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Spatially-Linked Manufacturing Data to Support Data Analysis

    Stefan Schabus, Johannes Scholz

GI_Forum 2017, Volume 5, Issue 1, pp. 126-140, 2017/06/30

Journal for Geographic Information Science

doi: 10.1553/giscience2017_01_s126

doi: 10.1553/giscience2017_01_s126


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doi:10.1553/giscience2017_01_s126



doi:10.1553/giscience2017_01_s126

Abstract

The paper presents a Linked Data approach within a manufacturing organization to foster sharing, reusing, integrating and the collaborative analysis of datasets originating from different business units and heterogeneous data sources. The paper relies on a semiconductor company that serves as case study. The authors elaborate on manufacturing data and their representation in a spatially-enabled graph database, and as Linked Data based on an ontology describing the indoor space and production processes. A graph database enables data sharing as well as the semantic search and retrieval of data utilizing web-based services. The results present the analysis of historic, future and spatio-temporal data as well as the analysis of similarities of semantically-annotated linked manufacturing data.

Keywords: linked manufacturing data, semantic annotations, smart manufacturing, graph databases