Gaining insight from data is the overarching goal of many Data Science related activities. However, without understanding the semantics of data and without having the means and techniques to represent semantics in a machine-processable form, insights could turn into wrong or misleading perceptions.
Since we strongly believe that people and scientific communities can learn from each other, this year, SEMANTiCS will feature a special Data Science track, which should close the gap between data science and semantics research. SEMANTiCS has a long-standing tradition in providing methods and techniques for representing data in an interoperable, standardized, and machine-processable fashion. By including researchers and practitioners interested in Data Science, we hope that we can bring together people with various backgrounds and goals to learn from each other and to stimulate a joint future research agenda at the intersection of semantics and data science research and practice.
What can you expect?
This year’s Data Science track will cover research and innovation papers as well as industry and use case presentations and stretch over both conference days. It includes sessions about typical steps in a data science workflow, ranging from “Data Normalization and Aggregation” to “Mining and Linking” and “Anomaly Detection”.
Special presentation format
Furthermore, we have decided to give it a try and allow a special presentation format, which should encourage the audience to actively participate in discussions around synergies, key problems and solutions, common questions, etc. This will be the first session, called “Data Normalization and Aggregation”, which will moderated by team members from the “Association for Knowledge Management”.
We, the chairs of the overall data science tracks are happy that the Data Science track attracted more than enough interest to be included in this year’s program of SEMANTiCS. We are looking forward to meet and exchange ideas with people who share similar interests and are convinced that this year’s SEMANTiCS will be a good place to start these discussions.
Bernhard Haslhofer and Laura Hollnik
Data Science Track Chairs