TY - JOUR
T1 - Shared data sources in the geographical domain—A classification schema and corresponding visualization techniques
AU - Mocnik, Franz Benjamin
AU - Ludwig, Christina
AU - Grinberger, A. Yair
AU - Jacobs, Clemens
AU - Klonner, Carolin
AU - Raifer, Martin
N1 - Funding Information: Funding: Franz-Benjamin Mocnik has been funded by Deutsche Forschungsgemeinschaft as part of the project A framework for measuring the fitness for purpose of OpenStreetMap data based on intrinsic quality indicators (FA 1189/3-1); Christina Ludwig and Martin Raifer, by the Klaus Tschira Stiftung; Carolin Klonner, by the Heidelberg Academy of Sciences and Humanities; and A. Yair Grinberger, by the Alexander von Humboldt Foundation. The publication has financially been supported by Deutsche Forschungsgemeinschaft within the funding programme Open Access Publishing, by the Baden-Württemberg Ministry of Science, Research and the Arts, and by Heidelberg University. Publisher Copyright: c 2019 by the authors.
PY - 2019/5/27
Y1 - 2019/5/27
N2 - People share data in different ways. Many of them contribute on a voluntary basis, while others are unaware of their contribution. They have differing intentions, collaborate in different ways, and they contribute data about differing aspects. Shared Data Sources have been explored individually in the literature, in particular OpenStreetMap and Twitter, and some types of Shared Data Sources have widely been studied, such as Volunteered Geographic Information (VGI), Ambient Geographic Information (AGI), and Public Participation Geographic Information Systems (PPGIS). A thorough and systematic discussion of Shared Data Sources in their entirety is, however, still missing. For the purpose of establishing such a discussion, we introduce in this article a schema consisting of a number of dimensions for characterizing socially produced, maintained, and used ‘Shared Data Sources,’ as well as corresponding visualization techniques. Both the schema and the visualization techniques allow for a common characterization in order to set individual data sources into context and to identify clusters of Shared Data Sources with common characteristics. Among others, this makes possible choosing suitable Shared Data Sources for a given task and gaining an understanding of how to interpret them by drawing parallels between several Shared Data Sources.
AB - People share data in different ways. Many of them contribute on a voluntary basis, while others are unaware of their contribution. They have differing intentions, collaborate in different ways, and they contribute data about differing aspects. Shared Data Sources have been explored individually in the literature, in particular OpenStreetMap and Twitter, and some types of Shared Data Sources have widely been studied, such as Volunteered Geographic Information (VGI), Ambient Geographic Information (AGI), and Public Participation Geographic Information Systems (PPGIS). A thorough and systematic discussion of Shared Data Sources in their entirety is, however, still missing. For the purpose of establishing such a discussion, we introduce in this article a schema consisting of a number of dimensions for characterizing socially produced, maintained, and used ‘Shared Data Sources,’ as well as corresponding visualization techniques. Both the schema and the visualization techniques allow for a common characterization in order to set individual data sources into context and to identify clusters of Shared Data Sources with common characteristics. Among others, this makes possible choosing suitable Shared Data Sources for a given task and gaining an understanding of how to interpret them by drawing parallels between several Shared Data Sources.
KW - Ambient Geographic Information (AGI)
KW - Conceptual space
KW - Geographical Shared Data Source (GSDS)
KW - Participatory Geographic Information (PGI)
KW - Semantics
KW - Shared Data Source (SDS)
KW - Visualization
KW - Volunteered Geographic Information (VGI)
UR - http://www.scopus.com/inward/record.url?scp=85066307681&partnerID=8YFLogxK
U2 - https://doi.org/10.3390/ijgi8050242
DO - https://doi.org/10.3390/ijgi8050242
M3 - Article
SN - 2220-9964
VL - 8
JO - ISPRS International Journal of Geo-Information
JF - ISPRS International Journal of Geo-Information
IS - 5
M1 - 242
ER -