链接开放数据有效性--来自ISWS 2018的技术报告
Linked Open Data Validity -- A Technical Report from ISWS 2018
摘要：
链接开放数据（LOD）是Web中公开可用的RDF数据。每个LOD实体都由URI标识，并可通过HTTP访问。LOD编码的全球范围内的知识可能提供给任何人以及人工智能，可能要从中受益的背景知识，以支持他们的任务。LOD已经成为自然语言处理、信息检索、计算机视觉、语音识别等不同领域应用的支柱。然而，无论基于LOD的工具旨在解决的具体任务，这些知识的重用可能是具有挑战性的各种原因，例如语义异构性，出处和数据质量。正如Heath等人恰当地指出的那样，“关联数据可能是过时的，不精确的，或者只是错误的”：有必要调查关联数据的有效性问题。这项工作报告了九个学生团队在同等数量的高级研究人员的指导下，参加国际语义网研究学院（ISWS 2018），从不同的角度以及不同的方法来解决这一问题。
英文摘要：
Linked Open Data (LOD) is the publicly available RDF data in the Web. Each LOD entity is identfied by a URI and accessible via HTTP. LOD encodes globalscale knowledge potentially available to any human as well as artificial intelligence that may want to benefit from it as background knowledge for supporting their tasks. LOD has emerged as the backbone of applications in diverse fields such as Natural Language Processing, Information Retrieval, Computer Vision, Speech Recognition, and many more. Nevertheless, regardless of the specific tasks that LOD-based tools aim to address, the reuse of such knowledge may be challenging for diverse reasons, e.g. semantic heterogeneity, provenance, and data quality. As aptly stated by Heath et al. Linked Data might be outdated, imprecise, or simply wrong": there arouses a necessity to investigate the problem of linked data validity. This work reports a collaborative effort performed by nine teams of students, guided by an equal number of senior researchers, attending the International Semantic Web Research School (ISWS 2018) towards addressing such investigation from different perspectives coupled with different approaches to tackle the issue.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
