- Describe an application in which it is crucial to maintain previous versions of the database
- Describe existing algorithms designed for performing dynamic queries
- Demonstrate how both the time criticality and the data security might determine whether one performs change detection on-line or off-line in a given scenario
- Explain why the lack of a data librarian to manage data can have disastrous consequences on the resulting dataset
- Produce viable queries for change scenarios using GIS or database management tools
Data management involves the theories and techniques for managing the entire data lifecycle, from data collection to data format conversion, from data storage to data sharing and retrieval, to data provenance, data quality control and data curation for long-term data archival and preservation.
Topics in this Knowledge Area are listed thematically below. Existing topics are in regular font and linked directly to their original entries (published in 2006; these contain only Learning Objectives). Entries that have been updated and expanded are in bold. Forthcoming, future topics are italicized.