KNIME (Konstanz Information Miner) is a modular environment that allows for the visual assembly and interactive execution of data pipelines. It serves as a teaching, research, and collaboration platform, enabling the integration of new algorithms, data manipulation, and visualization methods as new modules or nodes. The system is designed to be easy to use, intuitive, and allows for quick and interactive changes to the analysis. It is written in Java and features a graphical workflow editor as an Eclipse plug-in. The architecture of KNIME is based on three main principles: a visual, interactive framework; modularity; and easy expandability. The system consists of a pipeline of nodes connected by edges that transport data or models. Each node processes incoming data and/or models, producing results on its outputs. KNIME offers a wide variety of nodes for data I/O, manipulation, transformation, data mining, machine learning, and visualization. It also supports extending KNIME with new plug-ins, such as Weka, R, and JFreeChart. Current developments include meta-nodes for encapsulating workflows, high-performance distributed and parallel computing, and chem- and bioinformatics applications. KNIME also includes web services for accessing external computation resources. The system is continuously extended and improved, with a focus on modularity, scalability, and user-friendliness.KNIME (Konstanz Information Miner) is a modular environment that allows for the visual assembly and interactive execution of data pipelines. It serves as a teaching, research, and collaboration platform, enabling the integration of new algorithms, data manipulation, and visualization methods as new modules or nodes. The system is designed to be easy to use, intuitive, and allows for quick and interactive changes to the analysis. It is written in Java and features a graphical workflow editor as an Eclipse plug-in. The architecture of KNIME is based on three main principles: a visual, interactive framework; modularity; and easy expandability. The system consists of a pipeline of nodes connected by edges that transport data or models. Each node processes incoming data and/or models, producing results on its outputs. KNIME offers a wide variety of nodes for data I/O, manipulation, transformation, data mining, machine learning, and visualization. It also supports extending KNIME with new plug-ins, such as Weka, R, and JFreeChart. Current developments include meta-nodes for encapsulating workflows, high-performance distributed and parallel computing, and chem- and bioinformatics applications. KNIME also includes web services for accessing external computation resources. The system is continuously extended and improved, with a focus on modularity, scalability, and user-friendliness.