Capturing waste recycling science

Many institutions from the public and private sector are interested in the characterization of the research taking place in waste recycling (WR) science. Tech mining analysis can be applied to scientific databases with this purpose in mind, but difficulties do arise when designing the search strateg...

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Bibliographic Details
Published in:Technological forecasting & social change 2014-01, Vol.81, p.250-258
Main Authors: Garechana, Gaizka, Rio-Belver, Rosa, Cilleruelo, Ernesto, Gavilanes-Trapote, Javier
Format: Article
Language:English
Subjects:
Bibliometric analysis
Information retrieval
Problem solving
Recycling
Search strategies
Studies
Tech mining
Test systems
Waste recycling
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Summary:Many institutions from the public and private sector are interested in the characterization of the research taking place in waste recycling (WR) science. Tech mining analysis can be applied to scientific databases with this purpose in mind, but difficulties do arise when designing the search strategy to effectively capture this multidisciplinary area. This paper introduces the process followed to build a query system that aims to solve this problem. This system has been applied to a selection of scientific databases, and the steps followed to download and clean the data are detailed. Initial results are explained, indicating the relevance of each database and quantifying the overlap among them. The main subjects behind the retrieved data have been identified, namely, chemistry, biology and environmental sciences. A precision test conducted by random sampling indicated that, with a confidence level of 95%, the proportion of WR articles is between 74.2 and 79.2% of the retrieved items, while recall is expected to be high, according to available classifications. These results are deemed to be satisfactory enough for basing forthcoming tech mining analyses on this query system. ► We introduce a query system to capture waste recycling (WR) research activity. ► Four databases were selected according to their importance and specialization. ► An overlap of 38% is detected among databases. ► The scientific areas behind the retrieved data are analyzed. ► The proportion of WR articles present in the database lies between 74.2 and 79.2%.
ISSN:0040-1625
1873-5509
DOI:10.1016/j.techfore.2012.07.005