A Local-State Government Spatial Data Sharing Partnership

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Chapter 2 – Spatial Data and SDI in Context
characteristics of the organisation, characteristics of the data, characteristics of the
exchange and the constraints and impediments.
Table 2.4 summarises the taxonomy proposed by Calkins and Weatherbe. The taxonomy
provides a useful framework but does not consider the wider contextual issues, policies or
capacity.
Table 2.4 Data sharing taxonomy (Calkins & Weatherbe 1995, p. 71)
Organisational Characteristics Data Use Function, Organisational mandate,
Departmental Function, Organisational
structure, Data Sharing Role
Characteristics of Spatial Data Data type/format, Importance of data,
Organisation of data, Categories of data,
Nature of data, Quality assurance
Characteristics of Exchange Type of Partner, Partner relationship,
Sharing arrangement, Pricing, Schedule,
Frequency, Quantity, Medium, Initiation
Constraints and Impediments Access, Data confidentiality, Liability, Price,
Format and standards, Documentation,
Communication networks/technology
Kevany (1995) proposed a more detailed structure to assess the effectiveness of data
sharing. This structure was based on the author’s experience across a range of projects,
particularly at the county, municipality and city levels. Thirty factors that influence data
sharing were identified within nine broad areas: sharing classes, project environment, need
for shared data, opportunity to share data, willingness to share data, incentive to share data,
impediments to share data, technical capability for sharing and resources for sharing.
The factors from the broad areas were rated to provide a measurement framework for
assessing and comparing data sharing arrangements. The assessment was achieved
reasonably efficiently, but involved a degree of judgement and subjectivity (Kevany 1995).
Data sharing can also be viewed in terms of antecedents and consequences (Obermeyer &
Pinto 1994; Pinto & Onsrud 1995). The framework proposed by these authors included a
range of events or factors such as incentives, superordinate goals, accessibility, quality of
relationships, bureaucratisation and resource scarcity, which precede the process of data
sharing. The impact of these events and factors then mediated a range of data sharing
consequences such as efficiency, effectiveness and enhanced decision making. Within this
data sharing model the context of the data sharing arrangement was also considered (Pinto
& Onsrud 1995). The context of the exchanges could be project based where organisation
came together to use common data to solve a common problem. Another context was
where different organisations addressed different problems but had a need for similar
information. A third context was where organisations developed generalised patterns of
exchange which led to the development of a centralised data base.