8 Practical Tips to Create an Effective Data Management Plan for Researchers

The collection, analysis and management of research data have long been considered as fundamental to scientific study and scholarly growth. Today, as the sheer quantum of data being generated continues to swell, there is a growing focus on the importance of managing, integrating, and storing this information. 

While some researchers might consider data management as just another cumbersome administrative task, it is in fact especially important, as it increases the quality of analysis, allows validation, and helps reduce possible errors. On the other hand, the absence of a structured data management plan could prove disastrous in the event of loss of data. It would not only take researchers a long time to recover lost ground but could also prove expensive and even impossible in some cases. Therefore, planning and developing good data management practices even before you begin research is imperative.  

Sounds challenging? Don’t worry. Here are some practical data management tips to help you create an effective data management plan. 

1. Plan ahead and start early: The first step would be to create a structured plan that details how you will collect, store and share data gathered during your research. Build on the list to design a digital or paper-based data storage system to help catalog hard copies of raw materials. If you are unsure how to proceed, use online templates or ask your university about internal resources and available research data management tools. It is simpler to use existing templates than wasting precious time building one from scratch. 
2. Familiarize yourself with institutional or collaborator guidelines on data storage: Universities, funding agencies, and collaborating institutions sometimes have specific guidelines on where you are permitted to store your research data. This is done not only to manage security concerns but also to avoid administrative and legal challenges that may arise at a later stage. For example, institutions will be in an awkward position if they are unable to meet requests from publications for access to data because the researcher chose to save it on personal or external platforms instead of on the official servers. 
3. Create folders and follow a simple file name convention: Creating short, descriptive, easy to understand file names will make it easy to identify files that contain the specific information that you are looking for just from their titles. This will not only help you stay organized but will also help save time in the long run. Also, grouping documents that contain similar information into folders is a great way to ensure that data is organized into proper sections. This makes it a lot easier and quicker to find, manage, publish and re-use specific data when you later need to.
4. Use methodical version control in titles: Research data goes through many changes and additions – sometimes with inputs from different people in a team, over an extended period of time. Multiple iterations lead to errors and chaos. The best way to avoid this would be to create separate files with version numbers, or a ‘version control table‘ that captures the date, version number and initials of the person making changes to the document. This eliminates the confusion of having to sift through different versions of a document and makes it easier to roll back to a previous version if necessary. 
5. Collaboration and communication are crucial when working as a team: When collaborating with multiple team members on a specific project, it is important to ensure consistency on research data management strategies with respect to both where and how team members are storing and organizing their data. Each member of the team must be clear on the strategies agreed on to manage and store data generated in the course of research to ensure that it can be easily accessed by peer group researchers, journals, funding institutions and readers. 
6. Ensure that your research data is backed-up and secure: Data is transient and can easily be accidentally lost or tampered with due to security lapses. One of the most important aspects of research data management is to ensure that data is encrypted, backed up and stored both offline and on separate online servers. In fact, storing research data on secure cloud platforms which sync automatically with files on your local devices might be a great option to explore. It may be a good idea to periodically check on the software being used and upgrade or migrate to newer storage media when required. Most importantly, ensure that your systems are protected against malware and viruses that can corrupt or destroy your hard work. 
7. Use file formats that can be accessed by as many programs as possible: This would increase searchability of your research data, especially when the data is open or shared. Since technological progress may introduce new ways to access data, it would make sense to ensure that your research data is stored on file formats that can be easily retrieved even years later. 
8. Embed metadata within documents to make research easily available to others: Metadata typically contains information that makes research data easily searchable and understood by people who might want to use it. The easiest and best way to use metadata would be to embed it into the document itself using brief descriptions, labels, headers, or summaries.  

Finally, before beginning your research, it is important to remember one simple point – the more the data, and the more complex the data, the more time you will need to devote to planning an effective research data management strategy that will help you organize and store data generated.