PLOS Visualization Project

Physics Chemistry Engineering Biology Disease Medicine Brain Health Social Computer Patents

Visualizing PLoS Data

DHUG 2014February 11, 2014

Kevin Boyack, Bob Kasenchak, Margie Hlava


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AGENDABackgroundDataScience mappingMapping thesaurus directlyMapping thesaurus indirectly» SciTech S&T map» Thesaurus map

Overlays


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BACKGROUNDTo answer questions posed by PLoS using PLoS index (thesaurus) terms, a map of the thesaurus space is desirable» Where is the coverage thin, where is it dense?» What areas are core and which are emerging trends? Which fields are growing

quickly?» Which fields are interrelated?» Which fields have low activity but are related to very active fields?

Some questions require more than PLoS data» How does the coverage in PLoS journals relate to coverage in other databases?

A map of the thesaurus space can function as a template upon which various distributions can be overlaidSome questions are more amenable to tables than maps


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DATAThesaurus» 10,551 unique terms in 15,164 locations» 11 top level terms» 296 second level terms in 305 locations

PLoS article data parsed / indexed by Access Innovations» Article level data through mid-2013; 84,989 records» 72,796 records with index (thesaurus) terms; 171,181 terms

Scopus data» SciTech Strategies licenses use of Scopus data from Elsevier» 1996-2011; 25M records


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THESAURUS STRUCTUREBiology CS Earth Env Eng Medicine People Physical Methods SS


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SCIENCE MAPPINGA map is a visual representation of the relationships within a» Classification system (e.g., journal categories, taxonomy)» Document corpus

Science maps can/have been created using» Documents, Journals, Authors, Terms, Taxonomies

30-40 year tradition of science mapping» Well-established methodologies» Current computing power and data availability enable large scale mapping and

analysis

Maps used for communication, strategy, planning, evaluation …» Understanding of structure, relative location» Basis for metrics


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GENERAL PROCESS

Select data source and objects (e.g., docs) of interest Scopus / WoSPubMedPatentsYour own data

Calculate similarity between objects (doc-doc) Citations (links)Words (title/abstr)

Create a visual layout (map) of the objects / clusters Pajek / Gephi


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MAPPING PLOS TERMS DIRECTLYMapped second level terms» All terms rolled up to the second level term at the top of the branch

Cosine similarity between terms based on co-occurrence in articlesMap created using Fruchterman-Reingold mapping routine in Pajek» Based on only the top 3 links per term – strongest linkages

Each node (term) colored using top level terms» Biology and life sciences (light green)» Medicine and health sciences (salmon)» Physical sciences (purple)» Research and analysis methods (yellow)» Social sciences (light orange)» …


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MAPPING PLOS TERMS


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MAPPING PLOS TERMS DIRECTLYResulting map is difficult to use» Using second level terms leaves out needed detail» Term counts span several orders of magnitude – hard to map well» Terms within the same branch of the thesaurus don’t cluster well

Resulting map doesn’t account well for context (areas where PLoS has low coverage)Need a map that does a better job of providing context, and that better matches our current picture of scienceSo … we decided to index Scopus data using the PLoS rule-base and map based on that more inclusive context


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MAPPING PLOS TERMS INDIRECTLYUse existing map of all of scienceTriangulate term positions


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SCITECH S&T MAP20 million articles (1996-2011)3 million patents (1996-2011)

220,000 document clustersCluster contents using citationCluster positions using text

The visual is the final step(last 10%); the full process isneeded for robust analysis

Template on which other infocan be overlaid; documents (andrelated info) tied to map positions

We are the only ones in theworld who do contextual analysisat this scale


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TRIANGULATION

Use full S&T map as basis

Based on Scopus 2007-2011

Locate each thesaurus term as theaverage position of its documents

The resulting map contains 11,934terms; full coverage; interpretable

Terms with multiple colors appearmultiple times

The term map becomes the basemap


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THESAURUS BASEMAP

The term map becomes the basemap

Circle size - # documentsCircle color – top level term

Many small circles – detailed thesaurusand rule base that differentiates

Few large circles – broad terms andrule base that doesn’t differentiate

Location/size of terms facilitates questions- Is term well located in the thesaurus?- Is the rule base acting as desired?- Should term be broken up?


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NOT JUST PRETTY PICTURES

All visualizations are based on tabular dataPictures help form hypothesesDetailed analysis provides answers


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ANALYSES

Biology and life sciencesComputer and information sciencesEarth sciencesEcology and environmental sciencesEngineering and technologyMedical and health sciencesPhysical sciencesResearch and analysis methodsPeople and placesSocial sciencesScience policy

Circuit modelsChromatin immunoprecipitation

Evolutionary modelingElectron transport chain

IntelligenceLanguage

CognitionDecision making


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Biology and life sciencesComputer and information sciencesEarth sciencesEcology and environmental sciencesEngineering and technologyMedical and health sciencesPhysical sciences

People and placesSocial sciencesScience policy


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ANALYSES

Biology and life sciencesComputer and information sciencesEarth sciencesEcology and environmental sciencesEngineering and technologyMedical and health sciencesPhysical sciencesResearch and analysis methodsPeople and places


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ANALYSES

PLoS – All journals and yearsPLoS – All journals (2008)PLoS – All journals (2009)PLoS – All journals (2010)PLoS – All journals (2011)PLoS – All journals (2012)PLoS – All journals (2013)

PLoS BiologyPLoS Computational BiologyPLoS GeneticsPLoS MedicinePLoS NTDPLoS PathogensPLoS One


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ANALYSES

PLoS One – All yearsPLoS One (2008)PLoS One (2009)PLoS One (2010)PLoS One (2011)PLoS One (2012)PLoS One (2013)


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PLoS One (2007-2011)PLoS One (2008)PLoS One (2009)PLoS One (2010)PLoS One (2011)PLoS One (2012)PLoS One (2013)


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ANALYSES

2007-2011

PLoS OnePNASJACSJ Mat ChemPhys Rev LettJ Nanosci NanotechnLNCS


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2007-2011



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2007-2011



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2007-2011



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2007-2011



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2007-2011



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SUMMARYMapping the PLoS thesaurus directly (using co-occurrence) gave maps that were only partially useful.Indirect mapping of the PLoS thesaurus using a comprehensive map of the scientific literature (based on Scopus data) was very successful. The resulting visualization of the PLoS thesaurus became a stand-alone basemap, a template that can be used to:» Examine the thesaurus structure, content, and level of detail.» Show coverage and trends for various entities such as journals, institutions, authors,

etc.

This thesaurus mapping effort helped visualize which areas of the PLOS thesaurus were covered well, or not well enough, as well as which fields were emerging or well-established.All overlays based on tabular data, so detailed analysis is possible.


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QUESTIONS

Thank-you for your attention !