The amount of data and information produced by experimental laboratories studying complex systems is growing at an incredible rate. The knowledge is scattered and disseminated at an increasing number of publishing venues, making the manual analysis and integration of all available information impractical. This highlights the need for automated methods to retrieve and connect related pieces of the extensive yet fragmented collective knowledge, for the purpose of understanding, interpreting, explaining, and predicting the behavior of studied systems. To address this challenge, we have been developing a new tools suite, DySE (Dynamic System Explanation).

read more