How to persuade with data

How to find networked knowledge:About
Stories, that Persuade With Data
Anita de Waard
VP Research Data Collaborations
a.dewaard@elsevier.com
Federal Big Data Meetup, May 20 2014

Discourse Comprehension 101
• Letter < syllable < word < clause < sentence < discourse:
This is how linguistics is structured.
But it is not how we understand text!

• Kintsch and Van Dijk, ‘93: we read a text at three levels:
– surface code: literal text, exact words/syntax
– text base: preserves meaning, but not exact wording
– situation model: ‘microworld’ that the text is about:
constructed inferentially through interaction between the
text and background knowledge
• We use knowledge about text genre to activate a schema:
this allows creation of the text base and situation model

In summary, how scientists read:
• Surface code provides noun phrases and triples that offer
pointers re. topical relevance
• Text base and and situation model are created through specific
metadiscourse conventions (e.g. refs at the end) that create a
biological reasoning model:
• This can be expressed as a set of claims, linked to evidence, that
can help represent key points in the paper
• Journal name and author’s affiliation help define schema and
provide ‘willingness to be convinced’ socially/interpersonally.
We next asked whether …
To do so, we transiently inhibited…
Suppression of X enhanced invasion …
but F was unaffected …(Figure 3A). …
Collectively, these data indicated that … .
Hypothesis
Goal/Method
Result
Results
Implication

human breast cancer
noninvasive MCF7-Ras
antisense oligonucleotides
high-grade malignancy
cell viability
retroviral vector
miR-31
cloned
transiently expressed miRNA sponges
Is it pertinent? -> Possibly…
Is it true? -> ?
Is it new, but in agreement with what I know? -> -?
What is this paper about?
A. NOUN PHRASES

Noun Phrases: some issues
• Problem 1: disambiguating terms (© GoPubMed):
– Hnrpa1 = Tis = Fli-2 = nuclear ribonucleoprotein A1 = helix
destabilizing protein = single-strand binding protein = hnRNP core
protein A1 = HDP-1 = topoisomerase-inhibitor suppressed.
– Cellulose 1,4-beta-cellobiosidase = exoglucanase
– COLD =/ C.O.L.D. =/ cold (runny nose) =/ cold (low T)
• Problem 2: disambiguating entities (© M. Martone):
– 95 antibodies were (manually!) identified in 8 articles
– 52 did not contain enough information to determine the antibody
used
– Some provided details in other papers
– Failed to give species, clonality, vendor, or catalog number

Noun Phrases: some progress
• Despite these difficulties, noun phrase recall/precision is
quite high, e.g. I2B22011 [1], [2], others: 90%-98%
• Many tools, see [3] for a list; e.g. GoPubMed:

miR-31 PREVENT acquisition of aggressive traits
miR-31 INHIBIT noninvasive MCF7-Ras cells
miR-31 ENHANCE invasion
cell viability AFFECT inhibitor
miR-31 expression DEPRIVE metastatic cells
Is it pertinent? -> Possibly…
Is it true? -> ?
Is it new, but in agreement with what I know? ->?
B. TRIPLES

Triples: some issues:
• Contingent on good NP & VP detection
• Hard to parse text! E.g. a commercial tool gave:
insulin maintaining glucose homeostasis
When insulin secretion cannot be increased adequately (type I
diabetes defect) to overcome insulin resistance in maintaining
glucose homeostasis, hyperglycemia and glucose intolerance
ensues.
insulin may be involved glucose homeostasis
Because PANDER is expressed by pancreatic beta-cells and in
response to glucose in a similar way to those of insulin, PANDER
may be involved in glucose homeostasis.

Triples: some progress:
Biological Expression Language [4]:
We provide evidence that these miRNAs are potential novel oncogenes participating in the development
of human testicular germ cell tumors by numbing the p53 pathway, thus allowing tumorigenic growth in
the presence of wild-type p53.
Increased abundance of miR-372 decreases activity of TP53
r(MIR:miR-372) -| tscript(p(HUGO:Trp53))
Context: cancer
SET Disease = “Cancer”
Activity of TP53 decreases cell growth
tscript(p(HUGO:Trp53)) -| bp(GO:”Cell Growth”

The preceding observations demonstrated that X expression deprives Y cells of
attributes associated with Z.
We next asked whether X also prevents the acquisition of A traits by B cells.
To do so, we transiently inhibited X in C cells with either D or E.
Both approaches inhibited X function by > 4.5-fold (Figure S7A).
Suppression of X enhanced invasion by 20-fold and motility by 5-fold, but F was
unaffected by either inhibitor (Figure 3A; Figure S7B).
The E sponge reduced X function by 2.5-fold, but did not affect the activity of other
known Js (Figures S8A and S8B).
Collectively, these data indicated that sustained X activity is necessary to prevent the
acquisition of Z traits by both K and untransformed B cells.
Is it pertinent? -> Need content
Is it true? -> Sounds likely! I know this stuff!
Is it new, but in agreement with what I know? -> Need content
C. METADISCOURSE

Metadiscourse: why it matters
• Voorhoeve et al., 2006: “These miRNAs neutralize p53- mediated CDK
inhibition, possibly through direct inhibition of the expression of the tumor
suppressor LATS2.”
• Kloosterman and Plasterk, 2006: “In a genetic screen, miR-372 and miR-373
were found to allow proliferation of primary human cells that express
oncogenic RAS and active p53, possibly by inhibiting the tumor suppressor
LATS2 (Voorhoeve et al., 2006).”
• Yabuta et al., 2007: “[On the other hand,] two miRNAs, miRNA-372 and-373,
function as potential novel oncogenes in testicular germ cell tumors by
inhibition of LATS2 expression, which suggests that Lats2 is an important tumo
suppressor (Voorhoeve et al., 2006).”
• Okada et al., 2011: “Two oncogenic miRNAs, miR-372 and miR-373, directly
inhibit the expression of Lats2, thereby allowing tumorigenic growth in the
presence of p53 (Voorhoeve et al., 2006).”
“[Y]ou can transform .. fiction into fact just by adding or
subtracting references”, Bruno Latour [5]

Metadiscourse: some progress
• Hedging cues, speculative language, modality/negation:
– Light et al [6]: finding speculative language
– Wilbur et al (Hagit) [7]: focus, polarity, certainty, evidence, and
directionality
– Thompson et al (Sophia) [8]: level of speculation, type/source of
the evidence and level of certainty
• Sentiment detection (e.g. Kim and Hovy [9] a.m.o.):
– Holder of the opinion, strength, polarity as ‘mathematical
function’ acting on main propositional content
• Can make this part of the semantic web: (e.g., Ontology for
Reasoning, Certainty and Attribution, ORCA [10]):
– Value (Presumed True, Probable, Possible, Unknown)
– Source (Author, Named Other, Unknown)
– Basis (Data, Reasoning, Unknown)

Claim:
• sustained miR-31 activity is necessary to prevent the acquisition of aggressive
traits by both tumor cells and untransformed breast epithelial
Evidence: Method:
• We transiently inhibited miR-31 in noninvasive MCF7-Ras cells with either
antisense oligonucleotides or miRNA sponges.
Evidence: Result:
• Both approaches inhibited miR-31 function by >4.5-fold (Figure S7A).
• Suppression of miR-31 enhanced invasion by 20-fold and motility by 5-
fold, but cell viability was unaffected by either inhibitor (Figure 3A; Figure
S7B).
• The miR-31 sponge reduced miR-31 function by 2.5-fold, but did not affect
the activity of other known antimetastatic miRNAs (Figures S8A and S8B).
D. CLAIMS AND EVIDENCE
Is it pertinent? -> Probably
Is it true? -> Sounds likely!
Is it new, but in agreement with what I know? -> Check/know

Claims and Evidence: some issues:
• Data2Semantics [11]: linking clinical guidelines to evidence.
Inconsistency within guideline and guidelines v. evidence:
• Studies have demonstrated inconsistent results regarding the use of such
markers of inflammation as C-reactive protein (CRP), interleukins- 6 (IL-6) and
-8, and procalcitonin (PCT) in neutropenic patients with cancer [55–57].
• [55]: PCT and IL-6 are more reliable markers than CRP for predicting
bacteremia in patients with febrile neutropenia
• [56] In conclusion, daily measurement of PCT or IL-6 could help identify
neutropenic patients with a stable course when the fever lasts >3 d. …,
it would reduce adverse events and treatment costs.
• [57] Our study supports the value of PCT as a reliable tool to predict
clinical outcome in febrile neutropenia.
• Drug Interaction Knowledgebase [12]: how to identify evidence?
• R-citalopram_is_not_substrate_of_cyp2c19:
• At 10uM R- or S-CT, ketoconazole reduced reaction velocity to 55 -60% of
control, quinidine to 80%, and omeprazole to 80-85% of control (Fig. 6).

Claims and Evidence: some progress
• Defining ‘salient knowledge components’ in text:
– Argumentative zones, CoreSC can both be found
– Blake, Claim networks (2012)
– Claimed Knowledge Updates (Sandor/de Waard, 2012):

Finding claims in XIP:
E.g. through scientific discourse analysis:
In contrast with previous hypotheses compact plaques form before significant
deposition of diffuse A beta, suggesting that different mechanisms are involved in the
deposition of diffuse amyloid and the aggregation into plaques.
Entities
Relationships
Temporality
Connections thematic roles
Status
core information
(proposition)
information extraction
rhetorical
metadiscourse
discourse analysis
discourse analysisdiscourse structure
Sándor, Àgnes and de Waard, Anita, (2012).

Formalizing claims with hedging:
Biological statement with BEL/ epistemic
markup
BEL representation: Epistemic
evaluation
These miRNAs neutralize p53-mediated CDK
inhibition, possibly through direct inhibition
of the expression of the tumor-suppressor
LATS2.
r(MIR:miR-372) -
|(tscript(p(HUGO:Trp53)) -|
kin(p(PFH:”CDK Family”)))
Increased abundance of miR-
372 decreases abundance of
LATS2
r(MIR:miR-372) -|
r(HUGO:LATS2)
Value =
Possible
Source =
Unknown
Basis =
Unknown
Biological statement with
Medscan/epistemic markup
MedScan Representation: Epistemic
evaluation
Furthermore, we present evidence that the
secretion of nesfatin-1 into the culture
media was dramatically increased during the
differentiation of 3T3-L1 preadipocytes into
adipocytes (P < 0.001) and after treatments
with TNF-alpha, IL-6, insulin, and
dexamethasone (P < 0.01).
IL-6  NUCB2 (nesfatin-1)
Relation: MolTransport
Effect: Positive
CellType: Adipocytes
Cell Line: 3T3-L1
Value =
Probable
Source =
Author
Basis = Data

25
Schema’s: scientific articles are stories...
The Story of Goldilocks and the
Three Bears
Story Grammar Paper The AXH Domain of Ataxin-1 Mediates 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.
Pretty soon, she came upon a
house.
Location Experimental
setup
studied and compared in vivo effects and interactions to those of the
human protein
She knocked and, when no one
answered,
Goal Theme Research
goal
Gain insight into how Atx-1's function contributes to SCA1 pathogenesis.
How these interactions might contribute to the disease process and how
they might cause toxicity in only a subset of neurons in SCA1 is not fully
understood.
she walked right in. Attempt Hypothesis Atx-1 may play a role in the regulation of gene expression
At the table in the kitchen, there
were three bowls of porridge.
Name Episode 1 Name dAtX-1 and hAtx-1 Induce Similar Phenotypes When Overexpressed in File
Goldilocks was hungry. Subgoal Subgoal test the function of the AXH domain
She tasted the porridge from the
first bowl.
Attempt Method overexpressed dAtx-1 in flies using the GAL4/UAS system (Brand and
Perrimon, 1993) and compared its effects to those of hAtx-1.
This porridge is too hot! she
exclaimed.
Outcome Results Overexpression of dAtx-1 by Rhodopsin1(Rh1)-GAL4, which drives
expression in the differentiated R1-R6 photoreceptor cells (Mollereau et a
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 Atx-1 does not show obvious morphological
changes in the photoreceptor cells
So, she tasted the porridge from the
second bowl.
Activity Data (data not shown),
This porridge is too cold, she said Outcome Results both genotypes show many large holes and loss of cell integrity at 28 days

...that persuade (editors/authors/readers!)…
Aristotle Quintilian Scientific Paper
prooimion
Introduction
/ exordium
The introduction of a speech, where one announces the
subject and purpose of the discourse, and where one usually
employs the persuasive appeal to ethos in order to establish
credibility with the audience.
Introduction:
positioning
prothesis
Statement
of
Facts/narrati
o
The speaker here provides a narrative account of what has
happened and generally explains the nature of the case.
Introduction: research
question
Summary/
propostitio
The propositio provides a brief summary of what one is about
to speak on, or concisely puts forth the charges or accusation.
Summary of contents
pistis
Proof/
confirmatio
The main body of the speech where one offers logical
arguments as proof. The appeal to logos is emphasized here.
Results
Refutation/
refutatio
As the name connotes, this section of a speech was devoted to
answering the counterarguments of one's opponent.
Related Work
epilogos peroratio
Following the refutatio and concluding the classical oration, the
peroratio conventionally employed appeals through pathos,
and often included a summing up.
Discussion: summary,
implications.

What about the data?
Using antibodies
and squishy bits
Grad Students experiment
and enter details into their
lab notebook.
The PI then tries to make
sense of their slides,
and writes a paper.
End of story.

7. Trusted (validated/checked by reviewers)
Maslow’s Hierarchy of Needs for Research Data
6. Reproducible (others can redo
experiments)
9. Usable (allow tools to run on it)
4. Comprehensible (others can understand
data & processes)
2. Archived (long-term & format-
independent)
1. Preserved (existing in some form)
5. Discoverable (can be indexed by a system)
3. Accessible (can be accessed by others)
8. Citable (able to point & track citations)

1. Preserve: Data Rescue Challenge
• With IEDA/Lamont: award succesful data
rescue attempts
• Awarded at AGU 2013
• 23 submissions of data that was digitized,
preserved, made available
• Winner: NIMBUS Data Rescue:
– Recovery, reprocessing and digitization of the
infrared and visible observations along with their
navigation and formatting.
– Over 4000 7-track tapes of global infrared
satellite data were read and reprocessed.
– Nearly 200,000 visible light images were
scanned, rectified and navigated.
– All the resultant data was converted to HDF-5
(NetCDF) format and freely distributed to users
from NASA and NSIDC servers.
– This data was then used to calculate monthly sea
ice extents for both the Arctic d the Antarctic.
• Conclusion: we (collectively) need to do more
of this! How can we fund it?
7. Trusted (validated/checked by
reviewers)
experiments)
4. Comprehensible (others can
understand data & processes)
1. Preserved (existing in some
form)
5. Discoverable (can be indexed by
a system)
8. Citable (able to point & track
citations)
3. Accessible (can be accessed by
others)
independent)

reviewers)
experiments)
others)
form)
a system)
independent)
citations)
2. Archive: Olive Project
• CMU CS & Library: funded by a grant
from the IMLS, Elsevier is partner
• Goal: Preservation of executable content
- nowadays a large part of intellectual
output, and very fragile
• Identified a series of software packages
and prepared VM to preserve
• Does it work? Yes – see video (1:24)

reviewers)
experiments)
form)
a system)
citations)
3. Access: Urban Legend
others)
independent)
• Part 1: Metadata acquisition
• Step through experimental process in series of dropdown
menus in simple web UI
• Can be tailored to workflow of individual researcher
• Connected to shared ontologies through lookup table,
managed centrally in lab
• Connect to data input console (Igor Pro)

reviewers)
experiments)
form)
a system)
citations)
4. Comprehend: Urban Legend
others)
independent)
• Part 2: Data Dashboard
• Access, select and manipulate data (calculate
properties, sort and plot)
• Final goal: interactive figures linked to data
• Plan to expand to more neuroscience labs
• Plan to build for geochemistry use case

reviewers)
experiments)
form)
a system)
citations)
5. Discover: Data Indexing proposals
• Collaborated on Data Discovery Index
proposal with UCSD/Carnegie Mellon
• Also worked with UIUC!
• Interested in developing distributed
infrastructures on making data easier to
search: what is the ‘Goldilocks lndex’ where
search is scalable, yet useful?
• Looking for academic/industry partners/use
cases/platforms to address the next stage
• Discoverability is key driver for
metadata/data format structure!
others)
independent)

reviewers)
experiments)
form)
a system)
citations)
6. Reproduce: Resource Identifier Initiative
Force11 Working Group to add data identifiers
to articles that is
– 1) Machine readable;
– 2) Free to generate and access;
– 3) Consistent across publishers and journals.
• Authors publishing in participating journals
will be asked to provide RRID's for their
resources; these are added to the keyword
field
• RRID's will be drawn from:
– The Antibody Registry
– Model Organism Databases
– NIF Resource Registry
• So far, Springer, Wiley, Biomednet, Elsevier
journals have signed up with 11 journals,
more to come
• Wide community adoption!
others)
independent)

reviewers)
experiments)
form)
a system)
citations)
7.Trust: Moonrocks
others)
independent)
How can we scale up data curation?
Pilot project with IEDA:
• A database for lunar geochemistry:
leapfrog & improve curation time
• 1-year pilot, funded by Elsevier
• Main conclusion: if spreadsheet
columns/headers map to RDB
schema we can scale curation cost!

reviewers)
experiments)
form)
a system)
citations)
8. Cite: Force11 Data Citation Principles
• Another Force11 Working group
• Defined 8 principles:
• Now seeking endorsement/working on
implementation
others)
independent)
1. Importance: Data should be considered legitimate, citable products of
research. Data citations should be accorded the same importance in
the scholarly record as citations of other research objects, such as
publications.
2. Credit and attribution: Data citations should facilitate giving scholarly
credit and normative and legal attribution to all contributors to the
data, recognizing that a single style or mechanism of attribution may
not be applicable to all data.
3. Evidence: Where a specific claim rests upon data, the corresponding
data citation should be provided.
4. Unique Identification: A data citation should include a persistent
method for identification that is machine actionable, globally unique,
and widely used by a community.
5. Access: Data citations should facilitate access to the data themselves
and to such associated metadata, documentation, and other materials,
as are necessary for both humans and machines to make informed use
of the referenced data.
6. Persistence: Metadata describing the data, and unique identifiers
should persist, even beyond the lifespan of the data they describe.
7. Versioning and granularity: Data citations should facilitate
identification and access to different versions and/or subsets of data.
Citations should include sufficient detail to verifiably link the citing
work to the portion and version of data cited.
8. Interoperability and flexibility: Data citation methods should be
sufficiently flexible to accommodate the variant practices among
communities but should not differ so much that they compromise
interoperability of data citation practices across communities.

reviewers)
experiments)
form)
a system)
citations)
9. Use: Executable Papers
• Result of a challenge to come up with
cyberinfrastructure components to
enable executable papers
• Pilot in Computer Science journals
– See all code in the paper
– Save it, export it
– Change it and rerun on data set:
others)
independent)

10: Integrate data creation with data use
7. Trusted (validated/checked by reviewers)
experiments)
4. Comprehensible (others can understand
data & processes)
independent)
1. Preserved (existing in some form)
5. Discoverable (can be indexed by a system)
3. Accessible (can be accessed by others)
8. Citable (able to point & track citations)
Work with domain data repositories to develop easier
ways to upload data that confirms to their schema.
Follow Force11 Resource Identification initiative;
reproducibility imitative. Support standard protocols.
Content enrichment using data, e.g. executable papers,
virtual microsope, database linking, and others
Build tools that allow researchers to interpret and
reevaluate their data directly; drive adoption of ELNs.
Software standards change: need investment in updating,
e.g. Olive Project to save OSs.
Key is to have data be digital and preservable, e.g. data
rescue challenge. Need funding for digitisation projects.
Collaborate on grants to develop data discovery tools;
promote and use common standards, indices.
Build and encourage electronic lab notebooks to ensure
data can be shared if/when needed; follow workflow.
Force11 Data Citation Principles link data to papers and
v.v. Issues: need better identifiers, granularity, versioning.
10.Integrateupstreamanddownstream–makemetadatato
serveuse.

Thank you!
Collaborations and discussions gratefully acknowledged:
• CMU: Nathan Urban, Shreejoy Tripathy, Shawn Burton, Rick
Gerkin, Santosh Chandrasekaran, Matthew Geramita, Eduard
Hovy
• UCSD: Phil Bourne, Brian Shoettlander, David Minor, Declan
Fleming, Ilya Zaslavsky
• NIF/Force11: Maryann Martone, Anita Bandrowski
• OHSU: Melissa Haendel, Nicole Vasilevsky
• California Digital Library: Carly Strasser, John Kunze, Stephen
Abrams
• IEDA: Kerstin Lehnert, Annika
• Elsevier: Mark Harviston, Jez Alder, David Marques

Questions?
Anita de Waard
VP Research Data Collaborations
a.dewaard@elsevier.com
http://researchdata.elsevier.com/

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