Tools & Resources

Broad Overviews & Comprehensive Treatments

Looking for that resource that gives you the big picture? Check out our “Research Data Management Overview and Training” section, with a rich repository of resources.


For when you are writing data management plans: DMP Templates & Tools

Data Management Plan Templates
Funder-specific templates to help you create a data management plan.

DMP Review Checklist
A checklist to assist in reviewing & assessing your data management plans

Informed Consent Language from ICPSR 
Recommendations for informed consent language that permits data sharing – Helpful for your IRB applications.

Use this tool to identify tools and create a strategy for your tech-using project. Especially useful for research projects using technology to interact with participants.


For when you are collecting and analyzing your data: Analysis – Security – File naming – Versioning –  Metadata

Collaborative Research Platforms

  • LabArchives
    An Electronic Lab Notebook that is good for more than lab work! This platform is supported by CUIT, CUL and EVPR, and free for the Columbia Research community to use for active research and in classroom environments. LabArchives provides storage, versioning, audit trails and access control.Find out more here.
  • Open Science Framework (OSF)
    A collaborative research platform that pulls in many of the tools you already use into a single space that can encompass your entire research project. OSF provides storage, versioning, audit trails and access control.
  • REDCap
    REDCap is a secure web application for building and managing online surveys and databases. While REDCap can be used to collect virtually any type of data (including 21 CFR Part 11, FISMA, and HIPAA-compliant environments), it is specifically geared to support online or offline data capture for research studies and operations.

Resource & Tool Collections

  • Research and Data Integrity (ReaDI) Program
    Guidance, training, and resources for: Best practices for data management when using instrumentation, Good laboratory notebook practices, “Data-to-figure” map, Compilation of suggested practices for creation of a retrospective chart review form, Laboratory checklist for departing researchers, Telephone interview outline for hiring postdocs, staff scientists, technicians, etc., Options for data storage, transfer, and sharing for Columbia’s researchers, example laboratory and notebook procedures from Columbia PIs
  • Digital Research Tools (DiRT) “a registry of digital research tools for scholarly use”
  • Journalist’s Toolbox An amazing collection of tools and information sources
  • Open Data Tools A selection of tools and resources to use in achieving “open data”
  • Alidade: Use this tool to identify tools and create a strategy for your tech-using project. Especially useful for research projects using technology to interact with participants.


  • Getting started with HPC (High Performance Computing) at Columbia University:
    Columbia University resources + tools, tips & training to get you using the HPC resources available here
  • R vs. Python:
    Exactly like it sounds, this infographic provides an easy-to-understand review of R & Python for data analysis


File naming


There are many options for keeping track of versioning your data including filenaming practices, or services such as

Remember: Always a keep an undisturbed copy of your raw data!

You may also need to a place to keep track of your software/code while you are developing it, such as a development repository, aka repo. (This is different from a preservation repository) Guidelines to consider when choosing a development repository.


Data Visualization

Finally, back up your data! There are many options for this. You should choose one that best fits your workflow and resource requirements.


For when you are preparing your data for publication, preservation, or archiving: De-identification – Appraisal – Academic Commons – Data Repositories – File formats

Preparing Sensitive Data for Sharing

Managing risk for sharing

Sensitive data can be shared, responsibly! Here is a toolkit that can help you understand and ameliorate the risks associated with sharing your sensitive data: Open Data Release Toolkit


There are a variety of tools that can help you with the task of de-identification [comparison table], and guidance to assist you in applying them [link].

File Formats

Recommended file formats for long term storage.

Depositing Data in Academic Commons
Columbia’s online research repository, Academic Commons, is a great place to store your final data sets.


For when you are sharing or using shared data: Data Repositories – Licensing – Data Citation

Data Repositories

  • Academic Commons: Columbia University’s institutional research repository
  • Data Repositories: A list of some of the repositories available to Columbia researchers.

Data Citation

Licensing and Intellectual Property

Other Columbia University Resources

Frequently Asked Questions: Data Management at Columbia
Answers to common questions about data management best practices and policies at Columbia.

CUL/IS Digital Social Science Center (DSSC)
Information from the Columbia University Libraries/Information Services DSSC on resources available for research projects.

Data Management – Further Information & Training Opportunities
A list of some of the training materials and products available on the Web.

Questions? Please contact us at