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Erschienen in:
The Journal Impact Factor: A Brief History, Critique, and Discussion of Adverse Effects Kapitel lesen Erstes Kapitel lesen

2019 | OriginalPaper | Buchkapitel

30. Data Collection from the Web for Informetric Purposes

verfasst von : Judit Bar-Ilan

Erschienen in: Springer Handbook of Science and Technology Indicators

Verlag: Springer International Publishing

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Abstract

This chapter reviews the development of data collection procedures on the web with an emphasis on current practices, data cleansing and matching, data quality and transparency. There are several issues to be considered when collecting data from the web. Transparency is essential to know what is included in the data source, how recent and comprehensive the data are, what timeframe is covered etc. Data quality relates to reliability and accuracy. Mistakes are inevitable, data providers, aggregators, and researchers all make mistakes, but these mistakes should be reduced to a minimum so that meaningful conclusions may be reached from the data analysis. Extensive data cleansing before starting the analysis is needed to try to correct mistakes in the data. When several data sources are used, data from different sources should be matched, and duplicates should be removed.

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Vorheriges Kapitel Readership Data and Research Impact
Nächstes Kapitel Web Citation Indicators for Wider Impact Assessment of Articles
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Metadaten
Titel
Data Collection from the Web for Informetric Purposes
verfasst von
Judit Bar-Ilan
Copyright-Jahr
2019
Verlag
Springer International Publishing
Buch
Springer Handbook of Science and Technology Indicators

Print ISBN: 978-3-030-02510-6

Electronic ISBN: 978-3-030-02511-3

Copyright-Jahr: 2019

DOI
https://doi.org/10.1007/978-3-030-02511-3_30

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