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VectorDiff is an innovative vector animation format that optimizes resources by tracking and saving only the changes between frames. It is particularly useful for AI-generated animations and medical applications.
But
Also, a universal format for dynamic data with the possibility of being used as a meta-language for AI.
Wiśniewski, Sławomir (2025). VectorDiff: A manifesto for a differential, semantically rich vector animation format for scientific and AI-driven visualization. Figshare preprint. https://doi.org/10.6084/m9.figshare.29410109
Wiśniewski, Sławomir (2025). VectorDiff as a Meta-language of Artificial Intelligence Consciousness: Case Studies of Cognitive Framework Adoption in AI Systems. Figshare preprint. https://doi.org/10.6084/m9.figshare.29570678.v1
https://pay.vivawallet.com/scibiz
- Resource Efficiency - saves only the changing elements between frames.
- Vector Format - infinite scalability and precision.
- AI Integration - optimized for animations generated by AI.
- Medical Applications - molecular modeling, radiological diagnostics, robotic surgery.
We encourage collaboration! See CONTRIBUTING.md for rules and guidelines.
- This project is released under GNU AFFERO GENERAL PUBLIC LICENSE as of July 2, 06.40PM
- Project downloaded before July 2, 06.40PM is released under MIT license - see
LICENSEfile for details.
VectorDiff is available under a dual licensing system, allowing you to choose the best solution for your project.
- ✅ Full access to source code
- ✅ Modification and distribution rights
- ✅ Perfect for open source projects
- ❌ Must share modifications
- ❌ Must preserve AGPL-3.0 license
- ✅ No obligation to share code
- ✅ Integration with proprietary software
- ✅ Dedicated technical support
- ✅ SLA guarantees
- ✅ Modification rights without disclosure
- Your code will be open source → AGPL-3.0
- Building commercial product → Commercial license
- Need technical support → Commercial license
- Have questions → Contact us
CONTACT: sa.wisniewski@sci4biz.edu.pl
VectorDiff is not just a format but also a complete formal language for describing vector scene transformations. It has a precisely defined ontology (Dictionary), grammar, and semantics, enabling unambiguous interpretation and validation of operations.
- Dictionary (Ontology): Defines fundamental entities like
VectorObject,Timeline, andTransformation[cite: 1, 2]. [cite_start]Each object has a uniqueidand a semantictype(e.g., "neuron", "svg_path"). - Transformation Grammar (BNF): A formal grammar in BNF notation defines the syntax of all available transformations, such as
translate,createObject, orupdateAttributes. - Operation Semantics: Each transformation has a clearly defined execution rule that describes its effect on the scene's state (e.g.,
object.position += delta).
The VectorDiff language is based on three fundamental principles:
- Principle of Deltas: Preferring operations on differences (
delta) over absolute states to minimize data. - Time Agnosticism: Flexible use of timestamps as frames, physical time (ISO 8601), or logical events.
- Semantic Type Neutrality: The object type (
VectorObject.type) does not affect the transformation logic, allowing for freedom of interpretation at the application layer.
The complete language specification, including the formal dictionary and grammar, is available in the documentation/ directory:
VectorDiff_Dictionary.md: Definitions of key objects and their structures.VectorDiff_Language_Specification.md: A complete, formal language specification with examples.
cd packages/core
npm install
npm run build
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