Speaker
Description
The AiiDAlab platform is a computational environment that is tailored for the execution of integrated complex scientific workflows and enables researchers to utilize cloud resources in the form of a web application accessible through the browser. The platform is built on top of Jupyter and targeted specifically at users with only limited experience in the area of computational science and enables them to produce results quickly. Users can customize the environment for their needs by installing additional Python software via pip and by installing AiiDAlab apps from the built-in app store that were contributed by colleagues, collaborators, or the wider scientific community – including the AiiDAlab team – or by creating entirely new workflows and web interfaces. This is facilitated by providing a simple path for editing existing apps and through the availability of a rich library of basic building blocks. Newly created workflows can be easily redistributed via the aforementioned app store. AiiDAlab significantly simplifies the setup of a functional and well-integrated computational environment, which can present a major barrier especially to researchers with only limited computational experience, such as junior researchers and experimentalists. But the platform is also of interest to experienced computationalists who would like to use and develop intuitive graphical interfaces for AiiDA workflows based on Jupyter technology or who would like to take advantage of integration with other platforms and web applications. In particular we demonstrate how AiiDAlab can be integrated with existing infrastructure, e.g., for user management, but also for data exchange and inter-platform integrated workflows. AiiDAlab apps are powered by AiiDA and thus enable the execution of fully-automated workflows that keep track of full provenance of all data operations in accordance with FAIR data and open science principles.
| Speaker Country | Switzerland |
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