Before you begin the data management process, it is important to develop a good understanding of data. Data are the variety of information collected, used, manipulated, and analyzed throughout the research process and are necessary to validate research findings.
Data can take many forms including photographs, specimens, spreadsheets, images, software programs, survey responses, codebooks, digital objects or database content.
Examples of research data may include, but not limited to:
Understanding the Research Data Lifecycle
The research data lifecycle covers the stages through which research data is collected, recorded, processed, published, shared and preserved.
Using the research data lifecycle as a guide in data management is helpful because it initiates thoughtful planning and ensures that all phases of the research data lifecycle are covered including creation, processing, analysis, preservation, sharing, and reuse.
The video below, which was produced by the UK Data Service, provides examples of various research data management tasks and activities that can be performed at each stage of the research lifecycle.
Google's search feature useful for finding datasets online.
Weekly newsletter of useful/curious datasets.
Searchable registry of research data repositories.
Site where users can explore, analyze, and share quality datasets.
US government run site which allows users to find data, tools, and resources to conduct research, develop web and mobile applications, design data visualizations, and more.
The Earth Science Data Systems (ESDS) Program provides full and open access to NASA’s collection of Earth science data for understanding and protecting our home planet.
Global Health Observatory Data Repository
The Global Health Observatory is WHO's gateway to health-related statistics for more than 1000 indicators for its 194 Member States.
OpenML is an open platform for sharing datasets, algorithms, and experiments.
Open-source data, analysis, libraries, tools, and guides from BuzzFeed's newsroom.
The Planetary Data System (PDS) is a long-term archive of digital data products returned from NASA's planetary missions, and from other kinds of flight and ground-based data acquisitions, including laboratory experiments.
Provides freely usable datasets on US politics, journalism and media, internet and tech, science and society, religion and public life, amongst other topics.
A premier source for financial, economic and alternative datasets.
The research data management plan (DMP) is considered a formal "living document" because as you progress through the research process it should be kept up-to-date or modified often. This document should also be kept accessible to the entire research team both during and after a research project so that it can be used as a handy reference guide. This is also important because DMP's usually outlive the research project itself.
Requirements for the information to be included in your plan can vary by funding agency and institution. The required length and structure of your plan will also vary. The best way to start is to look for what your funder expects you to cover. You can find this information on the funder's website or by using the DMPtool.
The DMPonline is a free interactive online tool designed to help researchers create data management plans. This site provides step-by-step guidance as well as funder's template and sample data management plans.
The research division at A & T (DORED) provides a simple data management plan template as well as other resources on its website, if your funder does not provide guidance on data plans, this might be a good starting point.
Public DMPs are sample plans created using the DMPTool and shared publicly by their owners. They are not vetted for quality, completeness, or adherence to funder guidelines.
Questions to Consider Before Writing Your Data Management Plan
The webinar below outlines recommendations on creating a data management plan from ICPSR's Director of Data Acquisition Amy Pienta.