Good Enough? Nichesourcing in Data Quality Assessment. Lopez-Pellicer, F. J. & Barrera, J. IEEE Earthzine, 7(4):910203+, 2014.
abstract   bibtex   
It is tempting to integrate crowdsourced data into our databases for identifying a data quality issue (e.g., '' is my Earth observation data still valid?''). Here we present a use case developed during the Linked Map project (part of the EU FP7 project PlanetData) named '' nichesourcing of data quality assessment.'' In this use case, a small group of expert volunteers assessed if the quality of a conflation of data sourced from an official national map (the BTN25, a National Map database of Spain) and a volunteered geographic information (VGI) dataset (the OpenStreetMap database) is good enough using a crowdsourcing approach. We learned that '' good enough'' is a tricky concept especially when the crowd has a known face and can influence you.
@article{lopez-pellicerGoodEnoughNichesourcing2014,
  title = {Good Enough? {{Nichesourcing}} in Data Quality Assessment},
  author = {{Lopez-Pellicer}, Francisco J. and Barrera, Jesus},
  year = {2014},
  volume = {7},
  pages = {910203+},
  abstract = {It is tempting to integrate crowdsourced data into our databases for identifying a data quality issue (e.g., '' is my Earth observation data still valid?''). Here we present a use case developed during the Linked Map project (part of the EU FP7 project PlanetData) named '' nichesourcing of data quality assessment.'' In this use case, a small group of expert volunteers assessed if the quality of a conflation of data sourced from an official national map (the BTN25, a National Map database of Spain) and a volunteered geographic information (VGI) dataset (the OpenStreetMap database) is good enough using a crowdsourcing approach. We learned that '' good enough'' is a tricky concept especially when the crowd has a known face and can influence you.},
  journal = {IEEE Earthzine},
  keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-13491979,crowd-sourcing,data-uncertainty,featured-publication,niche-sourcing,participatory-modelling},
  lccn = {INRMM-MiD:c-13491979},
  number = {4}
}

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