Getting started with research

In this section, you will learn about research integrity and your responsibilities as a researcher at QUT under the provisions of the QUT Code for Responsible Conduct of Research. The Australian Code for the Responsible Conduct of Research, 2018 (also known as the Code) provides a range of guidelines for responsible research practices. Failure to comply may result in research misconduct.

The Code lists eight principles of responsible research conduct (honesty, rigour, transparency, fairness, respect, recognition, accountability and promotion):

P1 Honesty in the development, undertaking and reporting of research

  • Present information truthfully and accurately in proposing, conducting and reporting research.

P2 Rigour in the development, undertaking and reporting of research

  • Underpin research by attention to detail and robust methodology, avoiding or acknowledging biases.

P3 Transparency in declaring interests and reporting research methodology, data and findings

  • Share and communicate research methodology, data and findings openly, responsibly and accurately.
  • Disclose and manage conflicts of interest.

P4 Fairness in the treatment of others

  • Treat fellow researchers and others involved in the research fairly and with respect.
  • Appropriately reference and cite the work of others.
  • Give credit, including authorship where appropriate, to those who have contributed to the research.

P5 Respect for research participants, the wider community, animals and the environment

  • Treat human participants and communities that are affected by the research with care and respect, giving appropriate consideration to the needs of minority groups or vulnerable people.
  • Ensure that respect underpins all decisions and actions related to the care and use of animals in research.
  • Minimise adverse effects of the research on the environment.

P6 Recognition of the right of Aboriginal and Torres Strait Islander peoples to be engaged in research that affects or is of particular significance to them

  • Recognise, value and respect the diversity, heritage, knowledge, cultural property and connection to land of Aboriginal and Torres Strait Islander peoples.
  • Engage with Aboriginal and Torres Strait Islander peoples prior to research being undertaken, so that they freely make decisions about their involvement.
  • Report to Aboriginal and Torres Strait Islander peoples the outcomes of research in which they have engaged.

P7 Accountability for the development, undertaking and reporting of research

  • Comply with relevant legislation, policies and guidelines.
  • Ensure good stewardship of public resources used to conduct research.
  • Consider the consequences and outcomes of research prior to its communication.

P8 Promotion of responsible research practices

  • Promote and foster a research culture and environment that supports the responsible conduct of research.

Research integrity

Integrity in research is critical to assuring research and scientific excellence and public trust. Research integrity is exemplified by 'a commitment to intellectual honesty and personal responsibility for one's actions and to a range of practices that characterize responsible research conduct' (National Research Council (US) and Institute of Medicine (US) Committee on Assessing Integrity in Research Environments, 2002).

For the individual researcher, integrity embodies a range of good research practices and conduct, including:

  • intellectual honesty in proposing, performing, and reporting research
  • accuracy in representing contributions to research proposals and reports
  • fairness in peer review
  • accurate and fair acknowledgement of the work of others (referencing and citing)
  • collegiality in scientific interactions, including communications and sharing of resources
  • transparency in conflicts of interest or potential conflicts of interest
  • protection of human subjects in the conduct of research
  • humane care of animals in the conduct of research
  • adherence to the mutual responsibilities between investigators and their research participants.

All staff and students who are involved in research practice should be familiar with and must comply with:

Compliance with the principles outlined in the Code is a requirement for the receipt of funding from the Australian Research Council and the National Health and Medical Research Council.

QUT's Office of Research Ethics and Integrity has created Research Integrity Online (RIO), an online course in research integrity, that assists researchers to fulfill their obligations set out in the Code. A completion certificate is granted upon completion of the course.

Who must complete the course?

  • All HDR students (PhD, Master of Philosophy, Prof Doc) who have enrolled since 1 January 2017 (within the first three (3) months of candidature)
  • All staff involved in research, research management, or research support including, for example, academic researchers, lab assistants, research assistants, supervisors of HDRs, and research managers.

In addition to RIO, Graduate Research Education + Development (GRE+D) also facilitates a moderated online module called eGrad Research Integrity in Practice. This course is voluntary and will assist researchers to apply research integrity principles and values to practical, scenario-based research activities.

Research misconduct

The University requires all QUT researchers to maintain the highest standards of research practice in accordance with the QUT Code for Responsible Conduct of Research (D/2.6). The QUT Code is consistent with the Australian Code for the Responsible Conduct of Research, 2018, legislation, policies, the accepted practices within a discipline and the codes of relevant external funding bodies.

A deviation from these obligations may be considered either a breach or misconduct.

Breach refers to a deviation from the QUT Code for Responsible Conduct of Research where the extent, seriousness, wilfulness and/or consequences of the deviation are not significant. The repetition or continuation of a breach may, however, constitute research misconduct, particularly if the QUT researcher has been counselled about the standards of research conduct required by QUT.

Research misconduct refers to deviations from the QUT Code for Responsible Conduct of Research that are intentional and deliberate, reckless, or amount to gross and persistent negligence, and result in serious consequences. This might include:

  • fabrication, falsification, plagiarism or deception in proposing, carrying out or reporting the results of research
  • failure to declare or manage serious conflicts of interest
  • conducting research without ethics approval as required by legislation
  • wilful concealment or facilitation of research misconduct by others.

The QUT MOPP D/2.7 Managing and investigating potential breaches of the QUT Code for Responsible Conduct of Research outlines QUT's procedures for dealing with allegations of research misconduct. In addition, specific procedures for research misconduct apply to student researchers, such as E/8.1 Management of student misconduct.

Researchers, journal editors and scientific institutions worldwide also work together to improve communication about misconduct cases. The Committee on Publication Ethics (COPE) supports and offers training for editors and publishers about ethics relating to all aspects of publishing with particular focus on issues relating to misconduct around research and publication.

Plagiarism or scientific misconduct is formally identified and recorded in various ways including:

Activity – View a retraction

View this article retraction.

The retraction includes explanations, case studies and further readings.

What is research data?

Research data may refer to data in the form of facts, observations, images, computer program results, recordings, measurements or experiences on which an argument, theory, test or hypothesis is built. It relates to data generated, collected, or used, during research projects, and in some cases may include the research output itself. Data may be numerical, descriptive, visual or tactile. It may be raw, cleaned or processed, and held in any format or media.

Research data, in many disciplines, may by necessity include the software, algorithm, model and/or parameters used to arrive at the research outcome, in addition to the raw data that the software, algorithm or model is applied to MOPP D/2.8 Management of research data and primary materials. The table adapted from University of Edinburgh's (2022) MANTRA, Research data in context (Classification of research data) shows research data which has been classified according to processes used to gather or generate them.

Data Class Process Content examples Data examples
Experimental Generated by lab equipment Gene sequences; chromatograms Laboratory notes; specimens; samples; methodology; slides; artefacts
Computational/ Simulation Generated from computational models - the actual model (and its metadata) may be more important than the output data Climate models; economics prediction models Methodology; data files; models; algorithms; scripts; workflows; standard operating procedures and protocols; simulation software
Observational Recordings of specific phenomena at a specific time or location Seismic data, medical imaging, opinion polls, climate data, interview or survey results Transcripts; audio or video recordings; field notebooks; diaries; photographs; films; slides; questionaries; test responses; codebooks; text documents
Derived Produced via processing or combining of other data Data mining; compiled databases; GIS Database contents; spreadsheet data; data files
Reference Extracted from reference datasets Genbank, HILDA, ABS CURF datasets Spreadsheets; data files; contents of an application (schemas, input, output; log files for analysis software)

There are many forms of research data that do not fit into traditional definitions. Watch the recording below to hear about different ways in which data can be understood and used in research.

Watch the video: Non-Traditional Research Data: Interview with Dr Karike Ashworth (QUT Library) (MediaHub video, 4m04s)

Research data lifecycle

Good data management is the basis of successful research. It is important to plan how you will manage your data from the beginning of your project and throughout the research data lifecycle.

The research data lifecycle is a continuous circle of the following: plan, collect and capture, process, analyse, publish and share, preserve, reuse - then back to plan.
Research Data Lifecycle. Adapted from UK Data Service (2019) (YouTube video (1m40s)

The data management lifecycle signposts the different stages your data goes through from the beginning of the research project right through to publishing and reuse. It is important to note that data often has a longer lifespan than the research project that creates them. Good data management practices ensure:

This topic is relevant to data created in a digital form ('born digital'), data converted to a digital form (digitised) or primary material.