Data Science Soirée

Since the digital revolution the collection and processing of large amounts of data have become a major issue not only in natural sciences but also in humanities. Because of its importance the new work group “Data Science” was founded within the HeKKSaGOn-Network in 2017. With regard to bring together researchers from different fields of expertise and  invigorate interdisciplinary partnerships meetings are held to support networking and the exchange of ideas as well as research results.



■4rd Data Science Soirée(February 15, 2018・Kyoto)

Future of Data-Driven Higher-Education

Speaker: Hiroaki Ogata, Acacemic Center for Computing and Media Studies, Kyoto University 

Date: February 15, 2018 18:00-19:00

Venue: Kyoto University Library 3.Floor, Common Study Room 5, Kyoto University 


“Learning analytics” is one of the key words that draw attention by increasing importance of data utilization in higher education. In order to support education and learning, it is very important to utilize educational data accumulated by real-world classrooms and online e-learning courses, etc. This talk will introduce the analytics of education / learning data and its research and practice in Japan and discuss future of data-driven education / learning environments.



■3rd Data Science Soirée(January 11, 2018・Kyoto)

Computer Simulation for Nano Processing; Achievements and Limitations

Speaker: Aoki Takaaki, Institute for Information Management and Communication, Kyoto University 

Date: January 11, 2018 18:00-20:00

Venue: Academic Center for Computing and Media Studies, Meeting Hall 1.Floor, Kyoto University 


Nano-processing utilizing beam technologies has been developed along with both fundamental experiments and computer simulations. The author has been involved in large-scale molecular dynamics simulations to model the characteristic collisional process between cluster (several to huge aggregation of atoms or molecules) ion beam and solid target. In this presentation, several simulation results are demonstrated, which can be directly comparable to experimental results and applied for process modeling. On the other hand, commoditization of core simulation program has rapidly progressed. Along with this, we will also discuss that the weight on deep insight in simulation design and development of supporting tools to support it are increasing.



■2nd Data Science Soirée(December 7, 2017・Kyoto)

Delineating Attractive Futures of the Society by Integrating Deep Data Analysis and Speculative Design

Speaker: Prof. Dr. Daichi Kohmoto, Junior Associate Professor at the  Institute for Information Management and Communication

Date: December 7, 2017 18:00-20:00

Venue: Kyoto University Library 3.Floor, Common Study Room 5, Kyoto University 


Starting to explore the attractive futures of the society in many senses actively often leads to crucial problems and directions that we should urgently focus on. At this moment, we’ve already had many technical machineries and philosophical viewpoints (of course, with their known limitations) for resolving various kinds of problems on our ways; but the road sometimes breaks up if it goes beyond the scientific research. We’ll discuss how one can step forward with confidence by integrating these towards our better futures via introducing some examples, mainly focusing on the side of data science.



■1st Data Science Soirée(November 11, 2017・Kyoto)

Big Data Standardization and Trials to create World Grid Square Statistics

Speaker: Aki-Hiro Sato, Department of Applied Mathematics and Physics

Date: November 11, 2017 18:00-19:00

Venue: Kyoto University Library 3.Floor, Common Study Room 5, Kyoto University 


Big Data Standardization is crucial issues in international communities such as ISO, ITU, IEC and UN, recently. In this talk, I will mention current situations about Big Data Standardization. As an example of Big Data, I will explain my recent study to create World Grid Square Statistics. The grid square statistics is a kind of geospatial statistics in order to understand statistics regarding geographical locations and anonymization. I recently propose world grid square codes by extending Japanese grid square codes standardized in Japan Industrial Standards (JIS X0410). I will show some examples of grid square statistics created from point data collected from internet services, satellite images, and government official statistics.