Spatial Data Infrastructure (SDI)

Introduction

In [1] an SDI is defined as the relevant base collection of technologies, policies and institutional arrangements that facilitate the availability of and access to spatial data. Several definitions of an SDI exist, however, each adjusted slightly to fit specific needs (see [1]).

 

[1] D. Nebert, editor. Developing Spatial Data Infrastructures: The SDI Cookbook. The Global Spatial Data Infrastructure Association (GSDI), version 2.0 edition, 2004. http://www.gsdi.org/docs2004/Cookbook/cookbookV2.0.

Explanation

The way in which spatial data are perceived, expected, and consumed by users in their applications depends, to a large extent, on the current context and shape of technology, projects and markets. Interactions between these three drivers form the basis for the requirements of geoinformation systems at any given time. At present, these interactions translate into systems having to operate in an interconnected environment. As the systems that rely on spatial data have moved from single, separate working environments towards connected and cooperative environments, different needs, requirements and challenges have emerged. To address these changes, the spatial information community came up with the Spatial Data Infrastructure (SDI)initiative. Regardless of the author or the context, the issue comes down to one objective: interoperability, i.e. the property of diverse systems and organizations that allows them to work together, to inter-operate. The targeted objective of an SDI is, therefore, seamless access to all the constituent elements of a geoinformation system: data, operations, and results. These three elements are collectively called “geo-resources”. “Seamless” here means transparently over a network, regardless of computer platform, format or application. Central to this objective are standards. An SDI is not an entity in itself; it is rather an approach for working efficiently and effectively in a distributed, cooperative environment. There is, therefore, no recipe for the implementation of an SDI. Through the years, experts have come up with different interpretations of the concept and, therefore, different SDI implementations have been created too. The most familiar approach for implementation is based on the notion of a clearinghouse: i.e.epository to store descriptions of existing spatial data. These ˚ descriptions, known as meta-data, are created and stored in a standardized format. A clearinghouse allows spatial data producers to publish and disseminate meta-data, which in turn can be queried by users to discover spatial data resources. This approach describes the first generation of SDIs, and it was the way to go about implementing them in the early nineties. This could be achieved given the standards available and the maturity of the geoinformation technology of the day. The latest generation of SDI implementations focuses on geo-services. It is based on sounder standards and more robust technology. It uses webservices as a mechanism to provide access to georesources. The following subsections describe the developments that are considered to be state of the art in the realm of SDI.

 

Learning outcomes

  • 19 - SDI Environment

    Describe and apply the basic processes, processing, analysis and conversion in an SDI environment while combining multiple data sets from various remote sensing and other sources and explain challenges in data integration. Describe and use various methods of change detection. (Max. level 3)

Prior knowledge

Outgoing relations

  • Spatial Data Infrastructure (SDI) is based on Standards
  • Spatial Data Infrastructure (SDI) is part of Web 2.0

Incoming relations

  • SDI nodes is part of Spatial Data Infrastructure (SDI)
  • Web Portal is used by Spatial Data Infrastructure (SDI)

Learning paths