Resource distribution

1. A method for distributing resources, comprising the steps:

receiving, by one or more processors, values for attributes associated to respective identifiers from a plurality of different data sources,

blending, by the one or more processors, the received values for the attributes into a dataset, such that the dataset includes a plurality of identifiers and one or more values for one or more attributes are assigned to each of the identifiers,

assigning, by the one or more processors, data lineages to the values for the attributes based on the data source from which a respective value for a respective attribute was received,

receiving, by the one or more processors, a query for providing a data subset of the dataset based on one or more of the attributes,

providing, by the one or more processors, the data subset based on the query,

determining, by the one or more processors, a knowledge contribution of each of the data sources to the data subset based on the data lineages of the values for the attributes included in the dataset relevant for the query, and

instructing, by the one or more processors, a distribution of shares of resources to the different data sources based on the knowledge contribution of each of the data sources to the data subset.

2. The method according to claim 1 for distributing resources based on data usage, wherein the method comprises the steps:

providing, by the one or more processors, attribute weights to the attributes based on a type of a respective attribute, and

determining, by the one or more processors, a data usage of each of the data sources for the data subset based on the knowledge contribution of each of the data sources to the data subset and the attribute weights, and

wherein the shares of the resources to be distributed to the different data sources are determined based on the data usage of each of the data sources for the data subset.

3. The method according to claim 2 , wherein the method comprises the step:

providing, by the one or more processors, a respective attribute weight to each of the attributes based on heuristic rules or a machine learning model which optimizes the attribute weights based on one or more attribute parameters.

4. The method according to claim 2 , wherein the method comprises the step:

determining, by the one or more processors, the data usage of each of the data sources for the data subset based on the formula:

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with U(k,q) a data usage of the data source k for query q, N(k,j) a knowledge contribution of data source k to an attribute j, and W(j) an attribute weight of the attribute j, n a number of attributes, and m a number of data sources.

5. The method according to claim 1 , wherein the method comprises the step:

assigning, by the one or more processors, the received values for the attributes to cells of the dataset, such that each value for an attribute is a value for an atomic attribute included in one cell of the dataset and such that the values for the atomic attributes have identical data lineages as assigned to the values for the attributes.

6. The method according to claim 1 , wherein determining, by the one or more processors, the knowledge contribution of each of the data sources to the data subset is performed by counting a number of cells in the dataset that include a value for an atomic attribute with data lineage of a respective data source and which is relevant for the query for each of the data sources.

7. The method according to claim 1 , wherein the method comprises the step:

providing, by the one or more processors, a priority score to each data source for each attribute based on one or more priority parameters, and

wherein assigning the data lineages to the values for the attributes is performed additionally based on the priority scores.

8. The method according to claim 7 , wherein providing, by the one or more processors, the priority score to each data source for each attribute is performed based on heuristic rules or a machine learning model which optimizes the priority score based on the one or more priority parameters.

9. The method according to claim 7 , wherein providing, by the one or more processors, the priority score to each data source for each attribute is performed additionally based on an event trigger or a time trigger.

10. The method according to claim 7 , wherein the method comprises the step:

assigning, by the one or more processors, a respective value for a respective attribute received from a respective data source to a respective identifier based on the priority score of the respective data source for the respective attribute.

11. The method according to claim 1 , wherein the method comprises the steps:

providing, by the one or more processors, the data subset to a data target and

receiving resources from the data target.

12. The method according to claim 11 , wherein the method comprises the step:

distributing the shares of the resources to the different data sources.

13. A computer program product for distributing resources, wherein the computer program product comprises program code means for causing a resource distribution data system to carry out the method as defined in claim 1 , when the computer program product is run on the resource distribution data system.

14. A resource distribution data system for distributing resources,

wherein the resource distribution data system comprises:

one or more memory components having computer readable code stored thereon; and

one or more processors operatively coupled to the one or more memory components and configured to execute the computer readable code for:

receiving values for attributes associated to respective identifiers from a plurality of different data sources,

blending the received values for the attributes into a dataset, such that the dataset includes a plurality of identifiers and one or more values for one or more attributes are assigned to each of the identifiers,

assigning data lineages to the values for the attributes based on the data source from which a respective value for a respective attribute was received,

receiving a query for providing a data subset of the dataset based on one or more of the attributes,

providing the data subset based on the query,

determining a knowledge contribution of each of the data sources to the data subset based on the data lineages of the values for the attributes included in the dataset relevant for the query, and

sending control signals to a network, said control signals instructing a distribution of shares of resources to the different data sources based on the knowledge contribution of each of the data sources to the data subset.

15. A computer program product for distributing resources, wherein the computer program product comprises program code means for causing the resource distribution data system according to claim 14 when the computer program product is run on the resource distribution data system.

16. A computer readable medium having stored the computer program product of claim 14 .