Details
| Original language | English |
|---|---|
| Title of host publication | 2022 IEEE 24th Conference on Business Informatics, CBI 2022 - CBI Forum and Workshop Papers |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 9-16 |
| Number of pages | 8 |
| Volume | 2 |
| ISBN (electronic) | 9781665460163 |
| ISBN (print) | 978-1-6654-6038-5 |
| Publication status | Published - 2022 |
| Event | 24th IEEE International Conference on Business Informatics, CBI 2022 - Amsterdam, Netherlands Duration: 15 Jun 2022 → 17 Jun 2022 |
Publication series
| Name | IEEE Conference on Business Informatics |
|---|---|
| ISSN (Print) | 2378-1963 |
| ISSN (electronic) | 2378-1971 |
Abstract
In highly globalized, digitized, and complex Supply Chains (SCs), the view of SCs is based on seemingly siloed or outdated data-sets. Integrated analysis capabilities, that rely on consistent data structures and applications, facilitate grasping, controlling, and ultimately enhancing SC behavior. Master Data (MD) is defined as the high-value core information of an enterprise, shared across the business processes and systems of an organization. Master Data Management (MDM) is an essential prerequisite for companies to make agile reporting and correct decisions. Traditional MDM approaches are limited in integrating enterprise information as well as meeting requirements, e.g., stakeholders' involvement for MD analysis and reporting. Therefore, we propose a methodology for a knowledge-graph-based MDM, which relies on establishing a knowledge-graph (KG) layer for building a common understanding of the key business entities and semantic mappings from and to the original data sources. KnowGraph-MDM (KG-MDM) relies on iterations to incorporate stakeholders' inputs, allowing evolutionary development of the MD model. Thus, the ingestion and adoption of the new model increases among the stakeholders via deployment in the organization. We apply the proposed approach in a use case for a semiconductor manufacturer. The resulting KG depicts the core MD model that can be iteratively extended to incorporate different stakeholders' perspectives. KnowGraph-MDM enables integrated SC performance analysis and reporting, relying on consistent MD across the SC.
Keywords
- Knowledge Graph, Master Data Management, Methodology, Semantic Modeling
ASJC Scopus subject areas
- Decision Sciences(all)
- Information Systems and Management
- Decision Sciences(all)
- Management Science and Operations Research
- Computer Science(all)
- Artificial Intelligence
- Computer Science(all)
- Information Systems
- Decision Sciences(all)
- Decision Sciences (miscellaneous)
Cite this
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- BibTeX
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2022 IEEE 24th Conference on Business Informatics, CBI 2022 - CBI Forum and Workshop Papers. Vol. 2 Institute of Electrical and Electronics Engineers Inc., 2022. p. 9-16 (IEEE Conference on Business Informatics).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - KnowGraph-MDM
T2 - 24th IEEE International Conference on Business Informatics, CBI 2022
AU - Ramzy, Nour
AU - Durst, Sandra
AU - Schreiber, Martin
AU - Auer, Sören
AU - Chamanara, Javad
AU - Ehm, Hans
PY - 2022
Y1 - 2022
N2 - In highly globalized, digitized, and complex Supply Chains (SCs), the view of SCs is based on seemingly siloed or outdated data-sets. Integrated analysis capabilities, that rely on consistent data structures and applications, facilitate grasping, controlling, and ultimately enhancing SC behavior. Master Data (MD) is defined as the high-value core information of an enterprise, shared across the business processes and systems of an organization. Master Data Management (MDM) is an essential prerequisite for companies to make agile reporting and correct decisions. Traditional MDM approaches are limited in integrating enterprise information as well as meeting requirements, e.g., stakeholders' involvement for MD analysis and reporting. Therefore, we propose a methodology for a knowledge-graph-based MDM, which relies on establishing a knowledge-graph (KG) layer for building a common understanding of the key business entities and semantic mappings from and to the original data sources. KnowGraph-MDM (KG-MDM) relies on iterations to incorporate stakeholders' inputs, allowing evolutionary development of the MD model. Thus, the ingestion and adoption of the new model increases among the stakeholders via deployment in the organization. We apply the proposed approach in a use case for a semiconductor manufacturer. The resulting KG depicts the core MD model that can be iteratively extended to incorporate different stakeholders' perspectives. KnowGraph-MDM enables integrated SC performance analysis and reporting, relying on consistent MD across the SC.
AB - In highly globalized, digitized, and complex Supply Chains (SCs), the view of SCs is based on seemingly siloed or outdated data-sets. Integrated analysis capabilities, that rely on consistent data structures and applications, facilitate grasping, controlling, and ultimately enhancing SC behavior. Master Data (MD) is defined as the high-value core information of an enterprise, shared across the business processes and systems of an organization. Master Data Management (MDM) is an essential prerequisite for companies to make agile reporting and correct decisions. Traditional MDM approaches are limited in integrating enterprise information as well as meeting requirements, e.g., stakeholders' involvement for MD analysis and reporting. Therefore, we propose a methodology for a knowledge-graph-based MDM, which relies on establishing a knowledge-graph (KG) layer for building a common understanding of the key business entities and semantic mappings from and to the original data sources. KnowGraph-MDM (KG-MDM) relies on iterations to incorporate stakeholders' inputs, allowing evolutionary development of the MD model. Thus, the ingestion and adoption of the new model increases among the stakeholders via deployment in the organization. We apply the proposed approach in a use case for a semiconductor manufacturer. The resulting KG depicts the core MD model that can be iteratively extended to incorporate different stakeholders' perspectives. KnowGraph-MDM enables integrated SC performance analysis and reporting, relying on consistent MD across the SC.
KW - Knowledge Graph
KW - Master Data Management
KW - Methodology
KW - Semantic Modeling
UR - http://www.scopus.com/inward/record.url?scp=85142922361&partnerID=8YFLogxK
U2 - 10.1109/CBI54897.2022.10043
DO - 10.1109/CBI54897.2022.10043
M3 - Conference contribution
AN - SCOPUS:85142922361
SN - 978-1-6654-6038-5
VL - 2
T3 - IEEE Conference on Business Informatics
SP - 9
EP - 16
BT - 2022 IEEE 24th Conference on Business Informatics, CBI 2022 - CBI Forum and Workshop Papers
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 15 June 2022 through 17 June 2022
ER -