TY - GEN
T1 - Maturity assessment and strategy to improve master data management of geospatial data case study
T2 - 5th International Conference on Science and Technology, ICST 2019
AU - Rishartati, Peny
AU - Rahayuningtyas, Nia Dwi
AU - Maulina, Joanita
AU - Adetia, Aisha
AU - Ruldeviyani, Yova
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/7
Y1 - 2019/7
N2 - Geospatial data is important in supporting census and survey in Statistics Indonesia. Some problems exist about it are inaccurate maps, the existence of incomplete data attribute, and there are many versions exist in silo systems. They can impact the result of census or survey data quality. Improvement applied to overcome problems is managing geospatial data by adopting geodatabase. To improve the application in the future, it needs to be evaluated. By the reason, this research aims to measure the maturity level of master data management of geospatial data and arrange strategy to improve master data management of geospatial data in the future. This research used Master Data Management Maturity Model to measure the level of maturity and mapped the result to reference and master data management activity of Data Management Body of Knowledge. The result is Statistics Indonesia has not achieved any level yet for geospatial master data management and must concern to apply five activities for improvement in the future namely are to understand reference and master data integration needs, to identify reference and master data sources and contributors, to define and maintain the data integration architecture, to define and maintain match rules, and to establish golden record.
AB - Geospatial data is important in supporting census and survey in Statistics Indonesia. Some problems exist about it are inaccurate maps, the existence of incomplete data attribute, and there are many versions exist in silo systems. They can impact the result of census or survey data quality. Improvement applied to overcome problems is managing geospatial data by adopting geodatabase. To improve the application in the future, it needs to be evaluated. By the reason, this research aims to measure the maturity level of master data management of geospatial data and arrange strategy to improve master data management of geospatial data in the future. This research used Master Data Management Maturity Model to measure the level of maturity and mapped the result to reference and master data management activity of Data Management Body of Knowledge. The result is Statistics Indonesia has not achieved any level yet for geospatial master data management and must concern to apply five activities for improvement in the future namely are to understand reference and master data integration needs, to identify reference and master data sources and contributors, to define and maintain the data integration architecture, to define and maintain match rules, and to establish golden record.
KW - DMBOK
KW - Geospatial data
KW - Master Data Management
KW - Maturity Model
UR - http://www.scopus.com/inward/record.url?scp=85091340430&partnerID=8YFLogxK
U2 - 10.1109/ICST47872.2019.9166400
DO - 10.1109/ICST47872.2019.9166400
M3 - Conference contribution
AN - SCOPUS:85091340430
T3 - Proceedings - 2019 5th International Conference on Science and Technology, ICST 2019
BT - Proceedings - 2019 5th International Conference on Science and Technology, ICST 2019
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 30 July 2019 through 31 July 2019
ER -
