The article describes the academic data, which derived from a University E-government analytic platform, which supports the facilitation of blended learning in a Greek University during and after the COVID19 outbreak [1,2]. University e-government services refer to a set of information systems that facilitate the functionalities of the University and enable the management of the underlying information [3,4]. These educational, research and managerial services, also called U-EGOV, follow the four stages of e-government (Presence, Interaction, Transaction, Transformation) [5]. In the presented approach, the data was aggregated from the university services with an automated process and includes all the individual U-EGOV services, that is the synchronous and asynchronous educational platforms, the teleconferencing tool, etc. The dataset created contains information about the courses, the assignments, the grades, the examinations, as well as other significant academic elements of the synchronous and the asynchronous education that takes place in the University. The analysis spans from the spring semester of the academic year 2019–2020, the winter semester of the academic year 2020–2021 to the spring semester of 2020–2021 (three semesters in total). The sample consists of 4800 records and after the preprocessing 4765 records (statistics of courses attended by students) which include 1661 unique students within the university in twenty (20) courses. We have followed an educational data mining approach on the collected data by utilizing an automated data aggregation mechanism to gather data for the selected courses, in order to enhance the learning process and the quality of services. The dataset can be reused: i) as a reference point to measure the quality of the academic outputs and its progress through the years and ii) as a basis for similar analysis in other Higher Educational Institutions (HEIs).

Intensive Care Units (ICUs) generate a large amount of valuable data related to the health status of patients. In addition, ICUs can leverage other sources of big data, such as structured data, text, video, and images. In this work, a framework for the future ICU system is proposed, which is based on the Soft System methodology (SSM) and the use of big data technology. The framework and the related activity models ensure that the ICU can have its particularities and specialties, as well as its core services and functions. The application of the framework also implies that ICU can provide ongoing expertise and training to upgrade its staff, can improve interoperability with the National Health System, and ICU staff intercommunication and remote services.

The pandemic and the various natural disasters related to climate change force Universities to operate remotely during certain periods of time. Synchronous and asynchronous Learning Management System (LMS) platforms at University provide a framework for distant operation. But it is crucial to maintain low students' attrition rates and ensure the quality of offered education at universities. This paper presents a survey of students' perceptions regarding their participation in online distance examinations in a Department of a Greek University. In this research, an online questionnaire is used in order to capture students' opinions about online distance examinations and to reveal information concern accessibility issues during the educational activities. The survey also recorded the students' opinion concerning the use of distance learning platforms, the communication with the professors and interactions between the students. According to the analysis of the questionnaires, students are willing to express their opinion on critical issues, such as the distance examinations and the problems that they face this period anonymously. To a satisfactory degree, they have the necessary equipment needed to participate in the distance educational process and they use the existing blended learning infrastructure.