Usually, rural landscape characterization is implemented through geomatics techniques and subsequent production and analysis of geospatial data. Thanks to internet diffusion, practitioners and researchers can share data in the World Wide Web. Data sharing process can improve participatory planning processes and allow an easy comparison between different landscape areas. Sharing can be done with varying degrees of interoperability and different software tools, proprietary or open source. A widespread way to share geospatial data and metadata is by Spatial Data Infrastructures (SDI) taking advantage on Open Geospatial Consortium (OGC) standards. Anyway, the sharing of data by OGC service lacks in data harmonization and in semantic enablement, making difficult compare, search and analyze data given by different sources. Different data schemas and linguistic barrier hinder the usefulness of data obtained from different sources. In this study we present a novel data workflow implemented for sharing in an interoperable, harmonized and semantically enriched way multi-temporal land cover datasets collected in a previous landscape characterization researches.

Harmonization and Interoperable Sharing of Multi- temporal Geospatial Data of Rural Landscapes

Pratico S;Modica G
2019-01-01

Abstract

Usually, rural landscape characterization is implemented through geomatics techniques and subsequent production and analysis of geospatial data. Thanks to internet diffusion, practitioners and researchers can share data in the World Wide Web. Data sharing process can improve participatory planning processes and allow an easy comparison between different landscape areas. Sharing can be done with varying degrees of interoperability and different software tools, proprietary or open source. A widespread way to share geospatial data and metadata is by Spatial Data Infrastructures (SDI) taking advantage on Open Geospatial Consortium (OGC) standards. Anyway, the sharing of data by OGC service lacks in data harmonization and in semantic enablement, making difficult compare, search and analyze data given by different sources. Different data schemas and linguistic barrier hinder the usefulness of data obtained from different sources. In this study we present a novel data workflow implemented for sharing in an interoperable, harmonized and semantically enriched way multi-temporal land cover datasets collected in a previous landscape characterization researches.
2019
Spatial Data Infrastructures (SDIs); Inspire; Data harmonization; Sematic harmonization; Landscape
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12318/12981
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