## 2 Materials and Methods
### The Graph Designer Workflow  
The Graph Designer Workflow is a generic digitalization workflow used to model the metadata of arbitrary processes as an interoperable manageable knowledge graph. It includes an ontology, a process data model or process graph template, a set of tools (the Graph Designer Tool), and a data pipeline. It is generic enough to work for different processes, ontologies, and data models, with the outcome being structured data presented as ontology-based knowledge graph(s). The Graph Designer Workflow is also coupled with a data modeling philosophy, which relies on the concept of creating a data model (or graph) for each impartible process part of the process chain of a labeled product, attaching to each single process its corresponding relevant metadata. In this context, 'process chain' refers to the sequence of processes. An example of such an impartible process, including the input and output objects, is represented in Figure 2.  
The introduced digital workflow for data structuring is illustrated in Figure 3 and comprehends the following steps:  
Figure 1: The BWMD process instance modeling philosophy: BFO classes depicted in black, BWMD classes in green, and BWMD object properties in red. Figure 2: Schematic representation of the permanent mold casting process including the ingot as input and the cast part as output. 1. Domain knowledge extraction: the first step when semantically modeling a new process is establishing the necessary vocabulary to describe the knowledge and data to be digitalized. This step is vital and will determine the quality and richness of the digitalized process data. The successful completion of the digitalization process is contingent on efficient communication between domain experts and ontology developers. An interview template was created to overcome the existent knowledge gap between these two involved parties. The interview template enables structured interviews and serves as an information exchange protocol. The output of this step results in the process-specific shared vocabulary being integrated into the domain ontology selected for the concrete use case. The formalization of the new extracted domain-specific vocabulary into an existing ontology (or into a new domain ontology module) is then conducted with the help of the software Protege [37] or a customized Python script;
2. Creation of impartible process graph templates: at this point, a single process step is generically represented as a knowledge graph (from now on denoted as 'Process Graph'). For this purpose, the software InfoRapid KnowledgeBase Builder [38] is used, which offers a graphical user interface for generating graphs. The Process Graph template generation of an impartible process consists of modifying a generic Process Graph template based on the information gathered from the interview template filled in the previous step and consequent established domain-specific vocabulary (domain ontology). This step is accomplished with the help of the functionality **OWL2 KDB** of the 'Graph Designer Tool' [36], which allows the user to import concepts from an existing ontology into the graphing tool. Creating a process-specific Process Graph template is an iterative process. It might take a few hours to days to semantically represent all relevant parts of the modeled process, depending on its level of description detail and complexity. The generated graph for describing the relevant metadata of the digitalized process is then converted into an Excel template. This substep is performed with the help of another functionality of the Graph Designer Tool, referred to as **KDB2 Excel**;
3. Acquisition of process datasets: the previously generated Excel template is duplicated and filled in by the domain experts of the respective process step. In principle, the filling can also be script-controlled. In addition to the captured metadata, the raw data is collected and linked in the filled or annotated Excel template;
4.