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 of Conduct for Research. The Australian Code for the Responsible Conduct of Research provides a range of guidelines for responsible research practices. Failure to comply may result in research misconduct.

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

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' (Committee on Assessing Integrity in Research Environments, National Research Council, Institute of Medicine, 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.

The QUT Blueprint 5 articulates a cultural value of research and innovation, aimed at "Promoting a strong culture of research integrity and ethical research practices via appropriate training for academics, researchers and students". These values are consistent with national and international conventions on research integrity including the Singapore Statement on Research Integrity.

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

The Australian Code for the Responsible Conduct of Research provides a framework for responsible research conduct set out in a number of high-level principles and responsibilities, which apply to researchers and research institutions. The Code outlines expectations for the responsible, ethical and integral conduct of research in Australia. A failure to meet the principles and responsibilities is a breach in the Code.

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.

Research misconduct

The University requires all QUT researchers to maintain the highest standards of research practice in accordance with the QUT Code of Conduct for Research (D/2.6). The QUT Code is consistent with the Australian Code for the Responsible Conduct of Research, 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 of Conduct for 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 Research Code 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.

QUT policy D/2.7 Procedures for dealing with allegations of research misconduct 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) "provides advice to editors and publishers on all aspects of publication ethics and, in particular, how to handle cases of research and publication misconduct".

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.

The Integrity Online for Students (RSC_RIO) must be completed by All QUT HDR (PhD, Master of Philosophy & Prof Doc) students within the first three (3) months of their candidature. Failure to complete this course may affect your candidature status.

Activity – Code of Conduct quiz

The Research Integrity Online (RIO) quiz must be completed by all QUT HDR must be completed by all QUT HDR students who have commenced on or after January 1, 2017.

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.
Figure 1. Research Data Lifecycle. Adapted from UK Data Service Model 2017.

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 module is relevant to data created in a digital form ('born digital') or data converted to a digital form (digitised).

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). The table adapted from MANTRA 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)