Discovering seminal works with marker papers Bibliometric information retrieval in databases can employ different strategies. Commonly, queries are performed by searching in title, abstract andor author keywords (author vocabulary). More advanced queries employ database keywords to search in a controlled vocabulary. Queries based on search terms can be augmented with their citing papers if a research field cannot be curtailed by the search query alone. Here, we present another strategy to discover the most important papers of a research field. A marker paper is used to reveal the most important works for the relevant community. All papers cocited with the marker paper are analyzed using Reference Publication Year Spectroscopy (RPYS). For demonstration of the marker paper approach, density functional theory (DFT) is used as a research field. Comparisons between a prior RPYS on a publication set compiled using a keywordbased search in a controlled vocabulary and a cocitation RPYS (RPYSCO) show very similar results. Similarities and differences are discussed.

Theme Mapping and Bibliometrics Analysis of One Decade of Big Data Research in the Scopus Database Recently, the popularity of big data as a research field has shown continuous and widescale growth. This study aims to capture the scientific structure and topic evolution of big data research using bibliometrics and text miningbased analysis methods. Bibliographic data of journal articles regarding big data published between 2009 to 2018 were collected from the Scopus database and analyzed. The results show a significant growth of publications since 2014. Furthermore, the findings of this study highlight the core journals, most cited articles, top productive authors, countries, and institutions. Secondly, a unique approach to identifying and analyzing major research themes in big data publications was proposed. Keywords were clustered, and each cluster was labeled as a theme. Moreover, the papers were divided into four subperiods to observe the thematic evolution. The theme mapping reveals that research on big data is dominated by big data analytics, which covers methods, tools, supporting infrastructure, and applications. Other critical aspects of big data research are security and privacy. Social networks and the Internet of things are significant sources of big data, and the resources and services offered by cloud computing strongly support the management and processing of big data.