SiLA 2

Background and purpose SiLA 2 (Standardization in Lab Automation) is a community-driven, open standard designed to make laboratory instruments and informatics systems interoperable. Where proprietary interfaces historically required custom drivers and one-off integrations, SiLA 2 provides a standardized interface model, device class specifications and a repository of reference implementations and SDKs so labs, instrument vendors and integrators can connect equipment, LIMS, ELNs and analytics tools more quickly and reliably. SiLA 1.x is considered obsolete for new products; SiLA 2 is the recommended modern standard with published core specifications, mapping guidance and a features index. Core capabilities and technical resources The specification set for SiLA 2 is organized (Part A — overview, concepts and core specification; Part B — mapping specification; Part C — features index) and is complemented by device control and interface documents, device class design guidelines and a command dictionary. The project maintains an official GitLab with base repositories and language SDKs and examples (Java, C#, Python, C++) plus a Tecan SiLA 2 SDK to accelerate server/client development. SiLA also publishes white papers, application notes and training resources (recorded courses and in‑house training options) to help adopters implement the standard and to promote best practices for data capture, harmonization and long‑term retention. Typical use cases and benefits Practical applications of SiLA 2 include connecting balances, plate readers, LC‑MS feeders or colony pickers to a LIMS or ELN, integrating control software across devices for closed‑loop or autonomous workflows, and harmonizing data across labs for reproducibility and QA. Industry examples and application notes referenced by the SiLA community include chromatography system integration, high‑throughput screening preparation, robotic cell culture automation, autonomous lab robots and cloud lab enabling work. Benefits are tangible: dramatically reduced integration time and development cost, re‑usable device interfaces across workflows, improved data integrity by standardizing formats, and easier maintenance as lab configurations evolve. Several large vendors and labs (e.g., Tecan, Roche, Labforward, Novo Nordisk) and integrators have reported using SiLA 2 internally or exposing SiLA interfaces to customers to speed deployment and create modular automation solutions. Ecosystem, integrations and governance SiLA 2 is designed to work with laboratory informatics standards and tools rather than replace them. Published integrations and collaborations reference LIMS, ELN, Chromatography Data Systems (CDS), AnIML data formats, KNIME analytics and LES solutions such as Laboperator, illustrating how SiLA 2 can be the transport and control layer in broader data and analytics pipelines. The standard is developed and maintained by the SiLA consortium, which provides downloads (standards, white papers, SDKs), organizes conferences, workshops and hackathons, and publishes security and vulnerability policies. The consortium also offers guidance for vendors (how to develop SiLA standards), practical application notes, and a request‑for‑proposal process to review implementations for vulnerabilities—helping adopters balance openness with security and operational governance. How teams adopt SiLA 2 Adoption typically follows a staged approach: review the SiLA 2 Part A–C documentation and device class specs, use the available SDK or reference server/client code to build a SiLA 2 wrapper for the instrument or control software, and then validate integration with LIMS/ELN/analytics in a test environment. For organizations adopting automation at scale, SiLA 2 can become an internal integration standard to reduce long‑term total cost of ownership by enabling plug‑and‑play replacements, re‑use across workflows, and more rapid commissioning of new equipment. Training, community resources, and the GitLab repositories serve as practical entry points for developers, system integrators and lab managers aiming to future‑proof their automation and data strategies.