全球标本数字化建设及共享发展趋势

Global specimen digitization and sharing trends

关键词:  标本数字化, 数据共享, GBIF, 公众科学, 生物多样性

Key words:  specimen digitization, data sharing, GBIF, citizen science, biodiversity

摘要:

标本数字化建设是生物多样性保护和利用的重要工作基础,通过标本数据的整合分析,在生物分类学、生态学、生物工程、生物保护、粮食安全、生物多样性评估、教学教育和人类社会活动等方面提供数据支撑。为了了解全球标本数字化建设工作的现状以及数据共享的策略与技术发展趋势,该文分别调查梳理了北美洲、南美洲、欧洲、非洲、亚洲和大洋洲地区的标本数字化和平台建设情况,对标本数据共享现状和趋势从数据使用协议、新技术新方法和公众科学等方面进行了对比和分析,并为中国国内的标本数字化工作提出了工作建议,包括:(1)加强标本数字化建设、管理和动态更新方面的协同机制建设,确保实物资源和数字化资源信息同步;(2)加强数据整理和发布,促进数据质量的提升,充分开放数据使用协议,减少数据使用的阻碍;(3)加强对新技术的学习和引入,特别是开源软件、机器学习和人工智能技术的应用,能够在标签快速识别、自动鉴定和属性数据提取等方面发挥作用;(4)加强区域和国际合作,推动数据的整合应用;(5)推动公众科学项目发展,促进野外采集、室内整理、在线纠错、数据产品研发等工作的开展。

Abstract:

The digitization of specimens is an important basis for the conservation and utilization of biodiversity. Through the integrated analysis of specimen data, it can provide data support in taxonomy, ecology, bioengineering, biological protection, food security, biodiversity assessment, human social activities and education and other aspects. At present, the development situation varies from country to country. In order to understand the current status of global specimen digitization work, as well as data sharing strategies and technology development trends, this article summarizes the status of specimen digitization and platform construction in North America, South America, Europe, Africa, Asia and Oceania, and reviews the status and trends of specimen data sharing from data use agreements, new technologies and methods, and citizen science using. After comparison and analysis with the current situation in China, proposed work suggestions, including(1)strengthening the construction of coordination mechanisms in the digital construction, management and dynamic update of specimens, ensuring the synchronization of physical resources and digital resource information;(2)strengthening data collation and publishing, promoting data quality improvement, fully opening data use agreements, and reducing data use obstacles;(3)strengthening the learning and introduction of new technologies, especially the application of open source software, machine learning and artificial intelligence technologies, which can play a role in rapid tag identification, automatic identification and attribute data extraction;(4)strengthening regional and international cooperation to promote data, and the integration and application of data products;(5)promoting the development of citizen science projects, and promote the development of field collection, indoor sorting, online error correction, and data product research and development.