Artificial Intelligence (AI) is making a profound impact in almost every domain. A vital enabler
of its great success is the availability of abundant and high-quality data for building machine …

The ubiquity of data lakes has created fascinating new challenges for data management
research. In this tutorial, we review the state-of-the-art in data management for data lakes …

Data-centric AI is at the center of a fundamental shift in software engineering where machine
learning becomes the new software, powered by big data and computing infrastructure …

Data collection is a major bottleneck in machine learning and an active research topic in
multiple communities. There are largely two reasons data collection has recently become a …

Large language models (LLMs), such as GPT-4, are revolutionizing software's ability to
understand, process, and synthesize language. The authors of this paper believe that this …

Generating value from data requires the ability to find, access and make sense of datasets.
There are many efforts underway to encourage data sharing and reuse, from scientific …

Data analytics stands to benefit from the increasing availability of datasets that are held
without their conceptual relationships being explicitly known. When collected, these datasets …

Database and Artificial Intelligence (AI) can benefit from each other. On one hand, AI can
make database more intelligent (AI4DB). For example, traditional empirical database …

Data only generates value for a few organizations with expertise and resources to make
data shareable, discoverable, and easy to integrate. Sharing data that is easy to discover …

Database and Artificial Intelligence (AI) can benefit from each other. On one hand, AI can
make database more intelligent (AI4DB). For example, traditional empirical database …