AIOTI WG Standardisation Sub-Group High Level Architecture prepared a report on Guidance for the Integration of IoT and Edge Computing in Data Spaces.
The full report can be found here.
This document provides an analysis on the integration of IoT and edge computing in data spaces.
It explains the context, providing a definition of data spaces, enumerating challenges of data spaces, as well as the positioning of data spaces in the AIOTI high-level architecture (HLA).
It provides an architecture analysis of data spaces, covering:
It describes the relation to existing solutions:
It provides recommendations for data space standards.
This report has provided an analysis on the integration of IoT and edge computing in data spaces. Three recommendations are made:
The first recommendation is to agree on data space principles. This paper has identified 12 principles, detailed in Table 1 and summarised in Table 23.
Table 25 – Twelve data space principles
|1||Data spaces are ecosystems of systems|
|2||Data usage require provisioning from connecting devices|
|3||Data spaces support data lifecycle|
|4||Data interoperability enabled by a common language|
|5||Data usage enabled by common data models|
|7||Trust in data sharing & Data Sovereignty|
|8||Governance for ethical usage of data|
|10||Integrated data management|
|11||Extensible data spaces|
The second recommendation is to work on data space standards following an architecture of standard as showed in Figure 23:
The third recommendation is to integrate IoT, Edge and digital twin concerns in data space standards. Note that the standards should be jointly worked out by working groups focusing on AI, on data, on data governance, on IoT, on CPS and on digital twins.