EAGER: Open Science Data in Semantic Web Research

将开放科学确立为学术界的默认做法至关重要。报道一项研究成果不仅仅是手稿。它是实际进行的过程、数据(和元数据)、实现的软件(和环境)等等。询问与透明度和可再现性有关的问题也很重要，例如关于审查、发布元数据的问题，尤其是，作为其报告结果基础的数据和软件在哪里？通过开放科学实践在这些人工制品之间建立联系，它降低了理解(和复制)尖端研究的进入门槛，从而使研究民主化，同时通过减少重新实现软件或重新收集数据的需要，加快了新研究的速度。以有用和可理解的方式连接这些组件和数据是语义网研究的核心任务。投资促进机构建议利用内部监督办公室出版的语义网期刊的领导地位和声誉，以证明公开共享出版物底层的数据可以在没有重大管理费用的情况下进行，并提供显著的附加值。在这份期刊中，PIS将要求作者可持续地发布其结果所依据的数据和软件，将软件和数据提供作为同行审查评估的一部分，并为补充数据和软件发布丰富的元数据。PIS将开发支持开放科学的技术，并将与社区合作，完善软件和政策，以加强语义网期刊的开放科学。这种方法可以作为其他寻求采用类似开放科学数据实践蓝图的期刊编辑的典范。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Establishing Open Science as the default practice in the academic community is critical. Reporting a research result is more than just the manuscript. It is the actual process undertaken, the data (and metadata), the implemented software (and environment), and more. It is also important to ask questions pertaining to transparency and reproducibility, such as those regarding their reviews, publishing metadata, and, in particular, Where are the data and software that underlie their reported results? By making the connections between these artifacts through Open Science practices, it democratizes research by lowering the barrier of entry to understanding (and replicating) cutting edge research, while simultaneously accelerating novel research by reducing the need to re-implement software or re-collect data. Connecting these components and data in a useful and understandable way is a core mission of Semantic Web research. The PIs propose to leverage the leadership and reputation of the Semantic Web journal by IOS Press to demonstrate that the open sharing of data underlying publications can be done without significant overhead and provides significant added value. The PIs will, for this journal, require authors to sustainably publish the data and software underlying their results, include software and data provision as part of the peer review assessment, and publish rich metadata for the supplementary data and software. The PIs will develop technology in support of open science and will work with the community to refine the software and policies that enhance open science for the Semantic Web journal. The approach can serve as a model for other journal editors who seek a blueprint for adopting similar Open Science Data practices.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.