Apr. 01, 2020

Building 96, Room 001

Speaker: Professor Niv Ahituv, Tel Aviv University, Israel


Title: Introducing Data Science into Every Academic Discipline, and Building an Undergraduate Program in Data Science

Abstract:  The contemporary environment of a digital world has engendered a new academic discipline of Data Science (DS), mainly because of the need to cope with huge and diversified data -- Big Data. In parallel, there has been a rapid progress in the development of technologies that enable to identify patterns, to filter big data, and to provide relevant interpretation to data, due to deep learning and sophisticated inference techniques. In addition to becoming a full scale discipline, DS must be introduced into every academic field, ranging from Humanities via Social Sciences, Law, Management, and up to Life Sciences, Medicine, Engineering and more. In fact, every student commencing an academic program should have some fundamental savvy in DS, similar to mastering basic knowledge in English or Math.

The Israeli National Academy of Sciences and Humanities (hereafter – the Academy) has formed an ad-hoc committee whose mission is to suggest how to build a course that introduces DS campus wide. The course should be tuned to each academic discipline, and should be mandatory. In parallel, The Council for Higher Education (MALAG) has formed a committee whose task is to define the subjects and courses to be offered in an undergraduate program of DS.

Prof. Niv Ahituv is a member of the Committee of the Academy, which is close to making its recommendations. He also deals with delineating an undergraduate program. He is also the Chairperson of a special committee of the Ministry of Education of Israel that develops a concentration program for grades 10 to 12 in high schools entitled “Identifying and Retrieval of Digital Information”.

The basic model of DS is the Data Cycle, which looks as following[1]:

Niv Ahituv.png 

This is a generic model which holds for any decision making problem, be it an academic research, a business decision problem, a personal choice, or a public sector decision. Each step in the Cycle requires different tools and approaches. The talk presents a prototype of an undergraduate program in DS, as well as a suggestion for a campus-wide mandatory course.


[1] Niv Ahituv, What Should be Taught in an Academic Program of Data Sciences?,  Digital Presentation and Preservation of Cultural and Scientific Heritage. Conference Proceedings. Vol. 9, Sofia, Bulgaria: Institute of Mathematics and Informatics – BAS, 2019. ISSN: 1314-4006, eISSN: 2535-0366


Bio: Professor Niv Ahituv is a Professor Emeritus of Tel Aviv University (TAU). He retired in 2011 after serving for 30 years in TAU. In addition to being a researcher and lecturer in TAU, he served in the following positions: 2003 to 2011 – Founder and Director of the Institute for Internet Studies; 2009 to 2012 – Director of the Institute of Business Research; 1999 to 2002 – Vice President and Director General (CEO) of TAU; 1989 to 1994 – Dean of the Faculty of Management.

From 2006 to 2008, he was a team member in a research project for the EU on e-Government for Low Socioeconomic groups (ELOST). From 2010 to 2014, he was a member of a research consortium of the project PRACTIS (Privacy - Appraising challenges to Technologies and Ethics) supported by the EU.

He has published several books, chapters in book, and numerous articles. In a worldwide ranking of scientific publications in Information Systems published from 1985 to 1990, Professor Ahituv came out in third place.

 He holds degrees of B.Sc. in Mathematics, MBA, and M.Sc. and Ph.D. (1979) in Information Systems Management.​