Events

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Upcoming Events

A short list of the upcoming events. You can also visit the past events page.

Social Impact Data Hack 2017

Start:
2017/11/10
End:
2017/11/12
Location:
Tartu, Estonia
Link:
Social Impact Data Hack 2017
Description:

This datathon event is scheduled for October-November 2017.

DAPS2017: Data mining for the Analysis of Performance and Success

Start:
2017/11/18
End:
2017/11/18
Location:
New Orleans, USA
Link:
DAPS 2017
Description:
The increasing availability of Big Data, able to capture diverse collective phenomena, provides an unprecedented opportunity to explore the patterns underlying success. From the strategies followed by successful sportsmen to the emergence of runaway videos on YouTube, from popularity in social media to rising starts in the scientific enterprise, from widespread technologies to groundbreaking innovations, there is wealth of data that can be explored to answer common questions: How can we measure performance? What are the common patterns of success?

Data analysis & Social Mining for the Interconnected Society

Start:
2017/11/29
End:
2017/11/30
Location:
Department of Computer Science, University of Pisa, Largo B. Pontecorvo 3, Pisa, Italy
Link:
Data analysis & Social Mining for the Interconnected Society
Description:

Motivation of the Track

Digital Infrastructures for Research 2017

Start:
2017/11/30
End:
2017/12/01
Location:
Square, Brussels, Belgium
Link:
Digital Infrastructures for Research 2017
Description:
Europe's leading e-infrastructures, EGI, EUDAT, GÉANT, OpenAIRE, PRACE and RDA Europe, invite all researchers, developers and service providers for two days of brainstorming and discussions at the Digital Infrastructures for Research 2017 event (30 November - 1 December 2017).

Conference on Fairness, Accountability, and Transparency FAT*

Start:
2018/02/23
End:
2018/02/24
Location:
New York City, USA
Link:
FAT* Conference
Description:

Algorithmic systems are being adopted in a growing number of contexts. Fueled by big data, these systems filter, sort, score, recommend, personalize, and otherwise shape human experiences of socio-technical systems. Although these systems bring myriad benefits, they also contain inherent risks, such as codifying and entrenching biases; reducing accountability and hindering due process; and increasing the information assymmetry between data producers and data holders.