Take Your Data Practices from Good to Best with HSLS Data Services

The HSLS Data Services team is thrilled that Pitt has declared 2021-22 to be the Year of Data and Society, because for us, every day is a day for data. Whether you are embarking on your first research project or have dozens of completed studies under your belt, we are here to help you improve the efficiency and reliability of your data-handling workflows at every step in the research process. We offer consultations, classes, and customized trainings in the following areas:

Research data management

Organizing files, writing documentation, and safely storing datasets are key practices for working with data effectively. They are also required discussion items for data management plans, which will be mandated in all NIH grant applications after January 2023. (Read the official NIH notice.) We recommend our Introduction to Research Data Management workshops especially for new graduate students to set themselves up with good habits from the start, but in-depth consultations are available for any lab, research group, or individual.

Open science

“Open science” refers to the culture and practice of making data, methods, and code fully available to the public—beyond what is usually described in a paper—so that others can validate and reproduce results. Practicing open science has clear benefits for the trustworthiness of research, but it can add to the time and complexity of a given study. HSLS can help you apply best practices to streamline the process, including:

  • Incorporating the FAIR principles of findability, accessibility, interoperability, and reusability
  • Locating, responsibly re-using, and citing data
  • Making your own data findable, re-usable, and citable in a recommended research repository, data journal, and/or via the Pitt Data Catalog (see the HSLS guide Where should I publish? to get started)
  • Using LabArchives, an electronic research notebook
  • Managing projects on platforms like OSF (Open Science Framework)

Research programming, data science, and open-source software

Computational tools are crucial to much of the research conducted at Pitt. We connect researchers with software, offer trainings in their use, and help programmers develop better computational tools. Topics we can help with include:

  • Accessing licensed resources for bioinformatics data analysis
  • Version control (tracking changes to files) with Git and GitHub
  • Choosing an appropriate open-source license
  • Annotating research code, including both analysis code and original software tools
  • Principles of research programming, using Python (Jupyter Notebook), R, and the command line

If you have a data need that isn’t listed above, please contact us at HSLSDATA@pitt.edu. We are available for one-on-one consultations as well as customized workshops for classes, labs, and research groups—see our class catalog for previously taught topics, but do not hesitate to request something new.

~Helenmary Sheridan