Combining informetrics and trend analysis to understand past and current directions in electronic design automation

Abstract There has been increasing interest in the study of research communities with goal optimizing their outcomes and impact. While current methods can predict future trends, they offer little insight about causes trends. However, causal is important for strategic decision making to improve a community. This paper presents new method possible inefficiencies community by relating them disconnections between like trends number publications, patents, citations, so on. The combines traditional scientometric webometric metrics metric predictions recent model trend analysis proposed was used analyze electronic design automation (EDA) domain. showed intriguing papers, granted impact its main publications. suggests slightly decreasing visibility EDA, while having less novel, commonly-accepted knowledge area. gained three decisions EDA community: avoiding ignore ideas, reducing complexity framed problems, keeping minimal gap real-life needs academic solutions.