Skip to content

CSV Walkthrough

Beginner · No coding required · Works in Excel or Google Sheets

Overview

Questions:

  • How do I download and open the CSV template?
  • How do I fill in my reviewer details and answer all 28 questions?
  • How do I calculate my score and grade?
  • How do I save and submit my review?

Learning Objectives

By the end of this chapter, you will be able to:

  1. Open the review template in a spreadsheet application
  2. Fill in all 28 questions with Yes/No answers
  3. Correctly handle the Ethics questions (ACM-24–28)
  4. Calculate a weighted score and assign a grade
  5. Save and name your file ready for submission

Time: 30–60 minutes per dataset review (depending on how well you know the dataset)

Prerequisite: Complete Chapter 1 to confirm CSV is the right format for you.

Step 1 — Download the template

Download the blank review template:

metric/review_template.csv

On GitHub: click the link, then click the Download raw file button (down-arrow icon, top-right of the file view).

Reference file

The full question reference — with complete guidance text, weights, and source mappings — is also available as a CSV: metric/airbds_metric_v0.3.csv

Step 2 — Open in Excel or Google Sheets

File → Open → browse to the downloaded .csv file. If prompted about the file format, choose to keep it as CSV.

  1. Go to sheets.google.com
  2. Click Blank
  3. File → Import → Upload the .csv file
  4. Choose Comma as the separator type
  5. Click Import data

Once open, you will see two sections:

Rows Content
1–12 Section A — Reviewer and dataset information (fill in the value column)
13 Blank separator row
14 Column headers for the answer table
15–42 Section B — 28 questions (fill in answer and comments columns)

Step 3 — Fill in Section A: your details

Click in the value cell next to each field and type your information:

Field What to enter
schema_version Leave as 0.3
reviewer_name Your full name
reviewer_initials Your initials (e.g. CH)
reviewer_orcid Your ORCID (e.g. 0000-0000-0000-0000) — leave blank if none
reviewer_affiliation Your institution
review_date Today’s date in YYYY-MM-DD format (e.g. 2025-06-01)
dataset_name Name of the dataset you are reviewing
dataset_url URL of the dataset’s landing page
dataset_accession Accession number (e.g. E-MTAB-1234) if available
hosting_resource Where the dataset is hosted (e.g. ArrayExpress, Zenodo)
process_comments Any notes about your review process (optional)

Step 4 — Answer the 28 questions (Section B)

Scroll to row 15. You will see the answer table:

Column Purpose
question_id Question code (ACM-1 to ACM-28) — do not edit
scope Topic area — do not edit
theme Sub-topic — do not edit
weight Critical / Important / Optional — do not edit
question The question text — read this
guidance Detailed explanation to help you decide — read this
answer Type Yes or No here
not_applicable See Step 5 (Ethics questions only)
comments Optional: add any notes about your answer

Work through each of the 28 rows. Read the question and guidance columns, then type Yes or No in the answer column.

Hide the guidance column

Once you have read the guidance, you can hide that column to make the table less cluttered. Right-click the column header → Hide column (Excel) or Hide column (Google Sheets).

Weight matters

Questions marked Critical carry 80 points each. Getting one wrong has a large effect on the grade. Read the guidance carefully for ACM-4, ACM-5, ACM-9, ACM-12, ACM-13, ACM-17, ACM-20, and ACM-24/25.

Step 5 — Handle Ethics questions (ACM-24 to ACM-28)

The last five questions apply only to datasets that contain human or animal subject data.

Does your dataset contain human or animal subjects?

For each of ACM-24 to ACM-28:

  • Type Yes in the answer column
  • Type TRUE in the not_applicable column
  • Optionally add a comment such as “No human or animal subject data in this dataset”

Answer each of ACM-24 to ACM-28 normally (Yes or No) based on what you find in the dataset documentation. Leave not_applicable as FALSE.

Step 6 — Calculate your score

The score for each question = 1 (if Yes) or 0 (if No), multiplied by the weight points.

Weight tier Points
Critical 80
Important 5
Optional 2

Use these copy-paste formulas (assumes weight is in column D, answer in column G, rows 15–42):

Count Yes answers per tier: 

=COUNTIFS(D15:D42,"Critical",G15:G42,"Yes")
=COUNTIFS(D15:D42,"Important",G15:G42,"Yes")
=COUNTIFS(D15:D42,"Optional",G15:G42,"Yes")

Pass rates per tier (proportion answered Yes): 

Critical pass rate:  =COUNTIFS(D15:D42,"Critical",G15:G42,"Yes") / COUNTIF(D15:D42,"Critical")
Important pass rate: =COUNTIFS(D15:D42,"Important",G15:G42,"Yes") / COUNTIF(D15:D42,"Important")
Optional pass rate:  =COUNTIFS(D15:D42,"Optional",G15:G42,"Yes") / COUNTIF(D15:D42,"Optional")

Total weighted score in one formula: 

=SUMPRODUCT(
  (G15:G42="Yes") * (D15:D42="Critical") * 80
  + (G15:G42="Yes") * (D15:D42="Important") * 5
  + (G15:G42="Yes") * (D15:D42="Optional") * 2
)

Adjusting column letters

The formulas above assume the standard column layout of the template. If you have added extra columns, update the column letters (D, G) to match your spreadsheet.

Step 7 — Determine the grade

Look up your pass rates in this table:

Grade Critical pass rate Important pass rate Optional pass rate
🔴 Caution < 0.875 (< 7/8) any any
🟤 Bronze ≥ 0.875 (≥ 7/8) any any
⚪ Silver = 1.0 (all 8) ≥ 0.5 any
🟡 Gold = 1.0 (all 8) = 1.0 (all 11) ≥ 0.5

The full grade reference is in metric/scoring_schema.csv.

Step 8 — Save and name your file

Save your completed spreadsheet as a CSV file using this naming convention:

<dataset_accession>_<your_initials>_<review_number>.csv

Examples: - E-MTAB-1234_CH_1.csv - PRJNA987654_GF_1.csv

If there is no accession number, use a short descriptive name for the dataset.

In Excel: File → Save As → select CSV (Comma delimited) as the file type. In Google Sheets: File → Download → Comma-separated values (.csv).

Step 9 — Submit your review

Completed reviews are stored in the reviews/ folder.

See CONTRIBUTING.md for full submission instructions. The short version:

  1. Fork the repository on GitHub
  2. Add your CSV to the reviews/ folder
  3. Open a pull request against main

Not sure how to use GitHub?

If pull requests are unfamiliar, you can email your completed CSV to the working group. Contact details are at aibio.ac.uk/about/working-groups/airbds/.

Well done — you have completed a dataset review using the CSV format! 🎉

Continue to Further Resources or return to the About page.