It furthermore allows tech-savvy users to use components as blueprints for connecting to their lab devices via SiLA (without the need to recompile and package sources). by replacing one instance of the wrapper that is used in all components. This has also allowed us to iterate rapidly on the integration together with the other collaborators, e.g. Please note that in order to minimize the size of the components, the JAR file containing the wrapper is available separately. To make this usable (but also adaptable) by others, we have encapsulated this functionality into shared components. Early in the project we decided to go for a proof-of-concept implementation that uses Java Snippet nodes utilizing the aforementioned wrapper. Since the sources are publicly available, siobra was able to repackage this reference implementation and implement a light-weight wrapper that can readily be used from KNIME Analytics Platform. Among others, an implementation for Java is available at under MIT license. The SiLA consortium and its members maintain reference implementations of the SiLA 2 standard for various programming languages. SiLA and Biosero were at # SLAS2021 Digital International Conference and Exhibition sharing more about the collaboration and demonstrating 'the power of standards in action'! How does SiLA integrate with KNIME? Video demonstrating automatic retrieval and analysis of lab dataĬheck out this video to see the workflows we built for the two uses cases in action. The video demonstrates how KNIME workflows can automatically retrieve and analyze laboratory data in one simple and intuitive environment for end-to-end data science. With the demonstrated integration we enable lab scientists to perform their own analyses by building reproducible workflows to automatically retrieve their data, blend them with other data sources, and carry out different kinds of post-processing. These workflows are useful beyond these two use cases. The SiLA standard can be used in a lot of different scenarios, and the workflows easily adjusted and applied to diverse projects. We utilize the SiLA integration in two use cases that automatically analyze SiLA enables the automation and digitizing of scientific laboratories through free and open data standards and systems communication. In this blog post, we show how we integrated the SiLA standard (Standardization in Lab Automation) in KNIME Analytics Platform through a collaborative effort of siobra, Biosero, HDC, KNIME, and the SiLA consortium. Standardized lab automation with KNIME Analytics Platform A solution to this problem is to integrate standards and to simplify end-to-end integration. This hinders an effective implementation it often seems easier to stick to doing everything manually. However, the effort required to implement these is high, due to contending with inconsistent infrastructures as well as a diverse set of integration interfaces. The goal of such initiatives is to improve experimental reproducibility, reduce errors, increase productivity, and enhance the generated data through contextualization. Many life science companies have important digitalization initiatives that incorporate end-to-end integration.
0 Comments
Leave a Reply. |