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Databases to Efficiently Manage Medium Sized, Low Velocity, Multidimensional Data in Tissue Engineering

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What are data spaces? Systematic survey and future outlook.

Manlio Bacco^1,2, Alexander Kocian³, Stefano Chessa³

¹European Commission, Joint Research Centre (JRC), Ispra, Italy.

|February 17, 2025

Summary

This summary is machine-generated.

Data spaces are evolving for better data sharing and sovereignty. This paper surveys their components, architecture, and implementations, offering practical insights and highlighting future challenges for widespread adoption.

Keywords:

Connectors Data management Data space Specifications Systematic survey

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Area of Science:

Computer Science
Information Science
Distributed Systems

Background:

The concept of data spaces is gaining traction due to the growing demand for data interoperability and sovereignty.
Early explorations over the past two decades have paved the way for a current consolidation phase.

Purpose of the Study:

To provide a comprehensive overview of data spaces, including their architecture, components, and operational mechanisms.
To analyze the Reference Architectural Model (RAM) by the International Data Spaces (IDS) initiative.
To offer practical guidance for implementing and experimenting with data space software components.

Main Methods:

Systematic literature survey on data spaces.
Analysis of architectural models and specifications.
Review of existing mature software implementations.

Main Results:

Data spaces are converging towards standardization with evolving specifications and implementations.
A detailed architectural vision and analysis of the IDS Reference Architectural Model are presented.
Practical pointers for software component experimentation are provided.

Conclusions:

Data spaces represent a significant advancement in secure and sovereign data exchange.
Further research and development are needed to address open challenges for their successful implementation and adoption.