Data semantics is the study of the meaning and use of specific pieces of data in computer programming and other areas that employ data. When studying a language, semantics refers to what individual words mean and what they mean when put together to form phrases or sentences. In data semantics, the focus is on how a data object represents a concept or object in the real world. The term “Decentralized Semantics” is a representation of “data semantics” within an age of distributed ledger technology (DLT) solutions which continue to mould the current decentralisation movement.
Mission and
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Scope (as defined in the WG charter)
The mission of the WG is to define a data capture architecture consisting of immutable schema bases and interoperable overlays for Internet-scale deployment. The scope of the WG is to define specifications and best practices that bring cohesion to data capture processes and other Semantic Standards throughout the ToIP stack, whether these standards are hosted at the Linux Foundation or external to it. Other WG activities will include creating template Requests for Proposal (RFPs) and additional guidance to utility and service providers regarding implementations in this domain. This WG may also organise Task Forces to escalate the development of certain components if deemed appropriate by the majority of the WG members and in line with the overall mission of the ToIP Foundation.
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- Paul Knowles (Human Colossus Foundation)
- Robert Mitwicki (Human Colossus Foundation)
Chairs
To be elected
Mailing List
decentralized-semantics-wg@lists.trustoverip.org (subscribe by going to lists.trustoverip.org)
Meetings
This WG current meets weekly on Tuesdays. See the Meeting Page for the meeting schedule, agenda, and meeting notes. For a calendar invite with complete Zoom information, please send email to the mailing list above.
Description
The post millennial generation has witnessed an explosion of captured data points which has sparked profound possibilities in both Artificial Intelligence (AI) and Internet of Things (IoT) solutions. This has spawned the collective realization that society’s current technological infrastructure is simply not equipped to fully support de-identification or to entice corporations to break down internal data silos, streamline data harmonization processes and ultimately resolve worldwide data duplication and storage resource issues. Developing and deploying the right data capture architecture will improve the quality of externally pooled data for future AI and IoT solutions.
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