Data Management Systems Seminar: A Data Management Infrastructure for Data Science and AI Innovation

Title 

AGORA: A Data Management Infrastructure for Data Science and AI Innovation

Abstract

Data science and artificial intelligence are driven by a plethora of diverse data-related assets, including datasets, data streams, algorithms, processing software, compute resources, and domain knowledge. Providing all these assets requires a huge investment. As a result, data science and artificial intelligence technologies are currently dominated by a small number of providers who can afford these investments. This leads to lock-in effects and hinders features that require a flexible exchange of assets among users. 

I will present Agora, our vision towards a unified ecosystem that brings together data, algorithms, models, and computational resources and provides them to a broad audience. Agora (i) treats assets as first-class citizens and leverages a fine-grained exchange of assets, (ii) allows for combining assets to novel applications, and (iii) flexibly executes such applications on available resources. As a result, it enables easy creation and composition of data science pipelines as well as their scalable execution. In contrast to existing data management systems, Agora operates in a heavily decentralized and dynamic environment: Data, algorithms, and even compute resources are dynamically created, modified, and removed by different stakeholders. In this talk, I will particularly focus on the execution layer of Agora, which allows for compliance-aware and secure computation.

Bio

Jorge Quiané is Principal Researcher at the DIMA group (TU Berlin) and head of the Big Data Systems research group at the Berlin Institute for the Foundations of Learning and Data (BIFOLD). He is also Scientific Advisor at the IAM group (DFKI). Earlier in his career, he was Senior Scientist at the Qatar Computing Research Institute (QCRI) and Research Associate at Saarland University. Jorge’s research interests are in the broad area of scalable data management, including cross-platform data management and big data analytics. He has published numerous research papers on query and data processing as well as on novel system architectures. He also holds 5 patents in core database areas, such as join processing and data storage, and has been awarded with the best paper award at ICDE 2021. 

Contact Person

Yongluan Zhou