Approach
Modular Biotech Research, adaptable Data Workflow, Bioinformatics Innovation, scalability, reproducibility, polyglot, scalable, reproducible
Intuitive Data Workflow Approach
Our approach to data workflow development, powered by the Viash tool and Viash Hub platform, is built on years of experience in data workflow development and a deep understanding of our clients’ needs.
More than just developing functional data workflows, the solution champions a flexible, long-term, and future-proof approach in data processing that is easily integratable into existing environments, moving away from traditional fixed and manually developed data workflow structures.
Common Pitfalls and Challenges with Data Workflows
In biotech, creating robust omics data workflows demands careful navigation of various challenges to ensure reliability and robustness. Below are ten common pitfalls that can undermine success:
- Data quality: Unreliable data invalidates results, fosters errors.
- Reproducibility: Irreproducible workflows erode credibility and compliance.
- Scalability: Poor scaling ability stalls projects under enterprise-level datasets.
- Maintainability: Unmaintainable, badly designed workflows cause chaos.
- Dependencies: Multiple dependencies can lead to unpredictable behavior.
- Vendor lock-in: Vendor reliance limits flexibility and adaptability when shifting platforms.
- Efficiency & collaboration: Poor efficiency wastes research time and IT expert time.
- Multi-platform processing: Platform inconsistency creates operational inefficiencies.
- Security & compliance: Weak security jeopardizes compliance and confidence.
- Version control: Lacking version control fosters mismatched code and confusion.
For more information on these pitfalls, click here to open our blog post
“10 Common Pitfalls in Omics Data Processing—And How to Avoid Them”
Continuous Improvement
Whether deploying individual tools or building fully customized workflows, we ensure efficiency, accuracy, and scalability, with a focus on continuous improvement and long-term sustainability.
Ecosystem
Our Data Workflow Suite consists the Viash Tool, the Viash Hub platform and an extensive repository of biotech data workflows and tools: Viash Catalogue.
Viash Catalogue
The open-source catalogue on Viash Hub offers a comprehensive collection of publicly available biotech data workflows, modules, and useful tools , all ready for individual use or for composing into larger data workflows.
Viash Hub
Viash Hub Public is a platform for managing, developing, deploying, and sharing bioinformatics tools
and workflows.
It allows users to publish, share, and maintain versioned modules, ensuring accessibility and
reusability.
Optimised for cloud environments, it simplifies launching data workflows.
Available 2025
Viash
Viash is the open-source tool developed by Data Intuitive to create, standardise, and manage data workflows. It automates the generation of modular, executable components, ensuring that workflows are reproducible, scalable, and easily integrated into various computational environments.
Engineered with deep expertise in pipelines and Nextflow, Viash minimizes manual coded boilerplate
coding and development errors, significantly boosting efficiency.
Quality Framework
Through the quality framework, each data analysis building block is crafted to meet modularity, standardisation, and technically state-of-the-art best practices.
By generating the modular building blocks based on the predefined specifications, we can ensure a consistently high quality in built data analysis and workflow solutions.
Modularity
Modularity means biotech data analysis workflows are built up out of self-contained analysis building blocks, each with a specific function and the flexibility to operate independently or be combined into a larger data workflow.
These modular blocks enable efficient maintenance and reuse, improving workflow adaptability.
- Workflows consist of modular blocks, easily combined into workflows. Complete workflows can also be used as modular building blocks.
- Scientific research and IT operations are technically separated within each building block to optimise resource efficiency.
Standardisation
Standardisation ensures that each modular building block is built according to a predefined structure, promoting consistent quality, compatibility, and ease of use across workflows.
This framework provides a foundation that reduces the learning curve, making it easier for users to adopt and implement the workflows.
- Functional standardisation: script language independence, reproducibility, scalability, executability, and cross-platform compatibility.
- Development and usage standardisation: dependency and argument handling, documentation, code testing, maintenance and debugging.
Technical Excellence
Technical excellence ensures operational quality, reliability and optimal performance across all building blocks and technologies used , drawing on the company's years of biotech data analysis and data workflow development expertise.
Each technique is thoroughly documented and tested to create robust, industry-ready data analysis.
- Core capabilities: polyglot (all common scripting languages), scalability frameworks (currently Nextflow), containerisation for reproducibility (currently Docker, Podman, Singularity).
- Enhanced development support: CLI options, tools and aids that streamline development, testing and maintenance processes.
Code Generation
The Viash tool takes care of boilerplate code generation to automate the creation of executable workflows based on a user's description and the predefined technical excellence.
This ensures modularity, standardisation, and consistent code quality, while reducing manual coding efforts and preventing development errors.
- Automated outputs: ready-to-use data analysis with command-line options, documentation, and optimised code for each predefined technical framework.
- Efficiency & quality: simplifies development and deployment, enabling robust data analysis without extensive manual coding or specialised technical skills.