Data Management

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 linked directly to either their original (2006) or revised entries; forthcoming, future topics are italicized. 


Database Management Systems Events and Processes Plane Coordinate Systems
Data Retrieval Strategies Fields in Space & Time Tessellated Referencing Systems
Relational DBMS Integrated Models Linear Referencing
Extensions of the Relational Model Mereology: Structural Relationships Linear Referencing Systems
Object-oriented Spatial Databases Geneaological Relationships: Lineage, Inheritance Vertical Datums
Spatio-temporal GIS Topological Relationships Horizontal Datums
Database Change Modeling Tools Map Projection Properties
Modeling Database Change Conceptual Data Models Map Projection Classes
Managing Versioned Geospatial Databases Logical Data Models Map Projection Parameters
Reconciling Database Change Physical Data Models  
Data Warehouses Fuzzy Logic Georegistration
Ongoing GIS Revision Grid Compression Methods Systematic Georefencing Systems
Database Administration   Unsystematic Georeferencing Systems
Spatial Data Models   Spatial Data Infrastructure
Basic Data Structures Spatial Data Quality Spatial Data Infrastructures
Grid Representations Spatial Data Uncertainty Content Standards
The Raster Model Error-based Uncertainty Metadata
The Hexagonal Model Modeling Uncertainty Adoption of Standards
The Triangulated Irregular Network (TIN) Model Vagueness  
Hierarchical Data Models Mathemematical Models of Vaguness: Fuzzy Sets and Rough Sets  
Classical Vector Data Models    
The Topological Model Georeferencing Systems  
The Spaghetti Model History of Understanding Earth's Shape  
The Network Model Approximating the Geoid with Spheres & Ellipsoids  
Discrete Entities Approximating the Earth's Shape with Geoids  
Modeling 3D Entities The Geographic Coordinate System  


DM-40 - Managing versioned geospatial databases
  • 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
DM-54 - Map projection classes
  • Explain the concepts “developable surface” and “reference globe” as ways of projecting the Earth’s surface
  • Explain the mathematical basis by which latitude and longitude locations are projected into x and y coordinate space
  • Illustrate the graticule configurations for “other” projection classes, such as polyconic, pseudocylindrical, etc.
  • Classify various map projection types according to the geometric properties preserved
  • Classify various map projection types by the three main classes of map projections based on developable surfaces
DM-55 - Map projection parameters
  • Explain how the concepts of the tangent and secant cases relate to the idea of a standard line
  • Implement a given map projection formula in a software program that reads geographic coordinates as input and produces projected (x, y) coordinates as output
  • Identify the parameters that allow one to focus a projection on an area of interest
  • Use GIS software to produce a graticule that matches a target graticule
  • Identify the possible “aspects” of a projection and describe the graticule’s appearance in each aspect
  • Define key terms such as “standard line,” “projection case,” and “latitude and longitude of origin”
DM-53 - Map projection properties
  • Describe the visual appearance of the Earth’s graticule
  • Discuss what a Tissot indicatrix represents and how it can be used to assess projection-induced error
  • Interpret a given a projected graticule, continent outlines, and indicatrixes at each graticule intersection in terms of geometric properties preserved and distorted
  • Illustrate distortion patterns associated with a given projection class
  • Recognize distortion patterns on a map based upon the graticule arrangement
  • Explain the kind of distortion that occurs when raster data are projected
  • Explain the rationale for the selection of the geometric property that is preserved in map projections used as the basis of the UTM and SPC systems
  • Recommend the map projection property that would be useful for various mapping applications, including parcel mapping, route mapping, etc., and justify your recommendations
  • Define the four geometric properties of the globe that may be preserved or lost in projected coordinates
  • Explain the concept of a “compromise” projection and for which purposes it is useful
DM-31 - Mathematical models of vagueness: Fuzzy sets and rough sets
  • Compare and contrast the relative merits of fuzzy sets, rough sets, and other models
  • Differentiate between fuzzy set membership and probabilistic set membership
  • Explain the problems inherent in fuzzy sets
  • Create appropriate membership functions to model vague phenomena
DM-26 - Mereology: structural relationships
  • Describe particular geographic phenomena in terms of their place in mereonomic hierarchies (parts and composites)
  • Explain the contributions of formal mathematical methods such as graph theory to the study and application of geographic structures
  • Represent structural relationships in GIS data
  • Explain the effects of spatial or temporal scale on the perception of structure
  • Explain the modeling of structural relationships in standard GIS data models, such as stored topology
  • Identify phenomena that are best understood as networks
DM-57 - Metadata
  • Define “metadata” in the context of the geospatial data set
  • Use a metadata utility to create a geospatial metadata document for a digital database you created
  • Formulate metadata for a graphic output that would be distributed to the general public
  • Formulate metadata for a geostatistical analysis that would be released to an experienced audience
  • Compose data integrity statements for a geostatistical or spatial analysis to be included in graphic output
  • Identify software tools available to support metadata creation
  • Interpret the elements of an existing metadata document
  • Explain why metadata production should be integrated into the data production and database development workflows, rather than treated as an ancillary activity
  • Outline the elements of the U.S. geospatial metadata standard
  • Explain the ways in which metadata increases the value of geospatial data
DM-38 - Modeling database change
  • Describe techniques for managing long transactions in a multi-user environment
  • Describe techniques for handling version control in spatial databases
  • Define a set of rules for modeling changes in spatial databases
  • Explain why logging and rollback techniques are adequate for managing “short transactions”
DM-21 - Modeling three-dimensional (3-D) entities
  • Identify GIS application domains in which true 3-D models of natural phenomena are necessary
  • Illustrate the use of Virtual Reality Modeling Language (VRML) to model landscapes in 3-D
  • Explain how octatrees are the 3-D extension of quadtrees
  • Explain how voxels and stack-unit maps that show the topography of a series of geologic layers might be considered 3-D extensions of field and vector representations respectively
  • Explain how 3-D models can be extended to additional dimensions
  • Explain the use of multi-patching to represent 3-D objects
  • Explain the difficulties in creating true 3-D objects in a vector or raster format
  • Differentiate between 21/2-D representations and true 3-D models
DM-33 - Modeling tools
  • Compare and contrast the relative merits of various textual and graphical tools for data modeling, including E-R diagrams, UML, and XML
  • Create E-R and UML diagrams of database designs
  • Create conceptual, logical, and physical data models using automated software tools