University of Maryland School of Medicine, Institute for Genome Sciences, 670 W. Baltimore St., HSFIII, Baltimore, MD 21201, USA.
Database (Oxford). 2023 Feb 28;2023. doi: 10.1093/database/baad007.
As a genomic resource provider, grappling with getting a handle on how your resource is utilized can be extremely challenging. At the same time, being able to thus document the plethora of use cases is vital to demonstrate sustainability. Herein, we describe a flexible workflow, built on readily available software, that the Human Disease Ontology (DO) project has utilized to transition to semi-automated methods to identify uses of the ontology in the published literature. The novel R package DO.utils (https://github.com/DiseaseOntology/DO.utils) has been devised with a small set of key functions to support our usage workflow in combination with Google Sheets. Use of this workflow has resulted in a 3-fold increase in the number of identified publications that use the DO and has provided novel usage insights that offer new research directions and reveal a clearer picture of the DO's use and scientific impact. The DO's resource use assessment workflow and the supporting software are designed to be useful to other resources, including databases, software tools, method providers and other web resources, to achieve similar results. Database URL: https://github.com/DiseaseOntology/DO.utils.
作为基因组资源提供者,要掌握资源的利用方式可能极具挑战性。同时,能够记录大量的用例对于证明可持续性至关重要。在此,我们描述了一个灵活的工作流程,该流程基于现成的软件,人类疾病本体(DO)项目已经利用该流程过渡到半自动化方法,以识别本体在已发表文献中的使用情况。新颖的 R 包 DO.utils(https://github.com/DiseaseOntology/DO.utils)设计了一组关键功能,以支持我们的使用工作流程与 Google Sheets 结合使用。该工作流程的使用使识别出使用 DO 的出版物数量增加了 3 倍,并提供了新的使用见解,为新的研究方向提供了线索,并更清晰地展示了 DO 的使用情况和科学影响力。DO 的资源使用评估工作流程和支持软件旨在为其他资源(包括数据库、软件工具、方法提供程序和其他网络资源)提供帮助,以实现类似的结果。数据库 URL:https://github.com/DiseaseOntology/DO.utils。