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Data Management for Research: Managing Your Data

Research data management and data management plan support

Why manage research data?

→ To fulfill grant funding agency requirements

→ To provide greater visibility for your research

 To enable easier collaboration and sharing

→ To streamline data collection & findability within your lab or research group 

 

We can help facilitate your research processes now, and also ensure long-term access to your research data.

 

We provide:

 Assistance with developing data management plans for grant proposals

→ Advice and support in data management, standards, documentation and organization to support reuse and preservation

 Access to Northeastern's Digital Repository Service for data storage, sharing, and reuse.

Data management checklists

These checklists, tailored to stages of the research lifecycle, can help you streamline and organize work on your project.

General guidance

General guidance for data management

This site offers helpful tips on a host of data management topics, ranging from non-proprietary file formats to naming conventions to persistent identifiers to data documentation.

Data in Northeastern's Digital Repository Service

Whether you're depositing data for publishing or grant requirements, or just want to make the output of your research available to your colleagues, depositing data in a repository or digital archive will ensure your research will be discoverable and usable for a long time.

→ Northeastern's Digital Repository Service is currently home to over 150 datasets

→ Interested in adding your data?  Learn more about the DRS and find out how to prepare your data for deposit into the DRS.

Featured resource: The Practice of Reproducible Research

Searching for advice on how to best organize your project or your research group's work? 

→  Check out The Practice of Reproducible Research 

This free Gitbook features over 30 case studies that help bridge the gap between theory and real-world application.  The case studies describe in detail how researchers in various disciplines have combined tools and workflows to make their lives easier, and maximize the reproducibility of their work.

Contact Jen

Jen Ferguson's picture
Jen Ferguson

Webinar: File organization, naming, and management strategies

Missed our Summer 2020 Training Series? Watch the recorded webinar below that distills some of my favorite file organization and management tips in less than 20 minutes. Just click on the image below and log in to open up the webinar in a new tab. For questions, comments, and any accessibility or captioning requests, please email me

Note: The webinar is available to Northeastern affiliates only. If you wish to view the webinars and are not a Northeastern affiliate, please get in touch

File Organization Thumbnail

How can I organize and manage my digital stuff (in 20 minutes)?

Getting your digital house in order is like writing a love letter to your future self. We’ll share a few quick file organization, naming, and documentation tips that can help you – and your collaborators – remember what you did and find your stuff 6 months from now.

README files

README files describe your data, and help facilitate accurate understanding and reuse of your work.

Getting started

  • Create your README as a plain text file to avoid potential issues with proprietary file formats.  PDF can be used if formatting is important.
  • Choose whether to create a separate README file for each data file, or a README for the entire data package.
    • Example - separate README for each data file
    • Example - README for entire data package

Recommended README file content, in brief

  • Names and contact information for personnel involved with the project
  • Short description of the data contained in each file
  • File list, including a description of the relationships between the files
  • For tabular data, full names and definitions of column headings
  • Units of measurement
  • Any specialized abbreviations, codes, or symbols used
  • Copyright/licensing information
  • Limitations of the data
  • Funding sources

For more detail, please see this README file template.

Additional resources

Research Data Services - Support & Tools

Our Research Data Services team has experience in many techniques and tools. To match you with the expertise that fits your needs, please consult the tables of support services and tools below.

Finding Research Resources  

Finding research funding 

Use Pivot

Finding datasets

Contact subject specialist

Text mining library resources

See guide
Research Data Management  

Data management plans

See guide

File organization strategies

See guide
Analyzing, Visualizing, and Presenting Data  

GIS and geospatial services

Email Bahare Sanaie-Movahed

Data visualization

Email Kate Kryder

Poster design

Email Kate Kryder

Presentation design

Email Kate Kryder
Sharing and Publishing Research  

Data sharing and preservation 

See guide

Citations and bibliographies

See guide

Our Research Data Services team has experience in many techniques and tools. To match you with the expertise that fits your needs, please consult the tables of support services and tools below.

Research Data Management  

DMPTool

See guide

Jupyter Notebooks

Email Jen and Kate
GIS and Geospatial Services  

ArcGIS / ESRI suite

See guide

Maptitude

Email Bahare Sanaie-Movahed

Policy Map

See guide

QGIS

See guide

Simply Analytics

See guide

Social Explorer

See guide

Story Map JSON

Email Bahare Sanaie-Movahed
Data Visualization   

D3.js

Email Kate Kryder

Excel

Email Kate Kryder

R / Rstudio

Email Kate Kryder

Tableau

Email Kate Kryder
Presentation and Graphics  

Adobe Illustrator

Email Kate Kryder

Adobe InDesign

Email Kate Kryder

PowerPoint

Email Kate Kryder

Updated Pivot videos & training

Pivot integrates funding, collaborator discovery, and publishing opportunities into one powerful tool. 

This video demonstrates basic searching for funding opportunities in Pivot.  Check out the Pivot YouTube channel for training on other topics