David Rhind

A framework for evaluating geographical information

This paper introduces a framework for the evaluation of geographic information (GI), divided into representational and communicative aspects. The representational component is concerned with how ‘real-world’ phenomena situated in space and time come to be represented or modelled in GI, considered at ontological, modelling and system levels. The communicative component of GI is concerned with how representations of GI are understood by the users of the information, considered at relevance, commodification, exploration and management levels. This paper attempts to bring together the previous work in all these areas into an evaluative framework so that creators and users can assess the validity and success of the representational and communicative process overall. This paper also outlines the architecture of a client-server geolibrary designed for information sharing. This kind of architecture provides a distributed and open platform for the development of GI networks, upon which more productive use of GI can be built in future.

The Projected Characteristics of a National Topographic Digital Databank

Comparatively little is known concerning the likely characteristics of projected national digital topographic data bases. This paper describes an estimation of these characteristics for Great Britain, based on a sample of over 400 Ordnance Survey digital maps at 1 : 1250 and 1 : 2500 scales. The sources of the considerable uncertainty in the projections are discussed and it is concluded that some 3000 km of line work at map scale needs to be encoded to provide basic scale coverage apart from contours. With present Ordnance Survey methods of storage, this would require about 580 magnetic tapes.

Spatial Data Infrastructure

Spatial Data Infrastructures (SDIs) are being built and redefined in many countries. They underpin many of the activities of the state and of business. Geographical Information Systems are no longer simply technologies. They are embedded within SDIs and rely on some of the latters key elements to be able to operate effectively and efficiently. This article defines the nature of an SDI, noting the international variations in use of the term and sets out why these are of growing significance. It then considers separately as examples the US National Spatial Data Infrastructure and the putative Global Spatial Data Infrastructure, describing their successes, their problems to date, and possible futures. The relevance of all this for the social sciences is summarized.