Senior Librarian
Head Research Data Management Division
Hamzah Sendut Library
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+604 - 653 5365

It is universally acknowledged that researchers are interested in data of all kinds, regardless of origin or type.

Here are some of the recognised definitions of research data:

“Research data, unlike other types of information, is collected, observed, or created, for purposes of analysis to produce original research results.” Edinburgh University Data Library Research Data Management Handbook  

“Research data means data in the form of facts, observations, images, computer program results, recordings, measurements or experiences on which an argument, theory, test or hypothesis, or another research output is based. Data may be numerical, descriptive, visual or tactile. It may be raw, cleaned or processed, and may be held in any format or media”. The Queensland University of Technology Management of Research Data Policy

“The recorded information (regardless of the form or the media in which they may exist) necessary to support or validate a research project’s observations, findings or outputs”. The University of Oxford Policy on Management of Research Data and Records

In addition to research data, research data management also covers managing of research records both during and beyond the life of a project. Examples of such research records include:

• Correspondence (electronic mail and paper-based correspondence)
• Project files
• Grant applications
• Ethics applications
• Technical reports
• Research reports
• Signed consent forms

Source: Defining Research Data by the University of Oregon Libraries

What is Research Data MANAGEMENT (RDM)?

Research data management (RDM) refers to the process of collecting, storing, organizing, preserving, and sharing data that are generated during research. It involves the use of various techniques, tools, and procedures to ensure that research data are accurate, reliable, and available for reuse in future studies.

Effective research data management is critical for ensuring the integrity and reproducibility of research, as well as for maximizing the impact of research findings. It can also help researchers comply with ethical, legal, and regulatory requirements related to data management.

1. Data organization: This involves developing a plan for organizing data so that they are easy to find and use. This may involve creating a data dictionary or using a standard format for data files.
2. Data storage: This involves selecting an appropriate storage location for research data that is secure, backed up, and accessible. This may include cloud-based storage, local servers, or external hard drives.
3. Data sharing: This involves making research data available to others for reuse, replication, or validation. This may involve depositing data in a repository or sharing data through a data sharing platform.
4. Data preservation: This involves ensuring that research data are preserved for the long-term, so that they can be accessed and used in the future. This may involve creating a data management plan or using a preservation system.
5. Data security: This involves protecting research data from unauthorized access, loss, or corruption. This may involve using encryption, firewalls, or access controls to safeguard data.

Overall, effective research data management is an essential component of modern research, and can help to ensure that research findings are accurate, reliable, and impactful.

Research Data

Research data are the raw materials collected, processed and studied in the undertaking of research. They are the evidential basis that substantiates published research findings.

They may be primary data generated or collected by the researcher, or secondary data collected from existing sources and processed as part of the research activity.

Benefits of RDM

Data are your research capital. They enable you to answer your research questions; they provide the evidence base for the results you make public; they may have ongoing value to you and to others; and where they are used, they can be cited to your benefit. By actively managing your research data you will:

1. make life easier: well-organised data management increases your efficiency, and saves time and effort in the long run;
2. protect yourself and others: you can reduce the risk of costly/embarrassing/damaging accidents, such as losing data, or disclosing confidential data;
3. preserve the integrity of your research: well-documented data demonstrate the authenticity of your research and the reliability of your findings;
4. realise the full value of your data: data that are preserved and accessible in the long-term can be re-used to your benefit and others'.

Research data lifecycle

It can be helpful to think of research data management in terms of a research data lifecycle and the data-related activities that take place at stages during this lifecycle. The diagram below and the following legend illustrate this lifecyle in seven stages.

Here you will identify the data that will be collected or used to answer your research question, and will plan for data management throughout the lifecycle. This is the stage at which a data management plan would be created. Many public funders of research ask for a data management plan to be submitted as part of a research application.

This is the stage at which experiments are carried out, observations made, surveys undertaken, secondary materials acquired, etc. This will involve documentation of data collection instruments and methods and information necessary to interpret and use the data.

Data once collected will need to be processed in order to be usable. This might involve cleaning data to eliminate noise, combining data from multiple sources, transforming data from one state to another (e.g. by format conversion), and using procedures to validate or quality-control data. Any data processing will need to be documented, such that the end result could be replicated from the raw data.

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 research outputs. Instruments and methods used for analysis should be documented; code written for purposes of data analysis and visualisation may need to be preserved and made available in support of research results.

Towards the completion of your research you will preserve for the long term data that substantiate your research findings and have long-term value. Data will need to be prepared for preservation and archived in a suitable location. In many cases this will involve deposit of the digital data in a suitable data repository/data centre. Preservation activities may involve quality assurance of data, file format conversion, creation of metadata records with assignment of Digital Object Identifiers (DOIs) to datasets, licensing datasets for re-use, and putting in place any required access controls. Confidential and non-digital 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.

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.

Data that are available for discovery and access may be re-used by other researchers, either to substantiate the 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. Research data may also have other valuable uses, e.g. in policy-making, development of commercial products and services, and teaching.