The Scientific Discovery Specifications provide an open infrastructure framework for accelerating research, exploration, and innovation across natural sciences, engineering, materials science, and knowledge systems. They are designed to improve how scientific information is discovered, organized, validated, and applied by combining artificial intelligence, structured knowledge models, provenance tracking, and reproducible research workflows.
These specifications enable advanced scientific intelligence capabilities, including AI-assisted hypothesis generation, research gap identification, evidence analysis, knowledge graph construction, and intelligent retrieval of scientific information. They support researchers by connecting fragmented datasets, academic knowledge, experimental results, and technical documentation into interconnected systems that make discovery more efficient, transparent, and collaborative.
A major focus of the ecosystem is scientific reproducibility and trust. The specifications provide mechanisms for tracking the origin of information, preserving research history, validating evidence, documenting methodologies, and creating auditable chains of scientific knowledge. This allows researchers, institutions, and AI systems to better understand not only scientific conclusions but also the processes and evidence used to reach them.
The ecosystem also extends into the study of the natural world and sustainable innovation. It provides frameworks for analyzing biological resources, medicinal compounds, regional materials, geological resources, advanced materials, and environmentally responsible engineering approaches. By combining local knowledge with scientific intelligence, these systems support the discovery of new applications for natural resources while encouraging sustainable practices.
Together, the Scientific Discovery Specifications create a foundation for next-generation research environments where humans and AI can collaborate to explore unknown possibilities, accelerate innovation, preserve scientific knowledge, and build more transparent and accessible systems for discovery. They represent a modular approach to advancing science through open infrastructure, shared knowledge, and verifiable intelligence.
All specifications are released under the GNU Affero General Public License v3.0 or later (AGPL-3.0+) and may be freely used, modified, and distributed with the required attribution provisions outlined in Section 7 of the license. Organizations seeking attribution-free commercial deployment may obtain a Specification Branding License (SBL), with licensing terms and pricing based on the specification category, deployment scope, usage scale, and the size of the network or organization utilizing the specification.
Adaptive Materials Engine (AME)
https://roxanneardary.com/adaptive-materials-engine/
AI-assisted discovery and engineering framework for sustainable materials, composites, biomaterials, and advanced material systems. The specification focuses on accelerating material innovation through structured knowledge, simulation, and reproducible research workflows.
Arq
https://roxanneardary.com/arq/
A structured knowledge graph system designed to organize complex engineering, scientific, and architectural information. Arq enables relationships between concepts, components, systems, and technical documentation to support research and discovery.
CommonGrid
https://roxanneardary.com/commongrid/
A scientific data discovery and federation framework for organizing, connecting, and accessing distributed datasets and open research resources. CommonGrid supports collaborative scientific exploration through interoperable knowledge systems.
EurekaAI
https://roxanneardary.com/eurekaai/
An AI-powered scientific discovery platform designed to analyze research literature, identify knowledge gaps, generate hypotheses, and assist researchers in discovering new possibilities across scientific disciplines.
LocaleMaterials
https://roxanneardary.com/localematerials/
A local materials intelligence specification focused on discovering, cataloging, and analyzing region-specific natural resources such as stone, clay, timber, fibers, minerals, and biological materials. It supports sustainable design, regional manufacturing, and place-based material innovation.
MindCache
https://roxanneardary.com/mindcache/
A persistent knowledge memory system for storing, organizing, and retrieving scientific research knowledge. MindCache supports long-term research continuity, collaborative intelligence, and structured information management.
Nature Pharmacopeia
https://roxanneardary.com/nature-pharmacopeia/
A natural sciences knowledge system focused on medicinal plants, fungi, minerals, natural compounds, traditional remedies, and pharmacognosy research. It provides a structured framework for exploring natural sources of therapeutic and biological knowledge.
OpenChrona
https://roxanneardary.com/openchrona/
A scientific research specification exploring timekeeping, astronomy, calendars, historical measurement systems, and precision technologies. OpenChrona preserves and organizes knowledge around humanity’s systems for measuring time and celestial cycles.
OpenLedger Provenance System
https://roxanneardary.com/openledger-provenance-system/
A provenance infrastructure for scientific knowledge, experiments, datasets, and evidence chains. OpenLedger enables transparent tracking of research origins, methodologies, changes, and validation history.
PublicStack AI
https://roxanneardary.com/publicstackai/
An open knowledge retrieval infrastructure designed to index and connect public information sources, scientific repositories, and research materials. It supports accessible discovery of public-domain knowledge.
RAGBase
https://roxanneardary.com/ragbase/
A retrieval-augmented knowledge infrastructure specification for scientific documents, research archives, and specialized knowledge systems. RAGBase enables AI systems to access structured, contextual information for research assistance.
TraceGraph OS
https://roxanneardary.com/tracegraph-os/
A scientific intelligence operating system for modeling hypotheses, experiments, evidence, simulations, and research relationships. TraceGraph OS supports reproducible science through connected knowledge graphs and research provenance.
TruthLayer
https://roxanneardary.com/truthlayer/
An evidence-based analysis framework designed around transparent methodologies, reproducible calculations, verification systems, and trustworthy information evaluation.
Veridion System
https://roxanneardary.com/veridion-system/
A scientific validation and intelligence framework for transforming fragmented information into verified, explainable, and trustworthy signals. Veridion focuses on evidence validation, data integrity, and reliable knowledge creation.
Xythera
https://roxanneardary.com/xythera/
A scientific engineering platform for AI-assisted sensor design, hardware research, experimental validation, and reproducible fabrication. Xythera connects engineering knowledge with scientific discovery workflows.
A Specification Branding License can be purchased for the basket of Scientific Discovery Specs
Specification Basket Pricing:
| Network Size | # of Users | One-Time Price | Duration |
| Small | 1 – 20 | $500,000 | Perpetual License |
| Medium | 21- 1000 | $1,700,000 | Perpetual License |
| Large | 1001 + | Custom Quote | Custom Quote |
