Bibliometric dataset of pillared clays (PILCs) as retrieved from Scopus and Web of Science databases: research trends
The data correspond to metadata retrieved from the main databases (Scopus and WoS) of scientific publications on pillared clays (PILCs) used in chemical and environmental processes from 1980 to 2019. These data allow visualizing the research trends on the use of PILCs in catalytic processes over the last 40 years. The file named "PILCs 1980-2019.csv or PILCs 1980-2019.txt or PILCs 1980-2019.xml" allows text and data mining on the scientific productions of pillared clays. The thesaurus is composed of metadata extracted from the titles, abstracts, authors, affiliations (institutions) and keywords of publications related to PILCs. The data were filtered, standardized, double-counted documents and homonyms (institutions and authors) were removed. Thus, this thesaurus allows text mining to identify lines of research, catalytic uses and environmental applications of pillared clays. The scientific community working on the synthesis and characterization of layered solids, such as clays, can benefit from the information contained in this metadata. The data allow the identification of the most important applications of PILCs, as well as provide information of the scientific production of PILCs over the last four decades. The data also allow scientific mapping such as co-authorship networks, cooperation between countries and continents, authors and institutions that publish the most on pillared clays. In addition, it is possible to identify frequently used keywords, characterization and synthesis techniques, as well as areas of knowledge and journals of major interest on PILCs.
Steps to reproduce
Data were retrieved from the Scopus and Web of Science databases using the keywords "Pillared clays" /PILCs /PILC / "Pillared Interlayered clays" and the logical connector "OR". The dataset was retrieved from the databases and exported to VantagePoint Software. Through manual verification, the metadata was standardized and normalized. Also, double counted documents were eliminated and homonymous authors and institutions were removed. Using text mining, research trends on PILCs were identified. These data can be processed using VantagePoint, Excel and VosViewer software.