Data Management Services

~~ Serving Researchers on Homewood and Medical Campuses ~~

 

Effective data management can increase the pace of the research process, contribute to the soundness of research results, and meet funding agency requirements by making research data easy to share.

 


Supporting data management at every point in your research

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Where are you in your project?

Our Services

Consulting

Assistance with writing data sharing or management plans

Training

Best practices for data management and sharing

Archiving

Archive your research data for sharing & preservation

Subscribe to Data Management Services Mailing List

If you would like to receive our announcements, upcoming events and training sessions, please subscribe to our mailing list.

Training Schedule

(This schedule will be updated every July and December.)

Oct
25
Thu
Open Science Framework (OSF): A Platform for Collaborative and Reproducible Research @ Brody Learning Commons, Rm 5015/5017
Oct 25 @ 10:30 am – 1:00 pm

Please join us for a workshop, hosted by the Center for Open Science and JHU Data Management Services, to learn easy, practical steps researchers can take to increase the reproducibility of their work.

The workshop will be hands-on. (Please bring a laptop if possible.) Using an example study, attendees will actively participate in creating a reproducible project from start to finish.

Topics covered include:

  • Project documentation
  • Version control
  • Pre-analysis plans
  • Open source tools: in this specific instance, the Open Science Framework to easily implement these concepts in one easily accessible space

<Register here>

Nov
5
Mon
Introduction to Network Analysis: Basic Concepts, Applications, and Tools @ Homewood Campus, Brody Learning Commons Room 4040
Nov 5 @ 2:00 pm – 3:30 pm

What comes to mind when you hear the term network? The Internet? Facebook? Multiple computers sharing information? What if I told you there was a whole realm of scholarship where researchers explore the patterns of interaction in and among networks in their many forms? Network analysis is a research method that scholars in disciplines from public health, to business, to sociology and etc. use to explore and visualize relationships between objects, entities, or people. In this workshop we will take an introductory look at this concept and the basic underlying components of the method as well as discuss some ways that researchers are currently using the method. We’ll also identify types of online tools and software, discuss how to choose the best option for you, and construct a basic data set in excel. Finally, we will have demo of free and open source network visualization software Gephi. This is a basic introduction, no prior experience is necessary. Attendees may wish to bring a laptop to follow along with the demo.  <register here>

Nov
6
Tue
Georeferencing Scanned Maps for Use in Your GIS Project @ Lab#1, 2024 E Mountment St Building
Nov 6 @ 9:00 am – 11:00 am

Scanned images of early maps and aerial photography often provide an ideal historical backdrop upon which to overlaying contemporary geospatial data. You will be amazed at how georeferenced maps can be used to identify changes in both the physical and cultural landscape. In this class, we will introduce georeferencing and walk through the steps and decisions one makes throughout the process. You will also learn how to upload and share your final georeferenced maps to ArcGIS Online.

This is a hands-on session where you will make use of the library’s extensive collection of local scanned map images. We’ll also bring in authoritative GIS data layers from Baltimore City and our Maryland State government. There is no prerequisite for this class. Some knowledge of GIS may prove useful. <Register here>

De-identifying Human Subjects Data for Sharing @ Lab #1, 2024 Building, Medical Campus
Nov 6 @ 11:00 am – 12:30 pm

With researchers increasingly encouraged or required to share their data, preparing to share datasets with confidential identifiers of people and organizations is particularly challenging. Join JHU Data Management Services for an overview of techniques for assessing disclosure risk and hiding personal identifiers and Protected Health Information in quantitative and qualitative data, in compliance with IRB and HIPAA guidance. We also discuss preparing consent forms that facilitate data sharing, and keeping identifier data secure during and after projects. <Handout><Register here>

Nov
13
Tue
Best Practices for Research Data Management and Sharing @ Brody Learning Commons 4040, Homewood Campus
Nov 13 @ 1:00 pm – 2:00 pm

Effective data management can increase the pace of the research process, contribute to the soundness of research results, and meet funding agency requirements by making research data easy to share.  Join us for an overview of best practices including backup procedures, tips on effective file names, data security and access controls, and data documentation/metadata. This seminar is for faculty, postdoctoral researchers and graduate students from all disciplines. This course does not focus on creating or using any particular data collection or analysis tool (e.g. REDCap, SPSS), but discusses data management at a general level. <Register here><Handouts>

 

Introduction to ArcGIS Desktop using ArcGIS Pro @ Brody Learning Commons 5015/5017, Homewood Campus
Nov 13 @ 2:00 pm – 5:00 pm

This 3-hour workshop will introduce students to ArcGIS, the most widely used geographic information systems (GIS) software. Learn the basics of ArcGIS using the latest desktop application, ArcGIS Pro.  Students will leave being able to comfortably work with spatial data, by way of creating maps and managing the ArcGIS Pro interface. If your research calls for making maps or using a geographic information system to analyze data, then this class is for you. No prior knowledge of GIS is needed to take this introductory workshop.  <Register here>

Nov
14
Wed
De-identifying Human Subjects Data for Sharing @ Brody Learning Commons 4040, Homewood Campus
Nov 14 @ 3:00 pm – 4:30 pm

With researchers increasingly encouraged or required to share their data, preparing to share datasets with confidential identifiers of people and organizations is particularly challenging. Join JHU Data Management Services for an overview of techniques for assessing disclosure risk and hiding personal identifiers and Protected Health Information in quantitative and qualitative data, in compliance with IRB and HIPAA guidance. We also discuss preparing consent forms that facilitate data sharing, and keeping identifier data secure during and after projects. <Handout><Register here>

Nov
15
Thu
Open Research: The Good, the Bad, and the Ugly @ MSEL Hamburger Room, Homewood Campus
Nov 15 @ 12:00 pm – 1:00 pm

Curious about opening up your research? Bring your questions, lunch, and laptop to a discussion with Chen Chiu, Data Management Consultant from Data Services, and Robin Sinn, Scholarly Communication Librarian. We’ll talk about the benefits and concerns researchers have around sharing their research outputs such as data, code, methods, and articles. Drinks and cookies will be provided. <Register>

News and Highlights


New Online Training Available For Data in Spreadsheets

Regardless of discipline studied or methods used, it is likely that researchers use some sort of spreadsheet application (e.g. Excel) to investigate, manipulate, or share research data. Though easy to exchange with other researchers, difficulties can arise when using...

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Puerto Rico Hurricane Relief Map-a-thon

Please join us on a JHU Data Services event on October 5th to help the hurricane relief efforts in Puerto Rico. Date: Thursday, October 5, 3-5:30 PM (Pizza will be provided) Time: Great Hall at Levering (Homewood Campus) Join us for a map-a-thon to offer support to on...

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Upcoming Open Science Framework Workshop on Halloween

Workshop on Reproducible Research Practices and the Open Science Framework on October 31st, 2017 Please join us for a workshop, hosted by the Center for Open Science and JHU Data Management Services (http://dms.data.jhu.edu), to learn easy, practical steps researchers...

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Select Data Collection on JHU Data Archive