To share data, partners currently need to sign contracts on the use of the data in question. Those who receive the data also need to be trustworthy. These requirements limit the opportunities for data analysis. However, data spaces offer an alternative: they automate the shared use of data and allow suppliers to attach predefined guidelines to data transactions, thus guaranteeing the sovereignty of the supplier.
Data warehouses were considered the optimal solution for uniting structured data from heterogeneous sources for analysis in a central database. A data lake takes it one step further and saves both structured and unstructured data. The unformatted data are only processed for each given analysis. Data spaces dissolve this centrality and offer a decentralised solution where each participant can offer their own data. The data stay with the supplier and are made available through secure peer-to-peer communication with common semantics and data sovereignty.
The data mesh concept also supports the decentralised approach to data use. It structures large volumes of data as a "meshed" network and makes them usable through a shared, domain-oriented architecture: from the source to the applications, irrespective of the type and location of the source – even outside the company. Data can be used for self-service analysis across all departments, and can also be connected and combined as desired. Companies no longer rely on specialised data engineers to implement a data mesh solution.
Germany's Federal Ministry for Digital and Transport has launched a data space initiative which allows data to be be shared easily, transparently, and securely. Among other things, users can access real-time data from local public transport or bike rental locations. The Mobilithek is not an information system for travellers and road users, rather it provides a basis for new mobility services, as well as a digital space to develop data-based apps. The Telekom Data Intelligence Hub provides the components to facilitate the sovereign exchange of data.