Introduction

A DMP or a Data Management Plan is in the form of a formal document that highlights how data needs to be handled both during a research project and after its completion.

The goal of a Data Management Plan is to keep in perspective all the steps involved in data management i.e. data creation, data preservation and data analysis before the beginning of a project. This helps make sure that that the data is managed well in the present and preserved appropriately for future usage.

Before we go further into Data Management Planning, it is essential to know what data management is. The way we have described it will enable you to create a link between the two to make better sense of why a Data Management Plan or DMP is necessary for data management.

It’s essential for users to identify the data sets that need to be created. Then they also need to identify the activities involved in data management relevant to their assignment. In data management, people and their responsibilities are also defined prior to the commencement.

Data Management is a wide topic that covers many aspects of the architectures, policies, practices and procedures that help manage the data lifecycle within an organization. Everything that falls under the umbrella of data management has 2 primary goals:

  1. to have secure and organized storage,
  2. and access to the data.

Data management comprises of various steps that ensure the smooth flow of data and control from its creation, during processing, for utilization until storage or deletion. Data management is implemented using IT infrastructures coupled with effective management. It defines the administrative processes to be used throughout the lifecycle of the data.

There are four basic and iterative steps in data management:

Creation

Involves procedures for collecting the data, matters e.g. IP rights (if applicable), and the usage of standards or rules for naming and describing the data.

Manipulation

Involves steps needed in organizing the data, it also determines middle-term storage and the rights to access the data etc.

Sharing

Involves all matter concerned with the use of the data including, the definition of licenses etc.

Preservation

Concerns strategies for long-term storage of data, backups and data security. It involves steps like metadata creation, data quality monitoring, etc)

Why is it important?

Proper planning ensures success in any endeavour. Data is arguable your most important asset so having the right approach is key to your success. Firstly, having a data management plan prior to the data collection phase ensures that data is in the appropriate format. Good quality data will be well organized and well annotated too. This aspect of the data management plan helps immensely and ensures that the data is not required to be re-formatted or re-organized. Further, you will not also have to remember the details of the data. In this way, it saves time for those making use of the data for analysis and makes the analysis phase more efficient.

Conclusion

A sound Data Management Plan also ensures the authenticity of the data. This is because data with complete meta information, and proper annotations, make it easily understandable to the researchers making use of the data in the future.

To find out more, about how ZE can help you with your Data Management Plan, get in touch with us today!