The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Improving Spatial Data Quality through Spatial ETL Processes
Abstract
The growing availability of spatial data related to different aspects makes managers at different levels of administration aware of the possibilities to enhance decision making processes through map visualization. Currently, the so-called location intelligence is identified as an important trend for the next-generation business intelligence solutions. However, before considering spatial data as “first-class citizens,” users that are not experts in geo-fields (e.g., cartography, surveying) should learn about possible problems that may arise while using and producing spatial data. These problems must be solved to improve spatial data quality and to increase the benefits that this data can deliver. Unfortunately, there is still a poor connection in applying scientific solutions, international standards, or technological advances for improving spatial data quality in everyday usage of this data. In this chapter, the authors refer to different problems that may exist in handling spatial data and show several examples of how these problems can be detected and solved using spatial ETL tools. Problem detection is based on a set of control parameters derived from the international standard.
Related Content
|
Dina Darwish.
© 2024.
48 pages.
|
|
Dina Darwish.
© 2024.
51 pages.
|
|
Smrity Prasad, Kashvi Prawal.
© 2024.
19 pages.
|
|
Jignesh Patil, Sharmila Rathod.
© 2024.
17 pages.
|
|
Ganesh B. Regulwar, Ashish Mahalle, Raju Pawar, Swati K. Shamkuwar, Priti Roshan Kakde, Swati Tiwari.
© 2024.
23 pages.
|
|
Pranali Dhawas, Abhishek Dhore, Dhananjay Bhagat, Ritu Dorlikar Pawar, Ashwini Kukade, Kamlesh Kalbande.
© 2024.
24 pages.
|
|
Pranali Dhawas, Minakshi Ashok Ramteke, Aarti Thakur, Poonam Vijay Polshetwar, Ramadevi Vitthal Salunkhe, Dhananjay Bhagat.
© 2024.
26 pages.
|
|
|