With the advent of collaborative Web 2.0, spatial data creation is no more exclusively in the hands of professionals. For example, linked open data (LOD) promotes a new paradigm for online and freely accessible spatial information. Noteworthy initiatives in this direction are Geonames and OpenStreetMap. Moreover, as cities are continuously changing and growing, Points of Interest (POIs) are no more historical and their descriptions have to be updated frequently. One appropriate solution is to encourage participation of voluntary on-site experts to the process of information gathering and updating. In this context, we propose a human-enhanced framework, based on linked data principles and technologies, and devoted to collect, organize and rank user-generated corrections and completions in order to improve the accuracy and completeness of Geo-spatial LOD. Metrics have been defined for both human contributors and contents in order to estimate their reliability. The generated data introduces an additional linked data layer for hosting the revised version of the original datasets.
A Human-enhanced Framework for Assessing Open Geo-spatial Data
MELCHIORI, Michele
2014-01-01
Abstract
With the advent of collaborative Web 2.0, spatial data creation is no more exclusively in the hands of professionals. For example, linked open data (LOD) promotes a new paradigm for online and freely accessible spatial information. Noteworthy initiatives in this direction are Geonames and OpenStreetMap. Moreover, as cities are continuously changing and growing, Points of Interest (POIs) are no more historical and their descriptions have to be updated frequently. One appropriate solution is to encourage participation of voluntary on-site experts to the process of information gathering and updating. In this context, we propose a human-enhanced framework, based on linked data principles and technologies, and devoted to collect, organize and rank user-generated corrections and completions in order to improve the accuracy and completeness of Geo-spatial LOD. Metrics have been defined for both human contributors and contents in order to estimate their reliability. The generated data introduces an additional linked data layer for hosting the revised version of the original datasets.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
