Scientific Data Analysis Team (SDAT) intends to organize the first event on the value of data to provide data holders and data analyzers with an opportunity to extract maximum value from their data. This event is organized by International Statistical Institute (ISI) and SDAT hosted at the Bu-Ali Sina University, Hamedan, Iran. 

Organizers and the data providers will provide more information about the goals of the initial ideas, team arrangement, competition processes, and the benefits of attending this event on a webinar hosted at the ISI Gotowebianr system. Everyone invites to participate in this webinar for free, but it is needed to register at the webinar system by 30 December 2020. 

Event Time: 31 December 2020 - 13:30-16:30 Central European Time (CET)

Register for the webinar: https://register.gotowebinar.com/register/8913834636664974352 

More details about this event: http://sdat.ir/en/playdata 

Aims and outputs:

• Playing with real data by explorative and predictive data analysis techniques 
• A platform between a limited number of data providers and hundreds to thousands of data scientist Teams
• Improving creativity and scientific reasoning of data scientist and statisticians 
• Finding the possible “bugs” with the current data analysis methods and new developments
• Learn different views about a dataset.

AWARD-WINNING:

The best-report awards consist of a cash prize:
$400 for first place,
$200 for second place, and
$100 for third place.

Important Dates: 

Event Webinar: 31 December 2020 - 13:30-16:30 Central European Time (CET). 
Team Arrangement: 01 Jan. 2021 - 07 Jan. 2021
Competition: 10 Jan. 2021 - 15 Jan. 2021
First Assessment Result: 25 Jan. 2021
Selected Teams Webinar: 30 Jan. 2021
Award Ceremony: 31 Jan. 2021

Please share this event with your colleagues, students, and data analyzers. 

The Rfssa package is available at CRAN. Dr. Hossein Haghbin and Dr. Seyed Morteza Najibi (SDAT Members) have published this package to provide the collections of necessary functions to implement Functional Singular Spectrum Analysis (FSSA) for analysing Functional Time Series (FTS). FSSA is a novel non-parametric method to perform decomposition and reconstruction of FTS. For more information please visit github homepage of package.