09 July 2018 - 14 July 2018
Toulouse, France

A new era for migration data

IIASA researcher Dilek Yildiz will discuss migration data and the influence it can have on the understanding of migration, its relevant for policy-making, and  scientific evidence as factor in public debate at this international conference.

Travel connections © pingebat | Shutterstock

Travel connections © pingebat | Shutterstock

ESOF (EuroScience Open Forum) is the largest interdisciplinary science meeting in Europe. It is dedicated to scientific research and innovation and offers a unique framework for interaction and debate for scientists, innovators, policy makers, business people and the general public.

Created in 2004 by EuroScience, this biennial European forum brings together over 4 000 researchers, educators, business actors, policy makers and journalists from all over the world to discuss breakthroughs in science. More than 40% of the participants are students and young researchers. 

World Population Program researcher Dilek Yildiz is panel discussant at this conference during a session on "A new era for migration data?". Together with researchers from the European Commission's Joint Research Centre, the International Organization for Migration, EUROSTAT, and the University of Southampton, Yildiz will discuss how developments in data science can help our understanding of migration, how this information is relevant for policy-making, and how scientific evidence may help to balance public debate.

Yildiz research interests are in statistical demography with a focus on Bayesian projections/reconstruction of multistate populations, population count estimates, and investigating on the use of big data sources.

The 8th edition of ESOF will take place in Toulouse, France, from 9 till 14 July 2018.

For more information please visit the event website.


Globalisation, climate change, inequality, instability and conflicts will continue to push people to move in search of safety, a better life and better economic opportunities. As a result, migration will stay, and this will have an impact on multiple aspects of our lives, including employment, education, welfare and healthcare systems.

Accurate and timely data are needed to understand migration and its impact on societies. Although not replacing the need to improve official statistics and data collections, big data and alternative uses of existing data offer a way to reduce uncertainty and to overcome current gaps related to migration data.

Addressing data challenges, improving comprehensiveness, timeliness and comparability of data, employing new and innovative types of data (e.g. micro-census, social media or mobile phone data), using the most advanced methods to combine different data sources (e.g. techniques to derive migration flows worldwide from migration stock data)  and improving interactive data visualisation and customised views can further facilitate the understanding of the complexities behind migration and its new forms, their drivers and impacts.

The panel will discuss how developments in data science can help our understanding of migration, how this information is relevant for policy-making, and how scientific evidence may help to balance public debate.

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Last edited: 10 July 2018


Dilek Yildiz

Research Scholar

Multidimensional Demographic Modeling Research Group

Population and Just Societies Program

Migration and Sustainable Development Research Group

T +43(0) 2236 807 407

Research at IIASA's World Population Program

IIASA-JRC Centre of Expertise on Population and Migration


Lutz, W., Reiter, C. , Özdemir, C., Yildiz, D. , Guimaraes, R. , & Goujon, A. (2021). Skills-adjusted human capital shows rising global gap. Proceedings of the National Academy of Sciences 118 (7), e2015826118. 10.1073/pnas.2015826118.

Lutz, W., Striessnig, E. , Dimitrova, A., Ghislandi, S., Lijadi, A., Reiter, C. , Spitzer, S. , & Yildiz, D. (2021). Years of good life is a well-being indicator designed to serve research on sustainability. Proceedings of the National Academy of Sciences 118 (12), e1907351118. 10.1073/pnas.1907351118.


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