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‘Seed + expand’: a general methodology for detecting publication oeuvres of individual researchers

Identifieur interne : 000147 ( Pmc/Checkpoint ); précédent : 000146; suivant : 000148

‘Seed + expand’: a general methodology for detecting publication oeuvres of individual researchers

Auteurs : Linda Reijnhoudt [Pays-Bas] ; Rodrigo Costas [Pays-Bas] ; Ed Noyons [Pays-Bas] ; Katy Börner [Pays-Bas, États-Unis] ; Andrea Scharnhorst [Pays-Bas]

Source :

RBID : PMC:4190454

Abstract

The study of science at the individual scholar level requires the disambiguation of author names. The creation of author’s publication oeuvres involves matching the list of unique author names to names used in publication databases. Despite recent progress in the development of unique author identifiers, e.g., ORCID, VIVO, or DAI, author disambiguation remains a key problem when it comes to large-scale bibliometric analysis using data from multiple databases. This study introduces and tests a new methodology called seed + expand for semi-automatic bibliographic data collection for a given set of individual authors. Specifically, we identify the oeuvre of a set of Dutch full professors during the period 1980–2011. In particular, we combine author records from a Dutch National Research Information System (NARCIS) with publication records from the Web of Science. Starting with an initial list of 8,378 names, we identify ‘seed publications’ for each author using five different approaches. Subsequently, we ‘expand’ the set of publications in three different approaches. The different approaches are compared and resulting oeuvres are evaluated on precision and recall using a ‘gold standard’ dataset of authors for which verified publications in the period 2001–2010 are available.


Url:
DOI: 10.1007/s11192-014-1256-0
PubMed: 25328257
PubMed Central: 4190454


Affiliations:


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PMC:4190454

Le document en format XML

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<label></label>
DANS, Royal Netherlands Academy of Arts and Sciences (KNAW), The Hague, The Netherlands</aff>
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Center for Science and Technology Studies (CWTS)-Leiden University, Leiden, The Netherlands</aff>
<aff id="Aff3">
<label></label>
Cyberinfrastructure for Network Science Center, School of Informatics and Computing, Indiana University, Bloomington, IN USA</aff>
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<month>3</month>
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<year>2014</year>
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<lpage>1417</lpage>
<history>
<date date-type="received">
<day>18</day>
<month>11</month>
<year>2013</year>
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<copyright-statement>© The Author(s) 2014</copyright-statement>
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<bold>Open Access</bold>
This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.</license-p>
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<abstract id="Abs1">
<p>The study of science at the individual scholar level requires the disambiguation of author names. The creation of author’s publication oeuvres involves matching the list of unique author names to names used in publication databases. Despite recent progress in the development of unique author identifiers, e.g., ORCID, VIVO, or DAI, author disambiguation remains a key problem when it comes to large-scale bibliometric analysis using data from multiple databases. This study introduces and tests a new methodology called seed + expand for semi-automatic bibliographic data collection for a given set of individual authors. Specifically, we identify the oeuvre of a set of Dutch full professors during the period 1980–2011. In particular, we combine author records from a Dutch National Research Information System (NARCIS) with publication records from the Web of Science. Starting with an initial list of 8,378 names, we identify ‘seed publications’ for each author using five different approaches. Subsequently, we ‘expand’ the set of publications in three different approaches. The different approaches are compared and resulting oeuvres are evaluated on precision and recall using a ‘gold standard’ dataset of authors for which verified publications in the period 2001–2010 are available.</p>
</abstract>
<kwd-group xml:lang="en">
<title>Keywords</title>
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<kwd>Scalable methods</kwd>
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}}

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HfdIndexSelect -h $EXPLOR_AREA/Data/Pmc/Checkpoint/RBID.i   -Sk "pubmed:25328257" \
       | HfdSelect -Kh $EXPLOR_AREA/Data/Pmc/Checkpoint/biblio.hfd   \
       | NlmPubMed2Wicri -a CyberinfraV1 

Wicri

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