2020 QUARTER 01

A B C D E F G H I K L M N O P R S T U V W

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

Distance is a central concept in geography, and consequently, there are various types of operations that leverage the concept of distance. This short article introduces common distance measures, the purpose of distance operations, different types of operations and considerations, as well as sample applications in the physical and social domains. Distance operations can be performed on both vector or raster data, but the operations and results may differ. While performing distance operations, it is important to remember how distance is conceptualized while performing the operation.

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

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

Epistemology is the lens through which we view reality. Different epistemologies interpret the earth and patterns on its surface differently. In effect, epistemology is a belief system about the nature of reality that, in turn, structures our interpretation of the world. Common epistemologies in GIScience include (but are not limited by) positivism and realism. However, many researchers are in effect pragmatists in that they choose the filter that best supports their work and a priori hypotheses. Different epistemologies – or ways of knowing and studying geography – result in different ontologies or classification systems. By understanding the role of epistemology, we can better understand different ways of representing the same phenomena.

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