# Generating Transparency in the Worldwide Use of the Terminology Industry 4.0
## 2 Materials and Methods  
To achieve the goal of creating transparency within the usage of the term Industry 4.0, a quantitative literature review approach has been selected. The methodology that was chosen for our quantitative analysis is similar to that which was used by [PERSON] et al. [26]. To ensure the validity of our results, it is necessary to take into account:  
1. the quality of the selected articles;
2. their relevance to the subject to be reviewed;
3. their completeness [27]. Advancements in information technology have led to a growing quantity of quickly accessible research articles, many of which focus on similar topics under different headings. Thus, modern literature reviews intrinsically carry the risk of overlooking relevant literature [28]. Therefore, [PERSON] et al. [26; 27; 29; 30] underline the necessity of rigorously documented reviews. Systematic approaches have been introduced by [31; 32; 33]. Taking into account the aforementioned considerations and following the recommendations of the literature, our analysis consisted of a keyword-based approach that was executed using two different platforms, namely Scopus and ScienceDirect [34; 35]. In methodological terms, a keyword search refers to the process of inserting the keyword in the search mask of a scientific platform and analyzing the given output against predetermined conditions. The reasoning behind the usage of two platforms lies within an accompanying increase in the robustness of our analysis, as well as a minimization of platform bias. It should be noted that on the scientific platform Scopus, the ranking by number of citations was utilized. On ScienceDirect, however, a ranking by relevance was followed, as it was not possible to rank by citations. The algorithm used by ScienceDirect to determine the relevance of a paper is based on the frequency of relevant keywords [36]. A summary of the quantitative literature review approach is depicted in Figure 1. All methodological steps are explained in further detail within the following paragraphs. The keywords that were part of the final keyword list and thus were used for the quantitative assessment are depicted in Figure 2. Their assortment was based on a scientific working paper published by researchers from the TU Dortmund [10]. The set of keywords used in that study was further altered, divided, and expanded to depict a more holistic picture of Industry 4.0. Thus, we identified keywords linked to the terms Industrie 4.0 and Industry 4.0 in the course of a pre-study as follows: starting with the keywords provided by [10] the scope of relevant keywords was further expanded by searching for papers using the current set of keywords and adding further keywords according to their occurrence in the search results. In doing so, the papers were ranked by number of citations/relevance according to the databases Scopus and ScienceDirect. The resulting keywords are depicted in Figure 2.  
Figure 1: Methodology for the quantitative literature review approach, separated into pre-study for identifying the final keywords and the iterative literature review process. Figure 2: Categories and keywords used in the quantitative analysis. The following abbreviations are used: cyber–physical systems (CPS) and machine-to-machine (M2M). As shown in Figure 2, the resulting set of keywords could be arranged in four main categories, namely cyber-physical systems (CPS), data management and analysis (For reasons of brevity, this term is referred to as data management or data in the following), human-machine interaction, and smart. * CPS: This term revolves around the progressing topic of interconnected machine networks that can communicate with each other to optimize industrial processes. The keywords used here comprised the following: cyber-physical, machine-to-machine, and the abbreviation of the latter, M2M;
* Data management: The topic of data management is steadily increasing in size and importance due to the amount of data produced daily across industries.