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Most
spatial applications have interests at a national
level datasets, even if they are performed at
local level or small regions.
With this in mind, a National SDI can provide
the institutional, political, and technical basis
to ensure the national consistency of content
to meet user needs in the context of sustainable
development (Willaimson et al., 2003).
A National SDI provides the foundation to access
built and natural environmental datasets. However,
in most countries, these two foundation datasets
are normally managed separately to serve different
purposes. The lack of uniformity across different
jurisdictions within a country often creates problems
in attempts to integrate the two datasets at a
national level (Tsange, 2005). These issues are
caused due to technical heterogeneity, institutional
structure, policy issues, legal concerns and social
effects of the integration.
The most prominent technical issues recognised
so far comprise standards, interoperability, semantic,
reference system, format, and data quality. The
collaboration model (business model) between stakeholders
and funding models, and data management approaches
are key issues within the institutional arrangement
of SDI dealing with integration.
On the Policy side, political stability, priorities
of nations, legislation and
awareness of the users about the existence of
data have been found as
major issues. The defi nition of RRR (rights,
restrictions and responsibilities) surrounding
datasets and their use, copyright and intellectual
property rights (IPR), data access, privacy, pricing
and licensing may differ in jurisdictions and
even in different levels of a particular jurisdiction
are very challenging. Cultural differences, capacity
building, equity and minority, indigenous and
women rights are also paramount in the social
category, as shown in Table 1. These categories
show distinct items, however it must be remembered
that they also have effects on each other and
especially on SDI components. |
 |
| Conclusion |
This
paper discussed the importance and requirements
of spatial data integration in serving users’
needs and the importance of better understanding
multi-source data integration within SDI initiatives.
The primary goal is to design a methodological
framework to facilitate the integration of built
and natural datasets and will advance the knowledge
of the National SDI capacity in meeting sustainable
development objectives. This will be achieved
through the development of new concepts and policies
to integrate built and natural environmental datasets.
On the other hand, the merit of the data determines
the interests and willingness of the users to
spend for and use the data sets. One of the key
characteristics of the fit-for-use of data is
the integratability of the datasets and capability
of the datasets to be integrated easily and justifi
ably in terms of time and expense.
The diversity in data providers creates a great
deal of inconsistency in the integration of the
datasets, including institutional, technical,
social, legal and policy heterogeneity These heterogeneities
hinder different aspects and components of a spatial
society to facilitate data flow, access and integration. |
| References |
Fonseca,
F., 2005. System Heterogeneieties Analyses of
Interoperable Geospatial Information Systems.
Hakimpour, F., 2003. Using Ontologies to Resolve
Semantic Heterogeneity for Integrating Spatial
Database Schemata, Zurich University, Zurich.
Rajabifard, A. and Williamson, I., 2004. The Integration
of Built and Natural Environmental Datasets in
National Spatial Data Infrastructure Initiatives,
Eighth United Nations Regional Cartographic Conference
for the Americas, Newyork, pp. 7.
Taylor, M.J.a.G., 2004. Data Integration Issues
for a Farm Decision Suport System. Transactions
in GIS, 8(4): 459-477.
Tsange, N.A.a.Y.L., 2005. Technical Issues in
the Integration of Built and
Natural Datasets in National SDI Initiatives,
Victorian Pilot Study, Geomatics Department of
The University of Melbourne, Melbourne.
UNRCC-AP, 1997. Resolution of the 14th UNRCC-AP.
In: U. Nations (Editor).
Vandenberg, M., 2002. TBL Victoria Scoping Study,
TBL Victoria for the Victorian State Government
– Department of Premier and Cabinet.
Willaimson, I.P., Rajabifard, A. and Feeney, M.-E.F.,
2003. Developing Spatial Data Infrastructures:
From Concept to Reality. Taylor and francis.
Young, A.J.B.a.F.R., 2005. Digital Mapping Data
Currency Through Sharing: A Practical Study, SSC2005
Spatial Intelligence, Innovation and
Praxis, Melbourne, Australia. |
| |
 |
Hossein
Mohammadi
PhD candidate, Centre for SDIs and Land
Administration,
University of Melbourne.
hosseinm@pgrad. unimelb.edu.au |
|
| |
 |
Abbas
Rajabifard
Senior Research Fellow and Deputy Director,
Centre
for SDI and Land Administration, University
of Melbourne.
abbas.r@unimelb.edu.au |
|
| |
 |
Andrew
Binns
Research Fellow, Centre for SDI
and Land Administration, University of Melbourne.
a.binns@unimelb.edu.au |
|
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Ian
P Williamson
Professor of Surveying and Land
Information, Head of Geomatics Department
and Director of Centre for SDI and Land
Administration, University of Melbourne.
ianpw@unimelb.edu.au |
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