We sat down with Peter Haber and Manfred Mayr of the Salzburg University of Applied Sciences, both conference chairs of the 1st International Data Science Conference that will take place on 12-13 June in Salzburg, Austria. Our FutureTDM symposium will be held during this event: a great fit to actively engage with a community of researchers and practitioners and to hear their views.
This is the first time the event is taking place. Why has this initiative been taken, and what is the main aim of the event?
Everything started with the Salzburg Data Science Symposium in 2014, where we assume that a team of data scientist with different expert knowledge is necessary to analyze data-intensive problems. From this perspective, the idea to establish an international data science conference developed, where industry and science exchange state of the art solutions and their field of application as well swap new approaches and challenges.
Could you tell us more about the focus on two distinct tracks: Research and Industry?
The research track focuses on state of the art scientific approaches in data science from data extraction, data mining, machine learning and science application. The industry track showcases real practitioners of data-driven business and how they use data science to help achieve organizational goals. The talks will concentrate on our broad focus areas of manufacturing, retail and social good. The FutureTDM Symposium complements the conference by giving overarching policy recommendations and sector specific guidelines to help stakeholders overcome the barriers the FutureTDM consortium has identified. Therefore, users of data technologies can meet with peers and exchange ideas and solutions to the practical challenges of the data-driven business.
Which topics do you think are most debated at the moment in the international data science field?
Both the scientific as well industry community set the trend towards machine learning. Machine learning is a very complex task. Methods for data analytics like semantical, reasoning or predictive approaches are necessary.
Which barriers to the wider uptake of text and data mining do you see (for either research or industry)?
With the trend to industry 4.0 and the digitalization of the business processes data science as a profession will be getting more and more important. The iDSC 2017 seeks to establish a key data science event fostering the exchange of all stakeholders.
