# Merging Spatio-Temporal Objects and Business Processes: Land Reform Process Case Study
## 2 Geographical Database Modeling Background
### Business Process Modeling  
A Business process model is defined by a sequence of events and actions that lead to a defined \"state of affairs\" with a clear beginning and end [24]. It deals with data and events, takes inputs, and gives outputs. Business processes represent a strategic and critical intellectual asset that needs to be understood and proactively managed [25; 26]. Different organizations have proposed several standards for business process modeling and management (OMG, BPMI, OASIS, IMB, W3C, etc. ), as well as several research approaches, such as event-driven process chains [27], BPM [28], BPMN [24; 29] and UML-activity diagrams [30]. Among many approaches, BPMN and UML activity diagrams are the most popular business process models [29; 31; 32]. A UML Activity diagram describes the dynamic aspects of a given system. It can be defined as an improved version of a flow chart that models the flow between activities. The flow from one activity to another can be concurrent, sequential, or branched. Activity diagrams deal with all types of flow control and are used to visualize the dynamics of the system and to construct executable systems. However, the activity diagram does not display any \"message\" flow between activities. BPMN is a graph-oriented language that shows the steps of a business process and coordinates the sequence of processes and messages that pass by the different participants in the different activities [26]. BPMN has the expressiveness to model complex business processes and can be mapped to business executive language. BPMN consists of many abstractions, such as flow objects and connecting objects and artifacts [33]. A visual language based on the concrete BPMN syntax is used to query business process diagrams. This visual language matches the BPMN diagram to a query graph [34]. BPMN-Q is designed to query the core concepts of a business process model. Several authors have discussed the superiority of BPMN models over UML ones when addressing complex business-based approaches [33; 35; 36]. Researchers have recognized the advantages of utilizing conceptual and business models for information systems in both the general and GIS domains. On the one hand, UML and conceptual diagrams were employed by [21; 37] to model nonfunctional requirements in various systems such as a library information system, government-citizen participation, a big data smart agricultural system, and 2.5D/3D spatial data. Additionally, ref. [38] introduced a novel visual programming language that integrates the principles of conceptual modeling language and methodology, offering a unified diagram type with a universal ontology and built-in refinement abstraction mechanisms. On the other hand, ref. [39] employed model-driven business engineering to enhance formality and clarity, capture static and dynamic aspects of the business, and devise business solutions such as business plans, progress reports, and status reports. Ref. [40] studied the usage of BPMN notation for designing process collaboration, choreography, and conversation models, and investigated how to link good modeling practices with specific BPMN elements and modeling tools. Ref. [41] proposed an extension of BPMN to address spatial concerns. Ref. [42] assessed the state of research on business process simulation, mentioning the need to improve BPMN models for specific applications. However, to date, none of these models consider the integration of the representation of real-world phenomena with management tasks. However, such integration should enable a deeper understanding of why and how events occur in a geographical case study, aiding in the comprehension and prevention of their consequences. Our article introduces a model that offers a conceptualization framework with complete independence between data and process modeling, facilitating seamless integration. This also emphasizes model clarity and reuse, allowing researchers to effectively explain modifications affecting spatiotemporal data.