SiSOB data extraction and codification: A tool to analyze scientific careers

•The paper describes the methodology and software tool used to build a database on the careers and productivity of academics.•The software provides data crawling and data mining techniques used to transform webpage-based information and CV information into a relational database.•The software develop...

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Vydáno v:	Research policy Ročník 44; číslo 9; s. 1645 - 1658
Hlavní autoři:	Geuna, Aldo, Kataishi, Rodrigo, Toselli, Manuel, Guzmán, Eduardo, Lawson, Cornelia, Fernandez-Zubieta, Ana, Barros, Beatriz
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Amsterdam Elsevier B.V 01.11.2015 Elsevier Sequoia S.A
Témata:	Academic careers Academic staff Biological research Biomedicine Biotechnology Careers Crawling Data analysis Data mining Economic research Extraction Extraction and data integration General public Information Information retrieval Internet Mobility of research scientists Occupations Policy analysis Productivity Public information Research methodology Research productivity Scientists Social sciences Social scientists Software Studies United Kingdom United States United Kingdom > UK United States > US C88 Information retrieval Extraction and data integration Research productivity I23 O31 C81 Mobility of research scientists Academic careers
ISSN:	0048-7333, 1873-7625
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Abstract	•The paper describes the methodology and software tool used to build a database on the careers and productivity of academics.•The software provides data crawling and data mining techniques used to transform webpage-based information and CV information into a relational database.•The software developed is released under free software GNU General Public License.•The methodology and software tool are validated for a sample of US and UK biomedical scientists.•We show that CVs are a valuable source of data to identify the exact point and type of academic mobility.•It is important to differentiate between voluntary and forced mobility, as only the former is associated with higher research performance. This paper describes the methodology and software tool used to build a database on the careers and productivity of academics, using public information available on the Internet, and provides a first analysis of the data collected for a sample of 360 US scientists funded by the National Institute of Health (NIH) and 291 UK scientists funded by the Biotechnology and Biological Sciences Research Council (BBSRC). The tool’s structured outputs can be used for either econometric research or data representation for policy analysis. The methodology and software tool is validated for a sample of US and UK biomedical scientists, but can be applied to any countries where scientists’ CVs are available in English. We provide an overview of the motivations for constructing the database, and the data crawling and data mining techniques used to transform webpage-based information and CV information into a relational database. We describe the database and the effectiveness of our algorithms and provide suggestions for further improvements. The software developed is released under free software GNU General Public License; the aim is for it to be available to the community of social scientists and economists interested in analyzing scientific production and scientific careers, who it is hoped will develop this tool further.
AbstractList	This paper describes the methodology and software tool used to build a database on the careers and productivity of academics, using public information available on the Internet, and provides a first analysis of the data collected for a sample of 360 US scientists funded by the National Institute of Health (NIH) and 291 UK scientists funded by the Biotechnology and Biological Sciences Research Council (BBSRC). The tool's structured outputs can be used for either econometric research or data representation for policy analysis. The methodology and software tool is validated for a sample of US and UK biomedical scientists, but can be applied to any countries where scientists' CVs are available in English. We provide an overview of the motivations for constructing the database, and the data crawling and data mining techniques used to transform webpage-based information and CV information into a relational database. We describe the database and the effectiveness of our algorithms and provide suggestions for further improvements. The software developed is released under free software GNU General Public License; the aim is for it to be available to the community of social scientists and economists interested in analyzing scientific production and scientific careers, who it is hoped will develop this tool further. All rights reserved, Elsevier This paper describes the methodology and software tool used to build a database on the careers and productivity of academics, using public information available on the Internet, and provides a first analysis of the data collected for a sample of 360 US scientists funded by the National Institute of Health (NIH) and 291 UK scientists funded by the Biotechnology and Biological Sciences Research Council (BBSRC). The tool's structured outputs can be used for either econometric research or data representation for policy analysis. The methodology and software tool is validated for a sample of US and UK biomedical scientists, but can be applied to any countries where scientists' CVs are available in English. We provide an overview of the motivations for constructing the database, and the data crawling and data mining techniques used to transform webpage-based information and CV information into a relational database. We describe the database and the effectiveness of our algorithms and provide suggestions for further improvements. The software developed is released under free software GNU General Public License; the aim is for it to be available to the community of social scientists and economists interested in analyzing scientific production and scientific careers, who it is hoped will develop this tool further. •The paper describes the methodology and software tool used to build a database on the careers and productivity of academics.•The software provides data crawling and data mining techniques used to transform webpage-based information and CV information into a relational database.•The software developed is released under free software GNU General Public License.•The methodology and software tool are validated for a sample of US and UK biomedical scientists.•We show that CVs are a valuable source of data to identify the exact point and type of academic mobility.•It is important to differentiate between voluntary and forced mobility, as only the former is associated with higher research performance. This paper describes the methodology and software tool used to build a database on the careers and productivity of academics, using public information available on the Internet, and provides a first analysis of the data collected for a sample of 360 US scientists funded by the National Institute of Health (NIH) and 291 UK scientists funded by the Biotechnology and Biological Sciences Research Council (BBSRC). The tool’s structured outputs can be used for either econometric research or data representation for policy analysis. The methodology and software tool is validated for a sample of US and UK biomedical scientists, but can be applied to any countries where scientists’ CVs are available in English. We provide an overview of the motivations for constructing the database, and the data crawling and data mining techniques used to transform webpage-based information and CV information into a relational database. We describe the database and the effectiveness of our algorithms and provide suggestions for further improvements. The software developed is released under free software GNU General Public License; the aim is for it to be available to the community of social scientists and economists interested in analyzing scientific production and scientific careers, who it is hoped will develop this tool further.
Author	Fernandez-Zubieta, Ana Guzmán, Eduardo Geuna, Aldo Barros, Beatriz Lawson, Cornelia Kataishi, Rodrigo Toselli, Manuel
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SubjectTerms	Academic careers Academic staff Biological research Biomedicine Biotechnology Careers Crawling Data analysis Data mining Economic research Extraction Extraction and data integration General public Information Information retrieval Internet Mobility of research scientists Occupations Policy analysis Productivity Public information Research methodology Research productivity Scientists Social sciences Social scientists Software Studies United Kingdom United States
Title	SiSOB data extraction and codification: A tool to analyze scientific careers
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