Domain Models and Data Modeling as Drivers for Data Management: The ASSISTANT Data Fabric Approach

Research output: Contribution to journalArticlepeer-review

Abstract

To develop AI-based models capable of governing or providing decision support to complex manufacturing environments, abstractions and mechanisms for unified management of data storage and processing capabilities are needed. Specifically, as such models tend to include and rely on detailed representations of systems, components, and tools with complex interactions, mechanisms for simplifying, integrating, and scaling management capabilities in the presence of complex data requirements (e.g., high volume, velocity, and diversity of data) are of particular interest. A data fabric is a system that provides a unified architecture for management and provisioning of data. In this work we present the background, design requirements, and high-level outline of the ASSISTANT data fabric - a flexible data management tool designed for use in adaptive manufacturing contexts. The paper outlines the implementation of the system with specific focus on the use of domain models and the data modeling approach used, as well as provides a generic use case structure reusable in many industrial contexts.

Original languageEnglish
Pages (from-to)19-24
Number of pages6
JournalIFAC-PapersOnLine
Volume55
Issue number10
DOIs
Publication statusPublished - 2022
Event10th IFAC Conference on Manufacturing Modelling, Management and Control, MIM 2022 - Nantes, France
Duration: 22 Jun 202224 Jun 2022

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

Keywords

  • adaptive manufacturing
  • AI
  • Data Base
  • Data Fabric
  • Data Lake
  • Data Modeling
  • Domain Models
  • Knowledge Graph

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