## 1 Introduction
The term complex mission support system is introduced as a description/characterization of one system that is used for supporting the design, simulation, monitoring, and control of any type of operational procedure (or complex mission as it is called by many operational experts). In an extended sense, these systems are also called _command and control support systems_ because of their hierarchical operational structure [3]. Indeed, CMSS construction poses a significant technical challenge but, mainly, their creation  
Figure 1: CMSS as an intersection of DSS and IS. is considered of major importance for the design and maintenance of national defense and security policy operations. CMSSs need a multitude of information to operate properly. In particular, they usually demand georeferenced information which can be Two-Dimensional (2D) or Three-Dimensional (3D). In realistic operational scenarios, these CMS systems are dependent on information extracted from ill-designed data structures, either from data warehouses or other large-scale ISs. The creation of a CMS presents an emerging scientific and engineering area of interest, while its efficient design and implementation is crucial for national defense planning [4]. The proper execution of complex procedures has been one of the most important factors affecting their outcome. The need for the construction and utilization of CMS systems in complex missions arises due to multiple factors: Firstly, the _excessive complexity_ of the CMSS's internal operational procedures, an emergent property of its nature and the volume of the input data [5]. Furthermore, the increased _number of participant actors_ that are an internal part of the system in a mission, especially in cases of joint operations, which inherently demand a high level of coordination and synchronization [6]. Additionally, the _large volume of operational input data needed_, which are directly or indirectly geospatial [7]. Moreover, plenty of expertise of specialists and prior knowledge have already been standardized and/or formalized, both in the design phase and during the execution of a mission, but this knowledge is scattered and, in its totality, has not been integrated in a single IS. Last, but not least, the desire to use unexploited datasets of reliable quality (e.g., updated maps, regulations, guidelines, case laws in different geographical areas, etc. ), as well as successful operational procedures (e.g., successful coordination of actors in search and rescue missions, use of standardized operational methodology where available, etc.) [8]. In general terms, DSSs are capable of managing, controlling, monitoring, and executing operational procedures, either scheduled or in an emergency [9]. This type of system has already been developed for realistic cases in the political sector for addressing natural disasters [10], epidemic incidents [11], transportation of inflammable or other hazardous materials, etc. [12] and in the security sector for search and rescue missions [13], urgent air transportation of patients [14], supply missions [15], and other similar complex missions in several areas in case of emergency situations [16] (see Appendix A). However, it is widely known that these systems are designed ad hoc (i.e., for a specific purpose) and employ heuristic methodologies that may not necessarily be generalizable or applicable to other cases [17]. In the present study, it has been observed that the data required to support even simple operational procedures (e.g., search and rescue missions, transportation of sensitive or hazardous cargo, air transportation of patients and organs for transplantation, combating sea piracy, etc.) are usually of significantly high volume, often highly complex, and in the majority of cases, directly or indirectly related to maps [18]. In fact, the volume of these data continually increases, having already reached relatively large amounts. As a result, a system may become unmanageable or even uncontrollable.