All Topics

DM-20 - Discrete entities
  • Discuss the human predilection to conceptualize geographic phenomena in terms of discrete entities
  • Compare and contrast differing epistemological and metaphysical viewpoints on the “reality” of geographic entities
  • Identify the types of features that need to be modeled in a particular GIS application or procedure
  • Identify phenomena that are difficult or impossible to conceptualize in terms of entities
  • Describe the difficulties in modeling entities with ill-defined edges
  • Describe the difficulties inherent in extending the “tabletop” metaphor of objects to the geographic environment
  • Evaluate the effectiveness of GIS data models for representing the identity, existence, and lifespan of entities
  • Justify or refute the conception of fields (e.g., temperature, density) as spatially-intensive attributes of (sometimes amorphous and anonymous) entities
  • Model “gray area” phenomena, such as categorical coverages (a.k.a. discrete fields), in terms of objects
  • Evaluate the influence of scale on the conceptualization of entities
  • Describe the perceptual processes (e.g., edge detection) that aid cognitive objectification
  • Describe particular entities in terms of space, time, and properties
FC-14 - Distance, Length, and Direction
  • Describe several different measures of distance between two points (e.g., Euclidean, Manhattan, network distance, spherical)
  • Explain how different measures of distance can be used to calculate the spatial weights matrix
  • Explain why estimating the fractal dimension of a sinuous line has important implications for the measurement of its length
  • Explain how fractal dimension can be used in practical applications of GIS
  • Explain the differences in the calculated distance between the same two places when data used are in different projections
  • Outline the implications of differences in distance calculations on real world applications of GIS, such as routing and determining boundary lengths and service areas
  • Estimate the fractal dimension of a sinuous line
  • Describe operations that can be performed on qualitative representations of direction
  • Explain any differences in the measured direction between two places when the data are presented in a GIS in different projections
  • Compute the mean of directional data
  • Compare and contrast how direction is determined and stated in raster and vector data
  • Define “direction” and its measurement in different angular measures
KE-13 - Economics and the role of information
  • Discuss the general role of information in economics
  • Describe the role of economics in the use of geospatial information
  • Describe the role of economics in public and private production of geospatial information
GS-09 - Enforcing control
  • Explain the concept of “fair use” with regard to geospatial information
  • Describe defenses against various claims of copyright infringement
  • Discuss ways in which copyright infringements may be remedied
  • Identify types of copyright infringement
CP-29 - Enterprise GIS

Enterprise GIS is the implementation of GIS infrastructure, processes and tools at scale within the context of an organization, shaped by the prevailing information technology patterns of the day. It can be framed as an infrastructure enabling a set of capabilities, and a process for establishing and maintaining that infrastructure. Enterprise GIS facilitates the storage, sharing and dissemination of geospatial information products (data, maps, apps) within an organization and beyond. Enterprise GIS is integrated into, and shaped by the business processes, culture and context of an organization. Enterprise GIS implementations require general-purpose IT knowledge in the areas of performance tuning, information security, maintenance, interoperability, and data governance. The specific enabling technologies of Enterprise GIS will change with time, but currently the prevailing pattern is a multi-tiered services-oriented architecture supporting delivery of GIS capabilities on the web, democratizing access to and use of geospatial information products.

GS-13 - Epistemological critiques

As GIS became a firmly established presence in geography and catalysed the emergence of GIScience, it became the target of a series of critiques regarding modes of knowledge production that were perceived as problematic. The first wave of critiques charged GIS with resuscitating logical positivism and its erroneous treatment of social phenomena as indistinguishable from natural/physical phenomena. The second wave of critiques objected to GIS on the basis that it was a representational technology. In the third wave of critiques, rather than objecting to GIS simply because it represented, scholars engaged with the ways in which GIS represents natural and social phenomena, pointing to the masculinist and heteronormative modes of knowledge production that are bound up in some, but not all, uses and applications of geographic information technologies. In response to these critiques, GIScience scholars and theorists positioned GIS as a critically realist technology by virtue of its commitment to the contingency of representation and its non-universal claims to knowledge production in geography. Contemporary engagements of GIS epistemologies emphasize the epistemological flexibility of geospatial technologies.

FC-02 - Epistemology
  • Explain the notions of model and representation in science
  • Identify the epistemological assumptions underlying the work of colleagues
  • Bridge the differences in epistemological viewpoints to enable work with diverse colleagues
  • Define common theories on what constitutes knowledge, including positivism, reflectance-correspondence, pragmatism, social constructivism, and memetics
  • Justify the epistemological frameworks with which you agree
  • Recognize the influences of epistemology on GIS practices
  • Compare and contrast the ability of various theories to explain different situations
FC-25 - Error
  • Compare and contrast how systematic errors and random errors affect measurement of distance
  • Describe the causes of at least five different types of errors (e.g., positional, attribute, temporal, logical inconsistency, and incompleteness)
DM-32 - Error-based uncertainty
  • Define uncertainty-related terms, such as error, accuracy, uncertainty, precision, stochastic, probabilistic, deterministic, and random
  • Recognize expressions of uncertainty in language
  • Evaluate the causes of uncertainty in geospatial data
  • Describe a stochastic error model for a natural phenomenon
  • Explain how the familiar concepts of geographic objects and fields affect the conceptualization of uncertainty
  • Recognize the degree to which the importance of uncertainty depends on scale and application
  • Differentiate uncertainty in geospatial situations from vagueness
DM-69 - Exchange specifications
  • Describe the characteristics of the Geography Markup Language (GML)
  • Explain the purpose, history, and status of the Spatial Data Transfer Standard (SDTS)
  • Identify different levels of information integration
  • Identify the level of integration at which the Geography Markup Language (GML) operates
  • Describe the geospatial elements of Earth science data exchange specifications, such as the Ecological Metadata Language (EML), Earth Science Markup Language (ESML), and Climate Science Modeling Language (CSML)
  • Import data packaged in a standard transfer format to a GIS software package
  • Export data from a GIS program to a standard exchange format