Infrastructure Engineering - Research Publications
Permanent URI for this collection
Search Results
1 - 4 of 4
-
ItemSpatial Data Integration Challenges: Australian Case Studies(Spatial Sciences Institute, 2007)
-
ItemBridging SDI design gaps(Centre of Geo-Information Technologies (cGIT), 2006)The environment we inhabit is integrated and to properly manage the environment it is necessary to look at all environmental components and making multi-criteria decision about environment mostly needs an integrated view of built and natural environmental components to better interpret it.Despite the integrated nature of environment and requirements of users to integrate different components of environment, information about different elements of environment is being collected and managed by fragmented agencies under different and mostly inconsistent policies and standards to satisfy their own needs –for a single discipline- with little attention to the broad range of users – a multi-disciplinary approach. This fragmentation results in heterogeneity of technical and non-technical issues surrounding integration of datasets.An SDI is an initiative to facilitate the cooperation among all stakeholders and the interaction with standards and technological components and one of its objectives is to facilitate the integration of multi-source spatial data sets.This paper aims to address different issues connected to the integration of multi-source data sets in order to better serve different communities through their SDI initiatives and also a better management and sharing of their spatial data. The paper aims to discuss both technical and non-technical issues related to the integration of multi-source data sets in alignment with an ongoing research project devoted to developing models, guidelines and associated tools to facilitate the integration of multi-source datasets within an SDI.
-
ItemThe development of a frameworkand associated tools for the integration ofmulti-sourced spatial datasets( 2006)The world of today heavily relies on spatial data to manage the natural and built environments.Monitoring and controlling the impact of human activities on environment and the impact of naturalenvironment changes (including natural hazards) on built environment is a major policy driver formany jurisdictions. The mitigation of natural hazards including tsunami, earthquake and landslide andsecuring citizens against them has become another priority of nations , especially after Indonesia’stsunami. September 11 was also a remarkable point in history which attracts attentions towardsproviding more efficient counter-terrorism initiatives to secure citizens.In many countries meeting sustainable development objectives including social cohesion andenvironment protection together with economical growth is the most overwhelming policy driver. Inthese countries most of legislations and decisions are made, if they meet sustainable developmentobjectives.All above mentioned activities try to control the natural and built environments and monitor theimpacts of one environment on the other one. To control and monitor built and natural environments,the components of these environments need to be integrated to provide the factual model of realworld. Effective access and use of spatial data has been addressed by developing SDIs (Spatial DataInfrastructures) which one of its objectives is to address and provide requirements for effective dataintegration.The effective integration of built and natural environmental datasets is an ultimate goal of manyspatial decision making systems which has not been fully achieved, however technical integration andinteroperability of multi-sourced spatial data have received much attention. The integration of multisourcedspatial data due to the diversity of data providers needs more than technical tools andconsiderations. Institutional, social, legal and policy requirements must also be taken intoconsideration in order to achieve effective integratio
-
ItemGeo-web service tool for spatial data integrability( 2008)The integration of multi-source heterogeneous spatial data is one of the major challenges for many spatial data users. Users put much effort to identify and overcome inconsistency among data sets through a time-consuming and costly process. Spatial applications that rely on multi-source heterogeneous data also suffer from the lack of automatic mechanism to identify the inconsistency items and assign an appropriate solution for any particular item. An effective integration necessitates the identification of the inconsistency among data sets and the provision of necessary standards and guidelines in order to overcome the inconsistency, and then data sets can be manipulated based on the guidelines and proposed solutions.The paper follows two main streams. Firstly, the results of a number of case studies which have been conducted in order to identify the issues and challenges of spatial data integration are discussed. Then based on identified issues the design and development of a validation tool is discussed. The tool has been designed based on an approach which is presented in the paper. The tool aims to investigate multi-sourced spatial data and identify the items of inconsistency. The tool also proposes available guidelines to overcome the inconsistency. This tool can help practitioners and organizations to avoid the time-consuming and costly process of validating data sets for effective data integration.