Objective

Abstract: Connectivity and seamless interoperability are among the goals for many lab of the future projects. Standard protocols and data formats serve as infrastructure enablers for integration of instruments, systems, and seamless data flow.

With the growing interest in applying artificial intelligence and machine learning tools to lab data, the careful management of data and protocols becomes even more important in allowing the benefits of these technologies to be obtained.

We review the progress of the AnIML and SiLA standardization initiatives, which can provide key building blocks to establish interoperability.

While AnIML specifies an XML-based standard data format for analytical data, SiLA provides web service-based communication standards for interfacing with instruments. Clients can use SiLA to discover and interact with services in the lab. These services may be instruments or other systems. All services communicate using an open protocol, built on cutting-edge web technologies. AnIML provides the data format to plan and document lab experiments. By joining forces, a new ecosystem is emerging that allows end-to-end integration of instrument control, data capture, and enterprise system (ELN, LIMS) connectivity.

References: SiLA Consortium: http://www.sila-standard.org

AnIML: http://www.animl.org