Revisiting the ‘Is GIScience a science?’ debate (or quite possibly scientific gerrymandering)

Reitsma, Femke

doi:10.1080/13658816.2012.674529

Cited by 25 publications

(50 citation statements)

References 44 publications

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“…The ongoing debate surrounding the question of whether GIScience is a science or not is nearly as old as the field itself. Therefore, it has received much attention in literature and is a commonly discussed theme among GIScientists, who feel the need to defend their discipline to outsiders and to promote it as a justifiable field of research and teaching (Reitsma 2013). Since this issue has been recently comprehensively and, as we feel, very convincingly and appropriately addressed by F. Reitsma, we will keep this section very short and refer mainly to her line of arguments.…”

Section: Is Giscience a Science At All?mentioning

confidence: 98%

“…To determine whether GIScience is a science or not, one may look at the bounds of the term "science" itself. However, these are by no means clearly or uniformly defined, a problem which is commonly known as the "demarcation problem" (Reitsma 2013). The demarcation problem constitutes the issue of separating science from pseudo-science, anti-science, or para-science.…”

Section: Is Giscience a Science At All?mentioning

confidence: 99%

“…The demarcation problem constitutes the issue of separating science from pseudo-science, anti-science, or para-science. This problem has historically been based on the discordance of defining science based on a scientific method, as opposed to a universal set of sufficient demarcation criteria (Reitsma 2013). However, defining science based on a scientific method raises an entirely new debate as to the nature of a scientific method, which has been broadly discussed, yet has not resulted in a uniform or coherent conclusion.…”

Section: Is Giscience a Science At All?mentioning

confidence: 99%

“…Several authors have noted the advantages of multidisciplinary and interdisciplinary perspectives within the field of Geographic Information Science (Goodchild 1992(Goodchild , 2004bMark 2003;Blaschke, Strobl, et al 2012;Reitsma 2013) and within Geoinformatics. From an epistemological and from a bibliographic standpoint, however, the multidisciplinary nature of research on questions raised by GIS, the research field that will define the next generation of GIS, the body of knowledge that GIS implements, and the use of GIS as a tool for scientific research (Goodchild 2009, l. 527) may result in the fragmentation of an otherwise unified body of literature.…”

Section: Introductionmentioning

confidence: 99%

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Geographic information science as a multidisciplinary and multiparadigmatic field

Blaschke

Merschdorf

2014

Cartography and Geographic Information Science

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Despite the fact that the field of GIScience has been around for two decades, there is still little agreement as to the exact contents and boundaries of the field. Many authors have dedicated several publications concerned with defining the field, yet little consensus has been reached. Because of the highly dynamic nature of the discipline, new areas are constantly added and rigid borders may have a constraining influence on the field. On the contrary, one agreed part of the many GIScience definitions is the search for general principles, but principles for what? Can we define one field or discipline or all potential fields using geospatial information? Probably not. Therefore, rather than attempting to demarcate exact boundaries for GIScience as a discipline or a multidisciplinary field in order to prove its respectability, we herein attempt to analyze the contents of such a dynamic field on the basis of scientific literature and to assess the multidisciplinary and multiparadigmatic nature of GIScience. Such a discussion is not purely of academic nature, but also bears implications beyond academic discourse, in terms of external scientific funding and research grants. We question whether there is a "dominant" paradigmatic approach in GIScience and identify a need for adopting a multiparadigmatic view to accommodate the multifaceted nature of space, spatial representations, and the societal implications of geospatial information.

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Section: Is Giscience a Science At All?mentioning

confidence: 98%

Section: Is Giscience a Science At All?mentioning

confidence: 99%

Section: Is Giscience a Science At All?mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Geographic information science as a multidisciplinary and multiparadigmatic field

Blaschke

Merschdorf

2014

Cartography and Geographic Information Science

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“…Bridging the gap between the virtual world and the reality, GIS data model is also regarded as the core of geographic information sciences (Reitsma, 2013). Spatial concept models involve the information of spatial objects about geometry, relation, topology, semantics, attributes, etc., of which, the core issue lies in the effective and efficient representation of geometry (Zlatanova and Tempfli, 2000).…”

Section: Introductionmentioning

confidence: 99%

A ubiquitous knowledgeable data representation model (UKRM) for three-dimensional geographic information systems (3D GIS)

Zhang

Zhou

Zhang

et al. 2016

Sci. China Earth Sci.

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In the face of complicated, diversified three-dimensional world, the existing 3D GIS data models suffer from certain issues such as data incompatibility, insufficiency in data representation and representation types, among others. It is often hard to meet the requirements of multiple application purposes (users) related to GIS spatial data management and data query and analysis, especially in the case of massive spatial objects. In this study, according to the habits of human thinking and recognition, discrete expressions (such as discrete curved surface (DCS), and discrete body (DB)) were integrated and two novel representation types (including function structure and mapping structure) were put forward. A flexible and extensible ubiquitous knowledgeable data representation model (UKRM) was then constructed, in which structurally heterogeneous multiple expressions (including boundary representation (B-rep), constructive solid geometry (CSG), functional/parameter representation, etc.) were normalized. GIS's ability in representing the massive, complicated and diversified 3D world was thus greatly enhanced. In addition, data reuse was realized, and the bridge linking static GIS to dynamic GIS was built up. Primary experimental results illustrated that UKRM was overwhelmingly superior to the current data models (e.g. IFC, CityGML) in describing both regular and irregular spatial objects.

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T obler's First Law of Geography

Waters

2018

International Encyclopedia of Geography

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Tobler's first law (TFL) of geography was introduced into the geographical literature in an article that Waldo Tobler published in the journal Economic Geography in 1970. In this article, which described a simulation of population growth in Detroit, Tobler stated that to make his model operational he would “invoke the first law of geography: everything is related to everything else, but near things are more related than distant things.” This entry considers whether TFL is an accurate description of the real world. Specifically, it considers the following questions: Is TFL really a law and, if so, is it the most important law in geography? Do modern spatial interpolation techniques allow the model to be operationalized? How can “near” and “distant” be measured? Is it true for Euclidean and network space? Do classic models of human and urban geography conform to TFL?

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Revisiting the ‘Is GIScience a science?’ debate (or quite possibly scientific gerrymandering)

Cited by 25 publications

References 44 publications

Geographic information science as a multidisciplinary and multiparadigmatic field

Geographic information science as a multidisciplinary and multiparadigmatic field

A ubiquitous knowledgeable data representation model (UKRM) for three-dimensional geographic information systems (3D GIS)

T obler's First Law of Geography

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