{"title":"PyGeoweaver：有形的工作流程工具，用于提高科研生产力和公平性","authors":"Gokul Prathin, Ziheng Sun, Sanjana Achan","doi":"10.1016/j.softx.2024.101863","DOIUrl":null,"url":null,"abstract":"<div><p>Scientific research faces workflow inefficiencies and reproducibility issues. PyGeoweaver, a Python library, helps manage data pipelines to address these problems. It stands out for its accessibility and ease of use, making it ideal for individual researchers and small teams. Unlike traditional systems that demand extensive technical expertise, it is designed to be beginner-friendly, allowing anyone to work with it without encountering significant technical hurdles. It can help researchers intuitively design workflows, retrieve data, and analyse it efficiently. It also offers compelling benefits for AI use cases, enabling researchers to develop and deploy AI models with ease. Serving as a decentralised hub for workflow management, it ensures discoverability, accessibility, and reusability of scientific workflows, fostering collaboration and research reproducibility. The paper will introduce its technical framework, present successful applications, and share insights from user feedback. Based on our research experiences in the past two years, PyGeoweaver has proven to be a valuable tool, enabling researchers to attain significant research progress with minimal technical complexities.</p></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"27 ","pages":"Article 101863"},"PeriodicalIF":2.4000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352711024002334/pdfft?md5=978358f11fdf3f15caac910e16a9335e&pid=1-s2.0-S2352711024002334-main.pdf","citationCount":"0","resultStr":"{\"title\":\"PyGeoweaver: Tangible workflow tool for enhancing scientific research productivity and FAIRness\",\"authors\":\"Gokul Prathin, Ziheng Sun, Sanjana Achan\",\"doi\":\"10.1016/j.softx.2024.101863\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Scientific research faces workflow inefficiencies and reproducibility issues. PyGeoweaver, a Python library, helps manage data pipelines to address these problems. It stands out for its accessibility and ease of use, making it ideal for individual researchers and small teams. Unlike traditional systems that demand extensive technical expertise, it is designed to be beginner-friendly, allowing anyone to work with it without encountering significant technical hurdles. It can help researchers intuitively design workflows, retrieve data, and analyse it efficiently. It also offers compelling benefits for AI use cases, enabling researchers to develop and deploy AI models with ease. Serving as a decentralised hub for workflow management, it ensures discoverability, accessibility, and reusability of scientific workflows, fostering collaboration and research reproducibility. The paper will introduce its technical framework, present successful applications, and share insights from user feedback. Based on our research experiences in the past two years, PyGeoweaver has proven to be a valuable tool, enabling researchers to attain significant research progress with minimal technical complexities.</p></div>\",\"PeriodicalId\":21905,\"journal\":{\"name\":\"SoftwareX\",\"volume\":\"27 \",\"pages\":\"Article 101863\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2024-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2352711024002334/pdfft?md5=978358f11fdf3f15caac910e16a9335e&pid=1-s2.0-S2352711024002334-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SoftwareX\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352711024002334\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SoftwareX","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352711024002334","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
PyGeoweaver: Tangible workflow tool for enhancing scientific research productivity and FAIRness
Scientific research faces workflow inefficiencies and reproducibility issues. PyGeoweaver, a Python library, helps manage data pipelines to address these problems. It stands out for its accessibility and ease of use, making it ideal for individual researchers and small teams. Unlike traditional systems that demand extensive technical expertise, it is designed to be beginner-friendly, allowing anyone to work with it without encountering significant technical hurdles. It can help researchers intuitively design workflows, retrieve data, and analyse it efficiently. It also offers compelling benefits for AI use cases, enabling researchers to develop and deploy AI models with ease. Serving as a decentralised hub for workflow management, it ensures discoverability, accessibility, and reusability of scientific workflows, fostering collaboration and research reproducibility. The paper will introduce its technical framework, present successful applications, and share insights from user feedback. Based on our research experiences in the past two years, PyGeoweaver has proven to be a valuable tool, enabling researchers to attain significant research progress with minimal technical complexities.
期刊介绍：
SoftwareX aims to acknowledge the impact of software on today''s research practice, and on new scientific discoveries in almost all research domains. SoftwareX also aims to stress the importance of the software developers who are, in part, responsible for this impact. To this end, SoftwareX aims to support publication of research software in such a way that: The software is given a stamp of scientific relevance, and provided with a peer-reviewed recognition of scientific impact; The software developers are given the credits they deserve; The software is citable, allowing traditional metrics of scientific excellence to apply; The academic career paths of software developers are supported rather than hindered; The software is publicly available for inspection, validation, and re-use. Above all, SoftwareX aims to inform researchers about software applications, tools and libraries with a (proven) potential to impact the process of scientific discovery in various domains. The journal is multidisciplinary and accepts submissions from within and across subject domains such as those represented within the broad thematic areas below: Mathematical and Physical Sciences; Environmental Sciences; Medical and Biological Sciences; Humanities, Arts and Social Sciences. Originating from these broad thematic areas, the journal also welcomes submissions of software that works in cross cutting thematic areas, such as citizen science, cybersecurity, digital economy, energy, global resource stewardship, health and wellbeing, etcetera. SoftwareX specifically aims to accept submissions representing domain-independent software that may impact more than one research domain.
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