Process-Sensitive Naming: Trait Descriptors and the Shifting Semantics of Plant (Data) Science
Process-Sensitive Naming: Trait Descriptors and the Shifting Semantics of Plant (Data) Science
复制标题
过程敏感命名：性状描述符和植物（数据）科学的语义变化
DOI：
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
S. Leonelli
中科院分区：
文献类型：
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作者：
S. Leonelli
本文探讨了植物数据语义领域的分类实践，特别是用于标记植物性状的方法，以促进跨地点作物数据的收集、管理、联系和分析，这对植物和农业的研究和干预至关重要。共享数据所需的努力突出了用于捕获植物变异的生物和环境特征的系统的多样性形式：特别是生物，文化，科学和语义多样性影响植物性状的识别和描述，用于生成和处理数据的方法，以及具有相关专业知识的人（包括农民和育种者）的目标和技能。通过研究作物本体论（明确承认和谈判的多样性）及其应用木薯育种，我认为一个过程敏感的方法来命名的植物性状，重点是记录环境过程，而不是生物产品。我认为，这种方法可以促进植物数据的可靠联系和强大的再利用，同时促进数据科学家、植物研究人员、育种者和其他相关专家之间的对话，为农业干预提供重要信息。我的结论是，数据语义和相关的描述符的研究构成了一个富有成效的和underexplored的方式来思考植物科学中的命名特征的认识进口。努力阐明植物品种和数据处理方法之间的语义差异，可以产生新的包容性的方式来发展和交流生物知识。反过来，这种做法有可能挑战现有对生物学专业知识系统化和层次结构的理解，从而提高植物科学支持生物多样性和可持续农业的程度。
This paper examines classification practices in the domain of plant data semantics, and particularly methods used to label plant traits to foster the collection, management, linkage and analysis of data about crops across locations—which crucially inform research and interventions on plants and agriculture. The efforts required to share data place in sharp relief the forms of diversity characterizing the systems used to capture the biological and environmental characteristics of plant variants: particularly the biological, cultural, scientific and semantic diversity affecting the identification and description of plant traits, the methods used to generate and process data, and the goals and skills of those with relevant expertise—including farmers and breeders. Through a study of the Crop Ontology (which explicitly recognizes and negotiates diversity) and its application to cassava breeding, I argue for a process-sensitive approach to the naming of plant traits that focuses on documenting environmental processes instead of biological products. I claim that this approach can foster reliable linkage and robust re-use of plant data, while at the same time facilitating dialogue between data scientists, plant researchers, breeders, and other relevant experts in ways that crucially inform agricultural interventions. I conclude that the study of data semantics and related descriptors constitutes a productive and underexplored way to think about the epistemic import of naming traits within plant science. The effort to articulate semantic differences among plant varieties and methods of data processing can generate newly inclusive ways to develop and communicate biological knowledge. In turn, such practices have the potential to defy existing understandings of systematisation and hierarchies of expertise in biology, thus bolstering the extent to which plant science can support biodiversity and sustainable agriculture.
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植物和农业研究中人工智能的数据管理挑战
影响因子：
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作者：
Williamson H
通讯作者：
Williamson H
联合收割机会说出真相：论精准农业与算法合理性
影响因子：
8.5
作者：
Miles, Christopher
通讯作者：
Miles, Christopher