Abstract
Clarivate Analytics’ Web of Science Core Collection, a comprehensive database consisting of ten sub-datasets, is increasingly applied in academic research across over two hundred Web of Science categories. 271 English language SCIE and SSCI papers published in 2017–2018 from the category of Information Science and Library Science have mentioned “Web of Science” in the topic field. A manual check of the full texts of these papers reveals that 243 of them have used “Web of Science Core Collection” as the data source but over half of them haven’t specified the sub-datasets of Web of Science Core Collection used in the study. Since many institutions may only subscribe to a customized subset of the whole core collection, the non-transparency of the data source will hinder the reproducibility of some corresponding studies. This study suggests that researchers should specify the sub-datasets and corresponding coverage timespans when using Web of Science Core Collection as the data source.
Notes
The newly provided backfile of ESCI expands the coverage of the period 2005–2014. http://info.clarivate.com/ESCI?_ga=1.144241463.383957850.1488223989.
Different to the search strategy of Li et al. (2018), only the keyword “Web of Science” is used in this study since the purpose of this study is to verify whether a record has specified the sub-datasets of the Web of Science Core Collection.
By using both “Web of Science” and “Meta” as the keywords to search in the topic field, 9995 records can be retrieved. That is to say, 52% of the records used in this study is also meta related.
Researchers in the field of Information Science & Library Science are more likely to be familiar with the Web of Science Core Collection. They may prefer to specify the sub-datasets when using Web of Science Core Collection.
The author would like to thank the referee to suggest this important work of Dallas and his/her colleagues. It seems that both researchers from the fields of Bioscience and Scientometrics have noticed this important issue.
References
Bar-Ilan, J., & Halevi, G. (2018). Temporal characteristics of retracted articles. Scientometrics,116(3), 1771–1783. https://doi.org/10.1007/s11192-018-2802-y.
Berg, J. (2018). Progress on reproducibility. Science,359(6371), 9. https://doi.org/10.1126/science.aar8654.
Camerer, C. F., Dreber, A., Holzmeister, F., Ho, T. H., Huber, J., Johannesson, M., et al. (2018). Evaluating the replicability of social science experiments in nature and science between 2010 and 2015. Nature Human Behaviour,2(9), 637–644. https://doi.org/10.1038/s41562-018-0399-z.
Clarivate Analytics. (2019). Web of Science databases. Retrieved July 19, 2019, from https://clarivate.com/products/web-of-science/databases/.
Dallas, T., Gehman, A. L., & Farrell, M. J. (2018). Variable bibliographic database access could limit reproducibility. BioScience,68(8), 552–553. https://doi.org/10.1093/biosci/biy074.
Franceschini, F., Maisano, D., & Mastrogiacomo, L. (2016). Empirical analysis and classification of database errors in Scopus and Web of Science. Journal of Informetrics,10(4), 933–953. https://doi.org/10.1016/j.joi.2016.07.003.
Hu, G., Yang, Y., & Tang, L. (2019). Retraction and research integrity education in China. Science and Engineering Ethics,25(1), 325–326. https://doi.org/10.1007/s11948-017-0017-x.
Jacso, P. (2018). The scientometric portrait of Eugene Garfield through the free ResearcherID service from the Web of Science Core Collection of 67 million master records and 1.3 billion references. Scientometrics,114(2), 545–555. https://doi.org/10.1007/s11192-017-2624-3.
Lei, L., & Zhang, Y. (2018). Lack of improvement in scientific integrity: An analysis of WoS retractions by Chinese researchers (1997–2016). Science and Engineering Ethics,24(5), 1409–1420. https://doi.org/10.1007/s11948-017-9962-7.
Leydesdorff, L., Carley, S., & Rafols, I. (2013). Global maps of science based on the new Web-of-Science categories. Scientometrics,94(2), 589–593. https://doi.org/10.1007/s11192-012-0784-8.
Li, K., Rollins, J., & Yan, E. (2018). Web of Science use in published research and review papers 1997–2017: A selective, dynamic, cross-domain, content-based analysis. Scientometrics,115(1), 1–20. https://doi.org/10.1007/s11192-017-2622-5.
Liu, W. (2017). The changing role of non-English papers in scholarly communication: Evidence from Web of Science’s three journal citation indexes. Learned Publishing,30(2), 115–123. https://doi.org/10.1002/leap.1089.
Liu, W., Hu, G., & Tang, L. (2018). Missing author address information in Web of Science—An explorative study. Journal of Informetrics,12(3), 985–997. https://doi.org/10.1016/j.joi.2018.07.008.
Rafols, I., Porter, A. L., & Leydesdorff, L. (2010). Science overlay maps: A new tool for research policy and library management. Journal of the American Society for Information Science and Technology,61(9), 1871–1887. https://doi.org/10.1002/asi.21368.
Rousseau, R., Egghe, L., & Guns, R. (2018). Becoming metric-wise: A bibliometric guide for researchers. Cambridge, MA: Chandos Publishing. https://doi.org/10.1016/C2017-0-01828-1.
Tang, L. (2013). Does “birds of a feather flock together” matter—Evidence from a longitudinal study on US–China scientific collaboration. Journal of Informetrics,7(2), 330–344. https://doi.org/10.1016/j.joi.2012.11.010.
Tang, L., Hu, G., & Liu, W. (2017). Funding acknowledgment analysis: Queries and caveats. Journal of the Association for Information Science and Technology,68(3), 790–794. https://doi.org/10.1002/asi.23713.
Van Eck, N., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics,84(2), 523–538. https://doi.org/10.1007/s11192-009-0146-3.
Walsh, J. P., Lee, Y. N., & Tang, L. (2019). Pathogenic organization in science: Division of labor and retractions. Research Policy,48(2), 444–461. https://doi.org/10.1016/j.respol.2018.09.004.
Zhu, J., Hu, G., & Liu, W. (2019). DOI errors and possible solutions for Web of Science. Scientometrics,118(2), 709–718. https://doi.org/10.1007/s11192-018-2980-7.
Acknowledgements
This research is partially supported by the National Natural Science Foundation of China (Grant No. 71801189) and Zhejiang Provincial Natural Science Foundation of China (Grant No. LQ18G030010). The author would like to thank the referee for his/her insightful suggestions and comments which have significantly improved the manuscript.
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Liu, W. The data source of this study is Web of Science Core Collection? Not enough. Scientometrics 121, 1815–1824 (2019). https://doi.org/10.1007/s11192-019-03238-1
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DOI: https://doi.org/10.1007/s11192-019-03238-1