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  • Writer's pictureClara Richards

Structuring Data Management

[Editor’s note: This post was written by Bhavna Sharma, Database Management Consultant, and  Dr. Annapoorna Ravichander, Head Communication and Policy Engagement at the Center for Study of Science, Technology and Policy (CSTEP).]

According to the Wikipedia, “…as a general-purpose DBMS is designed to allow the definition, creation, querying, update, and administration of databases.”

A good database management system ensures accessibility, reliability, and timeliness of procuring data. It is a process by which the required data is acquired, validated, stored, protected, and processed.

Often many organisations find it difficult to provide responses or react to information that has been cited by a policy maker. This is more so relevant for a Think Tank, who are often engaged with policy decision making processes or with a policy maker to try and suggest feasible solutions for complicated matters. Database management should be necessarily become an integral part of a communication strategy of an organisation/Think Tank.  This is required because often research scientist are unable to convey important (complicated) matters into a simple language, to help policy makers use this rich information effectively. In many organisations, there is often a person or a communication team who are primarily employed to engage with policy makers. Since they have focused tasks and relecant experience, they are able to unpack information to suit an audience.

Most of the research organisations produce several types of documents which are required by various audiences/stakeholders. Many times some of the data/information is required for reference or for expanding a research study. Also, several organisations have different audience who require information for various reasons. For example, a senior researcher may want to refer to a document, the Head of an organisation/Think Tank may want a particular type of information. However, this task takes longer since information may not be stored appropriately. Something as simple as assigning an appropriate folder and file name, helps retrieve information quickly.


At the Center for Study of Science, Technology and Policy (CSTEP) we devised a simple method to store information, which can be retrieved by the various audiences quickly. Briefly we follow the methodology mentioned below to structure information:

Assemble and Plan Data

Plan for data management as per the research requisite/ organisational standards:

  1. Gather the data

  2. Plan for data management as per the research requisite

  3. Keep in mind the various users

  4. How will data be organised within a file?

  5. How will it be accessed?

Collect and Check Data

Collect data to ensure its usability later. Methods and documentation should be considered carefully:

  1. A template can be created for use during data collection. For example we have a template which primarily captures the various Events attended by a staff member.

  2. Perform basic quality assurance and quality control on the data during data collection, entry, and analysis

  3. Check the format of the data to maintain a consistency across the data set for example type of document, file name etc.

  4. Identify missing information

Select an appropriate repository to store data

Identify a data repository that is most appropriate for the data you will generate and for the group of people that will make use of the data. For example we have an internal system which provides access to different groups for a particular type of information.

As files are created, a data preservation plan is implemented that ensures that data can be recovered in the event of file loss (e.g. storing data routinely in different locations).

Data management_CSTEP

Importance of Data Management:

A good-quality data management is good for a research organization, as it facilitates an efficient research process, evasion of data loss and benefits of data reuse.

Data management for a research organization will help:

  1. Meet the requirements of funding agencies or stakeholders

  2. Accelerate the scientific process; saving time and resources in the long run

  3. Use or re-use the value, the uniqueness, and the importance of data

  4. Ensure that research data and records are accurate, complete, authentic and reliable

  5. Ensure research integrity and replication

  6. Increase research efficiency

  7. Enhance data security and minimize the risk of data loss

  8. Prevent duplication of effort by enabling others to use your data

  9. Comply with practices conducted in industry and commerce

In short, key benefits of a good data base management will

Improve Efficiency: If data is managed well, it will save a lot of time spent on corrective activity.

Protect from data-related risks: Backup and recovery procedures and data-handling procedures ensure that data, a major asset for any research project, is never permanently lost.

Accessible with easy navigation: By preserving data in appropriate folders, ensures easy access


While there are benefits, one needs to overcome challenges too.

  1. Time consuming

  2. Involves regular follow-up

  3. Establishing an organisation-level system for data management

  4. Documenting the process of data management

  5. Categorisation of folders and files for easy navigation


For a research organisation, research data is important and expensive because, they are the output of intellectual research processes. Research data are the crucial part of the evidence which is needed to assess the research results, and sometimes to restructure the proceedings and processes used to generate them. These data should be gathered and compiled into groups, so that can easily be accessible for re-use and also address new and challenging research questions. Moreover, this will increase their value as well. Lack of proper organization of data, greatly diminishes their value. To enhance the value of data management, new approaches are required to manage and provide access to research data.

As can be seen, managing and structuring data needs to become an important aspect of a communication strategy of all organisations/Think Tanks. A strong and well-structured document management system will always serve the purpose of being the first one to react to an issue or to respond to a query from a policy maker. 

[Editor’s note: For more blog posts on CSTEP’s experience dealing with think tanks’ decisions read Acknowledging a prominent think tank: the Center for Study of Science, Technology and Policy (CSTEP) in India.]

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