Home Articles Selecting funding models for SDI implementation

Selecting funding models for SDI implementation

Alan R Stevens
Garfield Giff
Department of Geodesy and Geomatics Engineering,
university of new brunswick, Canada
[email protected]

David Coleman
David Coleman
Professor and dean of engineering,
Department of Geodesy and Geomatics Engineering, University of New Brunswick
[email protected]
The aim of this paper is to introduce the concept of the application of SDSM to the selection of funding models for SDI implementation. SDSM will enable programme coordinators to replicate their implementation environment, track the application of the models over time, and observe their reaction to changes in key variables operating within the environment

The increase usage of spatial information (SI) by a wide sector of today’s society has fuelled the demand for accurate and reliable spatial information in the different format required by the market [Onsrud et al., 2004]. To facilitate better access to SI, at least 50 countries have implemented different qualities of Spatial Data Infrastructure (SDI). (See [Onsrud, 1999].) In the developed world, these first-generation SDIs are at the end of their current funding arrangements and therefore, will require new funding arrangements for future generations. Also, SDI initiatives now underway in emerging nations are in need of structured funding arrangements for their efficient implementation.

To address this problem, authors (e.g. [Rhind, 2000]; [Urban Logic, 2000]; and [Giff and Coleman, 2003]) have proposed different sets of funding models for the financing of future generations of SDIs. These models were designed for the generalized implementation environment and therefore, may not be specific enough for an individual environment. Therefore, SDI program coordinators are faced with the problem of selecting models more suitable to their implementation environment. A possible solution to this problem is the design and or selection of methodologies to evaluate the performance of the models when applied to a specific implementation environment. The authors-based on research carried out at the University of New Brunswick- propose the usage of System Dynamic Simulation Modelling (SDSM) technique as a possible method for the evaluation of SDI funding models applied to a specific implementation environment. SDSM will enable program coordinators to replicate their implementation environment, track the application of the models over time, and observe their reaction to changes in key variables operating within the environment.


Fig. 1: An illustration of the Symbol Used in a Feedback Loop

Fig. 2: An Example of The Application of SDSM to SDI Funding

Fig. 3: An Example of a SDSM of an SDI Funding Environment