Benchmarks for Natural Language Data Mining with LLMs
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Best Practices Guides
A practical governance framework that sets out the standards and best practices for designing, managing, and releasing FAIR, interoperable ontologies and semantic artefacts across the Pistoia Alliance ecosystem.
This UXLS resource explains what a UX Community of Practice (CoP) is, why it matters, and how it connects teams working in isolation.
The Digital Accessibility Starter Guide is a succinct one-page compilation of digital accessibility heuristics designed to guide interface reviews. While it is not comprehensive documentation, nor is it a substitute for a thorough audit, it can facilitate the early and consistent integration of digital accessibility considerations into the product and project roadmaps.
A FAIR toolkit/use case focused on best practices for the use of Artificial Intelligence and Machine Learning in Life Sciences research.
An operational framework to support life sciences organizations in scaling up their user research.
This guide was created and is maintained as part of the FAIR implementation project by the Pistoia Alliance and consists of three parts: Introduction, Metadata and Application.
Home of the HELM notation - representing complex biomolecules
These set of heuristics will help you to better apply good design practices when working with data driven projects.
Recently, artificial intelligence (AI) and machine learning (ML) technologies in the biotechnology and pharmaceutical industries moved beyond experiments conducted by a few dedicated specialists and entered the industry mainstream. With this transition comes the need to formalize and publish the lessons learned by early adopters.
These Best Practice Guidelines are created to provide a strategy that derives as much value as possible to the study collecting the data, the participants who supply the data and any external users who are reusing the data outside of its original intended use.
This Quality Data Generation and Ethical Use (QDatE) code of ethics is complementary to the Best Practice Guidelines and will ensure that the sensor-generated data from remote monitoring technologies (SDRM) is collected, stored, governed, used, and reused in a way that utilises the data to the best of its potential.
This document provides guidelines for implementing ISO 11238. This document is developed in response to a worldwide demand for guidance on the implementation of internationally harmonized specifications for medicinal products.
