IEEE MDM 2025 Diversity and Inclusion Awards

We support Diversity & Inclusion in the MDM community. We offer awards to help students and early stage researchers, who belong to underrepresented communities, to participate in MDM 2024. These grants are possible via sponsorship funds that come from: IEEE TCDE, Emeralds Horizon EU project, and the European Integrated Infrastructure for Social Mining and Big Data Analytics, SoBigData++ Horizon 2020 project. This application form will serve as the central entry point for all travel grant applications for our conference.

About the award

• One award is a maximum of 1100 EUR
• The sums spent by the awardee will be reimbursed only after they have been spent
• Covered expenditures include only event registration fees, transportation costs, and accommodation costs
• Awardees will be contacted before the event with further details regarding the reimbursement process and allowed expenditures

Selection Criteria

These awards aim to promote a more diverse participation to computer and data science events. The following factors will be considered in the selection. We thus encourage applicants to highlight them in their applications:
• Applicants who are students (undergraduate, graduate or PhD), or early career researchers
• Applicants based in countries with low GDP per capita
• Applicants who identify with a minority group, following the European Commission’s definition (https://home-affairs.ec.europa.eu/pages/glossary/minority_en)
• Awardees will be selected by a panel:
◦ within the SoBigData++ project for the SoBigData award
◦ within the MDM 2024 D&I committee for the MDM award
• One may apply for one or both awards, but can receive at most one of them.
• Taking into account the above factors, priority will be given to applicants with accepted papers at IEEE MDM 2025.

Selection Committee

• Bettina Berendt (TU Berlin, Weizenbaum Institute, DE; KU Leuven, BE) (MDM Award)
• Vana Kalogeraki (Athens University of Economics and Business, GR) (MDM Award)
• Dr. Marco Braghieri (Assistant Researcher in Social Big Data at the Department of Digital Humanities, King’s College London) (SoBigData Award)

Application Process

To apply, you only need to submit this application: https://docs.google.com/forms/d/e/1FAIpQLSdtnIeXxs40Ql8KVZg_fl28_Uir-FyA6e4BuN9LgqMOa2F-7A/viewform?usp=sf_link

Service Requirement

Please note that we ask all grant recipients to volunteer for four hours at the registration desk sometime during the conference week. You get to pick your time slots, so you will not be forced to miss anything you want to attend.

Deadlines

• The deadline for applications is Sunday April 28th, 2024, anywhere on earth.
• Notification is due May 6th, 2024.

After receiving the award

• Awardees recipients must register and attend the full conference
• Awardees will be asked to produce evidence of their expenditures (via receipts, confirmation of payments, et al.)
• Awardees of SoBigData award will be asked to write a short article about their participation in the event and current research work which will be published on the SoBigData website and publications
• Awardees of SoBigData award will be asked to give permission to the SoBigData consortium to use their name and image on the SoBigData communication channels and publications

About the SoBigData Award for Diversity and Inclusion

Computer and Data science currently fail to adequately address equality and diversity issues, as there are genders and minorities which remain woefully underrepresented. The European Integrated Infrastructure for Social Mining and Big Data Analytics, the SoBigData++ Horizon 2020 project has a mandate to promote equality and has established an award to promote a more diverse participation in computer and data science events. SoBigData++ has created the SoBigData Award for Diversity and Inclusion aimed at fostering participation from underrepresented groups, providing support to cover costs connected with the participation in computer and data science events.

SoBigData++ has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreements No. 871042