Research Data Management helps researchers navigate the increasingly complex landscape of data planning, storage, and sharing. This guide can be used to learn about best practices, tools, and services related to research data across disciplines. If you need assistance, contact RDM Consulting at

Improving campus services for working with sensitive data

Increasingly, researchers in a wide range of fields at UC Berkeley are applying novel data science approaches to very large sensitive and restricted data sets. Working closely with Berkeley Research Computing (BRC), the Research Data Management (RDM) Program has been helping dozens of faculty, students, and postdocs working with sensitive data by providing consulting expertise in a number of disciplines, including the biological sciences, public health, social welfare, demography, computer science, and more. The combined approach of providing data management and computation support helps researchers integrate data management and curation best practices into their larger research workflows while protecting their data. 

Flowchart for text and data mining Getting the sources you need for your text mining project

You have a great research question that you want to answer with text data mining (TDM) methods, and you've got some Python under your belt or you've decided to see what you can learn from a browser-based tool like Voyant. You're ready to get started on a computational text analysis project.

data graphic Publisher Data Requirements Revisited

In May and September of 2017, the Library wrote posts (read them here and here) about a number of publisher research data policies.

UC Berkeley's Research Data Management program and our partners provide consulting, training, and documentation around each of these areas. Read more below, or email to set up a consultation.