Spatially-Linked Manufacturing Data to Support Data Analysis

Stefan Schabus, Johannes Scholz

Research output: Contribution to journalArticleResearchpeer-review

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.
Original languageEnglish
Pages (from-to)126-140
Number of pages15
JournalGI_Forum - Journal for Geographic Information Science
Volume2017
Issue number1
DOIs
Publication statusPublished - 2017

Fingerprint

Ontology
Industry
Semantics
Semiconductor materials

Cite this

Spatially-Linked Manufacturing Data to Support Data Analysis. / Schabus, Stefan; Scholz, Johannes.

In: GI_Forum - Journal for Geographic Information Science , Vol. 2017, No. 1, 2017, p. 126-140.

Research output: Contribution to journalArticleResearchpeer-review

@article{6bab607b58014890846293920085bacd,
title = "Spatially-Linked Manufacturing Data to Support Data Analysis",
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.",
author = "Stefan Schabus and Johannes Scholz",
year = "2017",
doi = "10.1553/giscience2017_01_s126",
language = "English",
volume = "2017",
pages = "126--140",
journal = "GI_Forum - Journal for Geographic Information Science",
issn = "2308-1708",
publisher = "{\"O}sterreichische Akademie der Wissenschaften",
number = "1",

}

TY - JOUR

T1 - Spatially-Linked Manufacturing Data to Support Data Analysis

AU - Schabus, Stefan

AU - Scholz, Johannes

PY - 2017

Y1 - 2017

N2 - 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.

AB - 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.

U2 - 10.1553/giscience2017_01_s126

DO - 10.1553/giscience2017_01_s126

M3 - Article

VL - 2017

SP - 126

EP - 140

JO - GI_Forum - Journal for Geographic Information Science

JF - GI_Forum - Journal for Geographic Information Science

SN - 2308-1708

IS - 1

ER -