- Patent Title: Predictive determination of constraint data for application with linked data in graph-based datasets associated with a data-driven collaborative dataset platform
-
Application No.: US17163287Application Date: 2021-01-29
-
Publication No.: US11573948B2Publication Date: 2023-02-07
- Inventor: David Lee Griffith
- Applicant: data.world, Inc.
- Applicant Address: US TX Austin
- Assignee: data.world, Inc.
- Current Assignee: data.world, Inc.
- Current Assignee Address: US TX Austin
- Agency: Kokka & Backus, PC
- Main IPC: G06F16/23
- IPC: G06F16/23 ; G06F16/28 ; G06F16/901

Abstract:
Various embodiments relate generally to data science and data analysis, computer software and systems, and wired and wireless network communications to interface among repositories of disparate datasets and computing machine-based entities configured to access datasets, and, more specifically, to a computing and data storage platform to implement predict data constraints to validate one or more portions of a dataset, according to at least some examples. For example, a method may include predicting a subset of constraint data to validate a graph-based data arrangement, and analyzing the graph-based data arrangement against a subset of constraint data to determine an action. At least one action may include validating data in a graph-based data arrangement. Also, the method may include integrating graph-based data arrangement into a graph data arrangement responsive to determining data representing a validation.
Public/Granted literature
Information query