• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

轻量级分布式 Provenance 模型用于复杂的真实环境。

Lightweight Distributed Provenance Model for Complex Real-world Environments.

机构信息

BBMRI-ERIC, Neue Stiftingtalstrasse 2, 8010, Graz, Austria.

Faculty of Informatics, Masaryk University, Botanická 68a, 602 00, Brno, Czech Republic.

出版信息

Sci Data. 2022 Aug 17;9(1):503. doi: 10.1038/s41597-022-01537-6.

DOI:10.1038/s41597-022-01537-6
PMID:35977957
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9383664/
Abstract

Provenance is information describing the lineage of an object, such as a dataset or biological material. Since these objects can be passed between organizations, each organization can document only parts of the objects life cycle. As a result, interconnection of distributed provenance parts forms distributed provenance chains. Dependant on the actual provenance content, complete provenance chains can provide traceability and contribute to reproducibility and FAIRness of research objects. In this paper, we define a lightweight provenance model based on W3C PROV that enables generation of distributed provenance chains in complex, multi-organizational environments. The application of the model is demonstrated with a use case spanning several steps of a real-world research pipeline - starting with the acquisition of a specimen, its processing and storage, histological examination, and the generation/collection of associated data (images, annotations, clinical data), ending with training an AI model for the detection of tumor in the images. The proposed model has become an open conceptual foundation of the currently developed ISO 23494 standard on provenance for biotechnology domain.

摘要

起源是描述对象（如数据集或生物材料）血统的信息。由于这些对象可以在组织之间传递，因此每个组织只能记录对象生命周期的部分内容。因此，分布式起源部分的互连形成分布式起源链。根据实际起源内容，完整的起源链可以提供可追溯性，并有助于研究对象的可重复性和 FAIR 性。在本文中，我们定义了一个基于 W3C PROV 的轻量级起源模型，该模型能够在复杂的多组织环境中生成分布式起源链。该模型的应用通过一个用例演示，该用例跨越了现实世界研究管道的多个步骤——从获取标本开始，然后对其进行处理和存储，进行组织学检查，并生成/收集相关数据（图像、注释、临床数据），最后使用 AI 模型检测图像中的肿瘤。所提出的模型已成为目前正在开发的生物技术领域起源的 ISO 23494 标准的开放概念基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7744/9385740/f754bf266f53/41597_2022_1537_Fig16_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7744/9385740/02ca31a1c4d2/41597_2022_1537_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7744/9385740/88b85197e377/41597_2022_1537_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7744/9385740/7e37655701be/41597_2022_1537_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7744/9385740/047b27e24740/41597_2022_1537_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7744/9385740/e7a7aa568ec2/41597_2022_1537_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7744/9385740/834b13b553c7/41597_2022_1537_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7744/9385740/77d1fb455663/41597_2022_1537_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7744/9385740/8ac6908e1db1/41597_2022_1537_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7744/9385740/d0053d8e9a9e/41597_2022_1537_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7744/9385740/a567a8a48e31/41597_2022_1537_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7744/9385740/57f52b7cfed1/41597_2022_1537_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7744/9385740/40611effb86d/41597_2022_1537_Fig12_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7744/9385740/a5f1835ebe60/41597_2022_1537_Fig13_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7744/9385740/bc75df7d9ced/41597_2022_1537_Fig14_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7744/9385740/76776e4b6756/41597_2022_1537_Fig15_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7744/9385740/f754bf266f53/41597_2022_1537_Fig16_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7744/9385740/02ca31a1c4d2/41597_2022_1537_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7744/9385740/88b85197e377/41597_2022_1537_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7744/9385740/7e37655701be/41597_2022_1537_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7744/9385740/047b27e24740/41597_2022_1537_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7744/9385740/e7a7aa568ec2/41597_2022_1537_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7744/9385740/834b13b553c7/41597_2022_1537_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7744/9385740/77d1fb455663/41597_2022_1537_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7744/9385740/8ac6908e1db1/41597_2022_1537_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7744/9385740/d0053d8e9a9e/41597_2022_1537_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7744/9385740/a567a8a48e31/41597_2022_1537_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7744/9385740/57f52b7cfed1/41597_2022_1537_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7744/9385740/40611effb86d/41597_2022_1537_Fig12_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7744/9385740/a5f1835ebe60/41597_2022_1537_Fig13_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7744/9385740/bc75df7d9ced/41597_2022_1537_Fig14_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7744/9385740/76776e4b6756/41597_2022_1537_Fig15_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7744/9385740/f754bf266f53/41597_2022_1537_Fig16_HTML.jpg

相似文献

1
Lightweight Distributed Provenance Model for Complex Real-world Environments.轻量级分布式 Provenance 模型用于复杂的真实环境。
Sci Data. 2022 Aug 17;9(1):503. doi: 10.1038/s41597-022-01537-6.
2
Provenance of specimen and data - A prerequisite for AI development in computational pathology.标本和数据的来源——计算病理学中人工智能发展的前提。
N Biotechnol. 2023 Dec 25;78:22-28. doi: 10.1016/j.nbt.2023.09.006. Epub 2023 Sep 25.
3
The Common Provenance Model: Capturing Distributed Provenance in Life Sciences Processes.通用起源模型：捕获生命科学过程中的分布式起源。
Stud Health Technol Inform. 2022 May 25;294:415-416. doi: 10.3233/SHTI220489.
4
Sharing interoperable workflow provenance: A review of best practices and their practical application in CWLProv.共享可互操作的工作流溯源：最佳实践综述及其在 CWLProv 中的实际应用。
Gigascience. 2019 Nov 1;8(11). doi: 10.1093/gigascience/giz095.
5
PAV ontology: provenance, authoring and versioning.PAV本体：来源、创作与版本控制。
J Biomed Semantics. 2013 Nov 22;4(1):37. doi: 10.1186/2041-1480-4-37.
6
Practical Extension of Provenance to Healthcare Data Based on the W3C PROV Standard.基于W3C PROV标准的医疗数据溯源实用扩展
Stud Health Technol Inform. 2018;253:28-32.
7
Toward a common standard for data and specimen provenance in life sciences.迈向生命科学领域数据与样本来源的通用标准。
Learn Health Syst. 2023 Apr 18;8(1):e10365. doi: 10.1002/lrh2.10365. eCollection 2024 Jan.
8
Scientific Reproducibility in Biomedical Research: Provenance Metadata Ontology for Semantic Annotation of Study Description.生物医学研究中的科学可重复性：用于研究描述语义注释的来源元数据本体论
AMIA Annu Symp Proc. 2017 Feb 10;2016:1070-1079. eCollection 2016.
9
Decentralised provenance for healthcare data.医疗数据的去中心化来源。
Int J Med Inform. 2020 Sep;141:104197. doi: 10.1016/j.ijmedinf.2020.104197. Epub 2020 Jun 8.
10
Recording provenance of workflow runs with RO-Crate.使用 RO-Crate 记录工作流运行的出处。
PLoS One. 2024 Sep 10;19(9):e0309210. doi: 10.1371/journal.pone.0309210. eCollection 2024.

引用本文的文献

1
An open-source platform for structured annotation and computational workflows in digital pathology research.一个用于数字病理学研究中结构化注释和计算工作流程的开源平台。
Sci Rep. 2025 Aug 7;15(1):28910. doi: 10.1038/s41598-025-13546-7.
2
Recording provenance of workflow runs with RO-Crate.使用 RO-Crate 记录工作流运行的出处。
PLoS One. 2024 Sep 10;19(9):e0309210. doi: 10.1371/journal.pone.0309210. eCollection 2024.
3
Provenance Information for Biomedical Data and Workflows: Scoping Review.生物医学数据和工作流程的出处信息：范围综述。

本文引用的文献

1
The Common Provenance Model: Capturing Distributed Provenance in Life Sciences Processes.通用起源模型：捕获生命科学过程中的分布式起源。
Stud Health Technol Inform. 2022 May 25;294:415-416. doi: 10.3233/SHTI220489.
2
Decentralised provenance for healthcare data.医疗数据的去中心化来源。
Int J Med Inform. 2020 Sep;141:104197. doi: 10.1016/j.ijmedinf.2020.104197. Epub 2020 Jun 8.
3
The pandemic's first major research scandal erupts.这场疫情的首个重大研究丑闻爆发了。
J Med Internet Res. 2024 Aug 23;26:e51297. doi: 10.2196/51297.
4
Artificial intelligence based data curation: enabling a patient-centric European health data space.基于人工智能的数据整理：构建以患者为中心的欧洲健康数据空间。
Front Med (Lausanne). 2024 May 15;11:1365501. doi: 10.3389/fmed.2024.1365501. eCollection 2024.
5
Toward a common standard for data and specimen provenance in life sciences.迈向生命科学领域数据与样本来源的通用标准。
Learn Health Syst. 2023 Apr 18;8(1):e10365. doi: 10.1002/lrh2.10365. eCollection 2024 Jan.
6
"Be sustainable": EOSC-Life recommendations for implementation of FAIR principles in life science data handling.“保持可持续性”：EOSC-Life 关于在生命科学数据处理中实施 FAIR 原则的建议。
EMBO J. 2023 Dec 1;42(23):e115008. doi: 10.15252/embj.2023115008. Epub 2023 Nov 15.
Science. 2020 Jun 5;368(6495):1041-1042. doi: 10.1126/science.368.6495.1041.
4
Covid-19: 146 researchers raise concerns over chloroquine study that halted WHO trial.新冠疫情：146名研究人员对氯喹研究提出担忧，该研究叫停了世界卫生组织的试验。
BMJ. 2020 Jun 2;369:m2197. doi: 10.1136/bmj.m2197.
5
Sharing interoperable workflow provenance: A review of best practices and their practical application in CWLProv.共享可互操作的工作流溯源：最佳实践综述及其在 CWLProv 中的实际应用。
Gigascience. 2019 Nov 1;8(11). doi: 10.1093/gigascience/giz095.
6
Creating reproducible pharmacogenomic analysis pipelines.创建可重现的药物基因组学分析管道。
Sci Data. 2019 Sep 3;6(1):166. doi: 10.1038/s41597-019-0174-7.
7
The Possibility of Systematic Research Fraud Targeting Under-Studied Human Genes: Causes, Consequences, and Potential Solutions.针对研究不足的人类基因进行系统性研究欺诈的可能性：原因、后果及潜在解决方案
Biomark Insights. 2019 Feb 5;14:1177271919829162. doi: 10.1177/1177271919829162. eCollection 2019.
8
Enabling precision medicine via standard communication of HTS provenance, analysis, and results.通过标准的高通量筛选来源、分析和结果的交流来实现精准医疗。
PLoS Biol. 2018 Dec 31;16(12):e3000099. doi: 10.1371/journal.pbio.3000099. eCollection 2018 Dec.
9
Big Data Provenance: Challenges, State of the Art and Opportunities.大数据溯源：挑战、现状与机遇
Proc IEEE Int Conf Big Data. 2015 Oct-Nov;2015:2509-2516. doi: 10.1109/BigData.2015.7364047. Epub 2015 Dec 28.
10
Templates as a method for implementing data provenance in decision support systems.模板作为在决策支持系统中实现数据溯源的一种方法。
J Biomed Inform. 2017 Jan;65:1-21. doi: 10.1016/j.jbi.2016.10.022. Epub 2016 Nov 14.