A Local-State Government Spatial Data Sharing Partnership

A Local-State Spatial Data Sharing Partnership Model to Facilitate SDI Development
Nedovic-Budic et al. 2004a; Obermeyer & Pinto 1994; Onsrud & Rushton 1995b; Wehn de
Montalvo 2002). Many investigators consider these issues to fall under two categories
namely: barriers (constraints) or benefits (which motivate).
The underlying premise for sharing data is that it will eventuate in a range of benefits for
the organisations involved. The primary benefits or drivers for data sharing as introduced
in the previous section, include cost savings through lack of duplication of data collection
and maintenance efforts, improved data availability, and enhanced organisational
relationships through promotion of cross organisational relationships (Nedovic-Budic &
Pinto 2000).
Another important benefit of data exchange may also be the improvement in the quality of
the data sets, particularly where there are multi-organisational efforts to contribute to a
common or shared data base. Reduction in risk can also be seen as a benefit (Evans 1997)
if organisations are prepared to both contribute to the costs or development time for a
shared initiative.
The issues of cost recovery, copyright and legal liability have done little to encourage
organisations to provide access to spatial information (Rhind 1992). The majority of issues
relating to spatial data sharing are considered to be related to an organisational framework
in one form or another. For example the legal issues are primarily related to the
perspective of an individual organisation with regard to their organisation’s liability as a
result of sharing. Economic issues are also related to organisational budgets rather than
external funding in a large proportion of data sharing initiatives.
2.5.4 Data Sharing Frameworks and Models
The Mapping Science Committee of the National Research Council developed a generic
data sharing model to encompass all levels of government and the private sector. The
model involved a number of key components including data producers, data development
agreements, cost-sharing agreements, state level data advisors, quality assurance programs,
data and metadata standards, and users (National Research Council 1993). Although very
generic, this model identified a number of key issues including standard agreements,
quality assurance and technical standards.
One of the early efforts to describe a classification framework for data sharing was
undertaken by Calkins and Weatherbe (1995) with the development of a taxonomy for
research into spatial data sharing. The four primary components of the taxonomy were the
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