Reutemann, P. & Vanschoren, J. (2012). Scientific workflow management with ADAMS. In Lecture Notes in Computer Science, 2012, Volume 7524 LNAI, Issue Part 2: Machine Learning and Knowledge Discovery in Databases,pp. 833-837.
Permanent Research Commons link: http://hdl.handle.net/10289/6766
We demonstrate the Advanced Data mining And Machine learning System (ADAMS), a novel workflow engine designed for rapid prototyping and maintenance of complex knowledge workflows. ADAMS does not require the user to manually connect inputs to outputs on a large canvas. It uses a compact workflow representation, control operators, and a simple interface between operators, allowing them to be auto-connected. It contains an extensive library of operators for various types of analysis, and a convenient plug-in architecture to easily add new ones.