Time aware knowledge extraction to analyze nanosafety cluster scientific activities

With the rapid development ot biomedical sciences, a growing amount of papers reporting new scientific findings are published and indexed in different unstructured biomedical data sources. In order to really appreciate and effectively benefit from the availability of this amount of data there is an urgent need to support the deployment of intelligent information services, such as: temporal trends and group detection, expert finding, review experts, link prediction, and so on. This need is even more stressed if we analyze dissemination activity of emerging scientific communities that are working on specific research topics in the field of biomedical science. Motivated by the fact that nanotechnologies are one of the key enabling technologies nowadays, in this paper we instantiate and contextualize the Time Aware Knowledge Extraction (TAKE) methodology, introduced in previous work, as a tool to analyze the activities of the nano-safety scientific community coordinated by the EU NanoSafety Cluster (NSC). This methodology enables us to extract timed association rules. To validate and give evidence of the goodness of these rules, a summary of the so obtained results of the analysis is provided identifying distinguishing features, and detecting emerging collaboration among the NSC's Working Groups and their members over the timeline.