New UJ Center to focus on domain knowledge and how to leverage applied data science

The new Center for Applied Data Science (CADS) at the University of Johannesburg (UJ) aims to bring together computer scientists and scientists in the field to promote and accelerate data-intensive education with the aim of fostering research and l education in data-driven knowledge discovery.

Director of the School of Consumer Intelligence and Information Systems at UJ College of Business and Economics Professor Thanks notes that the centre, which is a collaboration with Toulouse Business School Education, will work to infuse the study of science by promoting various school-wide and outreach activities.

“The center is a multi-disciplinary space where different departments and disciplines work together, including on agricultural research, which many of our people on the continent depend on for a living, as well as transport, supply chain management and marketing research. The goal is for research to have an impact as it affects and should improve the lives of our people,” she said during a virtual launch of the center.

There are ongoing research projects at CADS on post-harvest waste, integrating transport options in the city of Johannesburg and beverage consumption, among others, UJ CADS Head Professor illustrated. Hossana Twinomurinzi.

“Data is the foundation of the fourth industrial revolution. They are already changing the way we work, live and communicate and are reshaping governments, education, health care, industries and commerce. The ability to use and analyze data will be one of the key drivers for businesses in the future,” said the UJ Vice Chancellor and Senior Professor. Tshilidzi Marwala.

“In this context, the center aims to provide evidence-based information to discover new ways of working as industries, organizations, communities and societies,” he said.

APPLIED DATA SCIENCE

The virtual launch of CADS on October 7 was part of UJ’s Artificial Intelligence (AI) Day virtual conference. A panel of researchers involved in data science research on post-harvest agriculture, marketing, smart mobility and learning at the new center gave an overview of their research.

Teacher Fawole Olaniyi pointed out that the application of data science in post-harvest agriculture is used to study the complex value chain in which many products are lost.

“The world produces enough food to feed 1.5 times its population, but 850 million people go hungry every day. If we prevent food waste, we would be able to feed everyone and minimizing losses would also bring economic benefit, allow industry to grow and ensure that nutrition and food are provided to the most vulnerable,” did he declare.

This can only be done by improving value chains. Agricultural value chains involve many stakeholders and generate a lot of information, and research at CADS focuses on understanding information. The center has a post-doc who is researching the application of machine learning for the identification, classification and sorting of fresh produce, he added.

In addition, the professor of transport economist Rose Luke said his team’s work was closely tied to what Olaniyi was working on, as they not only worked on transportation in general, but also made sure the right products got to the right markets.

“Currently, we are looking specifically at mobility challenges, as the city of Johannesburg lacks adequate public transport and needs to look at ways to optimize what is currently present in the environment and make better use of existing resources,” she pointed out.

Congestion, accidents, disruption from load shedding, urban sprawl, long journey times and high transport costs are common mobility challenges and adding capacity solely through infrastructure comes up against funding and other challenges, noted Luke.

Moreover, although there are many different modes of transport, the system is fragmented and does not work as a whole. Private car use is high. There is also some duplication in terms of funding and not the best use of resources on some subsidized corridors.

“We need to look at smart mobility solutions to leverage what’s out there and what we can do to solve some of these challenges. To do this, we need readily available data.

“The idea is to ensure that everyone’s individual mobility needs are taken into account and to use what we have more intelligently to reduce congestion and develop faster and more sustainable transport solutions”, a- she declared.

Smart mobility looks at how to reduce costs and how to move people sustainably or more sustainably. The resulting research questions generally focus on how smart mobility can be defined in the city of Johannesburg, and then what infrastructure, technologies and logistics are needed for smart mobility in a city like Johannesburg, explained Dr. Joas Magetowho works alongside Luke in the center.

The aim is to develop a holistic framework for mobility, environmental, social and economic benefits, potential challenges and also how solutions would be adopted and accepted, he said.

“We found that government cannot effectively participate in the provision of transport as a service, but should help create smart mobility solutions by providing the right laws, regulations and infrastructure that can support a mobility ecosystem smart,” he noted.

Additionally, prospective students and industry practitioners at CADS should have appropriate domain knowledge to serve as a basis on which to interpret the data, Mageto added in response to a question about what prospective students and practitioners industry should expect during classes at the center.

Meanwhile, Siyabonga Mhlongo was researching the use of data science to improve teaching and learning at CADS.

Larger volumes of data are being generated as many teaching and learning activities have moved online. The research explores how this data can be used to make the educational journey more exciting and impactful for learning, teachers and administrators, he said.

“Learning analytics explores this data to see what happened and to gain insight into what is happening in a teaching and learning environment. This is a new field and we are only beginning to understand the value that data can bring to the teaching and learning environment.