2022 QUARTER 04

A B C D E F G H I J K L M N O P R S T U V W
DM-20 - Entity-based Models

As we translate real world phenomena into data structures that we can store in a computer, we must determine the most appropriate spatial representation and how it relates to the characteristics of such a phenomenon. All spatial representations are derivatives of graph theory and should therefore be described in such terms. This then helps to understand the principles of low-level GIS operations. A constraint-driven approach allows the reader to evaluate implementations of the geo-relational principle in terms of the hierarchical level of mathematical space adopted.

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)
AM-106 - Error-based Uncertainty

The largest contributing factor to spatial data uncertainty is error. Error is defined as the departure of a measure from its true value. Uncertainty results from: (1) a lack of knowledge of the extent and of the expression of errors and  (2) their propagation through analyses. Understanding error and its sources is key to addressing error-based uncertainty in geospatial practice. This entry presents a sample of issues related to error and error based uncertainty in spatial data. These consist of (1) types of error in spatial data, (2) the special case of scale and its relationship to error and (3) approaches to quantifying error in spatial data.

CP-26 - eScience, the Evolution of Science

Science—and research more broadly—face many challenges as its practitioners struggle to accommodate new challenges around reproducibility and openness.  The current practice of science limits access to knowledge, information and infrastructure, which in turn leads to inefficiencies, frustrations and a lack of rigor.  Many useful research outcomes are never used because they are too difficult to find, or to access, or to understand.

New computational methods and infrastructure provide opportunities to reconceptualize how science is conducted, how it is shared, how it is evaluated and how it is reused.  And new data sources changed what can be known, and how well, and how frequently.  This article describes some of the major themes of eScience/eResearch aimed at improving the process of doing science.

GS-12 - Ethics for Certified Geospatial Professionals

This entry discusses ethics for certified geospatial professional, focusing on the Codes of Ethics for the American Society for Photogrammetry and Remote Sensing (ASPRS) and the GIS Certification Institute (GISCI). The entry begins by defining and discussing ethics, while providing some history of the evolution of ethics in the GIS community. It then compares and contrasts the ethical guidelines of GISCI and ASPRS, including sanctions that may be imposed upon individuals who have violated their codes of ethics. The entry concludes with a discussion of how certified professionals may address situations in which their codes of ethics may conflict with their employers’ proprietary interests.

FC-36 - Events and Processes
  • Compare and contrast the concepts of continuants (entities) and occurrents (events)
  • Describe the “actor” role that entities and fields play in events and processes
  • Discuss the difficulty of integrating process models into GIS software based on the entity and field views, and methods used to do so
  • Apply or develop formal systems for describing continuous spatio-temporal processes
  • Evaluate the assertion that “events and processes are the same thing, but viewed at different temporal scales”
  • Describe particular events or processes in terms of identity, categories, attributes, and locations
  • Compare and contrast the concepts of event and process
AM-19 - Exploratory data analysis (EDA)
  • Describe the statistical characteristics of a set of spatial data using a variety of graphs and plots (including scatterplots, histograms, boxplots, q–q plots)
  • Select the appropriate statistical methods for the analysis of given spatial datasets by first exploring them using graphic methods
DC-22 - Federal agencies and national and international organizations and programs
  • Describe the data programs provided by organizations such as The National Map, GeoSpatial One Stop, and National Integrated Land System
  • Discuss the mission, history, constituencies, and activities of international organizations such as Association of Geographic Information Laboratories for Europe (AGILE) and the European GIS Education Seminar (EUGISES)
  • Discuss the mission, history, constituencies, and activities of governmental entities such as the Bureau of Land Management (BLM), United States Geological Survey (USGS) and the Environmental Protection Agency (EPA) as they related to support of professionals and organizations
  • involved in GIS&T
  • Discuss the mission, history, constituencies, and activities of GeoSpatial One Stop
  • Discuss the mission, history, constituencies, and activities of the Open Geospatial Consortium (OGC), Inc.
  • Discuss the mission, history, constituencies, and activities of the Nation Integrated Land System (NILS)
  • Discuss the mission, history, constituencies, and activities of the Federal Geographic Data Committee (FGDC)
  • Discuss the mission, history, constituencies, and activities of the National Academies of Science Mapping Science Committee
  • Discuss the mission, history, constituencies, and activities of the USGS and its National Map vision
  • Discuss the mission, history, constituencies, and activities of University Consortium of Geographic Information Science (UCGIS) and the National Center for Geographic Information and Analysis (NCGIA)
  • Discuss the political, cultural, economic, and geographic characteristics of various countries that influence their adoption and use of GIS&T
  • Identify National Science Foundation (NSF) programs that support GIS&T research and education
  • Outline the principle concepts and goals of the “digital earth” vision articulated in 1998 by Vice President Al Gore
  • Assess the current status of Gore’s “digital earth”

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