# Merging Spatio-Temporal Objects and Business Processes: Land Reform Process Case Study
## 3 Methodology  
Besides the study of spatio-temporal data, processes, and events that impact geographical objects might provide additional clues for a better comprehension of the phenomena that arise. We believe that conceptual models should provide valuable support for modeling these processes, which are made up of a set of related events and actions as well as their causes, consequences, and correlations. [PERSON] in [43] highlighted the relevance of such modeling approaches. [PERSON] [44] formally specified how events interact, first, with other events (i.e., causality) and, secondly, with objects (i.e., an event can modify the state of an object, and the state of an object can trigger or stop another event). The design principles of our approach center on the separation of data and processes, which are modeled at different levels using MADS and BPMN, respectively:  
* \"Data\": the first level of the physical geographical objects together with their relationships that somehow materialize the spatio-temporal processes (STP) that occur in space and time, as we want to study them as well. * \"Processes\": the second level of the spatio-temporal processes, describing them and decomposing them into their components and events that arise and that overall impact the objects and their relationships. The framework of our approach is visually represented by Figure 1. In Step 1 of Figure 1, MADS takes center stage, serving as the foundational structure for primarily representing geographical data. It is a versatile framework that can be applied across a spectrum of studies catering to diverse business needs. This shared conceptual schema ensures uniformity and cohesion across a range of applications and usage scenarios. Moving on to Step 2, we employ the Business Process Model and Notation (BPMN) to accurately depict business processes. These processes are closely intertwined with the entities modeled by MADS. At this stage, a preliminary BPMN draft (for each specific business case) is automatically generated from MADS (Step 2a in Figure 1). Subsequently, the designer of each specific business model can enhance this draft, taking into account the constraints and specifications of their particular business model (Step 2b in Figure 1). Once the conceptual modeling, which encompasses data modeling and business processing, is complete, our methodology progresses to the implementation of the conceptual model into a logical model (comprising Steps 3, 4a, and 4b). Step 3 in Figure 1 illustrates the process of implementing MADS diagrams into a relational database. This step offers a structured representation of the spatial and temporal information associated with the case study, making it accessible and manageable. Step 4a involves encoding the BPMN diagram with Object Constraint Language (OCL) logical rules, effectively transforming it into a Petri net. Subsequently, Step 4b demonstrates the transformation of this Petri net into PostgreSQL/PostGIS. With the comprehensive logical model firmly established, it becomes highly efficient to manipulate it using SQL (Step 5). This empowers users to seamlessly engage with the model and extract insights from the data. Moreover, harnessing data collected from a diverse range of business applications, the methodology unlocks the potential for advanced AI classifiers with the ability to forecast forthcoming scenarios within geographical data, delivering substantial value across a multitude of industries and applications. To describe the technical implementation, we employ the development of our framework and ensure its applicability to any geographical case study. Further, we will outline the following technical stages, each of which will be dedicated to a subsection:  
1. Coupling MADS With BMPN: automatically generate a draft of the BPMN model based on the MADS model, aligning the business processes with the spatial and temporal dimensions of the case study. 2.