## 2 Materials and Methods
### Systematic Development of Organized and Sustainable Data Cores--Dissemination of Information
#### 2.5.5 Use of the Teleological Architecture for Organizing Systems (4 th Methodology)
For a detailed mathematical foundation of the methodology, along with a comprehensive set of mathematical formulas describing an explanatory implementation, the reader is referred to Appendix E.  
Figure 7: Data cores/indicators and computational methods. Exemplary Architecture of a System with Teleological Organization  
The exemplary implementation of a system can include several components, which are depicted in the following Figure 8. Further detailed information about the teleological architecture can be found in [26]. Methodology for Bringing Order within Systems Based on Teleological Architecture  
In this sub-section, according to the previously described teleological structure, an exact, novel methodology is presented for creating and maintaining highly organized datasets. For supporting complex missions and operational procedures, the methodology will be described in terms of a sequence of steps:  
* _Step 1_: Identify, at the highest possible level, important missions or complex operational procedures which a supporting system can substantially support. * _Step 2_: Assign priorities to the identified missions or complex operational procedures. If necessary, restrict the selection of missions according to technical, financial, or any other necessary criteria and select the missions which can be supported. The previous two steps are common at any level of command (e.g., national, strategic, and operational). * _Step 3_: For each remaining mission or set of complex operational procedures, start recursive decomposition into simpler sub-missions (or sub-procedures). Gradually, a tree-like structure is created that looks like an acyclic graph. This graph comprises many levels depending on the number of sub-missions which have been created. Every sub-mission is well-defined, detailed, and simpler than the layer above. Stop the decomposition at sub-missions that: (i) can no longer be divided into simpler ones. We shall call these sub-missions fundamental. In the tree-like structure, each fundamental sub-mission appears as leaf; (ii) have an unambiguous description of their input (data), methodology of computation (methods or programs), and output. This output consists of indicators which are the data that permit decision making. * _Step 4_: For each one of the fundamental sub-missions, specific data input will be needed for the SS. These input data are completely specified by the necessary indicators. Practice has shown that it is necessary to completely define the following: 1. The exact form and format, as well as the necessary characteristics, of these data, according to their intended use. 2. The sources from which these data have to be acquired. 3. Any necessary procedures for cleansing, filtering, transformation, or merging of the acquired input data, so that the needed data can be computed. This sub-step may have a very wide range of difficulty. 4. Exact procedures for regular and timely updating of the data. * _Step 5_: If data gaps remain, then:  
Figure 8: Exemplary system architecture with teleological organization. First, examine if there is a way to directly compute the missing data from other available data. 2. Then, examine if there are any other available data from which it is easy to make good-quality estimations for covering the gaps of missing data. 3. If good-quality estimations cannot be found, look for sub-missions similar to the fundamental ones (as defined in step 3), which may involve different indicators, computed from data, for which good-quality estimations can be obtained. 4. Otherwise, try to collect new input data. 5. _Step 6_: In the case that data gaps still remain after _steps 4_ and \(5\), try to further back-track in the tree-like structure of the decomposed missions for a sub-mission that can be modified so that, eventually, computable indicators can be found, without compromising the actual aims of the mission. In a considerable number of cases, this back-tracking may involve going several levels up, and actually redesign a part of the mission, until all data needs are satisfied.