
views
a
paper
as
the
humanly
readable

representa0on
of
a
scien0fic
inves0ga0on:
[45-‐page
guideline:

Liakata
&
Soldatova
2008]

-‐ 1st
layer:
Core
Scien4fic
Concepts
(CoreSCs):

Hypothesis,
Mo/va/on,
Goal,
Object,
Background,
Method,

Experiment,
Model,
Observa/on,
Result,
Conclusion

-‐ 2nd
layer:
Proper4es
of
CoreSCs.
s

Novelty
(New/Old)
and
Advantage
(advantage/disadvantage)
-‐ 3rd
layer:
Concept
Iden4fiers:

linking
sentences
together
which
refer
to
the
same
instance
of

a
CoreSC


3.1
CoreSC
Annota/on
tool:


3.1
CoreSC
Annota/on
tool:

• Automated
annota/on
with
CoreSC
system
well
underway!


3.2.
Ananiadou
et
al:
Metaknowledge
annota/on:

Knowledge
Type Certainty
Level
•
Inves4ga4on
•L3
•
Observa4on
•L2
•
Analysis
•L1
•
General

Par4cipants Bio-‐Event Class
/
Type
•
Theme(s) (Centred
on
an
Event
(Grounded
to
an
event

•
Actor(s) Trigger) ontology)

Source Manner Polarity
•
High
•
Other •
Nega4ve
•
Low
•
Current •
Posi4ve
•
Neutral


3.2
Example
of
Metaknowledge
annota/on:

S3 = These results suggest that Y has no effect on
expression of X

Knowledge Certainty Lexical

Event Manner Source
Type Level Polarity

E1 General L3 Posi4ve Neutral Current

E2 Analysis L2 Nega4ve Neutral Current


3.2
Example
of
Metaknowledge
annota/on:

S3 = These results suggest that Y has no effect on
expression of X

Knowledge Certainty Lexical

Event Manner Source
Type Level Polarity

E1 General L3 Posi4ve Neutral Current

E2 Analysis L2 Nega4ve Neutral Current

• Manual
annota/on
underway
of
the
GENIA
event
corpus
(1000
MEDLINE
abstracts)

3.3
de
Waard/Pander
Maat:
Discourse
Segment
Types

Both seminomas and the EC component of
nonseminomas share features with ES cells. To
exclude that the detection of miR-371-3 merely
reflects its expression pattern in ES cells, we tested
by RPA miR-302a-d, another ES cells-specific
miRNA cluster (Suh et al, 2004). In many of the
miR-371-3 expressing seminomas and
nonseminomas, miR-302a-d was undetectable (Figs
S7 and S8), suggesting that miR-371-3 expression
is a selective event during tumorigenesis.


3.3
de
Waard/Pander
Maat:
Discourse
Segment
Types

nonseminomas share features with ES cells.
exclude thatthat detection of miR-371-3 merely
To exclude the
reflects its expression pattern in ES cells,reflects its
the detection of miR-371-3 merely we tested
expression pattern in ES cells,
miRNA cluster RPA miR-302a-d, another ES cells-
we tested by (Suh et al, 2004). In many of the
m i R - 3 7 miRNAx p r e s s(Suh et e m2004). a s a n d
specific 1 - 3 e cluster i n g s al, i n o m
In many of the miR-371-3 expressing seminomas
S7 and S8), suggesting that miR-371-3undetectable
and nonseminomas, miR-302a-d was expression
(Figs S7 and S8),
suggesting that
miR-371-3 expression is a selective event during
tumorigenesis.


3.3
de
Waard/Pander
Maat:
Discourse
Segment
Types

Both seminomas and the EC component of Fact
To exclude the
the detection of miR-371-3 merely we tested
(Figs S7 and S8),
suggesting that
tumorigenesis.


3.3
de
Waard/Pander
Maat:
Discourse
Segment
Types

To exclude the
the detection of miR-371-3 merely we tested Hypothesis
(Figs S7 and S8),
suggesting that
tumorigenesis.


3.3
de
Waard/Pander
Maat:
Discourse
Segment
Types

To exclude the
specific 1 - 3 e cluster i n g s al, i n o m Method
(Figs S7 and S8),
suggesting that
tumorigenesis.


3.3
de
Waard/Pander
Maat:
Discourse
Segment
Types

To exclude the
and nonseminomas, miR-302a-d was expression Result
(Figs S7 and S8),
suggesting that
tumorigenesis.


3.3
de
Waard/Pander
Maat:
Discourse
Segment
Types

To exclude the
(Figs S7 and S8),
suggesting that
Implication
tumorigenesis.


3.3
de
Waard/Pander
Maat:
Discourse
Segment
Types

To exclude the Goal
(Figs S7 and S8),
suggesting that
Implication
tumorigenesis.


3.3
de
Waard/Pander
Maat:
Discourse
Segment
Types

To exclude the Goal
(Figs S7 and S8),
suggesting that Reg-Implication
Implication
tumorigenesis.


3.3
de
Waard/Pander
Maat:
Discourse
Segment
Types

Conceptual
Both seminomas and the EC component of knowledge
Fact
To exclude the Goal
(Figs S7 and S8),
Implication
tumorigenesis.


3.3
de
Waard/Pander
Maat:
Discourse
Segment
Types

Conceptual
Both seminomas and the EC component of knowledge
Fact
To exclude the Goal
Experimental
Evidence
(Figs S7 and S8),
Implication
tumorigenesis.


3.3
Iden/ﬁca/on
of
DSTs:

15


3.3
Iden/ﬁca/on
of
DSTs:
-‐ Verb
form:
tense,
e.g.

-‐ Concepts
in
‘state’
(gnomic)
present:
‘Dopaminergic
innerva/on
plays
a
major
role
in
the
control
of

mood
and
its
perturba/on’

-‐ Experiments
in
‘event’
past:

‘Four
out
of
seven
cell
lines
expressed
this
cluster’

15


3.3
Iden/ﬁca/on
of
DSTs:
-‐ Verb
form:
tense,
e.g.

-‐ Concepts
in
‘state’
(gnomic)
present:
‘Dopaminergic
innerva/on
plays
a
major
role
in
the
control
of

mood
and
its
perturba/on’

-‐ Experiments
in
‘event’
past:

‘Four
out
of
seven
cell
lines
expressed
this
cluster’
-‐ Seman4c
verb
class:

-‐ Research
verbs
(Inves/ga/on,
Predic/on,
Procedure,

Observa/on,
Interpreta/on)
-‐ Discourse
verbs

-‐ Proper/es
and
rela/onships
-‐
between
things
and
concepts

15


3.3
Iden/ﬁca/on
of
DSTs:
-‐ Verb
form:
tense,
e.g.

-‐ Concepts
in
‘state’
(gnomic)
present:
‘Dopaminergic
innerva/on
plays
a
major
role
in
the
control
of

mood
and
its
perturba/on’

-‐ Experiments
in
‘event’
past:

‘Four
out
of
seven
cell
lines
expressed
this
cluster’
-‐ Seman4c
verb
class:

-‐ Research
verbs
(Inves/ga/on,
Predic/on,
Procedure,

Observa/on,
Interpreta/on)
-‐ Discourse
verbs

-‐ Proper/es
and
rela/onships
-‐
between
things
and
concepts
-‐ Modality

-‐ Types:
Source
{Author,
others,
unknown},
Basis
{Data,

Reasoning,
0},
Value
{Certain,
probable,
possible,
unknown}
-‐ Markers:
Modal
aux,
verb
class
Interpreta/on,
epistemic
adverbs
15


3.
Same
Statement
annotated
three
ways:


3.
Same
Statement
annotated
three
ways:
CoreSC:
<annotationART atype="GSC" type="Res" conceptID="Res24" novelty="None" advantage="None">
Here we show that BOB.1/OBF.1 regulates Btk gene expression.
</annotationART>

BioEvent/MetaKnowledge:
<sentence id="S6">Here we show that
<term id="T13" sem="Protein_family_or_group">
<gene-or-gene-product id="G9">BOB.1</gene-or-gene-product>/
<gene-or-gene-product id="G10">OBF.1</gene-or-gene-product>
</term> regulates
<term id="T14" sem="Biological_process">
<term id="T15" sem="DNA_domain_or_region">
<gene-or-gene-product id="G11">Btk
</gene-or-gene-product> gene
</term> expression
</term>.
</sentence>

Discourse Segments:
<segment segID ="286" section = "D" segtype = "RegImplication">
Here we show that
</segment>
<segment segID ="287" section = "D" segtype = "Implication">


3.
Same
Statement
annotated
three
ways:
CoreSC:
<annotationART atype="GSC" type="Res" conceptID="Res24" novelty="None" advantage="None">
Here we show that BOB.1/OBF.1 regulates Btk gene expression.
</annotationART>

BioEvent/MetaKnowledge:
<sentence id="S6">Here we show that
<term id="T13" sem="Protein_family_or_group">
<gene-or-gene-product id="G9">BOB.1</gene-or-gene-product>/
<gene-or-gene-product id="G10">OBF.1</gene-or-gene-product>
</term> regulates
<term id="T14" sem="Biological_process">
<term id="T15" sem="DNA_domain_or_region">
<gene-or-gene-product id="G11">Btk
</gene-or-gene-product> gene
</term> expression
</term>.
</sentence>

Discourse Segments:
<segment segID ="286" section = "D" segtype = "RegImplication">
Here we show that
</segment>
<segment segID ="287" section = "D" segtype = "Implication">
BOB.1/OBF.1 regulates Btk gene expression.
</segment>

3.
Comparing
statement-‐level
annota/on
models
Who Why What How
Liakata:
CoreSC Iden/fy
main
Sentence Manual
corpus,

components
of
automated

scien/fic
inves/ga/on
annota/on
tools
-‐

for
machine
learning working
on

automated
detec/on

Ananiadou:
Enhance
informa/on
Events
(intra-‐ Manual
corpus,

MetaKnowledge/ extrac/on
for
senten/al):
can
be
working
on

BioEvents biomedical
texts
to
several
per
automated
detec/on
enable
metadiscourse
sentence,
or
one
in

annota/on more
sentences
de
Waard: Iden/fy
mechanisms
Clause Manual,
ideas
(but
no

Discourse
Segment
of
conveying
real
plans!)
for

Types (epistemic)
knowledge
automated

in
scien/fic

discourse iden/fica/on


4.
Rela.ons
a.Why?
-‐ Argumenta/on
visualisa/on
b.What,
by
whom?

-‐ Harmsze
(1999):
Ontology
of

content
rela/onships
-‐ IBIS,
ClaiMaker
(2001)
-‐ Diligent
argumenta/on

ontology
(2005)

-‐ SALT:
RST
(2007)
-‐ SWAN
(2010)
c. How?

-‐ So
far:
Manually 18


5.Claim-‐Evidence
Networks
(statement
+
rela/ons)

19


5.Claim-‐Evidence
Networks
(statement
+
rela/ons)
a.Why?

19


5.Claim-‐Evidence
Networks
(statement
+
rela/ons)
a.Why?
Show
argumenta/on

across
body
of
work

19


5.Claim-‐Evidence
Networks
(statement
+
rela/ons)
a.Why?
Show
argumenta/on

across
body
of
work
b.What,
by
whom?

19


5.Claim-‐Evidence
Networks
(statement
+
rela/ons)
a.Why?
Show
argumenta/on

across
body
of
work
b.What,
by
whom?
-‐ Buckingham
Shum,
1999

19


5.Claim-‐Evidence
Networks
(statement
+
rela/ons)
a.Why?
Show
argumenta/on

across
body
of
work
b.What,
by
whom?
-‐ Buckingham
Shum,
1999
-‐ SWAN:
Clark,
Ciccarese

et
al.,
2005

19


5.Claim-‐Evidence
Networks
(statement
+
rela/ons)
a.Why?
Show
argumenta/on

across
body
of
work
b.What,
by
whom?
-‐ Buckingham
Shum,
1999
-‐ SWAN:
Clark,
Ciccarese

et
al.,
2005
-‐ Nanopublica/ons:

Mons,
2010

19


5.Claim-‐Evidence
Networks
(statement
+
rela/ons)
a.Why?
Show
argumenta/on

across
body
of
work
b.What,
by
whom?
-‐ Buckingham
Shum,
1999
-‐ SWAN:
Clark,
Ciccarese

et
al.,
2005

Mons,
2010
-‐ Nanopublica/ons
+

SWAN,
2011

19


5.Claim-‐Evidence
Networks
(statement
+
rela/ons)
a.Why?
Show
argumenta/on

across
body
of
work
b.What,
by
whom?
-‐ Buckingham
Shum,
1999
-‐ SWAN:
Clark,
Ciccarese

et
al.,
2005

Mons,
2010
+

SWAN,
2011
c.How?

19


5.Claim-‐Evidence
Networks
(statement
+
rela/ons)
a.Why?
Show
argumenta/on

across
body
of
work
b.What,
by
whom?
-‐ Buckingham
Shum,
1999
-‐ SWAN:
Clark,
Ciccarese

et
al.,
2005

Mons,
2010
+

SWAN,
2011
c.How?

-‐ So
far:
manually 19


D2S
Use
case:
Claim-‐Evidence
Network
in
Medicine

B. Elsevier-published
A. Philips’ Electronic Patient Records Clinical Guideline

C. Elsevier (or other publisher’s)
Research Report or Data

20

D2S
Use
case:
Claim-‐Evidence
Network
in
Medicine
Step 1: Patient data +
diagnosis link to Guideline
recommendation



20

D2S
Use
case:
Claim-‐Evidence
Network
in
Medicine
recommendation


Step 2: Guideline recommendation
links to evidence in report or data


20

D2S
Use
case:
Claim-‐Evidence
Network
in
Medicine
recommendation


Step 2: Guideline recommendation
links to evidence in report or data


Related
HCLS
Use
Case:
Accelerate
uptake
of
medical
research

on
drug-‐drug
interac/on
in
product
inserts 20

Five
levels
of
scien/ﬁc
discourse
annota/on

21


Five
levels
of
scien/ﬁc
discourse
annota/on
Why What/Who How

Automated!

Sec/on Search,
UI ABCDE,
ORB/HCLS
Publisher
helps?

Harmsze/Kircz,
LiquidPub,

Module Content
reuse
HCLS
Manual:
templates

Teufel,
Ananiadou,

Summaries;
Working
towards

Statement towards
networks
Liakata,

automated
detec/on
UU

SALT,
ScholOnto,
Diligent,
Manual:
some
tools,

Rela/ons Networks
SWAN never
took
oﬀ...

Claim/ Argumenta/on

ScholOnto,
SWAN,
Manual-‐
towards

Evidence networks Nanopublica/ons,
D2S automa/on?

21


Five
levels
of
scien/ﬁc
discourse
annota/on
Why What/Who How

Automated!

Sec/on Search,
UI ABCDE,
ORB/HCLS
Publisher
helps?

Harmsze/Kircz,
LiquidPub,

Module Content
reuse
HCLS
Manual:
templates
MoFfs?

Teufel,
Ananiadou,

Summaries;
Working
towards

Statement towards
networks
Liakata,

automated
detec/on
UU

SALT,
ScholOnto,
Diligent,
Manual:
some
tools,

Rela/ons Networks
SWAN never
took
oﬀ...

Claim/ Argumenta/on

ScholOnto,
SWAN,
Manual-‐
towards

Evidence networks Nanopublica/ons,
D2S automa/on?

21


Ques.ons:

22


Ques.ons:
Scien/ﬁc
discourse
-‐>
fairy
tales:
how
can
we
transfer
knowledge

here
to
scien/ﬁc
discourse
community?

22


Ques.ons:
Scien/ﬁc
discourse
-‐>
fairy
tales:
how
can
we
transfer
knowledge

here
to
scien/ﬁc
discourse
community?

Issue:
Scien/sts
do
not
like
being
told
that
they
write
fairy
tales!

22


Ques.ons:
Scien/fic
discourse
-‐>
fairy
tales:
how
can
we
transfer
knowledge

here
to
scien/fic
discourse
community?

Issue:
Scien/sts
do
not
like
being
told
that
they
write
fairy
tales!
Fairy
tales
-‐>
scien/fic
discourse:
is
anyone
here/in
this
community

interested
in
working
on
inter-‐domain
transfer
of
tools,

technologies
and
theories?

22


Ques.ons:
Scien/fic
discourse
-‐>
fairy
tales:
how
can
we
transfer
knowledge

here
to
scien/fic
discourse
community?

Issue:
Scien/sts
do
not
like
being
told
that
they
write
fairy
tales!
Fairy
tales
-‐>
scien/fic
discourse:
is
anyone
here/in
this
community

interested
in
working
on
inter-‐domain
transfer
of
tools,

technologies
and
theories?

Anita
de
Waard,
a.dewaard@elsevier.com

-‐HCLS:
hEp://www.w3.org/wiki/HCLSIG/SWANSIOC
-‐UU:
hEp://elsatglabs.com/labs/anita

-‐D2S:
hEp://www.data2seman/cs.org
22


Overview of scientific discourse annotatoin

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