"Contextualized VGI" Creation and Management to Cope with Uncertainty and Imprecision

This paper investigates the causes of imprecision of the observations and uncertainty of the authors who create Volunteer Geographic Information (VGI), i.e., georeferenced contents generated by volunteers when participating in some citizen science project. Specifically, various aspects of imprecision and uncertainty of VGI are outlined and, to cope with them, a knowledge-based approach is suggested based on the creation and management of “contextualized VGI”. A case study example in agriculture is reported where contextualized VGI can be created about in situ crops observations by the use of a smart app that supports volunteers by means of both an ontology and the representation of the context of the geo-localization. Furthermore, an approach to cope with both ill-defined knowledge and volunteer’s uncertainty or imprecise observations is defined based on a fuzzy ontology with uncertainty level-based approximate reasoning. By representing uncertainty and imprecision of VGI, users, i.e., consumers, can exploit quality checking mechanisms to filter VGI based on their needs.

[1]  Robert LIN,et al.  NOTE ON FUZZY SETS , 2014 .

[2]  Umberto Straccia,et al.  The fuzzy ontology reasoner fuzzyDL , 2016, Knowl. Based Syst..

[3]  Gloria Bordogna,et al.  A Spatial Data Infrastructure Integrating Multisource Heterogeneous Geospatial Data and Time Series: A Study Case in Agriculture , 2016, ISPRS Int. J. Geo Inf..

[4]  Michael F. Goodchild,et al.  Citizens as Voluntary Sensors: Spatial Data Infrastructure in the World of Web 2.0 , 2007, Int. J. Spatial Data Infrastructures Res..

[5]  David Fairbairn,et al.  Assessing the accuracy of 'crowdsourced' data and its integration with official spatial data sets , 2010 .

[6]  Gloria Bordogna,et al.  On predicting and improving the quality of Volunteer Geographic Information projects , 2016, Int. J. Digit. Earth.

[7]  S. V. Ronzhin,et al.  Semantic enrichment of Volunteered Geographic Information using Linked Data: a use case scenario for disaster management , 2015 .

[8]  D. Richards,et al.  Ontology construction and concept reuse with formal concept analysis for improved web document retrieval , 2007, Web Intell. Agent Syst..

[9]  Umberto Straccia,et al.  A fuzzy description logic for the semantic web , 2006, Fuzzy Logic and the Semantic Web.

[10]  Jens Lehmann,et al.  LinkedGeoData: A core for a web of spatial open data , 2012, Semantic Web.

[11]  Umberto Straccia,et al.  Towards a Fuzzy Description Logic for the Semantic Web (Preliminary Report) , 2005, ESWC.

[12]  G. Bordogna,et al.  Semantic Interoperability of Volunteered Geographic Information based on Contextual Knowledge , 2016 .

[13]  Gloria Bordogna,et al.  Modeling linguistic qualifiers of uncertainty in a fuzzy database , 2000, Int. J. Intell. Syst..

[14]  Gloria Bordogna,et al.  Customizable Flexible Querying in Classical Relational Databases , 2008, Handbook of Research on Fuzzy Information Processing in Databases.

[15]  Ojs Jki,et al.  Growth stages of mono-and dicotyledonous plants , 2010 .

[16]  Thomas R. Gruber,et al.  Toward principles for the design of ontologies used for knowledge sharing? , 1995, Int. J. Hum. Comput. Stud..

[17]  Schade Sven,et al.  Survey report: data management in Citizen Science projects , 2016 .

[18]  Sebastian Rudolph,et al.  Foundations of Semantic Web Technologies , 2009 .

[19]  Alexander Zipf,et al.  Semantic Interoperability of Sensor Data with Volunteered Geographic Information: A Unified Model , 2013, ISPRS Int. J. Geo Inf..

[20]  Martinez Jimena Semantic integration of authoritative and VGI , 2013 .

[21]  Umberto Straccia,et al.  All About Fuzzy Description Logics and Applications , 2015, Reasoning Web.

[22]  M. Haklay Citizen Science and Volunteered Geographic Information: Overview and Typology of Participation , 2013 .

[23]  Thomas J. Stohlgren,et al.  Assessing citizen science data quality: an invasive species case study , 2011 .

[24]  Scott Freundschuh,et al.  Assessing uncertainty in VGI for emergency response , 2014 .