Company Filing History:
Years Active: 2016-2019
Title: Innovations of Benjamin D O'Gwynn
Introduction
Benjamin D O'Gwynn is an accomplished inventor based in Newton, MA (US). He has made significant contributions to the field of data analysis and ontology-based querying. With a total of 2 patents, his work focuses on enhancing the way data is queried and understood.
Latest Patents
O'Gwynn's latest patents include "Method and systems for enhanced ontology assisted querying of data stores." This patent discloses systems and methods that provide high-level, ontology-based analysis of low-level data stored within an unstructured key/value store. The systems allow analysts to make sense of massive amounts of data from diverse sources without needing knowledge of the underlying physical data storage. Additionally, it provides flexible ontology-assisted addressing, embedding such addressing in existing query languages like SQL, and returning results along with provenance information.
Another notable patent is "Knowledge registry systems and methods." This invention also focuses on high-level, ontology-based analysis of low-level data. It includes features such as feasibility queries to determine if requested data exists in the key/value store before performing an expensive query, automatic query optimization using secondary indexes, and a usage history service to identify performance bottlenecks and fine-tune the storage schema.
Career Highlights
O'Gwynn is affiliated with the Massachusetts Institute of Technology, where he continues to innovate and contribute to the field of data science. His work has been instrumental in advancing the understanding and accessibility of complex data systems.
Collaborations
He has collaborated with notable colleagues such as Suresh K Damodaran and Tamara H Yu, further enhancing the impact of his research and inventions.
Conclusion
Benjamin D O'Gwynn's contributions to ontology-assisted data querying represent a significant advancement in the field of data analysis. His innovative patents and collaborations continue to shape the future of how data is understood and utilized.