As material modeling and simulation has become vital for modern materials science, research data with distinctive physical principles and extensive volume are generally required for full elucidation ...

Disclaimer: If a data set is provided, it needs to be ready for analysis with clear documentation. We can provide guidance for creating and organizing datasets. We do not provide data extraction ...

UC Investments and UC Berkeley’s Institute for Data Science today (May 22) announced the formation of the AI Futures Lab, a new hub for groundbreaking research and collaboration at the intersection of ...

In today’s research world, data is produced faster than ever. Old methods like paper records or simple spreadsheets can’t keep up with the volume and complexity of this data. Lab Data Management ...

Informatics solutions such as Electronic Lab Notebooks (ELN) and LIMS systems (Laboratory Information Management System or LIS) may be insufficient to manage this amount of data, leading to ...

Artificial intelligence (AI) holds promise for healthcare, but real-world implementation remains difficult. The Mayo clinic platform (MCP) addresses this by providing scalable, multi-institutional, de ...

The substantial volume of data collected and analyzed by modern laboratories - irrespective of their sector - means that effective lab data management has never been ...

Empirical research requires good data to complement statistical rigor in providing answers to global poverty questions. Poor data quality can lead to biases in causal inference, lower the probability ...