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<!DOCTYPE html>
<html>
<head>
<meta charset='utf-8'>
<title>OCA Specification</title>
<style>
#instructions {
border: dashed 1px black;
padding: 1em;
background-color:#d0d0d0;
}
.replace-me {
font-style:italic;
color:magenta
}
</style>
<script src='https://www.w3.org/Tools/respec/respec-w3c-common' class='remove'></script>
<script class='remove'>
var respecConfig = {
specStatus: "unofficial",
logos: [{
src: 'https://github.com/the-human-colossus-foundation/media-assets/raw/master/HCF/_rgb/_png/LOGO_base_black.png',
href: "https://humancolosus.org",
alt: "The Human Colossus Foundation",
width: 193,
height: 184,
id: 'hcf-logo',
}],
editors: [
{
name: "Robert Mitwicki",
url: "https://www.linkedin.com/in/robertmitwicki",
company: "The Human Colossus Foundation",
companyURL: "https://humancolossus.foundation",
mailto: "[email protected]"
}
],
authors: [
{
name: "Robert Mitwicki",
url: "https://www.linkedin.com/in/robertmitwicki",
company: "The Human Colossus Foundation",
companyURL: "https://humancolossus.foundation",
mailto: "[email protected]"
},
{
name: "Paul Knowles",
url: "https://www.linkedin.com/in/jenral/",
company: "The Human Colossus Foundation",
companyURL: "https://humancolossus.foundation",
mailto: "[email protected]"
}
],
processVersion: 2020,
edDraftURI: "https://github.com/the-human-colossus-foundation/oca-spec",
shortName: "oca",
subtitle: "Overlays Capture Architecture",
github: "https://github.com/the-human-colossus-foundation/oca-spec",
wg: "The Human Colossus Foundation",
pluralize: true,
// To load highlighter for another lang, see https://github.com/w3c/respec/wiki/pre-and-code-elements
};
</script>
</head>
<body>
<section id='abstract'>
<p>
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 protect personally
identifiable information (PII) or to entice corporations to break down
internal data silos, streamline data harmonization processes and
ultimately resolve worldwide data duplication and storage resource issues.
</p>
<p>
The FAIR Data Principles are a set of guiding principles in order to make
data findable, accessible, interoperable and reusable (Wilkinson et al.,
2016). These principles provide guidance for scientific data management
and stewardship and are relevant to all stakeholders in the current
digital ecosystem.
</p>
<p>
In line with the FAIR principles, data harmonization
and interoperability processes between internal departments and functions
is a high priority for corporate organizations but the current cognitive
framework available for data capture across all industry sectors is
hampered by limitations to the foundational data object architecture.
</p>
</section>
<section id='sotd'>
<p>
</p>
</section>
<section id="intro" data-include="intro.html">
</section>
<section id="security-considerations" class="informative appendix" data-include="security.html">
</section>
<section id="privacy-considerations" class="informative appendix" data-include="privacy.html">
</section>
<section id="resources" class="informative appendix" data-include="resources.html">
</section>
</body>
</html>