GeoCroissant- A Metadata Framework for Geospatial ML-ready Datasets

Events > GeoCroissant- A Metadata Framework for Geospatial ML-ready Datasets

GeoCroissant- A Metadata Framework for Geospatial ML-ready Datasets

Webinar Speakers:

Dr. Rajat Shinde, Prof. Elena Simperl

Affiliation:

NASA IMPACT – The University of Alabama in Huntsville, King’s College London,

About the Webinar

Croissant is a standardized format engineered to simplify the utilization of ML-ready datasets in ML applications. Croissant facilitates a comprehensive metadata vocabulary based on schema.org and seamless integration across diverse ML platforms and repositories, enabling practitioners to incorporate datasets into their workflows with minimal coding. Its modular and extensible design supports integration with common ML tools for data preprocessing, analysis, and labeling. Additionally, Croissant emphasizes Responsible AI (RAI) by addressing critical aspects such as bias mitigation, fairness, and data robustness, thereby promoting ethical AI practices via the Croissant RAI extension.

Building upon the foundation of Croissant, GeoCroissant is specifically tailored for geospatial machine learning (Geo-ML) datasets. GeoCroissant format and supporting tools enhance the core Croissant framework by incorporating essential elements into the metadata. It is aimed at addressing unique challenges associated with large-scale geospatial data, including geographical biases and data-centric issues, ensuring responsible AI practices in Earth observation tasks.

This webinar is aimed at introducing the IEEE GRSS community with a concise overview of both Croissant and GeoCroissant, highlighting their features and applications in ML and geospatial contexts. The session will conclude with a dedicated question and answer segment, providing an opportunity for participants to engage with the speakers and deepen their understanding of these frameworks.

Join us to gain valuable insights into advancing your ML and geospatial projects through standardized and responsible ML-ready data management.

[1] mlcommons.org/croissant/1.0

[2] mlcommons.org/croissant/RAI/1.0

About the Speakers

Dr. Rajat Shinde is a Computer Scientist working at NASA Interagency Implementation and Advanced Concepts Team (IMPACT) with the University of Alabama in Huntsville. Rajat holds a Ph.D. in Geo-informatics from the Indian Institute of Technology Bombay, India and was a recipient of the Prime Minister’s Research Fellowship awarded to selected research scholars. He’s currently working on the Multi-Mission Algorithm and Analysis Platform (MAAP) and Foundation Models for geoscience where his research areas include Above-Ground Biomass (AGB) data related research and data-centric AI respectively. Rajat leads a collaborative effort on the development of GeoCroissant – a metadata standard for geospatial machine learning datasets. Also, he co-chairs the Earth-2 Working Group under the Earth Science Informatics Technical Committee of the IEEE Geosciences and Remote Sensing Society (GRSS) focusing on AI Foundation Models for Digital Twins. For his open source contributions, Rajat is an elected Vice-President on the Open Source Geospatial Foundation’s (OSGeo) Board of Directors.

Elena Simperl is a Professor of Computer Science and Deputy Head of Department for Enterprise and Engagement in the Department of Informatics at King’s College London. She is also the Director of Research for the Open Data Institute (ODI), a Fellow of the British Computer Society and the Royal Society of Arts, and a Hans Fischer Senior Fellow. Elena features in the top 100 most influential scholars in knowledge engineering of the last decade and in the Women in AI 2000 ranking. She obtained her doctoral degree in Computer Science from the Free University of Berlin, and her diploma in Computer Science from the Technical University of Munich. Prior to joining King’s in 2020, she was a Turing Fellow, and held positions in Germany, Austria and at the University of Southampton. Her research is at intersection between AI and social computing, helping designers understand how to build smart sociotechnical systems that combine data and algorithms with human and social capabilities. Elena led 14 European and national research projects, including recently QROWD, ODINE, Data Pitch,  Data Stories, ACTION, and MediaFutures.
Elena’s interest in leading initiatives within the scientific community has also taken form through chairing several conferences in her field, including the European and International Semantic Web Conference series, the European Data Forum, and the European Semantic Technologies conference. She is the president of the Semantic Web Science Association.