2016 QUARTER 02

A B C D E F G H I K L M N O P R S T U V W
GC2-2 - Computational intelligence
  • Describe computational intelligence methods that may apply to GIS&T
  • Exemplify the potential for machine learning to expand performance of specialized geospatial analysis functions
  • Identify artificial intelligence tools that may be useful for GIS&T
  • Describe a hypothesis space that includes searches for optimality of solutions within that space
CV5-1 - Computational issues in cartography and visualization
  • Explain how the concept “digital cartographic models” unifies a number of principles for computer cartography
  • Identify areas in cartography and visualization that have, and those that have not, advanced because of computational approaches
  • Explain how the rise of interoperability and open standards has affected the production of cartographic representations and visualizations
  • Explain how optimization techniques are improving the automated design of maps
  • Describe the structure and function of geographic names databases (i.e., gazetteer) for use in mapping
  • Differentiate between GIS and graphics software tools for mapping and those for visualization purposes
DA6-4 - Computer-Aided Software Engineering (CASE) tools
  • Use CASE tools to design geospatial software
  • Evaluate available CASE tools for their appropriateness for a given development task
DA4-2 - Conceptual model
  • Define entities and relationships as used in conceptual data models
  • Create a conceptual model diagram of data needed in a geospatial application or enterprise database
  • Design application-specific conceptual models
  • Deconstruct an application use case into conceptual components
  • Explain the objectives of the conceptual modeling phase of design
  • Describe the degree to which attributes need to be modeled in the conceptual modeling phase
GD12-2 - Content standards
  • Differentiate between a controlled vocabulary and an ontology
  • Describe a domain ontology or vocabulary (i.e., land use classification systems, surveyor codes, data dictionaries, place names, or benthic habitat classification system)
  • Describe how a domain ontology or vocabulary facilitates data sharing
  • Define “thesaurus” as it pertains to geospatial metadata
  • Describe the primary focus of the following content standards: FGDC, Dublin Core Metadata Initiative, and ISO 19115
  • Differentiate between a content standard and a profile
  • Describe some of the profiles created for the Content Standard for Digital Geospatial Metadata (CSDGM)
GS1-2 - Contract law
  • Differentiate “contracts for service” from “contracts of service”
  • Discuss potential legal problems associated with licensing geospatial information
  • Identify the liability implications associated with contracts
DN1-6 - Coordinate transformations
  • Cite appropriate applications of several coordinate transformation techniques (e.g., affine, similarity, Molodenski, Helmert)
  • Describe the impact of map projection transformation on raster and vector data
  • Differentiate between polynomial coordinate transformations (including linear) and rubbersheeting
DA5-3 - Coupling scientific models with GIS
  • Discuss the current state-of-the-art of the coupling of scientific models and simulations with GIS
  • Design a modeling procedure to integrate a spatial arrangement constraint for a mathematical optimization model
CF2-6 - Cultural influences
  • Collaborate effectively with colleagues of differing social backgrounds in developing balanced GIS applications
  • Describe the ways in which the elements of culture (e.g., language, religion, education, traditions) may influence the understanding and use of geographic information
  • Recognize the impact of one’s social background on one’s own geographic worldview and perceptions and how it influences one’s use of GIS
CV2-2 - Data abstraction: classification, selection, and generalization
  • Discuss advantages and disadvantages of various data classification methods for choropleth mapping, including equal interval, quantiles, mean-standard deviation, natural breaks, and “optimal” methods
  • Explain why the reduction of map scale sometimes results in the need for mapped features to be reduced in size and moved
  • Identify mapping tasks that require each of the following: smoothing, aggregation, simplification, and displacement
  • Illustrate specific examples of feature elimination and simplification suited to mapping at smaller scales
  • Demonstrate how different classification schemes produce very different maps from a single set of interval- or ratio-level data
  • Apply appropriate selection criteria to change the display of map data to a smaller scale
  • Write algorithms to perform equal interval, quantiles, mean-standard deviation, natural breaks, and “optimal” classification for choropleth mapping
  • Discuss the limitations of current technological approaches to generalization for mapping purposes
  • Explain how generalization of one data theme can and must be reflected across multiple themes (e.g., if the river moves, the boundary, roads and towns also need to move)
  • Explain how the decisions for selection and generalization are made with regard to symbolization in mapping

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