← VCE Data Analytics U3O2

De-identifying survey and interview data with participant codes

A code such as P01 used instead of a name. Names and indirect identifiers like school or suburb are removed, and the key list linking codes to people is stored separately.

Part of: VCE Data Analytics - U3O2 - Analysis and Design — Module 87, ACARA Digital Technologies Years 7–8 — Digital Footprints and Data Minimisation — Module 42, ACARA Digital Technologies Years 9–10 — Acquiring and Validating Data — Module 51, ACARA Digital Technologies Years 9–10 — Privacy Principles and Digital Footprints — Module 38, QCE Digital Solutions Unit 2 — Data and Programming Techniques — Module 122

Understanding De-identifying survey and interview data with participant codes in VCE Data Analytics U3O2

What it does: Even without a name, school plus suburb can point to one person, so these columns are removed or generalised. The transcript shows the code P03 as the speaker rather than the participant's real name. If the key list sits with the data, anyone with the data can reverse the codes. Keep it in a separate, secured location. Initials and birth year are indirect identifiers. Simple sequential or random codes reveal nothing about the person. De-identifying means removing names and indirect identifiers. Only the code P01 should remain with the response data.

Common mistakes: A suburb is an indirect identifier. Combined with other details it can point to a person. Both the name and the suburb must be deleted: DELETE name and suburb. Every row must use a participant code, not a name. Row 2 should start with P02 so the person cannot be identified.

Class: _____________________ · Name: _____________________ · Date: _________

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This module's key terms are also in a printable crossword (Modules 76–146) and word search (Modules 3–146).

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Learning

Duo

A student replaces each survey respondent's name with a code such as P01 before analysing the data. What is this called?

De-identifying the data using participant codesEncrypting the data so nobody can read it

Matches

P01, Sam Tran, Year 11, Glen Waverley SC

↓

The name, school and suburb are still in the dataset, so the participant can still be identified.

Applying

Meanings

Term

participant code

Meaning

A code such as P01 used instead of a name. Names and indirect identifiers like school or suburb are removed, and the key list linking codes to people is stored separately.

Practice

P01: I enjoy Maths at [school removed].

Testing

Gaps

SELECT , answer FROM survey;

Check Answer

Spots

2 code = next participant code

3 DELETE name but keep suburb

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Quick Questions

1. A student replaces each survey respondent's name with a code such as P01 before analysing the data. What is this called?

A. De-identifying the data using participant codes ✓

B. Encrypting the data so nobody can read it

A participant code such as P01 is used instead of a name. This de-identifies the dataset so individuals are not easily recognised.

2. Which interview transcript line is better de-identified?

A. Mia Chen: I think the app is too slow.

B. P03: I think the app is too slow. ✓

The speaker's name is replaced with a participant code. Leaving the name in means the person can still be identified.

3. After replacing names with codes, a dataset still lists each person's school and suburb. Is it fully de-identified?

A. No, school and suburb are indirect identifiers and should be removed or generalised ✓

B. Yes, once names are gone nobody can be identified

Indirect identifiers such as school and suburb can be combined to work out who someone is, so they must be removed or generalised too.

4. Which is an indirect identifier?

A. The suburb and school of a respondent ✓

B. The code P07 assigned to a respondent

Details like suburb or school can point to a person when combined. A participant code is meant to hide identity.

5. Where should the key list linking codes (P01, P02...) to real names be stored?

A. In an extra column in the same dataset

B. Separately from the de-identified dataset, with restricted access ✓

If the key list sits with the data, anyone with the data can reverse the codes. Keep it in a separate, secured location.

Match the Pairs

P01 → A participant code used in the dataset and transcripts in place of the person's name

Key list: P01 = Sam Tran → A separate record linking each code to a real person, stored apart from the dataset

Indirect identifiers such as school and suburb are removed so the person cannot be worked out → Delete columns: School, Suburb

Each participant gets a code in place of their name in the transcript → P03: I mostly use my phone to study.

P01, Sam Tran, Year 11, Glen Waverley SC → The name, school and suburb are still in the dataset, so the participant can still be identified.

Survey_results.xlsx (sheet 2: P01 = Sam Tran, P02 = Mia Lee) → The key list is stored in the same file as the data, so anyone with the file can re-identify participants.

Key Term

participant code

A code such as P01 used instead of a name. Names and indirect identifiers like school or suburb are removed, and the key list linking codes to people is stored separately.

Fill in the Blanks

1. SELECT participantCode, answer FROM survey;

Hint: Type the column that identifies each person by a code instead of a name.

2. ALTER TABLE survey DROP COLUMN suburb;

Hint: Type the SQL keyword that removes a column, such as an indirect identifier, from a table.

3. CREATE TABLE keyList (code, name);

Hint: Type the name of the separate table that links codes to real people.

4. participantCode ← "P0" + id

Hint: Type the operator that joins the text prefix to the participant number.

5. UPDATE survey SET school = NULL;

Hint: Type the keyword meaning no value, used to remove the school from every record.

Spot the Error

Question 1

A FOR each survey response

B code = next participant code

C DELETE name but keep suburb

D SAVE code with the answers

Line C — A suburb is an indirect identifier. Combined with other details it can point to a person. Both the name and the suburb must be deleted: DELETE name and suburb.

Question 2

A Header: code,year,answer

B Row 1: P01,Year 10,Agree

C Row 2: Mia,Year 11,Disagree

Line C — Every row must use a participant code, not a name. Row 2 should start with P02 so the person cannot be identified.

Question 3

A Assign codes P01, P02, P03

B Make a key list: code to name

C Swap names for codes in data

D Keep key list in the data file

Line D — The key list links codes to real people, so it must be stored separately from the dataset. Keeping it in the data file defeats the de-identification.

Question 4

A code = name[:3] + str(n)

B record['code'] = code

C del record['name']

D del record['school']

Line A — A participant code must not be built from the person's name, because it still reveals who they are. It should be a neutral code like 'P' + a number, e.g. P01.

Question 5

A Raw: Ava, Lowood, Year 10

B De-id: P01, Lowood, Year 10

C Key: P01 = Ava (stored apart)

Line B — The suburb Lowood is an indirect identifier and must be removed from the de-identified data. The line should be De-id: P01, Year 10.

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