Third Workshop on an Open Knowledge Network: Building the National Semantic Information Infrastructure

第三届开放知识网络研讨会：建设国家语义信息基础设施

• 批准号: 1758599
• 负责人: Sharat Israni
• 金额: $ 4.85万
• 依托单位: University of California-San Francisco
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-11-01 至 2018-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1758599&HistoricalAwards=false
• 关键词: Third; Workshop; Open; Knowledge; Network

This workshop engages a multidisciplinary community in a discussion about taking the initial steps in building an evolving Open Knowledge Network to encode all entities and the relationships among them, that would evolve continuously with new data and information. The OKN would thus be a fundamental building block in evolving the world-wide web to a new level of semantic understanding and application. The vision of such a knowledge graph is feasible given the availability of big data that are growing with time; advanced machine learning techniques that can aid in the creation of such a massive graph, and in its use; and, importantly, demonstration of the power of such knowledge graphs via extant commercial services such as Apple Siri; GoogleTalk; Amazon Alexa, and Microsoft Cortana. An Open Knowledge Network would enable a new generation of knowledge-rich intelligent applications and systems. The workshop examines the applicability of this idea across multiple disciplines and applications domains. Experts from a wide range of disciplines, including biomedicine, medicine, geosciences, finance, and manufacturing, will discuss domain-specific issues as well as identify common approaches and common issues that cut across domains. The workshop will develop concrete steps to be taken to help realize the vision of OKN.Natural interfaces to large knowledge structures have the potential to impact science, education and business to an extent comparable to the WWW. While the first wave of such technology is now available in consumer services such as Siri, GoogleTalk, Cortana and Alexa, these services are limited in their scope of knowledge; not open to direct access or to contributors beyond their corporate firewalls; and, able to answer only relatively limited questions in specific business domains. An open initiative of the type being proposed would allow for experimentation at scale across many user communities and would support research and innovation in academia, enable industry to experiment, and enable governments at various levels (local, state, federal) to create new services using Open Data. The vision for the proposed OKN is that it would aspire to be a listing of every known concept from the worlds of science, business, medicine and human affairs. It would include not just raw data, but semantic information in machine readable form. The architecture would allow contributors to encode the knowledge related to their topics of interest and, thus, connect that to the larger network, without having to go through so-called "gatekeepers". By providing an open service, OKN would enable the notion of "permission-less innovation." Indeed, an open resource like OKN may be in a better position to provide more trustworthy information/knowledge than proprietary, closed systems. The vision for creating such a common knowledge network resonates with the NSF Big Ideas of Harnessing the Data Revolution and Convergence.

本次研讨会吸引了多学科社区参与讨论，讨论如何采取初步步骤构建不断发展的开放知识网络，以对所有实体及其之间的关系进行编码，该网络将随着新的数据和信息而不断发展。因此，OKN 将成为将万维网发展到语义理解和应用新水平的基本构建块。考虑到随着时间的推移而增长的大数据的可用性，这种知识图谱的愿景是可行的；先进的机器学习技术可以帮助创建如此庞大的图表及其使用；重要的是，通过 Apple Siri 等现有商业服务展示了此类知识图的力量；谷歌谈话；亚马逊 Alexa 和微软 Cortana。开放知识网络将实现新一代知识丰富的智能应用程序和系统。该研讨会探讨了这一想法在多个学科和应用领域的适用性。 来自生物医学、医学、地球科学、金融和制造等多个学科的专家将讨论特定领域的问题，并确定跨领域的通用方法和常见问题。该研讨会将制定具体步骤来帮助实现 OKN 的愿景。与大型知识结构的自然接口有可能对科学、教育和商业产生与 WWW 相当的影响。虽然第一波此类技术现已应用于 Siri、GoogleTalk、Cortana 和 Alexa 等消费者服务中，但这些服务的知识范围有限；不向直接访问或超出公司防火墙的贡献者开放；并且只能回答特定业务领域中相对有限的问题。 所提议的此类开放倡议将允许在许多用户社区进行大规模实验，并支持学术界的研究和创新，使工业界能够进行实验，并使各级政府（地方、州、联邦）能够使用开放数据创建新服务。拟议的 OKN 的愿景是，它希望成为科学、商业、医学和人类事务领域所有已知概念的列表。它不仅包括原始数据，还包括机器可读形式的语义信息。该架构将允许贡献者对与其感兴趣的主题相关的知识进行编码，从而将其连接到更大的网络，而无需通过所谓的“看门人”。通过提供开放服务，OKN 将实现“无需许可的创新”的概念。事实上，像 OKN 这样的开放资源可能比专有的封闭系统更能提供更值得信赖的信息/知识。创建这样一个公共知识网络的愿景与 NSF 利用数据革命和融合的大理念产生了共鸣。