Data Management and Sharing

This guide gathers overviews and resources for data management and sharing following the research workflow for data, from preparing data management and sharing plans for grant proposals, conducting research, to sharing research data.

Help with Statistics

The Johns Hopkins Biostatistics Center

JHU Biostatistics Center provides consulting on biostatistical issues related to the effective collection and interpretation of health information including research design, professional and scientific report writing, and statistical analysis.

Statistics Help for Social Sciences and Behavioral Data

Senior Statistician, Bryce Corrigan, can help JHU affiliates to design and implement statistical analyses of social and behavioral data. For example, at the statistical planning stage, our experts can help you think about questions such as experimental or observational designs for empirical inquiry, decide upon an analysis and software, and figure out how much data you will need. He can help with various aspects of working with the data and software. We can help with common methodologies such as multi-level, panel, or longitudinal models, treatment effects estimation, examining residuals and handling non-linearity, and making predictions that help to convey your substantive findings. To access these social statistical consulting services, please set up an appointment or contact with a detailed explanation of your needs.

The Biostatistics, Epidemiology and Data Management (BEAD) Core

BEAD Core at the School of Medicine provides a myriad of consulting and support services around study design and analysis, database development, and survey design review. Please note, it is most beneficial to the researcher to receive help from BEAD prior to data collection. Check out their past seminars to learn more about BEAD Core.

Big Data

The Institute for Data Intensive Engineering and Science (IDIES)

IDIES fosters education and research in applying data-intensive technologies to problems of national interest in physical and biological sciences and engineering. The Institute also provides JHU faculty, researchers, and students with the structure and resources needed to accomplish these goals. IDIES offers the following resources for JHU researchers who work with big data: SciServer, IDIES Data Center, the Advanced Research Computing at Hopkins (ARCH) (formerly MARCC), and funding opportunitiesJoin IDIES to use their benefits and resources. 


The SciServer is a collaborative platform for big data. It hosts extremely large datasets and provides tools for data analysis and visualization. More information about SciServer can be found on their Help page

The Advanced Research Computing at Hopkins (ARCH)

ARCH is formerly known as MARCC. It is a  shared computing facility at Johns Hopkins University. You can watch their training videos or sign up for an introductory workshop to learn more about ARCH. The user guide and FAQs are also available online.

Joint High Performance Computing Exchange (JHPCE)

This is a high-performance computing facility in the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health. The facility is open to all Johns Hopkins-affiliated researchers. If you are interested in joining JHPCE, please contact

Data Science at NIH

Resources of NIH data science-related events and news include information about NIH’s Big Data to Knowledge (BD2K) initiative and NIH Commons. The BD2K Training Coordinating Center offers resources and tools for biomedical researchers to navigate the data science field. These BD2K Guide to the Fundamentals of Data Science Series can provide a basic understanding of data science for biomedical researchers.

The Fundations of Biomedical Data Science by the University of Virginia

This seminar series covers the basics of data management, representation, computation, statistical inference, data modeling, and other topics related to biomedical big data.  

Software Development

Software Carpentry

Software Carpentry provides workshops to teach researchers the computing skills they need for their research. Current courses include R, Python, MATLAB, Unix, and SQL. You can request a workshop for your institution, or attend an upcoming one at your institution. Also, see Data Carpentry‘s workshops for teaching basic data skills to researchers.


GitHub is a place to develop, store and share your software projects. You can work collaboratively with your colleagues to develop software and share it publicly with others. There are free and paid options for GitHub services. The free service includes one private repository and unlimited public repositories for users. GitHub has online online guides about how to use GitHub.


GitLab is another place to develop software projects collaboratively and share software publicly. It also offers free and paid service options. The free GitLab service provides unlimited private and public repositories for users.

Data Visualization

Guide for Data Visualization

A research guide for technologies, techniques, and best practices for data visualization. This guide provides resources for creating effective scientific figures, workshop and tutorial information, and how to plan for data visualization and network visualization. Contact if you need to schedule a consultation about data visualization. 

Technical Communication Lab at JHU

A Homewood-based Technical Communication Lab serves as a resource for technical communication for all JHU undergraduate and graduate students. Their services include consultations for technical writing, English as Second Language (ESL), presentation, and data visualization and design.   

COURSERA Data Visualization & Dashboarding with R Specialization

There are five courses about data visualization with R in this R specialization series of course. From the basic concepts of data visualization to advanced visualization with the ggplot2 package and building a dashboard with RShiny. These courses are taught by a JHU professor and it is free for all JHU-affiliated.