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.