YÜKSEK ÖĞRENİMDE AÇIK VERİ VE BÜYÜK VERİ MODELİ VE OLASI SONUÇLARI

Abstract

The basic outputs of universities can be listed as education, research-development and service to society. Managerial software systems at universities generate large amount of open data during daily operations. The data generated by these systems contain valuable public institutional performance information along with critical private information. These public data can be classified, collected and processed by using big data approaches for performance monitoring. In this study, an open data platform is modelled, and issues are discussed related how open data is collected, stored and processed using big data approaches to extract interested performance information. It is shown that institutional performance information can be presented according to a wide variety of metrics from the collected data. Scientific studies that can be carried out in higher education using big data are examined under 4 headings: Creating an open data directive for universities, development of open data platform, institutional accreditation service, creating a digital twin. This platform can be used for online institutional evaluation either by university management or accreditation agencies.