CCRI: Research Infrastructure: NEW: Semantic Scholar Open Data Platform: Enabling Research Into Scientific Search and Discovery

科学出版物的指数增长使得科学家很难跟踪各自领域的发展，也很难将不同的进展联系起来。作为回应，人工智能研究人员已经开始开发技术，使计算机能够阅读科学论文，并自动对主题进行分类，提取关键结果，总结贡献，识别联系，并选择一组可能是每位科学家特别感兴趣的个性化论文。我们的持久愿景是建立能够处理海量学术文档语料库的人工智能系统，并增强人类科学家的能力--加快科学发现，帮助人类快速应对新冠肺炎疫情等灾难。拟议的语义学者开放数据平台建立了支持这项研究的基础设施，首先收集了一套全面的论文，并安排了有效的索引。该系统处理PDF格式的论文以提取信息，并使用先进的分析处理方法为研究人员提供访问结果的途径。该基础设施将极大地降低新手进入学术文件处理领域的门槛，提高实验的重复性，并加快人工智能增强的科学发现这一重要领域的创新拟议的基础设施是独一无二的，因为替代学术论文来源要么是封闭的、不完整的，要么是有限的方案访问，要么已经退役。拟议的语义学者开放数据平台有三个部分：1)一套全面的在线服务，使研究人员能够以编程方式搜索、过滤、提取、汇总和分析大型且不断更新的文档语料库；2)新机制，使研究人员能够策划自己的特定领域文本语料库，因为该团队之前为冠状病毒研究创建了CORD-19数据集；3)开放源代码软件，包括预先培训的语言模型和用户界面模板，作为研究构建块。这些基础设施将极大地降低新手进入学术文档处理领域的门槛，提高实验的重复性，并加快人工智能增强的科学发现这一重要领域的创新。幸运的是，最近在学术文件处理方面的研究增加(例如，我们的CORD-19数据集的迅速采用)表明，计算机和信息科学界有兴趣和能力开发新的技术，以加速科学和帮助应对流行病和气候变化等全球社会挑战。由此产生的人工智能增强的科学发现方面的进展将造福于科学的所有领域，推动医学进步，创造新的就业机会，并改善盲人研究人员的机会。我们将通过提供开放的服务、数据集、代码和相关的教育材料来改善全球基础设施。该团队还将与代表不足的STEM学生接触，并通过K-12外展。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。

The exponential growth of scientific publication makes it difficult for scientists to track developments in their field and make connections between different advances. In response, artificial-intelligence researchers have started to develop techniques that allow computers to ‘read’ scientific papers and automatically classify topics, extract key results, summarize contributions, identify connections, and select a personalized set of papers that may be of special interest to each scientist. The enduring vision is to build AI systems that can process an immense corpus of scholarly documents and augment the capabilities of human scientists – accelerating scientific discovery and helping humanity quickly confront disasters such as the COVID-19 pandemic. The proposed Semantic Scholar Open Data Platform builds infrastructure to support this research by first gathering a comprehensive set of papers and arranging for efficient indexing. The system processes PDF-formatted papers to extract information and use advanced analytic processing approaches to provide researchers access to results. The infrastructure will dramatically lower the barrier to entry for newcomers to the field of scholarly document processing, improve reproducibility of experiments, and accelerate innovation in the important area of AI-augmented scientific discoveryThe infrastructure proposed is unique, because alternative sources of academic papers are either closed, incomplete, have limited programmatic access, or have been retired. The proposed Semantic Scholar Open Data Platform has three parts: 1) a comprehensive set of online services enabling researchers to programmatically search, filter, extract, summarize, and analyze a large and continually-updated corpus of documents; 2) a new mechanism that enables researchers to curate their own domain-specific text corpora, as the team previously created the CORD-19 dataset for coronavirus research; 3) open source software, including pretrained language models and user interface templates to serve as research building blocks. Together the infrastructure will dramatically lower the barrier to entry for newcomers to the field of scholarly document processing, improve reproducibility of experiments, and accelerate innovation in the important area of AI-augmented scientific discovery. Fortunately, the recent increase in research in scholarly document processing (e.g., the rapid uptake of our CORD-19 dataset) shows that the computer and information science community has the interest and capability to develop new technologies that accelerate science and help meet global societal challenges, such as pandemics and climate change. The resulting advances in AI-augmented scientific discovery will benefit all areas of science, spurring medical advances, creating new jobs, and improving access for blind researchers. We will improve global infrastructure by providing open services, data sets, code, and associated educational materials. The team will also engage with underrepresented STEM students and through K-12 outreach.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.