To share data, partners currently need to sign contracts on the use of the data. 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 and therefore guarantee the sovereignty of the supplier.
Data warehouses were considered the optimal solution to unite 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 decentralized solution where each participant can offer their own data. They stay with the supplier and are made available through secure peer-to-peer communication with common semantics and data sovereignty.