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Research Data Management and Sharing

This guide provides current resources available to the Brown University community for management, and, when appropriate, sharing of research data as required by research funders and scholarly journals

Resources for Data Curation

Data curation primers are peer-reviewed, living documents that detail a specific subject, disciplinary area or curation task and that can be used as a reference to curate research data. 

The Research Data Management Workbook is made up of a collection of exercises for researchers to improve their data management. The Workbook contains exercises across the data lifecycle, though the range of activities is not comprehensive. Instead, exercises focus on discrete practices within data management that are structured and can be reproduced by any researcher.

File Naming and Organization

File and folder naming conventions

  • To aid your and your collaborators ability to discover and access files in an efficient manner here are some best practices for naming files.

  • No spaces and no use of special symbols except for underscores ( _ ) or dashes ( -)

  • Try to only use a period ( .) only for the terminal file extension (e.g., .pdf)

  • Think of character length of file name <30 characters -- should be readable by human eyes

  • Standardize as much as possible information that could link the file back to an entry in a laboratory notebook such as:

  • Try to include meaningful content such as the initials of the person creating the file; create and use a project identifier (ID); abbreviation for method used to collect data (e.g., NMR) ; if any experiment include the run number or field work, an indicator related to project site.

  • The date… there is an international standard for writing the date: YYYYMMDD. Using this also sorts your files by date. If working on updates to a file you could also include a version number.

Resources for Documenting and Describing Your Data

Metadata is context. It should describe your data in enough detail for other researchers to make sense of your protocol, methods and materials, and the results produced and reported. It should also help other researchers to both discover your data as well as cite your data. Different research communities have developed metadata standards for helping members of their communities with describing their data in the same ways and to ensure that at least the minimal amount of descriptive information necessary is collected about a sample and its analysis and results for reporting purposes. 

Research Data Alliance (RDA) Metadata Standards Catalog

Fairsharing.org Standards Search Tool

 Digital Curation Centre (DCC) List of Metadata Standards

Cornell University Guide to Writing README-style metadata

How to Write a Good Codebook by Patrick Bélisle and Lawrence Joseph.

Storing and Backing Up Your Data During a Project

Brown University's Computing and Information Systems (CIS) can help you with selecting data storage and backup systems available at Brown. A helpful tip is called the 3-2-1 rule, whereby in addition to the data files on your laptop or personal machine, you keep a local backup copy on a separate storage (e.g., external hard drive) as well as a third 'remote' copy (e.g., Campus File Storage Home Folder, DropBox, Google Drive, GitHub). This will prevent loss of your data in case your computer crashes or there is an emergency (fire, flood) that destroys the local backup copies.

Decide How to Store Data at Brown by Stepanie Obboda

Use a Data Repository 

Transfer Large Data Files

Brown Globus Online [https://www.globus.org/]

Brown is a paying subscriber to Globus Online, which allows you to set up endpoints for transferring data files between your personal storage and Brown storage as well as between Brown storage systems (e.g., Google Drive, Campus File Storage / Department File Service, Rdata, etc.) Select Brown University from the dropdown and log-in with your Brown credentials. For assistance with setting up endpoints for Brown storage systems contact help@brown.edu.

Data Security

There are experts on campus to help you securely store and collect data. Consult with Brown's Information Security Group (ISG@brown.edu) and consult their website and security resources as well as their Information to Comply with Policy on the Handling of Restricted Information. Consult with Brown's Institutional Review Board (IRB) before receiving and/or sharing any data derived from human subjects research or containing any personally identifiable information (PII) or considered protected health information by our healthcare research partners. Please ensure any sharing of data complies with Brown University's Export Controls, Restricted Information, Research Privacy, and Patent & Invention Policies.    

 

Versioning

Even without Git or one of the platforms above, you can still keep a log of files and their version numbers (example V1, V1_1, V1_2 for minor changes and V2, V3, etc. for major changes as well as include the date (e.g., in ISO 8601 format YYYYMMDD). Get a unique identifier for distinct published versions of your works (https://repository.library.brown.edu/studio/doi/).