Collaborative Research: ABI Innovation: Rapid prototyping of semantic enhancements to biodiversity informatics platforms

合作研究：ABI 创新：生物多样性信息学平台语义增强的快速原型设计

• 批准号: 1356381
• 负责人: Andrew Deans
• 金额: $ 19.28万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-06-15 至 2016-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1356381&HistoricalAwards=false
• 关键词: Collaborative; Research; ABI; Innovation; Rapid

This research aims to help scientists develop and use relatively simple tools to describe species in a way that makes those descriptions easier to share with other scientists and easier for computers to process and analyze. Taxonomists are scientists who describe the world's biodiversity. Taxonomists' descriptions of millions of species allow scientists to do many different kinds of research, including basic biology, environmental science, climate research, agriculture, and medicine. The problem is that describing any one species is not easy. The language used by taxonomists to describe their data is complex, and typically not easily understandable by computers nor even other scientists. This situation makes it difficult to search for patterns across the millions of species that have been documented by thousands of different researchers over many decades of work worldwide. Innovation from this project is applicable to the long-term development of open source software initiatives serving laboratories throughout the world, and the research facilitates the production of open, shared data, as mandated by various federal agencies. As a result of this project, these data will become more accessible and informative to the general public. The project provides rich, real-world training for graduate students in library and information sciences, training them to be cross-disciplinary researchers in a field that is in need of new experts. Collaborating experts studying bees, wasps, and ants will receive training on the cutting edge theories and methods from the bioinformatics toolbox developed as a consequence of this project. In return their contributions of data will act as the basis for computational benchmarks needed in areas of logical inference and data modeling.This research addresses the problem of how to produce and utilize semantic data, specifically semantic phenotypes, within the taxonomic context of describing the Earth's biological diversity. The approach to be taken is bottom-up and iterative, involving the rapid prototyping of tools, combining of existing tools, and the tailoring of applications developed for one purpose but now being reused for this scientific activity. Scientists are busy innovating partial solutions by tinkering with and combining available computer programs and datasets. Their efforts comprise an incredibly productive source of innovation, since it is often much easier and faster to combine computer resources that already exist than to build something from scratch. However such cobbling together of resources to meet a need can benefit from analysis and active support. In particular, a more principled set of approaches can make innovations easier to share and to maintain. With a focus on the Hymenoptera, the researchers plan an innovative approach for biodiversity informatics based on work in the field of Computer Supported Cooperative Work (CSCW). Using a combination of ethnography to define work practice, user-centered design, and iterative agile software development, the collaboration between information scientists, biologists, and application developers aims to produce a suite of concrete deliverables, a rapid prototype portfolio, comprising interface and workflow tools, and end user requirements for semantic phenotype production. The project will explore and document examples of innovative prototyping of solutions by scientists to understand how it occurs, what it is that scientists most need, and how these can be most effectively supported. These components may be generalized to allow broader scientific use.

这项研究旨在帮助科学家开发和使用相对简单的工具来描述物种，使这些描述更容易与其他科学家分享，也更容易被计算机处理和分析。分类学家是描述世界生物多样性的科学家。分类学家对数以百万计的物种的描述使科学家能够进行许多不同种类的研究，包括基础生物学、环境科学、气候研究、农业和医学。问题是描述任何一个物种都不容易。分类学家用来描述他们的数据的语言很复杂，通常不容易被计算机甚至其他科学家理解。这种情况使得在全世界数千名不同的研究人员在数十年的工作中记录的数百万种物种中寻找模式变得困难。该项目的创新适用于为世界各地的实验室服务的开源软件计划的长期发展，并且该研究促进了开放、共享数据的生产，这是由各个联邦机构授权的。由于这个项目，这些数据将更容易为一般公众所获取和提供信息。该项目为图书馆与信息科学领域的研究生提供丰富的、现实的培训，培养他们成为一个需要新专家的领域的跨学科研究人员。研究蜜蜂、黄蜂和蚂蚁的合作专家将接受来自生物信息学工具箱的前沿理论和方法的培训，这些工具箱是该项目开发的结果。作为回报，他们提供的数据将作为逻辑推理和数据建模领域所需的计算基准的基础。本研究解决了如何在描述地球生物多样性的分类学背景下产生和利用语义数据，特别是语义表型的问题。要采取的方法是自底向上和迭代的，包括工具的快速原型，现有工具的组合，以及为一个目的开发的应用程序的裁剪，但现在被用于这项科学活动。科学家们正忙于通过修补和组合现有的计算机程序和数据集来创新部分解决方案。他们的努力构成了令人难以置信的富有成效的创新源泉，因为将已有的计算机资源组合起来通常比从头开始构建要容易得多，也要快得多。然而，这种拼凑资源以满足需求的做法可以从分析和积极支持中受益。特别是，一套更有原则的方法可以使创新更容易分享和维护。以膜翅目昆虫为研究对象，研究人员提出了一种基于计算机支持协同工作（CSCW）的生物多样性信息学创新方法。结合民族志来定义工作实践、以用户为中心的设计和迭代敏捷软件开发，信息科学家、生物学家和应用程序开发人员之间的合作旨在产生一套具体的可交付成果、一个快速的原型组合，包括接口和工作流工具，以及最终用户对语义表型生产的需求。该项目将探索并记录科学家创新解决方案原型的例子，以了解它是如何发生的，科学家最需要的是什么，以及如何最有效地支持这些解决方案。这些成分可以推广到更广泛的科学用途。