Laboratory & data terminology at a glance

Artificial intelligence (AI) refers to the simulation of human intelligence in computer systems that can analyze data, recognize patterns, make decisions, and automate complex tasks.

Assistance systems are digital or AI-based applications that help the laboratory to perform complex tasks more efficiently, faster and with less errors.

Data integration in the laboratory describes the merging of measurement data, recipes and master data from various sources into a uniform, evaluable database.

Data management is the structured collection, organisation, and use of data to ensure accuracy, accessibility, and security.

A digital twin is a virtual representation of a physical object or process, continuously updated with real-time data to simulate its behaviour and performance.

A laboratory information and management system (LIMS) is a software solution for centrally managing, tracking, and organizing samples, laboratory data, and workflows to ensure efficiency, data integrity, and regulatory compliance.

Laboratory digitization refers to the transformation of laboratory processes through digital technologies, automation and AI-supported data management.

Material intelligence describes the systematic use and linking of relevant data, workflows and AI to enable better decisions in R&D and QA.

Material development is the process of designing, optimizing, and testing new materials to meet specific performance, safety, and sustainability requirements.