Data Modeling Method and Application Practice on Identifiable Digital Object

Bin Xie, Juan Tian, Cheng Chi, Yang Liu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

The intelligent optimization closed loop of 'data-driven + industrial knowledge' is applied to the entire industrial chain and the entire value chain of the industry. The volume of industrial data is gradually increasing rapidly, and the content of industrial data is constantly enriched. A standardized industrial data model becomes the key to accelerating the precipitation, abstraction and reuse of industrial information. Based on the open and shared network ecosystem, this paper proposes the creation method and multi-role use process of the identifiable digital object (IDO) data model, and selects a specific industry product life cycle management scenario for data evaluation and analysis, and verifies the establishment of IDO It provides a more effective and complete method for users to share necessary industry information within or across enterprises.

Original languageEnglish
Title of host publicationProceedings - 2023 IEEE 6th International Conference on Industrial Cyber-Physical Systems, ICPS 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350311259
DOIs
Publication statusPublished - 2023
Externally publishedYes
Event6th IEEE International Conference on Industrial Cyber-Physical Systems, ICPS 2023 - Wuhan, China
Duration: 8 May 202311 May 2023

Publication series

NameProceedings - 2023 IEEE 6th International Conference on Industrial Cyber-Physical Systems, ICPS 2023

Conference

Conference6th IEEE International Conference on Industrial Cyber-Physical Systems, ICPS 2023
Country/TerritoryChina
CityWuhan
Period8/05/2311/05/23

Keywords

  • data model
  • identification
  • interoperability

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