Biomedical Scholarly Article Editing and Sharing using Holistic Semantic Uplifting Approach
Biomedical Scholarly Article Editing and Sharing using Holistic Semantic Uplifting Approach
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DOI：
10.32473/flairs.v35i.130695
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发表时间：
2022-05
期刊：
影响因子：
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通讯作者：
Asim Abbas;Steve Fonin Mbouadeu;Fazel Keshtkar;Joan DeBello;Syed Ahmad Chan Bukhari
中科院分区：
文献类型：
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作者：
Asim Abbas;Steve Fonin Mbouadeu;Fazel Keshtkar;Joan DeBello;Syed Ahmad Chan Bukhari
提供生物医学出版物的有效做法有助于将信息从科学研究界及时传递给同行研究人员和其他医疗保健从业者。目前，可移植文档格式（PDF）是离线共享科学知识的主要格式之一。此外，还引入了一些基于 HTML 的格式来在线共享科学内容。在线搜索引擎（例如 GoogleScholar）需要机器可解释的元数据，以上下文感知的方式正确索引项目，以实现准确的生物医学文献搜索。我们开发了一种轻量级技术基础设施（goSemantically），并将其小型化为 Google Docs 插件，帮助作者在创作生物医学内容时在内容和结构级别添加机器可解释的元数据。该基础设施使用 NCBO Bioportal 资源，用适当的语义词汇来注释生物医学内容。它进一步利用 Schema.org 元标记，并为用户提供直观的界面来在文档级别关联语义标记。此外，我们的基础设施支持用户以各种在线可互操作格式导出内容，保留嵌入的语义。因此，生物医学元数据内容很容易被搜索引擎索引，从而更适合语义智能搜索。
Efficient practices to provide access to biomedical publications facilitate the timely transfer of information from the scientific research community to peer investigators and other healthcare practitioners. At present, the portable document format (PDF) is one of the dominating formats to share scientific knowledge offline. Additionally, some HTML-based formats have been introduced to share scientific content online. Online Search engines, e.g., GoogleScholar, require machine-interpretable metadata to correctly index items in a context-aware manner for accurate biomedical literature searches. We have developed a lightweight technical infrastructure (goSemantically) and miniaturized that as Google Docs add-ons that helps authors to add machine-interpretable metadata at the content and structural levels while authoring biomedical content. The infrastructure uses the NCBO Bioportal resources to annotate the biomedical content with appropriate semantic vocabularies. It further utilizes the Schema.org meta tags and provides an intuitive interface for users to associate the semantics tags at the document level. Additionally, our infrastructure supports users in exporting their content in various online interoperable formats preserving the embedded semantics. As a result, the biomedical metadata content would easily be indexed by search engines, making them more favorable for semantic intelligence searches.