Manage and Share Your Data with Help from HSLS Data Services

The HSLS Data Services team can help you manage, publish, and share your data for any type of research project. We offer consultations, classes, and customized trainings in the following areas:

Research data management and sharing

Organizing files, writing documentation, and sharing datasets for reuse are crucial practices for improving the reproducibility of research. We offer personal consultations on data management topics and teach classes throughout the semester. In particular, we offer:

  • Synchronous classes on file-naming best practices, writing data management plans for grant applications, and responsibly reusing data (or making your data available for reuse).
  • Asynchronous self-paced learning modules (including one named “Sharing Data and Code”). Upon completion, you can earn badges to share on social media, LinkedIn, etc.
  • One-on-one consultations on writing and implementing a data management and sharing plan (DMSP) for the NIH’s Data Management and Sharing Policy or Pitt’s Research Data Management Interim Policy.
  • Review of DMSPs prior to submission with grant proposals. If you write your plan using one of the templates at DMPTool, use the “request feedback” tab to get comments and suggestions (please allow us at least five business days for an initial review of your plan).

Open science

Researchers, clinicians, and patients all benefit when scientists can examine each other’s work, build on existing data, and attempt to replicate experiments. The practice of making data, protocols, and scripts as publicly available as ethically and legally possible is called “open science.” But making your science open can be challenging, especially when you’re setting up new workflows and procedures for the first time. HSLS can help you with open science topics including:

  • Following the FAIR principles of findability, accessibility, interoperability, and reusability when putting your data and materials online
  • Locating, reusing, and citing data, and making your own data easily findable and citable
  • Disseminating articles, preprints, datasets, protocols, and software through formal publication or open distribution (please see our Where Should I Publish? guide for more info)
  • Creating complex projects on platforms like OSF (Open Science Framework)

Please contact us with any questions or to arrange a time to meet.

~Melissa Ratajeski