Universities and Institutions Are Pushing Data Science Research
Tags: university, funding, ddatascience
Published: 2020-04-13 09:29:40

Data science is exploding. The constant stream of data and increasing penetration of mobile devices and endless use of web and mobile applications is generating copious amount of data, reaching petabytes in amount. The industry realizes the potential data science has to offer, and is making all attempts to capitalize on it by pursuing research and development initiatives in the area. 

Data science research and development at universities and colleges   

Global and local educational institutions are equally inclined and driven to put data science to good use, especially in fields where impact can make huge difference – medicine and healthcare research. That’s something we’ve have imagined for data science to do for a long time and is beginning to be realized. 

The University of Manchester, for instance, has various ongoing data science research. The University is seeking proposals for many more research projects and offers a good corpus of fund for research.  While the University of Rochester has set up the Goergen Institute for Data Science, which promises 460 new jobs. The institute is out looking to fund various data science research. The University of Florida has a dedicated Data Science Research Lab working to address pressing industry problems. The Archimedes Project under research at the lab is sponsored by tech conglomerates and multi-national companies including Google, Amazon, Green Plum, Pivotal among others. The University of Oregon under its Research and Innovation department offers up to $60,000 fund for data science research. Clearly data science is growing by leaps and bounds and signs of lack of <a href="https://www.worlddatascience.org/world-data-science-initiative">university funding</a>, which was once a deterrent for research and development in many areas, are now absent. 

Data science talent development has been a major concern for both the industry and academia.  Earlier mostly Master’s program existed for data science. While world’s leading universities continue to offer Master’s program, many universities and colleges have begun to offer data science specialization as bachelor’s program. Yale University, for instance, offers an undergraduate in data science. This is a sign of educational institutions pushing themselves to meet the industry demands of the growing need for talent in data science – a resounding fact 

In addition to universities and colleges, private organizations have come to the frontline of data science research. World of Data Science, an international body, offers up to $300 million in grants in the field of data science. Education institutions worldwide can seek fund for their data science research and related projects from the organization. Such funding opportunity for data science are taking the field to an all new height. 

Data Science Consortiums 

While global conglomerates are playing their part to push the horizons of data science by university funding in research and development, data science communities are catering to the need of knowledge of skills and expertise required in the field. Data science consortiums and for profit organizations form a large part of this movement. Data Science Foundation, for instance, offers tutorial and courses to those who seek to learn and implement. Similarly, Singapore Data Science Consortium collaborates with public agencies and companies to develop data science capabilities in collaboration high educational institutions. And that comes with well-paid grants. The consortium offers up to $21,000 in grants. 

All in all, data science is getting bigger day by day, with the combined effort of industry and academia. While the industry seeks applications of the field to improve products and services, the academia is working to arm the industry with all necessary pre-requisites. Many more consortiums equipped with vast amount of collective knowledge and experience in the industry and academia are coming up to further push the boundary of data science research. At the same time,