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research-article

Using a suite of ontologies for preserving workflow-centric research objects

Authors:

Khalid Belhajjame,

Matthew Gamble,

Kristina Hettne,

José Manuel Gómez-Pérez,

Sean Bechhofer,

Carole GobleAuthors Info & Claims

Web Semantics: Science, Services and Agents on the World Wide Web, Volume 32, Issue C

Pages 16 - 42

https://doi.org/10.1016/j.websem.2015.01.003

Published: 01 May 2015 Publication History

Abstract

Scientific workflows are a popular mechanism for specifying and automating data-driven in silico experiments. A significant aspect of their value lies in their potential to be reused. Once shared, workflows become useful building blocks that can be combined or modified for developing new experiments. However, previous studies have shown that storing workflow specifications alone is not sufficient to ensure that they can be successfully reused, without being able to understand what the workflows aim to achieve or to re-enact them. To gain an understanding of the workflow, and how it may be used and repurposed for their needs, scientists require access to additional resources such as annotations describing the workflow, datasets used and produced by the workflow, and provenance traces recording workflow executions.In this article, we present a novel approach to the preservation of scientific workflows through the application of research objects-aggregations of data and metadata that enrich the workflow specifications. Our approach is realised as a suite of ontologies that support the creation of workflow-centric research objects. Their design was guided by requirements elicited from previous empirical analyses of workflow decay and repair. The ontologies developed make use of and extend existing well known ontologies, namely the Object Reuse and Exchange (ORE) vocabulary, the Annotation Ontology (AO) and the W3C PROV ontology (PROVO). We illustrate the application of the ontologies for building Workflow Research Objects with a case-study that investigates Huntington's disease, performed in collaboration with a team from the Leiden University Medial Centre (HG-LUMC). Finally we present a number of tools developed for creating and managing workflow-centric research objects.

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Cited By

Pan BStakhanova NRay S(2023)Data Provenance in Security and PrivacyACM Computing Surveys10.1145/359329455:14s(1-35)Online publication date: 22-Apr-2023
https://dl.acm.org/doi/10.1145/3593294
Crusoe MAbeln SIosup AAmstutz PChilton JTijanić NMénager HSoiland-Reyes SGavrilović BGoble CCommunity T(2022)Methods includedCommunications of the ACM10.1145/348689765:6(54-63)Online publication date: 20-May-2022
https://dl.acm.org/doi/10.1145/3486897
González EBenítez AGarijo D(2022)FAIROs: Towards FAIR Assessment in Research ObjectsLinking Theory and Practice of Digital Libraries10.1007/978-3-031-16802-4_6(68-80)Online publication date: 20-Sep-2022
https://dl.acm.org/doi/10.1007/978-3-031-16802-4_6
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Index Terms

Using a suite of ontologies for preserving workflow-centric research objects

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Reviews

Reviewer: Lalit P Saxena

Today, scientific workflows are gaining popularity among the scientific community because of their features like reusability, easy modifications while sharing, and so on. These workflows depend on research objects, which are based on ontologies, such as object reuse and exchange vocabulary, the annotation ontology, and the W3C PROV ontology. This paper develops tools for creating and managing workflow-centric research objects (WRO). The authors incorporate four ontologies in their proposed models. They further develop a suite of interoperable tools, such as research object manager, for creating, annotating, publishing, and managing WRO, and a research object digital library for dealing with collaboration, versioning, evolution, and quality management of WRO. The authors add an extension to myExperiment, a popular virtual research environment, which allows end users to create, share, publish, and curate research objects. For experiments, the authors present a case study, a workflow-based experiment investigating the epigenetic mechanisms involved in Huntington's disease (HD). They consider epigenetic datasets from CpG islands and chromatin marks for analyzing the HD gene expression data of three different brain regions. They further present two analyses and three workflows for gene interpretation. This aids in creating WRO containing information like original hypothesis, example inputs, workflow definitions, metadata descriptions, and implementation details. For their current project, the authors like to collaborate with other communities, such as the EU Scape project or Timbus project, the EU BioVel project, GigaScience, FigShare, and Dataverse. They further describe the potential of their work in preserving scientific workflows, reusing existing workflows, and promoting and encouraging data citation and sharing, making this paper an interesting read. Online Computing Reviews Service

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cover image Web Semantics: Science, Services and Agents on the World Wide Web

Web Semantics: Science, Services and Agents on the World Wide Web Volume 32, Issue C

May 2015

54 pages

ISSN:1570-8268

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Copyright © The Authors.

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Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 May 2015

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Cited By

Pan BStakhanova NRay S(2023)Data Provenance in Security and PrivacyACM Computing Surveys10.1145/359329455:14s(1-35)Online publication date: 22-Apr-2023
https://dl.acm.org/doi/10.1145/3593294
Crusoe MAbeln SIosup AAmstutz PChilton JTijanić NMénager HSoiland-Reyes SGavrilović BGoble CCommunity T(2022)Methods includedCommunications of the ACM10.1145/348689765:6(54-63)Online publication date: 20-May-2022
https://dl.acm.org/doi/10.1145/3486897
González EBenítez AGarijo D(2022)FAIROs: Towards FAIR Assessment in Research ObjectsLinking Theory and Practice of Digital Libraries10.1007/978-3-031-16802-4_6(68-80)Online publication date: 20-Sep-2022
https://dl.acm.org/doi/10.1007/978-3-031-16802-4_6
Richardson RCelebi Rvan der Burg SSmits DRidder LDumontier MKuhn TGentile AGonçalves R(2021)User-friendly Composition of FAIR Workflows in a Notebook EnvironmentProceedings of the 11th Knowledge Capture Conference10.1145/3460210.3493546(1-8)Online publication date: 2-Dec-2021
https://dl.acm.org/doi/10.1145/3460210.3493546
Gaignard ASkaf-Molli HBelhajjame KGarijo DVillanueva-Rosales NKauppinen T(2020)Findable and reusable workflow data productsSemantic Web10.3233/SW-20037411:5(751-763)Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.3233/SW-200374
Al Manir SNiestroy JLevinson MClark T(2020)Evidence Graphs: Supporting Transparent and FAIR Computation, with Defeasible Reasoning on Data, Methods, and ResultsProvenance and Annotation of Data and Processes10.1007/978-3-030-80960-7_3(39-50)Online publication date: 22-Jun-2020
https://dl.acm.org/doi/10.1007/978-3-030-80960-7_3
Butt AFitch P(2020)ProvONE+: A Provenance Model for Scientific WorkflowsWeb Information Systems Engineering – WISE 202010.1007/978-3-030-62008-0_30(431-444)Online publication date: 20-Oct-2020
https://dl.acm.org/doi/10.1007/978-3-030-62008-0_30
Fenlon KDownie SZhu QHahn J(2019)Modeling digital humanities collections as research objectsProceedings of the 18th Joint Conference on Digital Libraries10.1109/JCDL.2019.00029(138-147)Online publication date: 2-Jun-2019
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Ayadi AZanni-Merk Cde Beuvron FThompson JKrichen S(2019)BNO—An ontology for understanding the transittability of complex biomolecular networksWeb Semantics: Science, Services and Agents on the World Wide Web10.1016/j.websem.2019.01.00257:COnline publication date: 1-Aug-2019
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Garcia-Silva AGomez-Perez JPalma RKrystek MMantovani SFoglini FGrande VDe Leo FSalvi STrasatti ERomaniello VAlbani MSilvagni CLeone RMarelli FAlbani SLazzarini MNapier HGlaves HAldridge TMeertens CBoler FLoescher HLaney CGenazzio MCrawl DAltintas I(2019)Enabling FAIR research in Earth Science through research objectsFuture Generation Computer Systems10.1016/j.future.2019.03.04698:C(550-564)Online publication date: 1-Sep-2019
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