Fabricating research data as academic misconduct

Short answer

Yes. Making up data (fabrication) or altering, manipulating or selectively editing data (falsification) is one of the most serious forms of academic misconduct, and it applies squarely to survey responses, laboratory or practical results, and dissertation or thesis data. Every UK university treats this as a form of academic dishonesty, and at research degree level it also overlaps with the wider concept of research misconduct.

The two distinct wrongs

It helps to separate the two things universities are concerned about, because they are defined slightly differently.

Fabrication means creating data or results that do not exist. Examples include inventing survey responses that no participant ever gave, writing up lab measurements that were never taken, or reporting interviews or experiments that never happened. It can also extend to inventing supporting material such as participant consent forms or documentation.

Falsification means taking real data and manipulating, altering or selectively presenting it to give a misleading impression. Examples include changing numbers so they fit the hypothesis, deleting or ignoring inconvenient results, altering images or graphs, or cherry-picking only the data points that support your conclusion while suppressing the rest.

Both are dishonest and both are treated as academic misconduct. The UK Research Integrity Office defines research misconduct to include fabrication (making up data or results, or other aspects of research such as patient consent), falsification (manipulating or selecting research processes, materials, data etc. to present a false outcome) and misrepresenting data. Individual university regulations mirror this: for example, university academic integrity codes routinely list “the falsification of data or sources” and “the fabrication of false data or other aspects of research, including documentation and participant consent” as specific offences.

Why it applies to all three examples you gave

Survey responses: inventing responses, adding fictitious participants, or altering the answers people actually gave is fabrication or falsification. This is a common area of concern because it is easy to do and hard to detect, so universities take it seriously when it is discovered.

Lab or practical results: reports of laboratory or practical work must not contain results that are untrue or made up. If an experiment failed, produced messy data, or you did not have time to complete it, writing up the “expected” figures instead of the actual ones is misconduct even if the invented numbers look scientifically plausible.

Dissertation and thesis data: the same rules apply, and at postgraduate and doctoral level the stakes are higher. Fabricated or falsified data in a thesis can lead to failure, and if discovered after graduation it can result in the degree being revoked. It may also be treated as research misconduct with wider professional and reputational consequences.

The dishonesty element matters

Academic misconduct in this area generally requires an element of dishonesty or intent to deceive, not merely a mistake. This is an important distinction. There is a real difference between:

Genuine error or a legitimate methodological choice, such as excluding an outlier for a properly stated and defensible reason, rounding, or acknowledging that a dataset is incomplete. Explaining honestly in your write-up that results were limited, inconsistent or inconclusive is good academic practice, not misconduct.

Deliberate misrepresentation, such as knowingly inventing figures, secretly deleting data that undermines your argument, or dressing up a failed experiment as a successful one.

The line is crossed when you present something as true that you know is not, or when you manipulate data specifically to mislead the reader or examiner. If you are unsure whether a data-handling decision is legitimate, the safe course is to document exactly what you did and why, so your reasoning is transparent and can be checked.

How universities deal with it

The exact procedure depends on your institution’s regulations, so you should read your own university’s academic misconduct or academic integrity policy, which is the authoritative source for how your case would be handled. Broadly, though, most institutions follow a similar structure:

1. An allegation is raised, often by a marker, supervisor or examiner who notices anomalies (for example raw data that does not match the reported figures, statistically improbable results, or an inability to produce the underlying data when asked).

2. An investigation is carried out, sometimes by an investigating officer and then a panel or committee, depending on the seriousness.

3. You are given the chance to respond, usually in writing and often at a hearing, where you can explain what happened and put forward mitigation.

4. A decision and penalty follow if misconduct is found.

Penalties are typically graded by seriousness and can range from a formal warning or capped or zero mark on the assessment, through failing the module, to failing the whole programme, exclusion from the university, or withdrawal of an already-awarded degree in the most serious cases. Fabrication and falsification tend to sit at the more serious end because they involve deliberate dishonesty rather than, say, poor referencing.

If you are facing an allegation

If this is not just a general question and you are actually facing an investigation, the practical priorities are:

1. Get and read the specific allegation and your university’s academic misconduct regulations, so you understand exactly what is alleged and the process that applies.

2. Gather your evidence. Locate your raw data, lab books, survey response files, spreadsheets, timestamps, emails and drafts. Being able to produce genuine underlying data and show a clear audit trail is often the strongest defence, and its absence is often what triggers suspicion in the first place.

3. Prepare an honest account. If there was an innocent explanation (a genuine transcription error, a legitimate exclusion, a misunderstanding of the method), set it out clearly with supporting material. Do not try to further alter records after the event, which makes things far worse.

4. Get support. Your students’ union advice service is usually independent of the university and can help you prepare and can attend hearings with you. Many students’ unions have advisers who specialise in exactly this kind of case.

5. Note appeal rights. If a finding goes against you, there is normally an internal appeal route, and after exhausting that you can complain to the Office of the Independent Adjudicator for Higher Education, which reviews whether the university acted fairly and followed its own procedures.

Key point

The safest position is simple: report what you actually found, even if the results are disappointing, incomplete or contradict your hypothesis, and be transparent about any limitations or data-handling decisions. Honestly reported “bad” results are perfectly acceptable academically. Invented or manipulated “good” results are misconduct.

If you tell me which university you are dealing with and whether this is a general query or an actual allegation, I can be more specific about the applicable definitions, procedure and likely penalties.