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.
|Number of pages||15|
|Journal||GI_Forum - Journal for Geographic Information Science|
|Publication status||Published - 2017|
Schabus, S., & Scholz, J. (2017). Spatially-Linked Manufacturing Data to Support Data Analysis. GI_Forum - Journal for Geographic Information Science , 2017(1), 126-140. https://doi.org/10.1553/giscience2017_01_s126