## 4 Contemporary, Mainstream Methodologies for Creating Large-Scale Decision Support Systems  
First of all, a complete/thorough analysis and study, concerning the set of the required indicators, usually precedes the system design. This part of the DSS project is absolutely necessary; otherwise, corrections and additions at a later stage may be difficult or even impossible. The initial study must clearly and comprehensively offer information about the following, which will also prove very useful in the analysis of Sections 5 and 6:  
1. A comprehensive list of the general issues/problems, for which the DS system must provide support. We will use for it the term \"thematic list\". 2. A decomposition of each one of the aforementioned issues/problems to subcategories, further subcategories, etc., up to the fundamental, non-separable issues/problems. We will employ for this process the term \"thematic decomposition\". For example, the general transport issue of \"social/environmental impacts of transport\" must initially discriminate between the subcategories \"harmful impacts\" and \"beneficial impacts\". Then, the subcategory of \"harmful impacts\" must, among others, include:* \"Noise\";
* \"Congestion\";
* \"Pollutant emissions\". For example, a complete associated path could be the following: transport policy issues \(\rightarrow\) environmental impacts of transport \(\rightarrow\) harmful environmental impacts of transport \(\rightarrow\) noise \(\rightarrow\) noise produced at the transport network \(\rightarrow\) elementary/non-separable issue: noise produced by road traffic outside of the urban areas \(\rightarrow\) indicator(s): noise measurements for all links and nodes of the road network outside of the urban areas. On the other hand, the subcategory \"beneficial impacts\" must, among others, include:  
* \"Improved connectivity\" (e.g., better island connectivity);
* \"Transport time reduction\";
* \"Growth\" (e.g., residential or commercial relocation for a better environment, improvement of trade conditions, economic growth, etc.). It must be emphasized that the form of an indicator can greatly vary, from a simple set of numbers (e.g., the former Kyoto indicators for environmental pollution) [42; 43; 44; 45] to a complete database (e.g., a map indicating the road congestion of an area, with seasonal and daily indications). An ensemble of methods for either acquiring the indicators or computing them from the relevant data, using proper mathematical models. A complete list of the data, from which indicators must be evaluated. A complete list of the corresponding software, that is, programs that will implement the aforementioned abstract objects. A sufficient/adequate ensemble of \"metadata\", which are necessary for the description of all indicators, data, acquisition or evaluation methods and the justification of their choice. It must be emphasized that this step is quite often partially considered or even neglected in the design of impressively numerous very large-scale information systems. Designing a very large-scale information system and including a poor/insufficient set of metadata is a grave error that will practically render the system non-maintainable, non-upgradable and non-modifiable. The related information is, as a rule, a result of tedious efforts of experts, usually belonging to numerous scientific disciplines. Evidently, the work of the experts is supported by information technology and communication (ITS) engineers. As a next step, ITS experts, using the aforementioned abstract results, implement the following:  
* A user interface architectural tier, that is, an adequate number of computer systems to handle the communication of the users with the DS system. Nowadays, this is achieved through the Internet and/or an Intranet, if confidentiality reasons dictate so. * One or more databases and/or data warehouses specifically designed to handle large ensembles of data. The entire set of these tools is frequently called \"data tier\".