Taimur Khan

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About Taimur Khan:

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SEEK ID: https://workflowhub.eu/people/708

Location: Germany

ORCID: https://orcid.org/0000-0001-7833-5474

Joined: 27th Feb 2024

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BioDT

The Biodiversity Digital Twin prototype provides advanced models for simulation and prediction capabilities, through practical use cases addressing critical issues related to global biodiversity dynamics.

BioDT exploits the LUMI Supercomputer and employs FAIR data combined with digital infrastructure, predictive modelling and AI solutions, facilitating evidence-based solutions for biodiversity protection and restoration.

Funded by Horizon Europe call HORIZON-INFRA-2021-TECH-01-01 101057437, the ...

Teams: BioDT Use Case 4.1.1.2 Ecosystem services, BioDT Use Case 4.1.1.1 Biodiversity dynamics, BioDT Use Case 4.1.2.2 DNA detected biodiversity, poorly known habitats, BioDT Use Case 4.1.2.1 Crop wild relatives and genetic resources for food security, BioDT Use Case 4.1.3.1 Invasive species, BioDT Use Case 4.1.3.2 Endangered species, BioDT Use Case 4.1.4.1 Disease outbreaks, BioDT Use Case 4.1.4.2 Pollinators, BioDT additional pipelines, Senckenberg Digital Collection and Biodiversity Information Technologies

Web page: https://biodt.eu/

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BioDT additional pipelines

BioDT pipelines not associated with one of the BioDT use cases.

Space: BioDT

Public web page: Not specified

Organisms: Not specified

BioDT Use Case 4.1.3.1 Invasive species

Part of T.4.1.3 Dynamics and threats from and for species of policy concern (UFZ, GBIFS, Naturalis, UKCEH, LifeWatchERIC)

Space: BioDT

Public web page: Not specified

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Helmholtz-Centre for Environmental Research (UFZ)

Country: Germany

City: Leipzig

Web page: https://www.ufz.de/

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Applying the FAIR Principles to computational workflows

FAIR Computational Workflows, EuroScienceGateway

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Abstract

Not specified

Authors: Sean R. Wilkinson, Meznah Aloqalaa, Khalid Belhajjame, Michael R. Crusoe, Bruno de Paula Kinoshita, Luiz Gadelha, Daniel Garijo, Ove Johan Ragnar Gustafsson, Nick Juty, Sehrish Kanwal, Farah Zaib Khan, Johannes Köster, Karsten Peters-von Gehlen, Line Pouchard, Randy K. Rannow, Stian Soiland-Reyes, Nicola Soranzo, Shoaib Sufi, Ziheng Sun, Baiba Vilne, Merridee A. Wouters, Denis Yuen, Carole Goble

Date Published: 1st Dec 2025

Publication Type: Journal

DOI: 10.1038/s41597-025-04451-9

Citation: Sci Data 12(1),328

Created: 3rd Oct 2025 at 17:51, Last updated: 3rd Oct 2025 at 17:51

An Ecosystem of Services for FAIR Computational Workflows

FAIR Computational Workflows, EuroScienceGateway

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Abstract (Expand)

Computational workflows, regardless of their portability or maturity, represent major investments of both effort and expertise. They are first class, publishable research objects in their own right. … They are key to sharing methodological know-how for reuse, reproducibility, and transparency. Consequently, the application of the FAIR principles to workflows [goble_2019, wilkinson_2025] is inevitable to enable them to be Findable, Accessible, Interoperable, and Reusable. Making workflows FAIR would reduce duplication of effort, assist in the reuse of best practice approaches and community-supported standards, and ensure that workflows as digital objects can support reproducible and robust science. FAIR workflows also encourage interdisciplinary collaboration, enabling workflows developed in one field to be repurposed and adapted for use in other research domains. FAIR workflows draw from both FAIR data [wilkinson_2016] and software [barker_2022] principles. Workflows propose explicit method abstractions and tight bindings to data, hence making many of the data principles apply. Meanwhile, as executable pipelines with a strong emphasis on code composition and data flow between steps, the software principles apply, too. As workflows are chiefly concerned with the processing and creation of data, they also have an important role to play in ensuring and supporting data FAIRification. The FAIR Principles for software and data mandate the use of persistent identifiers (PID) and machine actionable metadata associated with workflows to enable findability, reusability, interoperability and reusability. To implement the principles requires a PID and metadata framework with appropriate programmatic protocols, an accompanying ecosystem of services, tools, guidelines, policies, and best practices, as well the buy-in of existing workflow systems such that they adapt in order to adopt. The European EOSC-Life Workflow Collaboratory is an example of such a digital infrastructure for the Biosciences: it includes a metadata standards framework for describing workflows (i.e. RO-Crate, Bioschemas, and CWL), that is managed and used by dedicated new FAIR workflow services and programmatic APIs for interoperability and metadata access such as those proposed by the Global Alliance for Genomics and Health (GA4GH) [rehm_2021]. The WorkflowHub registry supports workflow Findability and Accessibility, while workflow testing services like LifeMonitor support long-term Reusability, Usability and Reproducibility. Existing workflow management systems/languages and packaging solutions are incorporated and adapted to promote portability, composability, interoperability, provenance collection and reusability, and to use and support these FAIR services. In this chapter, we will introduce the FAIR principles for workflows, the connections between FAIR workflows, and the FAIR ecosystems in which they live, using the EOSC-Life Collaboratory as a concrete example. We will also introduce other community efforts that are easing the ways that workflows are shared and reused by others, and we will discuss how the variations in different workflow settings impact their FAIR perspective.

Authors: Sean R. Wilkinson, Johan Gustafsson, Finn Bacall, Khalid Belhajjame, Salvador Capella, José María Fernández González, Jacob Fosso Tande, Luiz Gadelha, Daniel Garijo, Patricia Grubel, Björn Grüning, Farah Zaib Khan, Sehrish Kanwal, Simone Leo, Stuart Owen, Luca Pireddu, Line Pouchard, Laura Rodriguez-Navas, Beatriz Serrano-Solano, Stian Soiland-Reyes, Baiba Vilne, Alan Williams, Merridee Ann Wouters, Frederik Coppens, Carole Goble

Date Published: 21st May 2025

Publication Type: InBook

DOI: 10.48550/arXiv.2505.15988

Citation:

Created: 3rd Oct 2025 at 17:43, Last updated: 3rd Oct 2025 at 17:45

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