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Data Space Pathway - Data oriented challenge dimensions

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Data Space Pathway - Data oriented challenge dimensions

DS Pathway - Data management levels Description

Pathway levels that describe the extent to which companies are implementing principles and techniques for data lifecycle management including quality and integrity

No Data Management Culture in the company

Data stored in Enterprise Application and managed from there

Cross application Data Management Bridges

Common set of data management application applied to data Source and Enterprise Application

Data Management Application used to assign a value to data

DS Pathway - Data protection levels Description

Pathway levels describing the extent to which companies are implementing privacy and anonymization mechanisms to facilitate data protection (cybersecurity)

No specific Data Protection measures in place regarding storage, computation and transfer of data

Each single Enterprise Application (ERP SCM PLM) is responsible for Data Protection

Secure Data Bridges between silos implemented on a case-by-case basis

Common Data Protection mechanisms and tools are shared at company level and used in every application

Data Protection mechanisms associated to Data Spaces increase the value of Data

DS Pathway - Data Processing Architecture Implementation Levels Description

Pathway levels describing the extent to which companies are implementing performant and scalable data-driven architectures for analytics of both data-at-rest and data-in-motion

Data not processed or processed by default procedures out of control for the company

Data processed inside Enterprise Applications (ERP SCM PLM) according to architectures and tools predefined by them

Data Processing architectures (embedded, edge, cloud) implemented for ad-hoc data bridges in Enterprise Applications

Common Data Processing architecture adopted for all Enterprise Applications, both Data at Rest and Data in Motion

Data Processing tools associated as a service to Data Sets, increasing value in the Data Space and implementing Data Economy services

DS Pathway - Data Visualisation and User Interaction Description

Pathway levels describing the extent to which companies are adopting advanced visualisation approaches for improved user experience including VR/AR

Data visualisation tools not implemented or implemented by third parties out of control of the company

Data visualisation tools embedded in Enterprise Applications on top of predefined sets of Data

Data visualisation applications are developed ad-hoc cross-silos to show data coming from different sources

Common agreed repository of Data Visualisation tools is shared in the company, at disposal for any application

Data Visualisation tools associated as a service to available Data Sets, increasing their value in the Data Space and implementing Data Economy services

DS Pathway - Ecosystems for Data Sharing Description

Pathway levels describing the extentto which companies are implementing secure and trusted Data Sharing spaces and platforms along the value chain, according to Data Sovereignty principles?

A common and agreed architecture for secure and sovereign Data Sharing implemented

Data Sharing applications associated as a service to available Data Sets, increasing value in the Data Space and implementing Data Economy services

Data Sharing not implemented or implemented without any control

Data Sharing allowed from inside Enterprise Applications to a predefined value ecosystem

Data Sharing from different sources implemented for specific suppliers and customers

DS Pathway - Data Analytics Implementation Levels Description

Pathway levels descringing the extent companies are implementing data analytics to improve data understanding, deep learning and the meaningfulness of data?

Data analytics not performed or performed by third parties out of control of the company

Data Analytics procedures implemented (and replicated) from inside Enterprise Applications only

Data Analytics procedures implemented across silos in an ad-hoc fashion

Common repository of Data Analytics tools is shared in the company, at disposal for any application

Data Analytics tools associated as a service to available Data Sets, increasing their value in the Data Space and implementing Data Economy services