## 2 Technology and Design
### Filtering and Relevance Approaches
Similarly to LOD, a widely used approach for map services is to design and hold maps of different scales. Lightweight, small-scale overview maps are presented to the user first. The user may then select an area of interest or zoom, which triggers the loading of a more detailed, large-scale map. This saves bandwidth, since only for a small area heavy data needs to be sent to the user. As treated earlier in Section 2.2., for maps that are encoded as raster images _progressive loading_ can be applied. A similar technique, _progressive rendering_, is also available for vector data. For example, the XML based Scalable Vector Graphics can render map content in the order it is coded in the document. A user will see parts of the map rendered right at the beginning of loading the document. Further map elements are successively rendered. This approach requires an intelligent map structure, _i.e._, designing maps in a layered, prioritizing way. The map elements that are most important, have to be coded first in the document and have to be separated from less important objects that will be coded later. Sophisticated map applications make use of program logics that will load only small amounts of data for parts of the map that have changed, instead of sending a whole new map to the client. The first time the whole map is sent to a client, but for any further map updates usually only small data packages need to be transmitted and loaded. One technique supporting this kind of updating is _Asynchronous JavaScript and XML_ (AJAX), which is, for instance, used in Google Maps [70]. In recent years, traditional GIS use has moved on to Spatial Data Infrastructures (SDI). SDI are a concerted effort on technological (e.g., OGC) and institutional standards on different spatial levels aiming at finding, distributing, serving, and using geographic information by diverse groups of users and for numerous applications, making geographic information more accessible [71]. Their objective is to share information rather than exchange data and therefore they are based on (web) services. The idea behind SDI is that data sources, data processing, and data provision is distributed in the Internet at different sites. Contrary to traditional GIS applications where complete, huge spatial data sets need to be stored locally first, the architecture of SDI generally requires only relatively small amount of data (e.g., as a response of an OGC WFS request) to be transmitted from servers to clients when needed by the user and only the spatial extent and content required by the application or problem to be solved. If promises of SDI holds over time, then less bandwidth capacity will be needed, even though searching for data in catalogues or Geoportals, specifying requests and processes to be run on servers, or the conflation of different, distributed data sources may cause extra network traffic. Another recent development that has to be considered in connection to bandwidth use is _cloud computing_. Cloud computing shares some characteristics with the client/server model, but essentially it is a marketing term that refers to the delivery of computational requirements (e.g., processing power, data storage, software and data access) as a utility over the Internet [72, 73]. Cloud computing is currently very popular and it is likely that it will stay that way because of its many advantages, such as efficient distributed computing and ubiquitous services. However, it also introduces a great demand on the bandwidth by turning the traditionally local processes and services into network services.