Research Data Management Services at JHU
Services We Provide
Data Management Resources from JHU Data Management Services
- Data Management Planning Questionnaire - a useful guide and foundation for developing your Data Management Plan as part of a grant proposal or at the start of a research project. We provide FREE assistance in developing data management and sharing plans in either case and for ALL funding agencies. Contact a DMS Consultant at firstname.lastname@example.org for assistance.
- Reviewer Guide and Worksheet for Data Management Plans - a user-friendly page of tables and checklists that can be used to quickly evaluate data management plans. More information about the worksheet can be found here.
- Guidelines for NIH Resource Sharing Plan/Data Sharing Plan - guidelines to help prepare NIH Resource and Data Sharing Plans in compliance with the 2003 NIH Data Sharing Policy. This policy is anticipated to be updated soon. More information about the guidelines can be found here.
- Selecting a Repository for Data Deposit - tips and set of questions researchers can use in determining whether a particular research data repository will work for their circumstances.
- Applications to Assist in De-identification of Human Subjects Research Data - a list of de-identification software tools and applications that researchers can use in de-identifying their research data for more public sharing.
- Online Guide to Metadata for Effective Research Data Management - What is metadata, and what does it have to with research data? Find here a description of metadata for research data management and ten questions/guidelines you can use in developing comprehensive metadata for your project.
- Handouts for JHUDMS Training Sessions
- Click on title for handouts from training sessions, available for Johns Hopkins faculty, staff and students (JHED credentials required).
Data Organization Best Practices Some quick tips for effectively naming files and organizing folders of research data. Research Backup Planning Guide Strategies for developing a plan for backups, security, and preservation for your research data De-Identifying Human Subjects Data (JHU version) Guidance for protecting and removing personal identifiers of research subjects for data sharing. (Version for non-JHU visitors) Making Spreadsheet Data Sharable/Re-usable Ten tips for making research data within spreadsheets sharable and re-usable. Research Data Documentation Workbook A spreadsheet tool to help organize and document a research project, its digital files, and derivative sets of files such as data associated with a publication or shared online.
In recent years, the Open Access movement has spread into the realm of data - especially data that has been paid for by public funds (government data sources and data collected through federal grants).
In 2010, the World Bank opened up a veritable treasure trove of data that they used to charge subscription fees for (World Development Indicators being the most notable). Former World Bank President, Robert Zoellick stated that "[i]t's important to make the data and knowledge of the World Bank available to everyone. Statistics tell the story of people in developing and emerging countries and can play an important part in helping to overcome poverty." Since opening up their full data catalog, demand for their data has only increased, which leads to new science and well-informed policies and directives.
Open Data Initatives (sampling - there are, and will continue to be, more to come):
The United Nations (UNData)
Data Sharing and Data Management Planning Mandates
All major US funders currently have research data sharing policies and requirements, or will be required to implement such policies within the next year or so. All will be requiring data management plans for proposals and open access to publications from funded projects. Most will require or strongly encourage sharing data, either by request or online through a data repository.
- Funding Agency current and future data sharing requirements are listed at this resource from SPARC
- There is not yet a similar resource for non-governmental foundation funding, but related information about foundation 'open licensing policies' and other foundation information can be found at the Foundation Center website.
Many international funder policies are listed here: Sherpa JULIET
A database of current funder policies for both data and publications can be found here: Sherpa JULIET. Many international and NGO/foundation funders are also listed. We recommend checking requirements of any funder and considering how your project can accommodate requests for data or open publications (contact JHU Data Management Services for additional guidance)
A growing number of journals also require or encourage sharing data that supports publications. Some ask that data be made available by request of researches, others require depositing data with the publisher or a data repository. Currently no single database tracks journal data sharing policies, so check your publishers' requirements. Examples include Nature, Science, PLOS, PNAS, and BioMed Central.
Contact JHU Data Management Services for expert guidance for complying with sharing and data management planning requirements.
Citing a source of data is just as important as citing a journal article or book. You need to give proper attribution to the data creator. Depending on the citation style you're required to use for your work it could look like any of the following:
United States Census Bureau. (2000). Census 2000 summary file 3: Maryland raw data. Retrieved 6/5/2010 from http://www2.census.gov/census_2000/datasets/Summary_File_3/Maryland/.
Pew Internet and American Life Project. (2010). Demographics of internet users. Retrieved 6/5/2010 from http://www.pewinternet.org/Trend-Data/Whos-Online.aspx.
Some data sources such as ICPSR provide you with citation information (ICPSR places theirs specifically in the full bibliographic record view).
MIT Libraries also have an Online Guide on citing data.
And the International Association for Social Science Information Services and Technology (IASSIST) has it's own section on Data Citation with handy-dandy how-to brochures.
There are efforts such as DataCite which are working toward the creation of persistent data identifiers (essentially DOIs). As this is a growing movement, the list of members will likely grow much longer (hopefully Hopkins included). This should make both proper attribution and discovery much easier.