
%0 Journal Article
%A MacLeod, I. 
%A Amorim, R. 
%A Valleau, N. 
%T DAP ? Large volume spatial data discovery and distribution over networks
%J Exploration Geophysics
%D 2003/06/01
%V 34
%N 2
%P 143-146
%K 
%R https://doi.org/10.1071/EG03143
%U https://www.publish.csiro.au/paper/EG03143 
%X The Internet, Intranets, and general globalization of networking technology have produced a dramatic increase in the type and volume of spatial data that are available to geoscientists. The development of protocols and underlying technologies for computers to access and share spatial data, both privately within organisations, and globally on the Internet, is key to our ability to use this information efficiently. In this paper, we describe the Data Access Protocol (DAP), which is a suite of client tools and proprietary server applications that enables geoscientists to find and evaluate data, and to automate windowing, reprojecting, and reformatting the data to suit a specific requirement. DAP technology addresses a variety of network situations including: 1. Simple web browser-based discovery and retrieval of data of interest in a specified format and coordinate system. 2. Support for the Open GIS Consortium Web Map Server (WMS) interface to allow any WMS-compatible application to retrieve "images" of the data for use as layers in a GIS application. 3. Direct support for DAP-enabled thick clients, such as Oasis montajÔ, to optimally retrieve data directly for their own use, and to transfer data to a hosting DAP environment. When communicating with DAP-enabled client applications, DAP addresses the movement of data (lossless compression, encryption and streaming) both to and from a data server over a network. The core DAP protocol effectively abstracts data formats to allow client applications to work in whatever environment is required. DAP servers can also connect to data in whatever native format is in use by a hosting organisation, which makes DAP suitable for use in many data storage environments. DAP also includes a number of spatially optimised data stores that can be used to deliver extremely high performance for data extraction and retrieval. 
