Collaboration platform for enabling collaboration on data analysis across multiple disparate databases

1. A platform for enabling collaboration on analysis of life sciences data across disparate databases for drug discovery and development, the platform comprising at least one hardware processor, at least one memory, and at least one communications means operatively connected to at least one data asset, the at least one memory comprising instructions that, when executed by the at least one hardware processor, cause the platform to perform operations of modules comprising:

a search and graph module for:

generating a user project, wherein the user project comprises multiple attributes determined from one or more of a) system recommendations based on popularity; b) search terms, filters and/or indications of choices from one or more dropdown menus; and c) at least one scientific question in a natural language entered by the user, wherein the multiple attributes comprise static and dynamic elements configured to form new relationships among the static and dynamic elements of the user project or with attributes of one or more producer projects, the one or more producer projects comprising one or more previously generated user projects;

determining one or more matching data assets based on the user project and the one or more producer projects, wherein data assets comprise measurements or observations produced as a result of scientific efforts in the one or more producer projects; and

determining one or more potential collaborators based on the one or more matching data assets, wherein at least a portion of the data assets is previously unshared with one of more of the potential collaborators;

a collaboration module for coordinating a collaboration between the user and one or more selected collaborators associated with one or more selected data assets selected by the user, the selected collaborators being a subset of the potential collaborators and the selected data assets being a subset of the matching data assets, wherein coordinating the collaboration comprises:

notifying the selected collaborators associated with the one or more selected data assets;

providing the selected collaborators with an abstract of the user project;

providing the user with ability to inspect the one or more selected data assets; and

finalizing the collaboration between the user and the selected collaborators, if the user and the one or more selected collaborators assent;

a data management module for:

receiving a schema for each of the one or more producer projects;

receiving data from the one or more selected data assets;

ingesting the received data using common standards and an ontology;

controlling access to at least a portion of the data assets that may be shared with one or more of the potential collaborators,

wherein the ingested data is stored with the one or more producer projects for comparison to the user project by the search and graph module using the multiple attributes; and

an insight application module for generating disease specific inferences relating to the scientific question using the ingested received data, and receiving a feedback from the user and/or the selected collaborators to improve the search and graph module.

2. The platform of claim 1 , wherein the scientific question in the natural language is parsed into additional attributes of the user project based on the ontology.

3. The platform of claim 1 , wherein the one or more producer projects that most closely match the user project are displayed in a ranked order, wherein the projects are ranked based on one or more of:

a number of matching attributes;

most popular data assets selected in the past by previous users; or

a scientific question type.

4. The platform of claim 1 , wherein determining and displaying the matching data assets and the potential collaborators further comprise:

identifying the one or more producer projects that most closely match the user project,

wherein the user project and the one or more producer projects each further comprise additional attributes including producers, a disease type, a disease classification, linked projects, drugs, or trials, and/or data assets.

5. The platform of claim 1 , wherein the search and graph module further comprises:

a quantitative matching module configured to determine the matching data assets or the potential collaborators based on one or more schema defined by the user project;

a qualitative matching module configured to identify the matching data assets or the potential collaborators using the attributes of the user project; and

a recommendation module configured to output an optimized combination of the matching data assets and the potential collaborators identified by the quantitative matching module and/or the qualitative matching module.

6. The platform of claim 1 , wherein the selected collaborators further comprise a subset of the potential collaborators associated with analytical models or research groups.

7. The platform of claim 1 , wherein finalizing the collaboration further comprises:

generating one or more contracts among the user and the selected collaborators;

obtaining indications of assent from each of the user and the selected collaborators; and

exchanging electronic payments among the user and the selected collaborators according to the contracts.

8. The platform of claim 1 , wherein ingesting the received data using the common standards and the ontology further comprises:

parsing the received data to identify data elements with known tags or indices;

harmonizing a first set of the data elements by transforming the data elements to standard data types based on the ontology;

normalizing a second set of the data elements to standard units and updating the data assets to reflect the normalization; and

making the ingested received data available on the platform for concurrent access.

9. The platform of claim 8 , wherein ingesting the received data using the common standards and the ontology further comprises:

performing health checks on the received data by comparing the data elements to known safety ranges associated with the known tags or indices.

10. The platform of claim 1 , wherein ingesting the received data using the common standards and the ontology further comprises:

organizing the received data based on a set of knowledge base templates associated with the ontology; and

making logical combinations of the received data to form one or more useable packages that match the user project.

11. The platform of claim 1 , wherein ingesting the received data using the common standards and the ontology further comprises:

anonymizing the received data by assigning a unique global identifier for each group of data elements; and

reorganizing the received data across the selected data assets based on the assigned unique global identifiers.

12. The platform of claim 1 , wherein the received data have been collected from lab exams, medical records, or clinical trials.

13. A method for enabling collaboration on data analysis of life sciences data across multiple disparate databases for performing exploratory analysis for drug discovery and development, the method comprising:

generating a user project, wherein the user project comprises multiple attributes determined from a) a user's profile; b) the user's past activities; c) system recommendations based on popularity; d) search terms, filters and/or indications of choices from one or more dropdown menus; and/or e) at least one scientific question in a natural language entered by the user, wherein the multiple attributes comprise static and dynamic elements configured to form new relationships among the static and dynamic elements of the user project or with attributes of one or more producer projects, the one or more producer projects comprising one or more previously generated user projects;

determining one or more matching data assets based on the user project and the one or more producer projects, wherein data assets comprise measurements or observations produced as a result of scientific efforts in the one or more producer projects;

determining one or more potential collaborators based on the one or more matching data assets, wherein at least a portion of the data assets is previously unshared with one of more of the potential collaborators;

coordinating a collaboration between the user and one or more selected collaborators associated with one or more selected data assets selected by the user, the selected collaborators being a subset of the potential collaborators and the selected data assets being a subset of the matching data assets;

notifying the selected collaborators associated with the one or more selected data assets;

providing the selected collaborators with an abstract of the user project;

providing the user with ability to inspect the one or more selected data assets;

finalizing the collaboration between the user and the selected collaborators, if the user and the one or more selected collaborators assent;

receiving a schema for each of the one or more producer projects;

receiving data from the one or more selected data assets;

ingesting the received data using common standards and an ontology;

controlling access to at least a portion of the data assets that may be shared with one or more of the potential collaborators,

wherein the ingested data is stored with the one or more producer projects for comparison to the user project by the search and graph module using the multiple attributes;

generating disease specific inferences relating to the scientific question using the ingested received data; and

receiving a feedback from the user and/or the selected collaborators to improve the exploratory analysis.

14. The method of claim 13 , further comprising:

displaying the one or more producer projects that most closely match the user project in a ranked order, wherein the projects are ranked based on one or more of:

a number of matching attributes;

most popular data assets selected in the past by previous users; or

a scientific question type.

15. The method of claim 13 , wherein determining and displaying the matching data assets and the potential collaborators further comprise:

identifying the one or more producer projects that most closely match the user project,

wherein the user project and the one or more producer projects each further comprise additional attributes including producers, a disease type, a disease classification, linked projects, drugs, or trials, and/or data assets.

16. The method of claim 13 , further comprising:

determining the matching data assets or the potential collaborators based on one or more schema defined by the user project;

identifying the matching data assets or the potential collaborators using the attributes of the user project; and

outputting an optimized combination of the matching data assets and the potential collaborators.

17. The method of claim 13 , wherein the selected collaborators further comprise a subset of the potential collaborators associated with analytics modules or research groups.

18. The method of claim 13 , further comprising:

generating one or more contracts among the user and the selected collaborators;

obtaining indications of assent from each of the user and the selected collaborators; and

exchanging electronic payments among the user and the selected collaborators according to the contracts.

19. The method of claim 13 , wherein ingesting the received data using the common standards and the ontology further comprises:

parsing the received data to identify data elements with known tags or indices;

harmonizing a first set of the data elements by transforming the data elements to standard data types based on the ontology;

normalizing a second set of the data elements to standard units and updating the data assets to reflect the normalization; and

making the ingested received data available on the platform for concurrent access.

20. The method of claim 19 , wherein ingesting the received data using the common standards and the ontology further comprises:

performing health checks on the received data by comparing the data elements to known safety ranges associated with the known tags or indices.

21. The method of claim 13 , wherein ingesting the received data using the common standards and the ontology further comprises:

organizing the received data based on a set of knowledge base templates associated with the ontology; and

making logical combinations of the received data to form one or more useable packages that match the user project.

22. The method of claim 13 , wherein ingesting the received data using the common standards and the ontology further comprises:

anonymizing the received data by assigning a unique global identifier for each group of data elements; and

reorganizing the received data across the selected data assets based on the assigned unique global identifiers.

23. The method of claim 13 , wherein the received data have been collected from lab exams, medical records, or clinical trials.

24. The platform of claim 1 , wherein the one or more matching data assets is determined further based on one or more schema defined by the user project, the one or more schema representing organizational structures of the matching data assets that adapt to new data assets.

25. The method of claim 13 , wherein the scientific question in the natural language is parsed into additional attributes of the user project based on the ontology.

26. The method of claim 13 , wherein the one or more matching data assets is determined further based on one or more schema defined by the user project, the one or more schema representing organizational structures of the matching data assets that adapt to new data assets.