Embodiments of the present invention relate to data confidence fabrics and systems for viewing annotations made by them. Distributed ledgers have problems with contextual value, ease of query, sequencing of ledger entries, and performance. IOTA and Data Confidence Fabrics for Dat...
- Embodiments of the present invention relate to data confidence fabrics and systems for viewing annotations made by them.
- Distributed ledgers have problems with contextual value, ease of query, sequencing of ledger entries, and performance.
IOTA and Data Confidence Fabrics for Data Annotations
Embodiments of the present invention relate to data confidence fabrics, specifically systems for viewing annotations made by a data confidence fabric to data. These systems may simplify the accessibility of annotations and enable greater flexibility in calculating data confidence scores.
New patent from @DellTech mentioning @iota Tangle for Data Confidence Fabric View Models. #iota #tangle #DLT #IoThttps://t.co/rs2XJ3wzqw pic.twitter.com/z53rweVvBk— Wonderer(@Wondere12985276) April 20, 2023
DCF Annotation and Scoring Framework
The DCF annotation and scoring framework is a mechanism that uses distributed annotation stores to keep track of the trustworthiness of data as it travels through the DCF. Data is generated at an edge device, such as an IoT sensor, and passed through the DCF. Each node in the DCF annotates the data with various confidence data and/or metadata.
Problems with Distributed Ledgers
Distributed ledgers have problems with contextual value, ease of query, sequencing of ledger entries, and performance. Each entry in a ledger may lack context and may not have the necessary context that makes the information valuable. Queries may not return the desired information.
The sequencing of events, such as annotations, stored on the ledger cannot be guaranteed. Finally, the ledger must be continuously queried for data confidence scores, which tends to slow operations.
DCF View Model Construction
Embodiments of the invention, such as those disclosed herein, may provide an annotation view model that supports queries by applications seeking to understand data lineage and overall confidence in data collected from the eco-system, with a granular view into which factors resulted in the total confidence.
A calculator application may be provided that employs a user-defined policy that allows some annotations to be weighted differently than others. Finally, a view model construction may be facilitated through any abstraction, thus providing a stream-like interface accessible by a user.
Conclusion
Embodiments of the present invention offer a mechanism for viewing annotations made by a data confidence fabric to data. They address the problems that distributed ledgers have with contextual value, ease of query, sequencing of ledger entries, and performance. Embodiments of the invention may provide an annotation view model that supports queries by applications, a calculator application that employs a user-defined policy, and a view model construction that is facilitated through any abstraction.