Text and Data Mining explained at FTDM

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Content Mining of Science and Medicine Peter Murray-Rust, ContentMine.org and UniversityofCambridge FTDM Knowledge Cafe, Leiden, NL, 2016-02-29 F/OSS tools from contentmine.org Images from Wikimedia CC-BY-SA

Transcript of Text and Data Mining explained at FTDM

Page 1: Text and Data Mining explained at FTDM

Content Mining of Science and Medicine

Peter Murray-Rust, ContentMine.org and UniversityofCambridgeFTDM Knowledge Cafe, Leiden, NL, 2016-02-29

F/OSS tools from contentmine.org

Images from Wikimedia CC-BY-SA

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Disclaimer

The opinions, software and objects in this presentation are those of PMR+ContentMine (CM), in its non-FutureTDM role. No FTDM resources were used in creating slides, software, artefacts.

PMR has tried to give an objective listing of most of the main components of TDM, but has used CM technology to illustrate this.

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The Right to Read is the Right to Mine* *PeterMurray-Rust, 2011

http://contentmine.org

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Mining strategy• Discover. negotiate permissions . => bibliography• Crawl / Scrape (download), documents AND

supplemental • Normalize. PDF => XML• Index: facets => Facts and snippets (“entities”)• Interpret/analyze entities => relationships,

aggregations (“Transformative”) • Publish

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catalogue

getpapers

query

DailyCrawl

EPMC, arXivCORE , HAL,(UNIV repos)

ToCservices

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

30, 000 pages/day Semantic ScholarlyHTML

Facts

CONTENTMINE Complete OPEN Platform for Mining Scientific Literature

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Semantic Fulltext• EuropePMC coherent OpenAccess• getpapers: query , download (through API).• AMI filters, checks[1], transforms facts in papers.

• sequences, species, genera, genes, dictionaries

[0] All operations shown run in total of <3 minutes.[1] Dictionaries and lookup.[2] Usable from home by anyone

Zika endemic areasWikimedia CC-BY-SA

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Download all Open Access “Zika” from EuropePMC in 10 seconds (click below for movie)

Aedes aegypti, Wikimedia CC-BY-SA

Note: movies of this and other slides can be seen at https://vimeo.com/154705161

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Downloaded all Open Access “Zika” from EuropePMC in 10 seconds

Final download screen

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Eyeballing 20/120 Zika papers, click below for movie

Yellow Fever Virus Wikimedia CC-BY-SA

Note: movie of this and other slides can be seen at https://vimeo.com/154705161

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3011 virus 1939 Ae./Aedes 1212 dengue 901 mosquito/es 894 species 791 ZIKV 721 using 716 DENV 567 detection 513 aegypti 484 infection 442 RNA 428 protein 401 albopictus 360 viral

Commonest words in 120 Zika papers

Mosquito spp. Wikimedia CC-BY-SA

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Filtering local files for sequence and viruses

AMI (part of ContentMine software)

(click below for movie)Note: movies of this and other slides can be seen at https://vimeo.com/154705161

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DNA Primers in running text

…the sodium channel voltage dependent gene (Nav). Primers used to amplify this fragment were AaNaA 5’-ACAATGTGGATCGCTTCCC-3’ and AaNaB 5’-TGGACAAAAGCAAGGCTAAG-3’(8). The primers amplify a fragment of approximately 472…

Snippet (quotable under 2014 UK Statutory Instrument (“Hargreaves”):

~/PMC4654492/results/sequence/dnaprimer/results.xml”

W3C Annotation

[PREFIX] [MATCH] (link to target)[SUFFIX]

CMine structure

pluginoption

DNA double stranded fragment Wikimedia CC-BY-SA

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Commonest species in 120 Zika papers423 Ae./Aedes aegypti 333 Ae./Aedes albopictus 63 Ae. bromeliae 58 Ae. lilii 46 Ae. hensilli 42 Glossina pallidipes 40 Plasmodium vivax 35 Ae. luteocephalus 28 Ae. vittatus 25 Ae. furcifer 22 Plasmodium falciparum 21 Drosophila melanogaster

pre=“fever (DHF), are caused by the world's most prevalent mosquito-borne virus. 37 DENV is carried by " exact="Aedes aegypti” post=" mosquito, which is strongly affected by ecological and human drivers, but also influenced by clima" name="binomial"/>

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183 Wolbachia 70 Aedes 69 Flavivirus/Flaviviridae 30 Glossina 17 Culex

Commonest genera in Zika papers

pre=”…-negative endosymbiotic bacterium, is a promising tool against diseases transmitted by mosquitoes. " exact="Wolbachia” post=" can be found worldwide in numerous arthropod species. More than 65% of all insect species are natu…”

Wolbachia in insect cell Wikimedia CC-BY-SA

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38 ITS20 MHC2TA19 COI20 CYPJ9221 CYP6BB222 CYP9J283 MHC

Commonest genes in 120 Zika papers

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• microcephaly 400/2400 papers; 2 mins;

commonest genes:

203 MCPH1 86 MECP2 54 SOX2 49 E2F1 47 SNAP29 40 IKBKG 40 NDE1

N-terminal domain of microcephalin Wikimedia CC-BY-SA

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Systematic Reviews

Researchers and their machines need to “read” hundreds of papers a day or even more.

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Polly has 20 seconds to read this paper…

…and 10,000 more

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ContentMine software can do this in a few minutes

Polly: “there were 10,000 abstracts and due to time pressures, we split this between 6 researchers. It took about 2-3 days of work (working only on this) to get through ~1,600 papers each. So, at a minimum this equates to 12 days of full-time work (and would normally be done over several weeks under normal time pressures).”

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400,000 Clinical TrialsIn 10 government registries

Mapping trials => papers

http://www.trialsjournal.com/content/16/1/80

2009 => 2015. What’s happened in last 6 years??

Search the whole scientific literatureFor “2009-0100068-41”

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Extracting scientific information

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Mining strategy• Discover. negotiate permissions . => bibliography• Crawl / Scrape (download), documents AND

supplemental • Normalize. PDF => XML• Index: facets => Facts and snippets (“entities”)• Interpret/analyze entities => relationships,

aggregations (“Transformative”) • Publish

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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

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catalogue

getpapers

query

DailyCrawl

EuPMC, arXivCORE , HAL,(UNIV repos)

ToCservices

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

30, 000 pages/day Semantic ScholarlyHTML

Facts

CONTENTMINE Complete OPEN Platform for Mining Scientific Literature

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http://chemicaltagger.ch.cam.ac.uk/

• Typical

Typical chemical synthesis

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Open Content Mining of FACTs

Machines can interpret chemical reactions

We have done 500,000 patents. There are > 3,000,000 reactions/year. Added value > 1B Eur.

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Facts in contextdaily IUCN endangered species news

en.wikipedia.org CC By-SA

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ContentMine Fact of The Day

• Fact of the day• Endangered species in recent science• Facts• Bubbles

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https://en.wikipedia.org/wiki/Tree_of_life CC BY-SA

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“Root” 4500 papers each with 1 tree

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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)

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Supertree for 924 species

Tree

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Supertree created from 4300 papers

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ContentMine working with Libraries

• Cambridge: Library, Plant Sciences, Epidemiology, Chemistry

• Cochrane Collaboration on Systematic Reviews of Clinical Trials

• FutureTDM (H2020, LIBER)• Running workshops and training

• Offers services for information extraction and indexing for born-digital documents.

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CM Future

• Hypothes.is use ContentMine results for annotation• (with Cambridge Univ Library) extracting daily scientific

facts from open and closed literature.• with EBI, Cochrane Collaborations, JISC, OKF, LIBER,

TGAC/JohnInnes, DNADigest.• Running workshops, hackdays.• Planned outreach: MEPs, EC, Slashdot, Reddit,

Kickstarter, geekdom

• http://contentmine.org (OpenLock non-profit)

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The Right to Read is the Right to Mine* *PeterMurray-Rust, 2011

http://contentmine.org