About
Datalayer allows you to create custom Open Science Platform for various cases listed on this page. Our platform is Cloud native, 100% compatible with Jupyter and WEB developer friendly.
You will need a combination of technologies and deployments to run the Datalayer platform.
If you are already running with JupyterHub, that is absolutely fine, you can easily upgrade your existing solution with Datalayer on JupyterHub.
If are just want a plain React.js Web Application to deliver custom and rich experience to your users, that is also absolutely fine with Jupyter UI.
🤖 Artificial Intelligence (AI)
Datalayer is a versatile tool for AI projects, offering support for exploratory data analysis, machine learning prototyping, model training and evaluation, deployment, experimentation, collaboration, and education.
We facilitate interactive development, integrates with popular AI libraries, and promotes reproducibility, making it a preferred choice for AI practitioners and researchers.
✍️ Literate Notebook
As successor to JupyterLab, we are developing a brand new user interface Literate Notebook to better address literate programming requirements, compatible with Jupyter and ObservableHQ as envisioned by Donald Knuth back in 1983.
As a developer, you can create your own custom data product a-la-google-docs as shown below. Your custom Literate Notebook can be shipped as a standalone component, as Jupyter Notebook, JupyterLab and as Visual Studio Code extension.
We are adding collaborative and Realtime collaboration features as well as a integration with Microsoft Office 365 and Google Workspace.
Literate programming is a programming paradigm introduced by Donald Knuth in which a computer program is given an explanation of its logic in a natural language, such as English, interspersed with snippets of macros and traditional source code, from which compilable source code can be generated. The approach is used in scientific computing and in data science routinely for reproducible research and open access purposes.
📈 Data Products
Data Products goal is to provide a custom and better Jupyter experience.
- Accessible.
- Collaborative.
- Performant.
- Reproducible.
- Reusable.
- Scalable.
- Secured.
- Shareable.
🏄 Dashboarding
Datalayer can be utilized for dashboarding by integrating data visualization libraries, interactive widgets, and flexible layout options. It allows real-time data updates, embedding external content, and sharing through various formats and deployment options.
Customization features enhance user experience, making Jupyter a versatile tool for creating interactive and informative dashboards.
👩🎓 Education
Datalayer notebooks are versatile tools for education, facilitating interactive learning, code demonstration, data analysis, and collaboration. They enable students to engage directly with course material, run code, visualize data, and experiment freely.
Datalayer notebooks promote active learning, documentation, reproducibility, and integration with other educational tools, making them valuable resources for teaching and learning in diverse fields.