NFDI4DS - NFDI for Data Science and Artificial Intelligence

NFDI4DataScience(NFDI4DS)的愿景是支持复杂和跨学科研究数据生命周期的所有步骤，包括收集/创建、处理、分析、发布、归档和重复使用数据科学和人工智能中的资源。过去几年发生了范式转变，计算方法越来越依赖于数据驱动的方法，往往是基于深度学习的方法，导致数据科学作为一门学科的建立和普遍存在，这一学科受到计算机科学领域的进步的推动，但与大多数科学学科相关。由于当代数据科学方法的复杂性，透明度、可重复性和公平性已成为数据科学和人工智能面临的关键挑战，这些方法往往依赖于用于训练的代码、模型和数据的组合。考虑到数据科学和人工智能方法对计算机科学以及广泛的科学学科日益重要，NFDI4DS将促进公平和开放的研究数据基础设施，通过综合方法支持所有相关资源，如代码、模型、数据或出版物。NFDI4DS的总体目标是为德国的数据科学和人工智能社区开发、建立和维持一个全国性的研究数据基础设施。这也将为需要数据分析解决方案的更广泛的社区带来好处，无论是在国家外国直接投资之内还是之外。其关键思想是努力提高数据科学和人工智能项目的透明度、再现性和公平性，通过提供所有数字文物，将它们相互联系，并提供创新的工具和服务。基于这些数字对象的重复使用，新的和创新的研究将成为可能。NFDI4DS打算在学术界代表数据科学和人工智能社区，这是一个植根于计算机科学的跨学科领域。我们的目标是重新利用现有的解决方案，并与其他NFDI财团和其他财团密切合作。在初始阶段，NFDI4DS将专注于四个数据科学密集应用领域：语言技术、生物医学科学、信息科学和社会科学。NFDI4DS提供的与数据科学和人工智能、基础设施开发和进一步的领域知识有关的专门知识确保了元数据标准可以跨域互操作，并产生了处理数字对象的新方法。

The vision of NFDI4DataScience (NFDI4DS) is to support all steps of the complex and interdisciplinary research data lifecycle, including collecting/creating, processing, analysing, publishing, archiving and reusing resources in Data Science and Artificial Intelligence. The past years have seen a paradigm shift, with computational methods increasingly relying on data-driven and often deep learning-based approaches, leading to the establishment and ubiquity of Data Science as a discipline driven by advances in the field of Computer Science but being of relevance to most scientific disciplines. Transparency, reproducibility and fairness have become crucial challenges for Data Science and Artificial Intelligence due to the complexity of contemporary Data Science methods, often relying on a combination of code, models and data used for training. Taking into account the increasing importance of Data Science and Artificial Intelligence methods for Computer Science as well as a broad range of scientific disciplines, NFDI4DS will promote FAIR and open research data infrastructures supporting all involved resources such as code, models, data, or publications through an integrated approach. The overarching objective of NFDI4DS is the development, establishment and sustainment of a national research data infrastructure for the Data Science and Artificial Intelligence community in Germany. This will also deliver benefits for a wider community requiring data analytics solutions, within the NFDI and beyond. The key idea is to work towards increasing the transparency, reproducibility and fairness of Data Science and Artificial Intelligence projects, by making all digital artefacts available, by interlinking them, and by offering innovative tools and services. Based on the reuse of these digital objects, new and innovative research will be enabled. NFDI4DS intends to represent the Data Science and Artificial Intelligence community in academia, which is an interdisciplinary field rooted in Computer Science. We aim to reuse existing solutions, and to collaborate closely with the other NFDI consortia and beyond. In the initial phase, NFDI4DS will focus on four Data Science intense application areas: language technology, biomedical sciences, information sciences and social sciences. The expertise available in NFDI4DS related to Data Science and Artificial Intelligence, infrastructure development and further domain knowledge ensures that metadata standards are interoperable across domains, and that new ways of dealing with digital objects arise.