Analyzing publication productivity using a web-based system: A preliminary study

There is no automated system that collect Universiti Malaysia Sabah (UMS) academic staff publication from Scopus. Previously, data collection is made by retrieving the records from Scopus by searching for UMS affiliation and filtering by year. The data then is matched with Staff ID of the academic staff. This requires time and may lead to error because the work is done manually. In addition, the author name that are retrieved from Scopus may not be affiliated with UMS anymore, so the data is invalid. Thus, this paper highlights the significance of a project proposed as a platform for universities to gauge scholars’ research productivity in the Scopus database. Data from Scopus were extracted, analyzed and visualized using criterions such as age, academic position, as well as teaching loads that may affect a scholar’s research productivity. This paper focuses on the datest of academic staff from UMS, and their publication in Scopus, relative to their socio-demographic data