The following elements are highly recommended that every data management plan should have to make sure the efficiency and effectiveness.
Data description and format
This looks at how information is collected as well as the scale of the data that will be generated. Then another element to be considered is format of the data, in which the information will be generated, maintained and made available. Of course, there is a need of a justification for the appropriate procedures and archive of those formats.
For instance, your plan would include a project generating survey data for a country with social backgrounds, political predispositions, social and political values, different opinions and so on.
When it comes to the formats, quantitative survey data files produced will be conducted and submitted to a repository, such as the SPSS system files with DDI XML documentation. The data will then be allocated into different formats which are often used, such as ASCII, SAS, SPSS and Stata. On the other hand, documentation is made under PDF format. What’s more, digital video files made will be processed under the .mp4 format.
This is a description of the metadata offered together with the generated data as well as a discussion of the metadata standards utilized. For example, metadata will be tagged in XML through the format named Data Documentation Initiative. The codebook has all information regarding study design, sampling methods, field work, details as well as any other detail needed for a secondary analyst to take advantage of the data in a correct manner.
Storage and backup
As from the title you can see, these are the storage methods and backup procedures for the data, such as the physical and network resources along with any equipment or facility adopted to preserve and store the research data securely and effectively.
Intellectual property rights
These will be entities and people who have the intellectual rights to the data, and how IP will be secured when needed. Any copyright issues should also be taken into consideration.
Accessing and sharing
This goes with a description of how data would be shared. More precisely, there should be access procedures, technical systems to disseminate and whether approach is permitted for anyone or just a specific user group. A time frame in which the data will be shared or published should be noted. Possible mechanisms to share and publish data include such elements as domain repository as ICPSR, self-dissemination via a dedicated web site that the research team will make and secure. If this option is what they choose, it is highly suggested that the data maker should organize the final archiving of the data after the self-dissemination period stops and make the schedule to share data in a clear manner. Another factor is preservation with delayed dissemination. Specifically, the data generator will arrange with a public data repository for archival protection of the data with dissemination to take place at another day, usually in a year. In addition, institutional repositories at academic centers need to preserve and make some part of the academic job available for their students, faculties and employees. It should be considered that not all institutional repositories are able to approve and curate data.
For instance, a master copy of each digital file will be placed, such as research data files, documentation and so on, in Archival Storage, with different copies placed at designated locations in order to be synced with the master via the Storage Resource Broker.
Archiving and preservation
This is the procedure made for long-term archiving and protection of the information, coming with many plans by which the data should be the expected archiving entity and go out of existence.
For example, the investigators working on a project for their organizations will have the right to handle the research data they generate. Also, the data collected will make use of a copyrighted method for some questions. A reproduction of this method will be offered to a repository as documentation for the data deposited with the intention that the instrument be distributed under the correct usage to allow for data sharing. However, this will not be disseminated one more time by users.
Ethics and privacy
Ethics and privacy mean a discussion of how informed consent can be achieved and how security can be protected, including any organization that should be included to make sure confidentiality as well as other ethical problems that may take place. For instance, the research data from this project will be deposited with a repository to make sure that the research group can have approach to the data in long term. Another example is that the project team will make a dedicated website in order to control and allocate the data as the audience for the data is not too much. The site can be made via a content management system such as Drupal or Joomla.
There are also some other factors which are regarded as optional elements. Existing data is a survey of the current data which is related to the project as well as a discussion of whether these data can be integrated and how this step can be done.
Data organization defines how the data will be controlled during the project, with information related to version control, naming and so on.
Quality assurance is the procedures used to make sure data quality during the project. Moreover, security includes a description of technical protections for data, such as confidential information and how restrictions and permissions can be carried out.
Responsibility factor comes with names of those who are responsible for data management in the research project whereas budget is the costs for data preparation and documentation to archive and how these costs are allocated. There should be requests for funding.
Legal requirements are a list of all related funder demands for managing and sharing data. Last but not least, there is a description of how data would be chosen for archiving