Making Software FAIR: A machine-assisted workflow for the research software lifecycle

让软件公平:研究软件生命周期的机器辅助工作流程

基本信息

  • 批准号:
    EP/Y036352/1
  • 负责人:
  • 金额:
    $ 15.7万
  • 依托单位:
  • 依托单位国家:
    英国
  • 项目类别:
    Research Grant
  • 财政年份:
    2024
  • 资助国家:
    英国
  • 起止时间:
    2024 至 无数据
  • 项目状态:
    未结题

项目摘要

A key issue hindering the discoverability, attribution and reusability of open research software is that its existence often remains hidden within the manuscript of research papers. For these resources to become first-class bibliographic records, they first need to be identified and subsequently registered with persistent identifiers (PIDs) to be made FAIR (Findable, Accessible, Interoperable and Reusable). To this day, much open research software fails to meet FAIR principles and software resources are mostly not explicitly linked from the manuscripts that introduced them or used them.This project will extend the capabilities of critical and widely used open scholarly infrastructures (CORE,Software Heritage, HAL) and tools (GROBID) operated by the consortium partners, delivering and deploying an effective solution for the management of the research software lifecycle, including: 1)ML-assisted identification of research software assets from within the manuscripts of scholarly papers, 2)validation of the identified assets by authors, 3) registration of software assets with PIDs and their archival. The solution will be optimised for deployment over open content available through the global network of open repositories aggregated by CORE (core.ac.uk), which constitutes with over 32 million full texts and250m+ metadata records from over 10k repositories currently the world's largest collection of open access documents. Our ML software for extraction and disambiguation of software assets will be realised as an extension of the state-of-the-art GROBID tool. We will build on established protocols, such as asOpenAIRE Guidelines v4.0, RIOXX v3 and Codemeta, to encode information about software assets and their links to research manuscripts establishing an interoperable and extensible workflow connecting open repositories (represented by HAL), aggregators (represented by CORE) and software archives(represented by Software Heritage). The efficacy of the developed tools and workflow will be validated in three use cases: 1) a life sciences demonstrator (for Europe PMC), 2) a multi-disciplinary demonstrator for institutional repositories (represented by HAL) and a 3) digital humanities case study (with links to DARIAH and EOSC).
阻碍开放研究软件的可解释性、归属性和可重用性的一个关键问题是,它的存在往往隐藏在研究论文的手稿中。为了使这些资源成为一流的书目记录,首先需要对其进行标识,然后使用永久标识符(PID)进行注册,以使其成为FAIR(可查找,可扩展,可互操作和可重用)。迄今为止,许多开放式研究软件未能满足FAIR原则,软件资源大多没有与介绍或使用它们的手稿明确链接。本项目将扩展关键和广泛使用的开放式学术基础设施的功能(CORE,Software Heritage,HAL)和工具(GROBID)由联盟合作伙伴运营,为研究软件生命周期的管理提供和部署有效的解决方案,包括:1)ML辅助从学术论文的手稿中识别研究软件资产,2)由作者验证识别的资产,3)用PID登记软件资产并存档。该解决方案将针对通过CORE(core.ac.uk)聚合的开放资源库全球网络提供的开放内容进行优化部署,该网络由来自超过1万个资源库的超过3200万个全文和2.5亿+元数据记录组成,目前是世界上最大的开放获取文档集合。我们用于提取和消除软件资产歧义的ML软件将作为最先进的GROBID工具的扩展来实现。我们将建立在已建立的协议上,如OpenAIRE Guidelines v4.0、RIOXX v3和Codemeta,对有关软件资产及其与研究手稿的链接的信息进行编码,建立一个可互操作和可扩展的工作流程,连接开放存储库(以HAL为代表)、聚合器(以CORE为代表)和软件存档(以Software Heritage为代表)。开发的工具和工作流程的有效性将在三个用例中得到验证:1)生命科学演示器(欧洲PMC),2)机构知识库的多学科演示器(由HAL代表)和3)数字人文案例研究(与DARIAH和EOSC链接)。

项目成果

期刊论文数量(0)
专著数量(0)
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会议论文数量(0)
专利数量(0)

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Petr Knoth其他文献

Information Retrieval Evaluation in Knowledge Acquisition Tasks
知识获取任务中的信息检索评估
  • DOI:
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Yasin Ghafourian;Petr Knoth;A. Hanbury
  • 通讯作者:
    A. Hanbury
Semantic annotation of multilingual learning objects based on a domain ontology
基于领域本体的多语言学习对象语义标注
  • DOI:
  • 发表时间:
    2009
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Petr Knoth
  • 通讯作者:
    Petr Knoth
Quantifying the influence of Open Access on innovation and patents
量化开放获取对创新和专利的影响
  • DOI:
    10.12688/openreseurope.14680.1
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    0
  • 作者:
    N. Jahn;Thomas Klebel;David Pride;Petr Knoth;Tony Ross
  • 通讯作者:
    Tony Ross
VoMBaT: A Tool for Visualising Evaluation Measure Behaviour in High-Recall Search Tasks
VoMBaT:高召回率搜索任务中可视化评估测量行为的工具
Can we do better than Co-Citations? - Bringing Citation Proximity Analysis from idea to practice in research article recommendation
我们能比共同引用做得更好吗?
  • DOI:
  • 发表时间:
    2017
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Petr Knoth;Anita Khadka
  • 通讯作者:
    Anita Khadka

Petr Knoth的其他文献

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