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When multiple objects are involved in a process, there is an opportunity for processes to be discovered from different angles with new information that previously might not have been analyzed from a single object point of view. This does require that all the information of event/object attributes and their values are stored within logs including attributes that have a list of values or attributes with values that change over time. It also requires that attributes can unambiguously be linked to an object, an event or both. As such, object-centric event logs are an interesting development in process mining as they support the presence of multiple types of objects. First, this paper shows that the current object-centric event log formats do not support the aforementioned aspects to their full potential since the possibility to support dynamic object attributes (attributes with changing values) is not supported by existing formats. Next, this paper introduces a novel enriched object-centric event log format tackling the aforementioned issues alongside an algorithm that automatically translates XES logs to this Data-aware OCEL (DOCEL) format.

Digital transformation is the rapidly expanding research field dealing with the increased impact of digital technologies on both business and society. Due to the large number of papers and the semantic ambiguity surrounding the terminology, covering such a broad topic is difficult. To help researchers gain a better understanding of the knowledge structure of the research field, we conduct a scoping review using scientometrics. We searched for publications dealing with digital transformation on both Scopus and Web of Science. We downloaded their bibliometric data and thoroughly merged and cleaned it using lemmatization and stemmatization. This dataset was analyzed using VOSviewer to create co-author networks and co-word occurrence graphs of the titles, abstracts, and keywords. We also visualized the growth of the research field and retrieved the top conferences and journals based on the number of papers and the number of citations. K-means clustering was performed on the abstracts and keywords to find similar research focuses. These findings highlight the broad scope of the research field, the ambiguity of the terminology, the lack of collaboration, and the absence of research into the impact of digital transformation on society. Moving forward, more research needs to be done to establish the boundaries of digital transformation and to investigate the importance of society in this phenomenon.

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