LEGOLAS project is an attempt to provide an interface to explore various temporal profiles of authors in PubMed identified by the Author-ity dataset. These profiles are possible because of the high quality (98% recall) of the Author-ity dataset of disambiguated authors in PubMed. The project can help scholars identify trends in author metrics over time. While many metrics are standard like number of papers, number of citations, etc.; we also provide additional metrics like author expertise and self-citation rates based on our research. This project complements the GIMLI project which introduced the idea of temporal profiles for author novelty.