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NIH, Bethesda, US, 2016-11-15
High throughput mining of the
scholarly literature
Peter Murray-Rust1,2
[1]University of Cambridge
[2]TheContentMine
pm286 AT cam DOT ac DOT uk
Scientific knowledge is for everyone
Themes
ā€¢ 500 Billion$ of funded STM research/year
ā€¢ 85% of medical research is wasted (Lancet 2011)
ā€¢ An Open mining toolset
ā€¢ Wikidata as the semantic backbone
ā€¢ Community involvement
ā€¢ Sociopolitical issues
ā€¢ My gratitude to NIH
ā€¢ Offers of collaboration; data ingestion? Software?
Sources?
http://www.nytimes.com/2015/04/08/opinion/yes-we-were-warned-about-
ebola.html
We were stunned recently when we stumbled across an article by European
researchers in Annals of Virology [1982]: ā€œThe results seem to indicate that
Liberia has to be included in the Ebola virus endemic zone.ā€ In the future,
the authors asserted, ā€œmedical personnel in Liberian health centers should be
aware of the possibility that they may come across active cases and thus be
prepared to avoid nosocomial epidemics,ā€ referring to hospital-acquired
infection.
Adage in public health: ā€œThe road to inaction is paved with research
papers.ā€
Bernice Dahn (chief medical officer of Liberiaā€™s Ministry of Health)
Vera Mussah (director of county health services)
Cameron Nutt (Ebola response adviser to Partners in Health)
A System Failure of Scholarly Publishing
CLOSED ACCESS
MEANS PEOPLE DIE
The Right to Read is the Right to Mine**PeterMurray-Rust, 2011
http://contentmine.org
(2x digital music industry!)
Scholarly publishing is ā€œBig Dataā€
[2] https://en.wikipedia.org/wiki/Mont_Blanc#/media/File:Mont_Blanc_depuis_Valmorel.jpg
586,364 Crossref DOIs 201507 [1] per month
2.5 million (papers + supplemental data) /year [citation needed]*
each 3 mm thick
ļƒž 4500 m high per year [2]
* Most is not Publicly readable
[1] http://www.crossref.org/01company/crossref_indicators.html
1 yearā€™s scholarly output!
What is ā€œContentā€?
http://www.plosone.org/article/fetchObject.action?uri=info:doi/10.1371/journal.pone.01113
03&representation=PDF CC-BY
SECTIONS
MAPS
TABLES
CHEMISTRY
TEXT
MATH
contentmine.org tackles these
Demos of mining
http://chemicaltagger.ch.cam.ac.uk/
ā€¢ Typical
Typical chemical synthesis
Automatic semantic markup of chemistry
Could be used for analytical, crystallization, etc.
AMI https://bitbucket.org/petermr/xhtml2stm/wiki/Home
Example reaction scheme, taken from MDPI Metabolites 2012, 2, 100-133; page 8, CC-BY:
AMI reads the complete diagram,
recognizes the paths and
generates the molecules. Then
she creates a stop-fram animation
showing how the 12 reactions
lead into each other
CLICK HERE FOR ANIMATION
https://bytebucket.org/petermr/xhtml2stm/wiki/animation.s
vg?rev=793a4d9ffa0616a84ff4aeabf80e657b5142ed33
(may be browser dependent)
Andy Howlett, Cambridge
ChemDataExtractor
ā€¢ http://chemdataextractor.org/docs/intro
ā€¢ http://chemdataextractor.org/demo
Swain, M. C., & Cole, J. M. "ChemDataExtractor: A Toolkit for Automated Extraction of
Chemical Information from the Scientific Literature", J. Chem. Inf. Model. 2016, 56 (10),
pp 1894ā€“1904 http://pubs.acs.org/doi/abs/10.1021/acs.jcim.6b00207
Europe PubMedCentral
2015
2016
Dictionaries!
catalogue
getpapers
query
Daily
Crawl
EuPMC, arXiv
CORE , HAL,
(UNIV repos)
Crossref PDF HTML
DOC ePUB
TeX XML
PNG
EPS CSV
XLSURLs
DOIs
crawl
quickscrape
norma
Normalizer
Structurer
Semantic
Tagger
Text
Data
Figures
ami
UNIV
Repos
search
Lookup
CONTENT
MINING
Chem
Phylo
Trials
Crystal
Plants
COMMUNITY
plugins
Visualization
and Analysis
PloSONE, BMC,
peerJā€¦ Nature, IEEE,
Elsevierā€¦
Publisher Sites
scrapers
queries
taggers
abstract
methods
references
Captioned
Figures
Fig. 1
HTML tables
100, 000 pages/day
Semantic ScholarlyHTML
(W3C community group)
Facts
Latest 20150908
abstract
methods
references
Captioned
Figures
Fig. 1
HTML tables
abstract
methods
references
Captioned
Figures
Fig. 1
HTML tables
Dict A
Dict B
Image
Caption
Table
Caption
MINING
with sections
and dictionaries
[W3C Annotation / https://hypothes.is/ ]
Disease Dictionary (ICD-10)
<dictionary title="disease">
<entry term="1p36 deletion syndrome"/>
<entry term="1q21.1 deletion syndrome"/>
<entry term="1q21.1 duplication syndrome"/>
<entry term="3-methylglutaconic aciduria"/>
<entry term="3mc syndromeā€
<entry term="corpus luteum cystā€/>
<entry term="cortical blindness" />
SELECT DISTINCT ?thingLabel WHERE {
?thing wdt:P494 ?wd .
?thing wdt:P279 wd:Q12136 .
SERVICE wikibase:label {
bd:serviceParam wikibase:language "en" }
}
wdt:P494 = ICD-10 (P494) identifier
wd:Q12136 = disease (Q12136) abnormal condition that
affects the body of an organism
Wikidata ontology for disease
Example statistics dictionary
<dictionary title="statistics2">
<entry term="ANCOVA" name="ANCOVA"/>
<entry term="ANOVA" name="ANOVA"/>
<entry term="CFA" name="CFA"/>
<entry term="EFA" name="EFA"/>
<entry term="Likert" name="Likert"/>
<entry term="Mann-Whitney" name="Mann-Whitney"/>
<entry term="MANOVA" name="MANOVA"/>
<entry term="McNemar" name="McNemar"/>
<entry term="PCA" name="PCA"/>
<entry term="Pearson" name="Pearson"/>
<entry term="Spearman" name="Spearman"/>
<entry term="t-test" name="t-test"/>
<entry term="Wilcoxon" name="Wilcoxon"/>
</dictionary>
ā€œMann-Whitneyā€ link to Wikipedia entry and Wikidata (Q1424533) entry
Annotation (entity in context)
prefix
surface
label
location
suffix
Lars Willighagen (NL) and Tom Arrow. visualisation of single facts and groups from
Corpus. https://tarrow.github.io/factvis/#cmid=CM.wikidatacountry136
Machine version
Wikidata demo
ā€¢ Find all architecturally significant buildings in
Cambridge UK
ā€¢ https://tools.wmflabs.org/wikishootme/#lat=52.204082366142&lng=0.11190176010131837&zoom=16&l
ayers=wikidata_image,wikidata_no_image&sparql_filter=%3Fq%20wdt%3AP1435%20wd%3AQ15700834
credit: Magnus Manske https://en.wikipedia.org/wiki/Magnus_Manske
Story: Magnus used FOI to get metadata for tens of thousands of ā€œlisted
buildingsā€ [1] from English Heritage and put all data into Wikidata
[1] https://www.wikidata.org/wiki/Q570600
Is chemistry in Wikidata?
ā€¢ https://pubchem.ncbi.nlm.nih.gov/
PubChem (P662) is a Wikidata ā€œPropertyā€
143347 PubChem items
Wikidata knows about PubChem
PubChem Item (Q27140241)
label O-acetylcarnitine
Wikidata
Identifiers
https://chemapps.stolaf.edu/jmol/jmol.php?&model=InChI=
1S/C9H13NO3/c1-10-5-9(13)6-2-3-7(11)8(12)4-6/h2-4,9-
13H,5H2,1H3/t9-/m0/s1
Search for ā€œZikaā€ in EuropePMC and
Wikidata
ā€¢ https://github.com/ContentMine/amidemos/blob/master/WIKIDATA.md#content
mine-demos (list of demos)
ā€¢ https://rawgit.com/ContentMine/amidemos/master/zika/full.dataTables.html
ā€¢ (datatables extracted - disease, gene, species, etc.)
ā€¢ Lars Willighagen (NL) and Tom Arrow. visualisation of single facts and groups from
Corpus. https://tarrow.github.io/factvis/#cmid=CM.wikidatacountry136
ā€¢ https://contentmine-demo.herokuapp.com/cooccurrences Coocurrence of
diseases - suggest select 25 and disease.
https://rawgit.com/ContentMine.amidemos/master/zika/full.dataTables.html
Search on publicly accessible papers on ā€œZikaā€
<dictionary title="tropicalVirus">
<entry term="ZIKV" name="Zika virus"/>
<entry term="Zika" name="Zika virus"/>
<entry term="DENV" name="Dengue virus"/>
<entry term="Dengue" name="Dengue virus"/>
<entry term="CHIKV" name="Chikungunya virus"/>
<entry term="Chikungunya" name="Chikungunya virus"/>
<entry term="WNV" name="West Nile virus"/>
<entry term="West Nile" name="West Nile virus"/>
<entry term="YFV" name="Yellow fever virus"/>
<entry term="Yellow fever" name="Yellow fever virus"/>
<entry term="HPV" name="Human papilloma virus"/>
<entry term="Human papilloma virus"
name="Human papilloma virus"/>
</dictionary>
Terms co-ocurring with ā€œZikaā€
Diagram mining
ā€¢ TL; DR We can get high-precision scientific
data out of diagrams
PMR is collaborating with the European Bioinformatics
Institute to liberate metabolic information from journals
Chemical Computer Vision
Raw Mobile photo; problems:
Shadows, contrast, noise, skew, clipping
Binarization (pixels = 0,1)
Irregular edges
Ln Bacterial load per fly
11.5
11.0
10.5
10.0
9.5
9.0
6.5
6.0
Days postā€”infection
0 1 2 3 4 5
Bitmap Image and Tesseract OCR
http://www.slideshare.net/rossmounce/the-pluto-project-ievobio-2014
Ross Mounce (Bath), Panton Fellow
ā€¢ Sharing research data:
http://www.slideshare.net/rossmounce
ā€¢ How-to figures from PLOS/One [link]:
Ross shows how to bring figures to life:
ā€¢ PLOSOne at http://bit.ly/PLOStrees
ā€¢ PLOS at http://bit.ly/phylofigs (demo)
4300 images
Note Jaggy and
broken pixels
NEW Bacteria must have a phylogenetic tree
Length
_________Weight
Binomial Name Culture/Strain GENBANK ID
Evolution
Rate
OCR (Tesseract)
Norma (imageanalysis)
(((((Pyramidobacter_piscolens:195,Jonquetella_anthropi:135):86,Synergistes_jonesii:301):131,Thermotoga
_maritime:357):12,(Mycobacterium_tuberculosis:223,Bifidobacterium_longum:333):158):10,((Optiutus_te
rrae:441,(((Borrelia_burgdorferi:ā€¦202):91):22):32,(Proprinogenum_modestus:124,Fusobacterium_nucleat
um:167):217):11):9);
Semantic re-usable/computable output (ca 4 secs/image)
Bacillus subtilis [131238]*
Bacteroides fragilis [221817]
Brevibacillus brevis
Cyclobacterium marinum
Escherichia coli [25419]
Filobacillus milosensis
Flectobacillus major [15809775]
Flexibacter flexilis [15809789]
Formosa algae
Gelidibacter algens [16982233]
Halobacillus halophilus
Lentibacillus salicampi [18345921]
Octadecabacter arcticus
Psychroflexus torquis [16988834]
Pseudomonas aeruginosa [31856]
Sagittula stellata [16992371]
Salegentibacter salegens
Sphingobacterium spiritivorum
Terrabacter tumescens
ā€¢ [Identifier in Wikidata]
ā€¢ Missing = not found with Wikidata API
20 commonest organisms (in > 30 papers) in trees from IJSEM*
Half do not appear to be in Wikidata
Can the Wikipedia Scientists comment?
*Int. J. Syst. Evol. Microbiol.
Supertree for 924 species
Tree
Supertree created from 4300 papers
But we can now
turn PDFs into
Science
We canā€™t turn a hamburger into a cow
Pixel => Path => Shape => Char => Word => Para => Document => SCIENCE
UNITS
TICKS
QUANTITY
SCALE
TITLES
DATA!!
2000+ points
Dumb PDF
CSV
Semantic
Spectrum
2nd Derivative
Smoothing
Gaussian Filter
Automatic
extraction
C) Whatā€™s the problem with this spectrum?
Org. Lett., 2011, 13 (15), pp 4084ā€“4087
Original thanks to ChemBark
After AMI2 processingā€¦..
ā€¦ AMI2 has detected a square
http://www.lisboncouncil.net/publication/publication/134-text-and-data-mining-for-research-and-innovation-.html
Asian and U.S. scholars continue to show a huge interest in text and data mining
as measured by academic research on the topic. And Europeā€™s position is falling
relative to the rest of the world.
Legal clarity also matters. Some countries apply the ā€œfair-useā€ doctrine, which
allows ā€œexceptionsā€ to existing copyright law, including for text and data mining.
Israel, the Republic of Korea, Singapore, Taiwan and the U.S. are in this group.
Others have created a new copyright ā€œexceptionā€ for text and data mining ā€“ Japan,
for instance, which adopted a blanket text-and-data-mining exception in 2009, and
more recently the United Kingdom, where text and data mining was declared fully
legal for non-commercial research purposes in 2014. Some researchers worry that
the UK exception does not go far enough; others report that British researchers are
now at an advantage over their continental counterparts.
the Middle East is now the worldā€™s fourth largest region for research on text and
data mining, led by Iran and Turkey.
@Senficon (Julia Reda) :Text & Data mining in times of
#copyright maximalism:
"Elsevier stopped me doing my research"
http://onsnetwork.org/chartgerink/2015/11/16/elsevi
er-stopped-me-doing-my-research/ ā€¦ #opencon #TDM
Elsevier stopped me doing my research
Chris Hartgerink
I am a statistician interested in detecting potentially problematic research such as data fabrication,
which results in unreliable findings and can harm policy-making, confound funding decisions, and
hampers research progress.
To this end, I am content mining results reported in the psychology literature. Content mining the
literature is a valuable avenue of investigating research questions with innovative methods. For
example, our research group has written an automated program to mine research papers for errors in
the reported results and found that 1/8 papers (of 30,000) contains at least one result that could
directly influence the substantive conclusion [1].
In new research, I am trying to extract test results, figures, tables, and other information reported in
papers throughout the majority of the psychology literature. As such, I need the research papers
published in psychology that I can mine for these data. To this end, I started ā€˜bulkā€™ downloading research
papers from, for instance, Sciencedirect. I was doing this for scholarly purposes and took into account
potential server load by limiting the amount of papers I downloaded per minute to 9. I had no intention
to redistribute the downloaded materials, had legal access to them because my university pays a
subscription, and I only wanted to extract facts from these papers.
Full disclosure, I downloaded approximately 30GB of data from Sciencedirect in approximately 10 days.
This boils down to a server load of 0.0021GB/[min], 0.125GB/h, 3GB/day.
Approximately two weeks after I started downloading psychology research papers, Elsevier notified my
university that this was a violation of the access contract, that this could be considered stealing of
content, and that they wanted it to stop. My librarian explicitly instructed me to stop downloading
(which I did immediately), otherwise Elsevier would cut all access to Sciencedirect for my university.
I am now not able to mine a substantial part of the literature, and because of this Elsevier is directly
hampering me in my research.
[1] Nuijten, M. B., Hartgerink, C. H. J., van Assen, M. A. L. M., Epskamp, S., & Wicherts, J. M. (2015). The
prevalence of statistical reporting errors in psychology (1985ā€“2013). Behavior Research Methods, 1ā€“22.
doi: 10.3758/s13428-015-0664-2
Chris Hartgerinkā€™s blog post
WILEY ā€¦ ā€œnew security featureā€¦ to prevent systematic download of content
ā€œ[limit of] 100 papers per dayā€
ā€œessential security feature ā€¦ to protect both parties (sic)ā€
CAPTCHA
User has to type words
http://onsnetwork.org/chartgerink/2016/02/23/wiley-also-stopped-my-doing-my-research/
Wiley also stopped me (Chris Hartgerink) doing my research
In November, I wrote about how Elsevier wanted me to stop downloading scientific articles for my research. Today, Wiley
also ordered me to stop downloading.
As a quick recapitulation: I am a statistician doing research into detecting
potentially problematic research such as data fabrication and
estimating how often it occurs. For this, I need to download many scientific articles, because my research
applies content mining methods that extract facts from them (e.g., test statistics). These facts serve as my data to answer my research
questions. If I cannot download these research articles, I cannot collect the data I need to do my research.
I was downloading psychology research articles from the Wiley library, with a maximum of 5 per minute. I did this using the tool quickscrape,
developed by the ContentMine organization. With this, I have downloaded approximately 18,680 research articles from the Wiley library,
which I was downloading solely for research purposes.
Wiley noticed my downloading and notified my university library that they detected a compromised proxy, which they
had immediately restricted. They called it ā€œillegally downloading copyrighted content
licensed by your institutionā€. However, at no point was there any investigation into whether my user credentials were
actually compromised (they were not). Whether I had legitimate reasons to download these articles was never discussed.
The original email from Wiley is available here.
As a result of Wiley denying me to download these research articles, I cannot collect data from
another one of the big publishers, alongside Elsevier. Wiley is more strict than Elsevier by immediately condemning the
downloading as illegal, whereas Elsevier offers an (inadequate) API with additional terms of use (while legitimate access
has already been obtained). I am really confused about what the publisherā€™s stance on content mining is, because Sage
and Springer seemingly allow it; I have downloaded 150,210 research articles from Springer
and 12,971 from Sage and they never complained about it.
Julia Reda, Pirate MEP, running ContentMine
software to liberate science 2016-04-16
WikiFactMine
ā€¢ https://meta.wikimedia.org/wiki/Grants:Project/ContentMine/WikiFactMine
anyone can review the grant
comments help to refine proposal
(2x digital music industry!)
Themes
ā€¢ 500 Billion$ of funded STM research/year
ā€¢ 85% of medical research is wasted (Lancet 2011)
ā€¢ An Open mining toolset
ā€¢ Wikidata as the semantic backbone
ā€¢ Community involvement
ā€¢ Sociopolitical issues
ā€¢ My gratitude to NIH
ā€¢ Offers of collaboration; data ingestion? Software?
Sources?
Additional material
Typical medical paper
From http://journals.plos.org/plosmedicine/article/authors?id=10.1371/journal.pmed.1002150
(licence CC-BY)
Typical scholarly text
http://journals.plos.org/plosmedicine/article/authors?id=10.1371/journal.
pmed.1002150 (licence CC-BY)
Table in a scientific paper
http://dx.doi.org/10.1371/journal.pmed.1002150.t001
Typical scientific diagram
(bitmap, so not machine-understandable)

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High throughput mining of the scholarly literature; talk at NIH

  • 1. NIH, Bethesda, US, 2016-11-15 High throughput mining of the scholarly literature Peter Murray-Rust1,2 [1]University of Cambridge [2]TheContentMine pm286 AT cam DOT ac DOT uk Scientific knowledge is for everyone
  • 2. Themes ā€¢ 500 Billion$ of funded STM research/year ā€¢ 85% of medical research is wasted (Lancet 2011) ā€¢ An Open mining toolset ā€¢ Wikidata as the semantic backbone ā€¢ Community involvement ā€¢ Sociopolitical issues ā€¢ My gratitude to NIH ā€¢ Offers of collaboration; data ingestion? Software? Sources?
  • 3.
  • 4. http://www.nytimes.com/2015/04/08/opinion/yes-we-were-warned-about- ebola.html We were stunned recently when we stumbled across an article by European researchers in Annals of Virology [1982]: ā€œThe results seem to indicate that Liberia has to be included in the Ebola virus endemic zone.ā€ In the future, the authors asserted, ā€œmedical personnel in Liberian health centers should be aware of the possibility that they may come across active cases and thus be prepared to avoid nosocomial epidemics,ā€ referring to hospital-acquired infection. Adage in public health: ā€œThe road to inaction is paved with research papers.ā€ Bernice Dahn (chief medical officer of Liberiaā€™s Ministry of Health) Vera Mussah (director of county health services) Cameron Nutt (Ebola response adviser to Partners in Health) A System Failure of Scholarly Publishing
  • 6. The Right to Read is the Right to Mine**PeterMurray-Rust, 2011 http://contentmine.org
  • 7. (2x digital music industry!)
  • 8. Scholarly publishing is ā€œBig Dataā€ [2] https://en.wikipedia.org/wiki/Mont_Blanc#/media/File:Mont_Blanc_depuis_Valmorel.jpg 586,364 Crossref DOIs 201507 [1] per month 2.5 million (papers + supplemental data) /year [citation needed]* each 3 mm thick ļƒž 4500 m high per year [2] * Most is not Publicly readable [1] http://www.crossref.org/01company/crossref_indicators.html 1 yearā€™s scholarly output!
  • 12. Automatic semantic markup of chemistry Could be used for analytical, crystallization, etc.
  • 13. AMI https://bitbucket.org/petermr/xhtml2stm/wiki/Home Example reaction scheme, taken from MDPI Metabolites 2012, 2, 100-133; page 8, CC-BY: AMI reads the complete diagram, recognizes the paths and generates the molecules. Then she creates a stop-fram animation showing how the 12 reactions lead into each other CLICK HERE FOR ANIMATION https://bytebucket.org/petermr/xhtml2stm/wiki/animation.s vg?rev=793a4d9ffa0616a84ff4aeabf80e657b5142ed33 (may be browser dependent) Andy Howlett, Cambridge
  • 14. ChemDataExtractor ā€¢ http://chemdataextractor.org/docs/intro ā€¢ http://chemdataextractor.org/demo Swain, M. C., & Cole, J. M. "ChemDataExtractor: A Toolkit for Automated Extraction of Chemical Information from the Scientific Literature", J. Chem. Inf. Model. 2016, 56 (10), pp 1894ā€“1904 http://pubs.acs.org/doi/abs/10.1021/acs.jcim.6b00207
  • 18. catalogue getpapers query Daily Crawl EuPMC, arXiv CORE , HAL, (UNIV repos) Crossref PDF HTML DOC ePUB TeX XML PNG EPS CSV XLSURLs DOIs crawl quickscrape norma Normalizer Structurer Semantic Tagger Text Data Figures ami UNIV Repos search Lookup CONTENT MINING Chem Phylo Trials Crystal Plants COMMUNITY plugins Visualization and Analysis PloSONE, BMC, peerJā€¦ Nature, IEEE, Elsevierā€¦ Publisher Sites scrapers queries taggers abstract methods references Captioned Figures Fig. 1 HTML tables 100, 000 pages/day Semantic ScholarlyHTML (W3C community group) Facts Latest 20150908
  • 19. abstract methods references Captioned Figures Fig. 1 HTML tables abstract methods references Captioned Figures Fig. 1 HTML tables Dict A Dict B Image Caption Table Caption MINING with sections and dictionaries [W3C Annotation / https://hypothes.is/ ]
  • 20. Disease Dictionary (ICD-10) <dictionary title="disease"> <entry term="1p36 deletion syndrome"/> <entry term="1q21.1 deletion syndrome"/> <entry term="1q21.1 duplication syndrome"/> <entry term="3-methylglutaconic aciduria"/> <entry term="3mc syndromeā€ <entry term="corpus luteum cystā€/> <entry term="cortical blindness" /> SELECT DISTINCT ?thingLabel WHERE { ?thing wdt:P494 ?wd . ?thing wdt:P279 wd:Q12136 . SERVICE wikibase:label { bd:serviceParam wikibase:language "en" } } wdt:P494 = ICD-10 (P494) identifier wd:Q12136 = disease (Q12136) abnormal condition that affects the body of an organism Wikidata ontology for disease
  • 21. Example statistics dictionary <dictionary title="statistics2"> <entry term="ANCOVA" name="ANCOVA"/> <entry term="ANOVA" name="ANOVA"/> <entry term="CFA" name="CFA"/> <entry term="EFA" name="EFA"/> <entry term="Likert" name="Likert"/> <entry term="Mann-Whitney" name="Mann-Whitney"/> <entry term="MANOVA" name="MANOVA"/> <entry term="McNemar" name="McNemar"/> <entry term="PCA" name="PCA"/> <entry term="Pearson" name="Pearson"/> <entry term="Spearman" name="Spearman"/> <entry term="t-test" name="t-test"/> <entry term="Wilcoxon" name="Wilcoxon"/> </dictionary> ā€œMann-Whitneyā€ link to Wikipedia entry and Wikidata (Q1424533) entry
  • 22. Annotation (entity in context) prefix surface label location suffix Lars Willighagen (NL) and Tom Arrow. visualisation of single facts and groups from Corpus. https://tarrow.github.io/factvis/#cmid=CM.wikidatacountry136 Machine version
  • 23. Wikidata demo ā€¢ Find all architecturally significant buildings in Cambridge UK ā€¢ https://tools.wmflabs.org/wikishootme/#lat=52.204082366142&lng=0.11190176010131837&zoom=16&l ayers=wikidata_image,wikidata_no_image&sparql_filter=%3Fq%20wdt%3AP1435%20wd%3AQ15700834 credit: Magnus Manske https://en.wikipedia.org/wiki/Magnus_Manske Story: Magnus used FOI to get metadata for tens of thousands of ā€œlisted buildingsā€ [1] from English Heritage and put all data into Wikidata [1] https://www.wikidata.org/wiki/Q570600
  • 24.
  • 25.
  • 26.
  • 27. Is chemistry in Wikidata?
  • 29. PubChem (P662) is a Wikidata ā€œPropertyā€ 143347 PubChem items Wikidata knows about PubChem PubChem Item (Q27140241) label O-acetylcarnitine
  • 32. Search for ā€œZikaā€ in EuropePMC and Wikidata ā€¢ https://github.com/ContentMine/amidemos/blob/master/WIKIDATA.md#content mine-demos (list of demos) ā€¢ https://rawgit.com/ContentMine/amidemos/master/zika/full.dataTables.html ā€¢ (datatables extracted - disease, gene, species, etc.) ā€¢ Lars Willighagen (NL) and Tom Arrow. visualisation of single facts and groups from Corpus. https://tarrow.github.io/factvis/#cmid=CM.wikidatacountry136 ā€¢ https://contentmine-demo.herokuapp.com/cooccurrences Coocurrence of diseases - suggest select 25 and disease.
  • 34.
  • 35.
  • 36. <dictionary title="tropicalVirus"> <entry term="ZIKV" name="Zika virus"/> <entry term="Zika" name="Zika virus"/> <entry term="DENV" name="Dengue virus"/> <entry term="Dengue" name="Dengue virus"/> <entry term="CHIKV" name="Chikungunya virus"/> <entry term="Chikungunya" name="Chikungunya virus"/> <entry term="WNV" name="West Nile virus"/> <entry term="West Nile" name="West Nile virus"/> <entry term="YFV" name="Yellow fever virus"/> <entry term="Yellow fever" name="Yellow fever virus"/> <entry term="HPV" name="Human papilloma virus"/> <entry term="Human papilloma virus" name="Human papilloma virus"/> </dictionary> Terms co-ocurring with ā€œZikaā€
  • 37. Diagram mining ā€¢ TL; DR We can get high-precision scientific data out of diagrams
  • 38. PMR is collaborating with the European Bioinformatics Institute to liberate metabolic information from journals
  • 39.
  • 40.
  • 41. Chemical Computer Vision Raw Mobile photo; problems: Shadows, contrast, noise, skew, clipping
  • 42. Binarization (pixels = 0,1) Irregular edges
  • 43. Ln Bacterial load per fly 11.5 11.0 10.5 10.0 9.5 9.0 6.5 6.0 Days postā€”infection 0 1 2 3 4 5 Bitmap Image and Tesseract OCR
  • 45. Ross Mounce (Bath), Panton Fellow ā€¢ Sharing research data: http://www.slideshare.net/rossmounce ā€¢ How-to figures from PLOS/One [link]: Ross shows how to bring figures to life: ā€¢ PLOSOne at http://bit.ly/PLOStrees ā€¢ PLOS at http://bit.ly/phylofigs (demo)
  • 47. Note Jaggy and broken pixels NEW Bacteria must have a phylogenetic tree Length _________Weight Binomial Name Culture/Strain GENBANK ID Evolution Rate
  • 49.
  • 50. Bacillus subtilis [131238]* Bacteroides fragilis [221817] Brevibacillus brevis Cyclobacterium marinum Escherichia coli [25419] Filobacillus milosensis Flectobacillus major [15809775] Flexibacter flexilis [15809789] Formosa algae Gelidibacter algens [16982233] Halobacillus halophilus Lentibacillus salicampi [18345921] Octadecabacter arcticus Psychroflexus torquis [16988834] Pseudomonas aeruginosa [31856] Sagittula stellata [16992371] Salegentibacter salegens Sphingobacterium spiritivorum Terrabacter tumescens ā€¢ [Identifier in Wikidata] ā€¢ Missing = not found with Wikidata API 20 commonest organisms (in > 30 papers) in trees from IJSEM* Half do not appear to be in Wikidata Can the Wikipedia Scientists comment? *Int. J. Syst. Evol. Microbiol.
  • 51. Supertree for 924 species Tree
  • 52. Supertree created from 4300 papers
  • 53. But we can now turn PDFs into Science We canā€™t turn a hamburger into a cow Pixel => Path => Shape => Char => Word => Para => Document => SCIENCE
  • 56.
  • 57.
  • 58. C) Whatā€™s the problem with this spectrum? Org. Lett., 2011, 13 (15), pp 4084ā€“4087 Original thanks to ChemBark
  • 59. After AMI2 processingā€¦.. ā€¦ AMI2 has detected a square
  • 60.
  • 61.
  • 62. http://www.lisboncouncil.net/publication/publication/134-text-and-data-mining-for-research-and-innovation-.html Asian and U.S. scholars continue to show a huge interest in text and data mining as measured by academic research on the topic. And Europeā€™s position is falling relative to the rest of the world. Legal clarity also matters. Some countries apply the ā€œfair-useā€ doctrine, which allows ā€œexceptionsā€ to existing copyright law, including for text and data mining. Israel, the Republic of Korea, Singapore, Taiwan and the U.S. are in this group. Others have created a new copyright ā€œexceptionā€ for text and data mining ā€“ Japan, for instance, which adopted a blanket text-and-data-mining exception in 2009, and more recently the United Kingdom, where text and data mining was declared fully legal for non-commercial research purposes in 2014. Some researchers worry that the UK exception does not go far enough; others report that British researchers are now at an advantage over their continental counterparts. the Middle East is now the worldā€™s fourth largest region for research on text and data mining, led by Iran and Turkey.
  • 63. @Senficon (Julia Reda) :Text & Data mining in times of #copyright maximalism: "Elsevier stopped me doing my research" http://onsnetwork.org/chartgerink/2015/11/16/elsevi er-stopped-me-doing-my-research/ ā€¦ #opencon #TDM Elsevier stopped me doing my research Chris Hartgerink
  • 64. I am a statistician interested in detecting potentially problematic research such as data fabrication, which results in unreliable findings and can harm policy-making, confound funding decisions, and hampers research progress. To this end, I am content mining results reported in the psychology literature. Content mining the literature is a valuable avenue of investigating research questions with innovative methods. For example, our research group has written an automated program to mine research papers for errors in the reported results and found that 1/8 papers (of 30,000) contains at least one result that could directly influence the substantive conclusion [1]. In new research, I am trying to extract test results, figures, tables, and other information reported in papers throughout the majority of the psychology literature. As such, I need the research papers published in psychology that I can mine for these data. To this end, I started ā€˜bulkā€™ downloading research papers from, for instance, Sciencedirect. I was doing this for scholarly purposes and took into account potential server load by limiting the amount of papers I downloaded per minute to 9. I had no intention to redistribute the downloaded materials, had legal access to them because my university pays a subscription, and I only wanted to extract facts from these papers. Full disclosure, I downloaded approximately 30GB of data from Sciencedirect in approximately 10 days. This boils down to a server load of 0.0021GB/[min], 0.125GB/h, 3GB/day. Approximately two weeks after I started downloading psychology research papers, Elsevier notified my university that this was a violation of the access contract, that this could be considered stealing of content, and that they wanted it to stop. My librarian explicitly instructed me to stop downloading (which I did immediately), otherwise Elsevier would cut all access to Sciencedirect for my university. I am now not able to mine a substantial part of the literature, and because of this Elsevier is directly hampering me in my research. [1] Nuijten, M. B., Hartgerink, C. H. J., van Assen, M. A. L. M., Epskamp, S., & Wicherts, J. M. (2015). The prevalence of statistical reporting errors in psychology (1985ā€“2013). Behavior Research Methods, 1ā€“22. doi: 10.3758/s13428-015-0664-2 Chris Hartgerinkā€™s blog post
  • 65. WILEY ā€¦ ā€œnew security featureā€¦ to prevent systematic download of content ā€œ[limit of] 100 papers per dayā€ ā€œessential security feature ā€¦ to protect both parties (sic)ā€ CAPTCHA User has to type words
  • 66. http://onsnetwork.org/chartgerink/2016/02/23/wiley-also-stopped-my-doing-my-research/ Wiley also stopped me (Chris Hartgerink) doing my research In November, I wrote about how Elsevier wanted me to stop downloading scientific articles for my research. Today, Wiley also ordered me to stop downloading. As a quick recapitulation: I am a statistician doing research into detecting potentially problematic research such as data fabrication and estimating how often it occurs. For this, I need to download many scientific articles, because my research applies content mining methods that extract facts from them (e.g., test statistics). These facts serve as my data to answer my research questions. If I cannot download these research articles, I cannot collect the data I need to do my research. I was downloading psychology research articles from the Wiley library, with a maximum of 5 per minute. I did this using the tool quickscrape, developed by the ContentMine organization. With this, I have downloaded approximately 18,680 research articles from the Wiley library, which I was downloading solely for research purposes. Wiley noticed my downloading and notified my university library that they detected a compromised proxy, which they had immediately restricted. They called it ā€œillegally downloading copyrighted content licensed by your institutionā€. However, at no point was there any investigation into whether my user credentials were actually compromised (they were not). Whether I had legitimate reasons to download these articles was never discussed. The original email from Wiley is available here. As a result of Wiley denying me to download these research articles, I cannot collect data from another one of the big publishers, alongside Elsevier. Wiley is more strict than Elsevier by immediately condemning the downloading as illegal, whereas Elsevier offers an (inadequate) API with additional terms of use (while legitimate access has already been obtained). I am really confused about what the publisherā€™s stance on content mining is, because Sage and Springer seemingly allow it; I have downloaded 150,210 research articles from Springer and 12,971 from Sage and they never complained about it.
  • 67. Julia Reda, Pirate MEP, running ContentMine software to liberate science 2016-04-16
  • 69. anyone can review the grant
  • 70. comments help to refine proposal
  • 71. (2x digital music industry!)
  • 72. Themes ā€¢ 500 Billion$ of funded STM research/year ā€¢ 85% of medical research is wasted (Lancet 2011) ā€¢ An Open mining toolset ā€¢ Wikidata as the semantic backbone ā€¢ Community involvement ā€¢ Sociopolitical issues ā€¢ My gratitude to NIH ā€¢ Offers of collaboration; data ingestion? Software? Sources?
  • 74. Typical medical paper From http://journals.plos.org/plosmedicine/article/authors?id=10.1371/journal.pmed.1002150 (licence CC-BY)
  • 76. Table in a scientific paper http://dx.doi.org/10.1371/journal.pmed.1002150.t001
  • 77. Typical scientific diagram (bitmap, so not machine-understandable)

Editor's Notes

  1. ChemBark