检索结果-南通市图书馆

The Specimen Data Refinery:A Canonical Workflow Framework and FAIR Digital Object Approach to Speeding up Digital Mobilisation of Natural History Collections

引用

Data Intelligence 2022年第2期4卷 320-341页

作者： Alex Hardisty Paul Brack Carole Goble Laurence Livermore Ben Scott Quentin Groom Stuart Owen stian soiland-reyes School of Computer Science and Informatics Cardiff UniversityCardiff CF243AAUK The Department of Computer Science The University of ManchesterManchester M139PLUK The Natural History Museum London SW75BDUK Meise Botanic Garden 1860 MeiseBelgium Informatics Institute Faculty of ScienceUniversity of Amsterdam1090 GH AmsterdamThe Netherlands

A key limiting factor in organising and using information from physical specimens curated in natural science collections is making that information computable,with institutional digitization tending to focus more on imaging the specimens themselves than on efficiently capturing computable data about them.Label data are traditionally manually transcribed today with high cost and low throughput,rendering such a task constrained for many collection-holding institutions at current funding levels.We show how computer vision,optical character recognition,handwriting recognition,named entity recognition and language translation technologies can be implemented into canonical workflow component libraries with findable,accessible,interoperable,and reusable(FAIR)characteristics.These libraries are being developed in a cloudbased workflow plaform-the Specimen Data Refinery'(SDR)-founded on Galaxy workflow engine,Common Workflow Language,Research Object Crates(RO-Crate)and WorkflowHub technologies.The SDR can be applied to specimens'labels and other artefacts,offering the prospect of greatly accelerated and more accurate data capture in computable form.Two kinds of FAIR Digital Objects(FDO)are created by packaging outputs of SDR workflows and workflow components as digital objects with metadata,a persistent identifier,and a specific type definition.The first kind of FDO are computable Digital Specimen(DS)objects that can be consumed/produced by workflows,and other applications.A single DS is the input data structure submitted to a workflow that is modified by each workflow component in turn to produce a refined DS at the end.The Specimen Data Refinery provides a library of such components that can be used individually,or in series.To cofunction,each library component describes the fields it requires from the DS and the fields it will in turn populate or enrich.The second kind of FDO,RO-Crates gather and archive the diverse set of digital and real-world resources,configurations,and actions(the provenance)contributing to a unit

关键词： Digital Specimen Workflow FAIR Digital Object RO-Crate

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Making Canonical Workflow Building Blocks Interoperable across Workflow Languages

引用

Data Intelligence 2022年第2期4卷 342-357页

作者： stian soiland-reyes Genis Bayarri Pau Andrio Robin Long Douglas Lowe Ania Niewielska Adam Hospital Paul Groth Department of Computer Science The University of ManchesterManchester M139PLUK Informatics Institute University of AmsterdamAmsterdam 1098 XHThe Netherlands Institute for Research in Biomedicine(IRB Barcelona) The Barcelona Institute of Science and Technology(BIST)Barcelona O8028Spain The Spanish National Bioinformatics Institute(INB) Barcelona Supercomputing Center(BSC)Barcelona 08034Spain Data Science Institute Lancaster UniversityLancasterLancashire LA14YWUK Research IT IT ServicesThe University of ManchesterManchester M139PLUK European Bioinformatics Institute(EMBL-EBI) HinxtonCambridgeshire CB101SDUK

We introduce the concept of Canonical Workflow Building Blocks(CWBB),a methodology of describing and wrapping computational tools,in order for them to be utilised in a reproducible manner from multiple workflow languages and execution platforms.The concept is implemented and demonstrated with the BioExcel Building Blocks library(BioBB),a collection of tool wrappers in the field of computational biomolecular simulation.Interoperability across different workflow languages is showcased through a protein Molecular Dynamics setup transversal workflow,built using this library and run with 5 different Workflow Manager Systems(WfMS).We argue such practice is a necessary requirement for FAIR Computational Workflows and an element of Canonical Workflow Frameworks for Research(CWFR)in order to improve widespread adoption and reuse of computational methods across workflow language barriers.

关键词： Scientific workflows Interoperable FAIR Computational tools Containers Software packaging FAIR digital object(FDO),BioExcel Building Blocks library(BioBB),Canonical Workflow Frameworks for Research(CWFR)

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

FAIR Computational Workflows

引用

Data Intelligence 2020年第1期2卷 108-121,307,308,309页

作者： Carole Goble Sarah Cohen-Boulakia stian soiland-reyes Daniel Garijo Yolanda Gil Michael R.Crusoe Kristian Peters Daniel Schober Department of Computer Science The University of ManchesterOxford RoadManchester M139PLUK Laboratoire de Recherche en Informatique CNRSUniversitéParis-SaclayBatiment 650UniversitéParis-Sud91405 ORSAY CedexFrance Information Sciences Institute University of Southern CaliforniaMarina Del Rey CA 90292USA Common Workflow Language project Software Freedom ConservancyInc.137 Montague St STE 380NY 11201-3548USA Leibniz Institute of Plant Biochemistry(IPB Halle) Department of Biochemistry of Plant InteractionsWeinberg 306120 Halle(Saale)Germany

Computational workflows describe the complex multi-step methods that are used for data collection,data preparation,analytics,predictive modelling,and simulation that lead to new data products.They can inherently contribute to the FAIR data principles:by processing data according to established metadata;by creating metadata themselves during the processing of data;and by tracking and recording data provenance.These properties aid data quality assessment and contribute to secondary data usage.Moreover,workflows are digital objects in their own right.This paper argues that FAIR principles for workflows need to address their specific nature in terms of their composition of executable software steps,their provenance,and their development.

关键词： Computational workflow Reproducibility Software FAIR data Provenance

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Unique,Persistent,Resolvable:Identifiers as the Foundation of FAIR

引用

Data Intelligence 2020年第1期2卷 30-39,302页

作者： Nick Juty Sarala M.Wimalaratne stian soiland-reyes John Kunze Carole A.Goble Tim Clark Department of Computer Science The University of ManchesterOxford RoadManchester M139PLUK European Bioinformatics Institute(EMBL-EBI) HinxtonCambridgeCB101SDUK California Digital Library OaklandCalifornia 94612-2901USA Data Science Institute University of VirginiaCharlottesvilleVA 22903-1738USA

The FAIR principles describe characteristics intended to support access to and reuse of digital artifacts in the scientific research ecosystem.Persistent,globally unique identifiers,resolvable on the Web,and associated with a set of additional descriptive metadata,are foundational to FAIR data.Here we describe some basic principles and exemplars for their design,use and orchestration with other system elements to achieve FAIRness for digital research objects.

关键词： Identifiers metadata findability FAIR data data infrastructures

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：