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Granular Computing
Erschienen in: Granular Computing 3/2016

01.09.2016 | Original Paper

Granular computing as a basis of human–data interaction: a cognitive cities use case

verfasst von: Gwendolin Wilke, Edy Portmann

Erschienen in: Granular Computing | Ausgabe 3/2016

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Abstract

The article proposes granular computing as a theoretical, formal and methodological basis for the newly emerging research field of human–data interaction (HDI). We argue that the ability to represent and reason with information granules is a prerequisite for data legibility. As such, it allows for extending the research agenda of HDI to encompass the topic of collective intelligence amplification, which is seen as an opportunity of today’s increasingly pervasive computing environments. As an example of collective intelligence amplification in HDI, we introduce a collaborative urban planning use case in a cognitive city environment and show how an iterative process of user input and human-oriented automated data processing can support collective decision making. As a basis for automated human-oriented data processing, we use the spatial granular calculus of granular geometry.
Vorheriger Artikel Solving equations (and systems of equations) under uncertainty: how different practical problems lead to different mathematical and computational formulations
Nächster Artikel Semi-greedy heuristics for feature selection with test cost constraints

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Fußnoten
6
With it, of course, comes the ever more pressing issue of data privacy, as discussed as a main challenge of HDI by Mortier et al. (2014).
 
7
An example for defective geometric reasoning with exact representatives in GIS is given by Wilke (2012) and Wilke and Frank (2010c). She proposes to augment exact reasoning with representatives by a simplified granular calculus that only propagates granule sizes as a measure of worst case error.
 
8
e.g., by assuming a suitable underlying topology in a dual point space, cf. Wilke (2012).
 
10
Notice here, that it would be sensible to use a granular geometry that supports fuzzy position granules, instead of crisp position granules. In this case, we could specify a fuzzy diameter for typical dwarf fruit trees.
 
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Metadaten
Titel
Granular computing as a basis of human–data interaction: a cognitive cities use case
verfasst von
Gwendolin Wilke
Edy Portmann
Publikationsdatum
01.09.2016
Verlag
Springer International Publishing
Erschienen in
Granular Computing / Ausgabe 3/2016
Print ISSN: 2364-4966
Elektronische ISSN: 2364-4974
DOI
https://doi.org/10.1007/s41066-016-0015-4