US 12,380,074 B2
Optimizing metadata enrichment of data assets
Thomas Hampp-Bahnmueller, Stuttgart (DE); Peter Gerstl, Holzgerlingen (DE); Yannick Saillet, Stuttgart (DE); Michael Baessler, Bempflingen (DE); Albert Maier, Tuebingen (DE); and Oliver Suhre, Stuttgart (DE)
Assigned to International Business Machines Corporation, Armonk, NY (US)
Filed by International Business Machines Corporation, Armonk, NY (US)
Filed on Jan. 4, 2023, as Appl. No. 18/149,882.
Claims priority of application No. 2216661 (GB), filed on Nov. 9, 2022.
Prior Publication US 2024/0152494 A1, May 9, 2024
Int. Cl. G06F 16/215 (2019.01); G06F 16/22 (2019.01); G06F 16/28 (2019.01); G06F 16/907 (2019.01)
CPC G06F 16/215 (2019.01) [G06F 16/221 (2019.01); G06F 16/285 (2019.01); G06F 16/907 (2019.01)] 19 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
determining, by one or more computer processors, for an input data asset of a relational database system, a metadata value descriptive of the input data asset, wherein the metadata value comprises a tuple having three entries including a column name, a file name, and a data class;
determining, by one or more computer processors, characteristics of the metadata value of the input data asset using a machine learning model, wherein the machine learning model receives, as input, a definition of an enrichment workflow and the metadata value;
computing, by one or more computer processors, at least one informativeness score of the metadata value of the input data asset using the determined characteristics, wherein:
the at least one informativeness score indicates a level of information that is provided by content of the metadata value; and
the at least one informativeness score indicates that the column name is computer-generated and that a semantic comparison with real language terms is precluded;
determining, by one or more computer processors, input characteristics of enrichment steps by parsing code implementing the enrichment steps;
for each step of the enrichment steps:
determining, by one or more computer processors, that the input characteristic of the enrichment step is part of the determined characteristics; and
responsive to determining that the input characteristic of the enrichment step is part of the determined characteristics, executing, by one or more computer processors, the enrichment step using the input characteristic as input, based on the at least one informativeness score; and
labeling, by one or more computer processors, the data asset with a combination of labels resulting from the executed enrichment steps, wherein the combination of labels describe the data asset.