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Towards provenance-aware geographic information systems
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Geographic Information Systems archive
Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems table of contents
Irvine, California
POSTER SESSION: Poster session table of contents
Article No. 70  
Year of Publication: 2008
ISBN:978-1-60558-323-5
Authors
Shaowen Wang  University of Illinois at Urbana Champaign
Anand Padmanabhan  University of Illinois at Urbana Champaign
James D. Myers  University of Illinois at Urbana Champaign
Wenwu Tang  University of Illinois at Urbana Champaign
Yong Liu  University of Illinois at Urbana Champaign
Sponsors
: Google
: Oak Ridge National Laboratory
: ESRI
Microsoft : Microsoft
Publisher
ACM  New York, NY, USA
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ABSTRACT

GIS (Geographic Information Systems) play an important role to acquire and communicate geospatial knowledge based on spatial data and the use of spatial analysis, modeling, and visualization. The assurance of the validity and quality of spatial data handling and analysis remains a great challenge, in part, because of sophisticated procedures are often required for collaborative geospatial problem-solving and decision making. These procedures, when specified as knowledge derivation workflows, require carefully configured parameters and spatiotemporal specifications guided by specific contexts and purposes. The information of spatial data lineage and related analysis workflow is defined as spatial provenance in this research. Such information is often not well recorded or managed during spatial data handling and related analysis. This paper presents a provenance-aware GIS architecture that incorporates spatial provenance to address this shortcoming and facilitate the assurance of validity and quality of spatial data handling and analysis. Spatial provenance in this architecture is generated and managed to allow queries on data lineage and workflow information to support geospatial problem-solving. Basic elements of spatial provenance are captured using a spatial provenance model. The illustration of the provenance-aware GIS architecture and its proof-of-concept implementation reveals the similarity and difference in the use of spatial provenance in GIS applications. Overall, the architecture and implementation described in the paper demonstrates the necessity and feasibility of introducing provenance into GIS.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Shaowen Wang: colleagues
Anand Padmanabhan: colleagues
James D. Myers: colleagues
Wenwu Tang: colleagues
Yong Liu: colleagues