Lessons Learned from local, National and Global Spatial data Infrastructures
David Rhind
Vice-Chancellor, City University, London EC1V 0HB
Email: d.rhind@city.ac.uk
Abstract
There are claimed to be National Spatial Data Infrastructures under development in about 40 countries. In addition, many lower level governments are creating them and attempts are being made to create a Global Spatial Data Infrastructure. This paper summarises the overall concepts and progress, using the USA and the UK as particular (and disparate) examples. It highlights the problems that have been faced and the lessons learned.
Introduction
National Spatial Data Infrastructures are being created in many different countries (see table 1). The ‘drivers’ for this include the development of Geographical Information Systems (GIS); without routinely useable tools to collate, refine, analyse and distribute information, many decision-making processes are hampered. Other relevant factors include the advent and widespread use of the Internet, globalisation of many businesses and the export of certain types of management approaches to the public sector in many countries (see Longley et al 2001)
| Argentina |
Hungry |
Northern Ireland |
| Australia |
India |
Norway |
| Canada |
Indonesia |
Pakistan |
| Colombia |
Japan |
Poland |
| Cyprus |
Kiribati |
Russian Federation |
| Finland |
Macau |
South Africa |
| France |
Malaysia |
Sweden |
| Germany |
Mexico |
United Kingdom |
| Greece |
Netherlands |
USA |
| |
New Zealand |
|
Table 1 Countries which have assembled or are assembling National Spatial Data Infrastructures as of mid-2000. Source H Tom, Oracle Corporation.
The history of GIS has been summarized by Coppock and Rhind (1991) and Foresman (1997). What began as a hugely expensive - and thus rare - mainframe computer tool for inventorying and mapping purposes in the mid-1960s blossomed in the 1990s. The statistics suggest that there are now about two million users of GIS world-wide and this figure is growing at about 20% per annum. Many of the active users of GIS are carrying out tasks on behalf of citizens, notably those carried out in governments. In addition, there are many everyday users of services which include GIS elements, sometimes without this being obvious (e.g. in many Internet searches). The annual commercial revenues generated from sales of GIS software are now over $1 billion world-wide. Typically this leverages a ratio of about 15 in terms of expenditures on hardware, staff training, data collection and operations. Thus the total annual GIS expenditure is now likely – in so far as it can be estimated – to be of the order of $15 to 20 billion. This figure is supported by estimates of expenditure by known users e.g. cadastral and mapping agencies. One surrogate for the growth of GIS is the number of people attending conferences: the numbers attending the user conference of the most popular GIS software have grown from 23 in 1981 to over 10000 in 2001. All this is not surprising for the range of applications of GIS is now truly extraordinary (Longley et al 2001). GIS has thus moved in 30 years from an esoteric side issue, based on the creation of software by academics and government, to a fully fledged global business. The great bulk of the software revenues are earned by a small number of US-based firms but other GIS expenditures are typically more local.
A key requirement is for appropriate ‘fuel’ for GIS. Mapping is important but the range of geographical information required is typically far beyond that held in map form (e.g. demographic, health, environmental, sales and market opportunities information). Most countries have governmental bodies charged with providing key data sets, especially ‘framework mapping’. But the ideal of having these information in machine form, manufactured to common and publicly defined standards, to be ‘interoperable’ and with ready accessibility is not met in any country. It might be thought that the situation is best in the most economically advanced countries. That is not necessarily true: the problems with the existing ad hoc situation in the USA have been summarised by the US Federal Geographic Data Committee (1997) as follows
‘In the United States, geographic data collection is a multibillion-dollar business. In many cases, however, data are duplicated. For a given piece of geography, such as a state or a watershed, there may be many organizations and individuals collecting the same data. Networked telecommunications technologies, in theory, permit data to be shared, but sharing data is difficult. Data created for one application may not be easily translated into another application. The problems are not just technical - institutions are not accustomed to working together. The best data may be collected on the local level, but they are unavailable to state and federal government planners. State governments and federal agencies may not be willing to share data with one another or with local governments. If sharing data among organisations were easier, millions could be saved annually, and governments and businesses could become more efficient and effective.
Public access to data is also a concern. Many government agencies have public access mandates. Private companies and some state and local governments see public access as a way to generate a revenue stream or to recover the costs of data collection. While geographic data have been successfully provided to the public through the Internet, current approaches suffer from invisibility. In an ocean of unrelated and poorly organized digital flotsam, the occasional site offering valuable geographic data to the public cannot easily be found.
Once found, digital data may be incomplete or incompatible, but the user may not know this because many data sets are poorly documented. The lack of metadata or information on the “who, what, when, where, why, and how” of databases inhibits one’s ability to find and use data, and consequently, makes data sharing among organizations harder…If finding and sharing geographic data were easier and more widespread, the economic benefits to the nation could be enormous’.
This statement actually understates the scale of the problems encountered in typical GIS projects or programmes. These normally involve dealing with the assembly of data from multiple sources and coping with scarce staff skills, ‘state of the art’ technology and frequently contested outcomes. Making effective and safe use of data encoded by different people to different levels of resolution and accuracy, collected at different times and without certification of quality, is often non-trivial. These are some of the problems that Spatial Data Infrastructures are designed to resolve.