Internal, open access

Research Data Management in detail

 

Filing cabinetResearch Data Management (RDM) encompasses the sum of activities undertaken in relation to the collection, processing, retention and disposal of research data.

These activities are carried out by both researchers and support and curation services provided by stakeholder organisations.

Research Data Management can be conceptualised in terms of a research lifecycle process and the data-related activities that take place at stages during this lifecycle.

The diagram below and the following legend illustrate this lifecyle in terms of an 8-stage process:


Research Data Lifecycle


Plan

At the research planning stage a researcher will consider what data will be required to undertake the research, and how they will be managed throughout the research process. This is the stage at which a data management plan would be created.

Collect

Data collection is the stage at which experiments are carried out, observations made, surveys undertaken, secondary materials acquired, etc.

Process

Data once collected will need to be processed in order to be useable. This might involve cleaning or calibrating instrument data, separating signal from noise, or carrying out other transformations, such as transcribing and coding interviews, anonymising data, etc. Data processing also involves documentation of the stages by which the data have been produced and recording other information necessary to their interpretation.

Analyse

Data analysis is the stage at which the raw materials of research are interrogated to produce the insights that constitute the research findings, which will be written up and published in articles, papers, monographs and other publications.

Appraise and select

Towards the completion of the project it will be necessary to determine which data will substantiate the research findings or have long-term value and should be retained, and which have little or no value beyond their function in the research process and can be destroyed. Appraisal and selection will have regard to any requirements for data retention specified by the research sponsor and the re-use potential of the data.

Preserve

Once data have been selected they will be prepared for preservation and archived in a suitable location. In many cases this will involve handover of the data to a repository/preservation service. Preservation activities may involve processes such as quality assurance of data, file format conversion, creation of metadata records, licensing the data for re-use, specifying retention schedules, and putting in place any required access controls. Data may be held locally or in a non-public location, in which case they should be managed by an accountable person or group, who can ensure they are stored and preserved properly. 

Provide access

Publications based on data should include a data citation or a statement indicating where and on what terms the data can be accessed. A data repository will enable discovery of the data in its care by exposing the metadata online, and will provide access to the data when this is permitted. Data may be made publicly available, or restrictions on access may be imposed where data are of a sensitive or confidential nature. Data held locally or in non-public locations should be managed in such a way that others can discover and apply for access to the data.

Re-use

Data that are available for discovery and access may be re-used by other researchers, either to substantiate the published findings of the original research, or to generate new insights through further interrogation and analysis. At this stage the data may become raw materials collected within a new cycle of research.

 

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