A community conference for data makers everywhere, returns in person!

Featuring stories about data sharing and data analysis from science, journalism, government, and open source.

April 19-20 2023, Buenos Aires, Argentina.

Conference location: Novotel, Av. Corrientes 1334

Conference Keynotes

Dr. Laura Ación

I am a Research Scientist at the National Research Council in Argentina (CONICET), where I lead a multidisciplinary artificial intelligence and data science co-laboratory. Our co-laboratory pushes for the responsible use of data, including open science and reproducibility in research, but we also train scientists in these practices. I believe in the transformational power of inclusive collective efforts, that is why I was an instructor and trainer for The Carpentries and co-founded MetaDocencia, a Spanish-speaking organization inspired by the Carpentries that I currently co-direct. I also contributed to catalyze and co-lead other communities of practice such as R-Ladies Global, R-Ladies Buenos Aires, R en Buenos Aires, and LatinR, a trilingual Latin American R conference.

Giuseppe Sollazzo

Giuseppe is Deputy Director of the AI Lab at the UK National Health Service, where he is Head of AI Skunkworks & Deployment, running a programme of AI-driven pilots dedicated to open source knowledge sharing and scrutiny of AI. A data activist and wrangler by background, he helped support the UK Government's open data agenda as a member of the Open Data User Group, and was Head of Data at the Department for Transport. He writes the data newsletter "Quantum of Sollazzo".

Dr. Alex Hanna

Dr. Alex Hanna is Director of Research at the Distributed AI Research Institute (DAIR). A sociologist by training, her work centers on the data used in new computational technologies, and the ways in which these data exacerbate racial, gender, and class inequality. She also works in the area of social movements, focusing on the dynamics of anti-racist campus protest in the US and Canada. Dr. Hanna has published widely in top-tier venues across the social sciences, including the journals Mobilization, American Behavioral Scientist, and Big Data & Society, and top-tier computer science conferences such as CSCW, FAccT, and NeurIPS. Dr. Hanna serves as a co-chair of Sociologists for Trans Justice, as a Senior Fellow at the Center for Applied Transgender Studies, and sits on the advisory board for the Human Rights Data Analysis Group and the Scholars Council for the UCLA Center for Critical Internet Inquiry. FastCompany included Dr. Hanna as part of their 2021 Queer 50, and she has been featured in the Cal Academy of Sciences New Science exhibit, which highlights queer and trans scientists of color. She holds a BS in Computer Science and Mathematics and a BA in Sociology from Purdue University, and an MS and a PhD in Sociology from the University of Wisconsin-Madison.

Karthik Ram

He is a research scientist at UC Berkeley’s Institute for Data Science and Berkeley Initiative for Global Change Biology. His research is interdisciplinary and covers a range of topics, including the impacts of climate change on ecological communities, reproducible research, sustainable scientific software, and open science. He is the co-founder and director of The rOpenSci Project, co-founder and project lead at the US Research Software Sustainability Institute, a founder and editor at the Journal of Open Source Software, and a founding editor of The rOpenSci Software Review.

csv,conf is about...

Building Community

csv,conf brings diverse groups together to discuss data topics, and features stories about data sharing and data analysis from science, journalism, government, and open source.

People who love data

csv,conf is a non-profit community conference run by folks who really love data and sharing knowledge. If you are as passionate about data and its application to society as we are, then this is the conference for you.

Big and small

csv,conf conferences aren't just about spreadsheets. We curate content on broader topics like advancing the art of data collaboration- from putting your data on GitHub, to producing meaningful insight by running large scale distributed processing on a cluster.