high throughput mining of the scholarly literature; talk at nih
TRANSCRIPT
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
• 500 Billion$ of funded STM research/year• 85% of medical research is wasted (Lancet 2011)• An Open mining toolset• Wikidata as the semantic backbone• Community involvement• Sociopolitical issues• My gratitude to NIH• 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]: “The results seem to indicate that Liberia has to be included in the Ebola virus endemic zone.” In the future, the authors asserted, “medical 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,” referring to hospital-acquired infection.
Adage in public health: “The road to inaction is paved with research papers.”
Bernice Dahn (chief medical officer of Liberia’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 “Big Data”
[2] https://en.wikipedia.org/wiki/Mont_Blanc#/media/File:Mont_Blanc_depuis_Valmorel.jpg
586,364 Crossref DOIs 201507 [1] per month2.5 million (papers + supplemental data) /year [citation needed]*
each 3 mm thick 4500 m high per year [2] * Most is not Publicly readable[1] http://www.crossref.org/01company/crossref_indicators.html
1 year’s scholarly output!
What is “Content”?
http://www.plosone.org/article/fetchObject.action?uri=info:doi/10.1371/journal.pone.0111303&representation=PDF CC-BY
SECTIONS
MAPS
TABLES
CHEMISTRYTEXT
MATH
contentmine.org tackles these
Demos of mining
http://chemicaltagger.ch.cam.ac.uk/
• 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 ANIMATIONhttps://bytebucket.org/petermr/xhtml2stm/wiki/animation.svg?rev=793a4d9ffa0616a84ff4aeabf80e657b5142ed33
(may be browser dependent)
Andy Howlett, Cambridge
ChemDataExtractor
• http://chemdataextractor.org/docs/intro • 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 1894–1904 http://pubs.acs.org/doi/abs/10.1021/acs.jcim.6b00207
Europe PubMedCentral
2015
2016
Dictionaries!
catalogue
getpapers
query
DailyCrawl
EuPMC, arXivCORE , HAL,(UNIV repos)
Crossref PDF HTMLDOC ePUB TeX XML
PNGEPS CSV
XLSURLsDOIs
crawl
quickscrape
normaNormalizerStructurerSemanticTagger
Text
DataFigures
ami
UNIVRepos
search
LookupCONTENTMINING
Chem
Phylo
Trials
CrystalPlants
COMMUNITY
plugins
Visualizationand Analysis
PloSONE, BMC, peerJ… Nature, IEEE, Elsevier…
Publisher Sites
scrapersqueries
taggers
abstract
methods
references
CaptionedFigures
Fig. 1
HTML tables
100, 000 pages/day Semantic ScholarlyHTML(W3C community group)
Facts
Latest 20150908
abstract
methods
references
CaptionedFigures
Fig. 1
HTML tables
abstract
methods
references
CaptionedFigures
Fig. 1
HTML tables
Dict A
Dict B
ImageCaption
TableCaption
MININGwith sectionsand 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 syndrome” <entry term="corpus luteum cyst”/> <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) identifierwd: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>
“Mann-Whitney” 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
• Find all architecturally significant buildings in Cambridge UK
• https://tools.wmflabs.org/wikishootme/#lat=52.204082366142&lng=0.11190176010131837&zoom=16&layers=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 “listed buildings” [1] from English Heritage and put all data into Wikidata
[1] https://www.wikidata.org/wiki/Q570600
Is chemistry in Wikidata?
PubChem (P662) is a Wikidata “Property”
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 “Zika” in EuropePMC and Wikidata
• https://github.com/ContentMine/amidemos/blob/master/WIKIDATA.md#contentmine-demos (list of demos)
• https://rawgit.com/ContentMine/amidemos/master/zika/full.dataTables.html • (datatables extracted - disease, gene, species, etc.)• Lars Willighagen (NL) and Tom Arrow. visualisation of single facts and groups from
Corpus. https://tarrow.github.io/factvis/#cmid=CM.wikidatacountry136
• 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 “Zika”
<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 “Zika”
Diagram mining
• 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 post—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
• Sharing research data: http://www.slideshare.net/rossmounce • How-to figures from PLOS/One [link]:
Ross shows how to bring figures to life: • PLOSOne at http://bit.ly/PLOStrees • 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
EvolutionRate
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_terrae:441,(((Borrelia_burgdorferi:…202):91):22):32,(Proprinogenum_modestus:124,Fusobacterium_nucleatum:167):217):11):9);
Semantic re-usable/computable output (ca 4 secs/image)
Bacillus subtilis [131238]*Bacteroides fragilis [221817]Brevibacillus brevisCyclobacterium marinumEscherichia coli [25419]Filobacillus milosensisFlectobacillus major [15809775]Flexibacter flexilis [15809789]Formosa algaeGelidibacter algens [16982233]Halobacillus halophilusLentibacillus salicampi [18345921]Octadecabacter arcticusPsychroflexus torquis [16988834]Pseudomonas aeruginosa [31856]Sagittula stellata [16992371]Salegentibacter salegensSphingobacterium spiritivorumTerrabacter tumescens
• [Identifier in Wikidata] • 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 can’t turn a hamburger into a cow
Pixel => Path => Shape => Char => Word => Para => Document => SCIENCE
UNITS
TICKS
QUANTITYSCALE
TITLES
DATA!!2000+ points
VECTOR PDF
Dumb PDF
CSV
SemanticSpectrum
2nd Derivative
Smoothing Gaussian Filter
Automaticextraction
C) What’s the problem with this spectrum?
Org. Lett., 2011, 13 (15), pp 4084–4087
Original thanks to ChemBark
After AMI2 processing…..
… 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 Europe’s position is falling relative to the rest of the world.
Legal clarity also matters. Some countries apply the “fair-use” doctrine, whichallows “exceptions” 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 “exception” for text and data mining – Japan,for instance, which adopted a blanket text-and-data-mining exception in 2009, andmore recently the United Kingdom, where text and data mining was declared fullylegal for non-commercial research purposes in 2014. Some researchers worry thatthe UK exception does not go far enough; others report that British researchers arenow at an advantage over their continental counterparts.
the Middle East is now the world’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/elsevier-stopped-me-doing-my-research/ …
#opencon #TDM
Elsevier stopped me doing my researchChris 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 ‘bulk’ 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 (1985–2013). Behavior Research Methods, 1–22. doi: 10.3758/s13428-015-0664-2
Chris Hartgerink’s blog post
WILEY … “new security feature… to prevent systematic download of content
“[limit of] 100 papers per day”
“essential security feature … to protect both parties (sic)”
CAPTCHAUser 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 researchIn 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 “illegally downloading copyrighted content licensed by your institution”. 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 publisher’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• https://meta.wikimedia.org/wiki/Grants:Project/ContentMine/WikiFactMine
anyone can review the grant
comments help to refine proposal
(2x digital music industry!)
Themes
• 500 Billion$ of funded STM research/year• 85% of medical research is wasted (Lancet 2011)• An Open mining toolset• Wikidata as the semantic backbone• Community involvement• Sociopolitical issues• My gratitude to NIH• 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 paperhttp://dx.doi.org/10.1371/journal.pmed.1002150.t001
Typical scientific diagram(bitmap, so not machine-understandable)