US 12,147,554 B2
Contextualization of organization data and handling storage quantification
Fang Lu, Billerica, MA (US); Clement Decrop, Arlington, VA (US); Zachary A. Silverstein, Georgetown, TX (US); Jeremy R. Fox, Georgetown, TX (US); and Pratyush Kumar, Hajipur (IN)
Assigned to International Business Machines Corporation, Armonk, NY (US)
Filed by INTERNATIONAL BUSINESS MACHINES CORPORATION, Armonk, NY (US)
Filed on Mar. 15, 2022, as Appl. No. 17/654,833.
Prior Publication US 2023/0297705 A1, Sep. 21, 2023
Int. Cl. G06F 21/62 (2013.01)
CPC G06F 21/6218 (2013.01) 20 Claims
OG exemplary drawing
 
1. A processor-implemented method for contextualization for storage quantification, the method comprising:
receiving root data, wherein the root data comprises a plurality of datasets;
analyzing the root data to determine a context of each dataset within the plurality of datasets;
analyzing sharing patterns for interactions between entities, wherein the sharing patterns comprise data sharing patterns between one or more stakeholders and a user;
determining whether the context of each dataset within the plurality of datasets is new;
processing a new context of each dataset within the plurality of datasets to build access hierarchy upon determining that the context of at least one of the datasets within the plurality of datasets is new;
identifying one or more accessing users based on monitoring behavior of the one or more accessing users related to each of the datasets within the plurality of datasets;
appending metadata associated with the new context of each of the datasets within the plurality of datasets based on the determined context and the analyzed sharing patterns of the one or more identified accessing users; and
setting access restrictions to each dataset in the metadata based on the context and the one or more identified accessing users.