## 2 Background
### BIM Users' Behavior and Performance and BIM Log Files  
One key factor in the study of BIM users' behavior and performance in a collaborative work environment is the identification and development of appropriate collaboration models to improve user performance rates [22]. However, this area of research has mainly focused on using data from BIM logs to improve collaborative, design, and non-design practices [23; 24; 25].  
Autodesk Revit is a BIM software with a set of tools to coordinate the different disciplines in a project, thus minimizing the risk of errors in execution and decreasing production times and associated costs [10]. This software automatically generates log files as a database in which all the relevant information is recorded, from the technical specifications of the computer to the commands executed by the user, including when and for how long the program was used. Due to the huge amount of data they contain, reviewing these log files is a considerably complex and time-consuming task; consequently, they are frequently only used to investigate possible failures in the software or the computer in use. However, lately, new and innovative uses are being given to these sources of valuable information.  
For example, [PERSON] et al. [26] analyzed the content of log files from an architecture and design firm to investigate the presence of design patterns and to characterize the performance of BIM modelers. To that end, they searched the log files of different modelers, identified patterns of at least three sequential commands, and quantified the time it took these modelers to execute them, thus determining both individual work behavior and performance of those modelers.  
[PERSON] and [PERSON] [22] developed a systematic procedure for extracting data from BIM log files in order to monitor and measure productivity in the design process. They used a set of techniques known as 'process mining', which is usually divided into three branches according to the objective: (1) 'process discovery', (2) 'process conformance', and (3) 'process improvement' [27]. Of these, 'process discovery', which involves using saved records as an input to generate a process model, is the most widely employed [28]. In their case, [PERSON] and [PERSON] [22] presented a novel methodology that used these records to capture and model collaboration patterns between designers and generated social networks according to their behavior. To do this, they used the social network analysis (SNA) metric-type 2, which, in a design context, measures the number of times two designers interact with each other to contribute to the same project.  
In a second study, [PERSON] et al. [23] focused on identifying patterns in designer behavior and found that in general there are three commands of greatest use, which vary among the different designers. It was also possible to measure which patterns were the most efficient when working on a project. In this research, the pattern discovery process focused on the description of user operations as represented by executed commands.  
In addition, [PERSON] et al. [24] developed a conceptual model of collaboration in BIM through a literature review in order to identify collective behavior. And [PERSON] and [PERSON] [25] studied event logs archived during the design process of building projects using IFC (Industry Foundation Classes) files, discovering different approaches to support BIM management.  
Finally, [PERSON] and [PERSON] [29] applied fuzzy clustering methods to explore a massive amount of BIM log files from an international architecture design firm in order to identify productivity patterns in the modelers' behavior. They organized the process in three main stages: data preparation, clustering, and knowledge discovery. The analysis at individual level revealed specific time periods where the modelers showed better performance. The application of team-level clustering made it possible to evaluate if grouping designers with similar design productivity would provide better results for the firm.