License: 
Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.COSIT.2017.22
URN: urn:nbn:de:0030-drops-77553
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2017/7755/
Robertson, Colin ;
Feick, Rob
Defining Local Experts: Geographical Expertise as a Basis for Geographic Information Quality
Abstract
As more data are produced by location sensors, mobile devices, and online participatory processes, the field of GIScience has grappled with issues of information quality, context, and appropriate analytical approaches for data with heterogeneous and/or unknown provenance. Data quality has often been viewed through a bifurcated lens of experts and amateurs, but consideration of what the nature of geographical expertise is reveals a much more more nuanced situation. We consider how adapting frameworks from the field of studies of experience and expertise may provide a conceptual basis and methodological framework for evaluating the quality of geographic information. For contributed geographic information, quality is typically derived from a data user’s trust in and/or perception of the reputation of the data producer. Trust and reputation of producers of geographic information has typically been derived from the presence or absence of professional qualifications and training. However this framework applies exclusively to ‘crisp’ notions of data quality, and has limited utility for more subjective contributions associated with volunteered geographic information which may provide a rich source of geographic information for many applications. We hypothesize that a conceptual framework for geographical expertise may be used as the basis for assessing information quality in both formal and informal sources of geospatial data. Two case studies are used to highlight the new concepts of geographical expertise introduced in the paper.
BibTeX - Entry
@InProceedings{robertson_et_al:LIPIcs:2017:7755,
author = {Colin Robertson and Rob Feick},
title = {{Defining Local Experts: Geographical Expertise as a Basis for Geographic Information Quality}},
booktitle = {13th International Conference on Spatial Information Theory (COSIT 2017)},
pages = {22:1--22:14},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {978-3-95977-043-9},
ISSN = {1868-8969},
year = {2017},
volume = {86},
editor = {Eliseo Clementini and Maureen Donnelly and May Yuan and Christian Kray and Paolo Fogliaroni and Andrea Ballatore},
publisher = {Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
address = {Dagstuhl, Germany},
URL = {http://drops.dagstuhl.de/opus/volltexte/2017/7755},
URN = {urn:nbn:de:0030-drops-77553},
doi = {10.4230/LIPIcs.COSIT.2017.22},
annote = {Keywords: data quality, expertise, geographic information, conceptual framework}
}
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Keywords: |
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data quality, expertise, geographic information, conceptual framework |
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Collection: |
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13th International Conference on Spatial Information Theory (COSIT 2017) |
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Issue Date: |
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2017 |
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Date of publication: |
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29.08.2017 |
