EDITORIAL
Editors’ Note: Special Issue on Canonical Workflow
Frameworks for Research
Peter Wittenburg1†, Alex Hardisty2, Amirpasha Mozzafari3, Limor Peer4, Nikolay Skvortsov5,
Alessandro Spinuso6, Zhiming Zhao7
1Gemeindweg 55, 47533 Kleve, Alemania
2Universidad de Cardiff, Cardiff, South Glamorgan , CF14 3UX, Wales, Reino Unido
3Forschungszentrum Jülich GmbH, 52425 Jülich, Alemania
4Institution for Social and Policy Studies, Yale University, nuevo refugio, CT 06520, EE.UU
5Vavilov 44/2, 121351 Moscow, Russia
6Utrechtseweg 297, 3731 GA De Bilt, Los países bajos
7University of Amsterdam, PO-Box 94323, 1090 GH Amsterdam, Los países bajos
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Citación: Wittenburg, PAG. et al.: Editors’ Note: Special Issue on Canonical Workflow Frameworks for Research. Data Intelligence.
4(2), 149-154 (2022). Doi: 10.1162/dint_e_00122
This special issue is on Canonical Workflow Frameworks for Research (CWFR). A workflow refers to a
sequence of activities, which may be more or less computer-based, used with regularity in the research
proceso. CWFR aim to identify common patterns in such scientifically motivated workflows and to offer
libraries of components based on FAIR Digital Objects as the integrative standard. Such CWFR components
can be reusable independent of particular technologies, benefitting researchers in their daily work by
making recurring activities more efficient, using automated workflow methods that would immediately
create FAIR compliant data without adding burden.
It is the goal of this special issue to provide readers with a deep exploration of CWFR and how it relates
to research driven workflows, to existing workflow technologies, and to the use of FAIR Digital Objects.
This issue covers articles examining core research activities including experimentation, data processing
and analysis, data management, reproducibility, and publication. The articles comment on CWFR and its
relation to these workflows, either conceptually in view of the current research ecosystem and infrastructure
or more practically, focusing on a specific implementation, diseño, tool, or context relating to CWFR.
The contributing authors are experts in their area. They include researchers, data professionals, datos
managers and curators, IT specialists and others who are using, developing, or experimenting with the
†
Autor correspondiente: Peter Wittenburg (Correo electrónico: peter.wittenburg@mpcdf.mpg.de; ORCID: 0000-0003-3538-0106).
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© 2022 Academia China de Ciencias. Publicado bajo una atribución Creative Commons 4.0 Internacional (CC POR 4.0) licencia.
Editors’ Note: Special Issue on Canonical Workfl ow Frameworks for Research
effective use of canonical workflows and workflow patterns for data intensive research. As guest editors, él
has been a privilege to work with such accomplished authors.
It is our hope that this issue will stimulate further exploration of this subject. The papers in this issue
address timely questions such as, what are the recurring patterns of work within or across institutions and
research communities? What are the core elements of workflow technologies and how can they relate to
the core ideas of CWFR? How well do existing integration standards and best practices address this?
What is the potential of FDOs to support the goals of CWFR? How can research be protected against the
ever-changing technological fashions?
Finalmente, we are grateful to the journal for the opportunity to publish this special issue and to Dr. Fenghong
Liu, Managing Editor-in-Chief, for her skilled guidance and support.
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150
Data Intelligence
Editors’ Note: Special Issue on Canonical Workfl ow Frameworks for Research
AUTHOR BIOGRAPHY
Peter Wittenburg has a background in electrical engineering, has been
working as Technical Director at the Max Planck Institute for Psycholinguistics
for many years and acted as member of the IT Advisory board of the president
of the MPS. The Max Planck Institute was from the beginning focusing on
digital technologies to understand the functioning of the brain with respect
to language processing. The institutes need for getting access to data from
other institutes to feed the stochastic engines they applied rather early led
him to become an expert in building data/research infrastructures. He was
responsible for the technological aspects of three large international and
European research infrastructures: DOBES, CLARIN and EUDAT. In this
function he understood that data work across silos is highly inefficient and
that harmonisation and standardisation is required to improve the situation.
This was the reason that he co-founded the Research Data Alliance in 2013
and the FAIR Digital Object Forum in 2019.
ORCID: 0000-0003-3538-0106
Alex Hardisty was before his recent retirement Director of Informatics
Projects in the School of Computer Science and Informatics, Universidad de Cardiff,
Reino Unido. He is interested in bio/geodiversity informatics, the engineering of large-
scale distributed information systems for data management and processing,
virtual research environments and socio-technical issues of new technology
adoption. Alex is a technical architect. Before his retirement he was leading
DiSSCo technical work on open Digital Specimens (openDS), Mínimo
Information about Digital Specimens/Collections (MIDS/MICS) and exploiting
machine-actionable FAIR Digital Objects. Alex was co-chairing the CWFR
Working Group of the FDO Forum and was a member of the FDO Forum’s
Technical Specification and Implementation (TSIG) Working Group and the
FDO Forum Steering Committee.
ORCID: 0000-0002-0767-4310
Data Intelligence
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Editors’ Note: Special Issue on Canonical Workfl ow Frameworks for Research
Amirpasha Mozaffari is a postdoctoral researcher of the group on Earth
System Data Exploration (ESDE) at the Jülich Supercomputing Centre (JSC).
He is trained as a geoscientist and recently defended his PhD in computational
Geohydrophysics from RWTH Aachen. He is active in the field of data
management, workflow design and FAIR data practices. He is co-chair the
canonical workflow framework for research in the Fair Digital Object forum.
ORCID : 0000-0001-6719-0425
Limor Peer, PhD, is Associate Director for Research and Strategic Initiatives
at the Institution for Social and Policy Studies (ISPS), Yale University. Limor
works on research transparency and reproducibility and is especially interested
in the connection between generating and preserving scientific knowledge.
Limor created the ISPS Data Archive, a digital repository for research produced
by scholars affiliated with ISPS with a focus on experimental design and
methods. She led the project to develop YARD, the Yale Application for
Research Data, a workflow tool for reviewing and enhancing research outputs.
Limor is co-founder of the CURE (Curation for Reproducibility) Consorcio
of social science data archives. She co-chairs the CURE-FAIR working group
at the Research Data Alliance, and the Practices working group of the ACM’s
Emerging Interest Group on Reproducibility and Replicability. She sits on the
board of the Roper Center for Public Opinion Research and serves on a
number of advisory and task force groups working on data curation and
research transparency. Prior to joining ISPS, Limor was Research Director at
Northwestern University’s Media Management Center and Readership
Instituto, and Associate Professor (clinical) at the Medill School of Journalism.
ORCID: 0000-0002-3234-1593
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Editors’ Note: Special Issue on Canonical Workfl ow Frameworks for Research
The general research interests of Nikolay Skvortsov are ontological and
conceptual modeling of research domains and data semantic interoperability
asuntos. He has been affiliated with the Institute of Informatics Problems,
Federal Research Center “Computer Science and Control”, Russian Academy
of Sciences, Moscow, Russia. In recent years Nikolay Skvortsov investigates
requirements for the reuse of data, research methods, and processes in
research communities primarily using examples of problem development and
solving in astronomical research domains
ORCID: 0000-0003-3207-4955
Alessandro Spinuso is a researcher at the R&D Observations and Data
Technology division of the KNMI (Royal Netherlands Meteorological
Instituto). He earned his PhD in Computer Science at the University of
Edimburgo (Uk) en 2017. At KNMI, he covers the roles of Researcher and
Product Owner within an Agile R&D team developing Provenance-aware
Data Analysis services. His main research interest is the management and the
exploitation of provenance information in the context of user controlled
computational environments, providing notebooks and workflow systems for
data-intensive analysis. He is involved in several international initiatives
focusing on the development of e-science infrastructures for Earth Science
research in Europe (EPOS, ENVRIFair, IS-ENES3, DARE, C3S). More recently,
he is an invited expert to the IPCC TG-Data. A Working group dedicated to
the FAIR management of the data and methods that will be published in the
next IPCC reports.
ORCID: 0000-0002-0077-8491
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Editors’ Note: Special Issue on Canonical Workfl ow Frameworks for Research
Zhiming Zhao received his Ph.D. in computer science in 2004 from the
University of Amsterdam (UvA). He is an assistant professor in the Multiscale
Network Systems (MNS) at UvA, and the technical manager of the Virtual Lab
and Innovation Center (VLIC) of LifeWatch ERIC, a European research
infrastructure in ecology and biodiversity science. His research focuses on
innovative programming and control models for quality critical systems on
programmable infrastructures such as Clouds, Edges, and Software-Defined
Networking using optimization, semantic linking, blockchain, and artificial
intelligence technologies. He leads the UvA effort in several EU projects
including ARTICONF, CLARIFY, ENVRI-FAIR, and SWITCH.
ORCID: 0000-0002-6717-9418
Yann Le Franc, PhD is the CEO and Scientific Director of e-Science Data
Factory S.A.S.U., a French R&D company aiming at proposing innovative
solutions for FAIR data management to accelerate growth and progress.
Yann Le Franc has a PhD in Neurosciences and Pharmacology (2004). Después
a postdoctoral experience in the US, he worked on data management projects
in Neurosciences at the University of Antwerp (Bélgica) and in the context
of the International Neuroinformatics Coordinating Facility (INCF) dónde
he developed a strong expertise in ontology design and semantic web
tecnologías. He then contributed to several Horizon 2020 Investigación
Infrastructure projects (EUDAT, EOSC-Hub,…) as an expert on Semantic Web
and ontology design. He is co-chairing the Research Data Alliance Vocabulary
and Semantic Service Interest Group and the FDO Semantic Group. He is
also a member of the EOSC Semantic Interoperability Task Force. He is
actively involved in the FAIRification and standardization of semantic artefacts
in the context of FAIRsFAIR and OntoCommons projects. In parallel, he is the
technical manager of the EOSC-Pillar project for the French National
Computing Center for Higher Education (CINES).
ORCID: 0000-0003-4631-418X
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